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COVID-19 was declared a world pandemic in early-mid 2020. After about a year, several vaccines for this virus have been found and become alternative solutions to reduce the spread of the COVID-19 pandemic and build up herd immunity in society. Since early 2021, Indonesia has been one of the countries that participate in using vaccines for the public to fight the COVID-19 pandemic. However, there are a lot of positive and negative responses from Indonesian society related to these COVID-19 vaccines. Implementing a sentiment analysis model for a specific topic like a "vaccine" from social media could help us to see and understand the responses from society in Indonesia towards the vaccine program that is being conducted by the Indonesian government. Understanding society's response towards vaccines is expected to be able to support the Indonesian government, for example in formalizing the distribution strategy of vaccines in the future. This paper discusses how to develop a sentiment analysis model, by implementing several existing technologies such as Twitter API, TextBlob , and Googletrans Python libraries. The utilization of these existing technologies could show how a sentiment analysis model could be developed conveniently, for example in using cases to analyse Indonesian society's responses towards the COVID-19 vaccine program. Besides the solution design, this paper also shows a sample of data visualization of the sentiment analysis model in a meaningful infographics format. [ABSTRACT FROM AUTHOR]

Along with the popularity of the environment, social and governance (ESG) concerns, the circular economy concept has gained tremendous attraction from the industries, policy makers and academicians. On a firm level, this is implemented through the so-called Circular Business Model (CBM), which is seen through various initiatives. This includes firms in the energy industry, who are transitioning from conventional to renewable energy sources. Nevertheless, despite of the importance and the omnipresence of the practice, there is still lack of empirical research within the CBM topic. In particular, empirical research combining the CBM and technological innovation topic within energy industry (as technology-intensive and high risk industry) in developing country such as Indonesia, is still lacking. To answer this gap, using literature review as research method, this paper has arrived into the following propositions as main result; (1) there is a positive relationship between firm's level of CBM and technology innovation adoption to firm's performance, where (2) the two antecedents that are positively impacting firm's level of CBM and technology innovation adoption are leader's innovativeness and perceived level of technology. For academicians, this research is expected to provide contribution to the energy transition literatures within CBM and technology innovation adoption topic. Propositions provided in this paper is expected to serve as valuable basis in conducting further empirical research. For practitioners, this research is expected to provide valuable insights to make improvements and/or innovations in terms of business model, technology adoption, and strategy. At last, this research is expected to support energy transition. [ABSTRACT FROM AUTHOR]

This paper examines the responses of credit and business cycle to various policy actions of the Government of Indonesia during the COVID-19 crisis. Specifically, the paper addresses two key questions (1) How do the credit and business cycle behave during the COVID-19 crisis in Indonesia? (2) Do the central bank and government policy responses effectively stabilize the credit and business cycle? Using the concordance Index and DCC-GARCH methodology, we found that the COVID-19 crisis increased Indonesia's credit and business cycle co-movements. Similarly, using the mixed data sampling regression technique, our findings suggest fiscal policy measures and government support help the business cycle revival during the COVID-19 pandemic. However, the monetary policy transmission is weak during the pandemic [ABSTRACT FROM AUTHOR]

In developing countries like Indonesia, adding a new unit for hydroprocessing facilities is more efficient than modifying the existing equipment. When the addition occurs, refiners should analyze if the existing hydrogen network can supply enough hydrogen to the new unit before constructing a costly hydrogen plant. Current studies on the hydrogen network have yet to consider pressure drop adequately. Therefore, this paper integrates pressure drop estimation and density prediction into the multi-objective MINLP-based hydrogen network. The multi-objective problem is solved sequentially by adding a minor unit to obtain each configuration's maximum flowrate and total annual cost. The optimal configuration based on the combined objective function is to add 1 PSA and compressor for a hydrogen purity of 0.84 and specified pressure requirements. The pressure drop integration shows an insignificant impact averaging 0.004 m3/s of maximum flowrate difference compared to optimization without pressure drop. • The addition of a new hydroprocessing unit is more efficient than existing refiners. • Multi-objective MINLP-based hydrogen network is used to analyze retrofit options. • The pressure drop integration shows a small impact on the overall. • Network. • The optimal configuration is to add one PSA and one compressor. [ABSTRACT FROM AUTHOR]

Higher education institutions in Indonesia are required to report their academic data to the national higher institution database (namely PDDikti) through a synchronization mechanism. Because the PDDikti database has been used as the reference for nationwide programs such as university ranking, diploma verification, faculty promotion, and tenure, academic data in their reports have to be valid, accurate, and up to date. Yet, data quality is an issue among higher institutions, while data governance is the heart of data quality. This paper investigates challenges encountered by a public university in Indonesia in implementing data governance and how to resolve them. The findings outline six main challenges in data governance implementation. [ABSTRACT FROM AUTHOR]

This study aims to predict the determinants of mobile fintech apps and digital financial inclusion from the perspective of the Bottom of the Pyramid (BOP) segment in Indonesia. To address the complexities of BOP users, this paper theoretically grounded on Mobile Technology Acceptance Model (MTAM) (i.e. mobile usefulness (MU), mobile ease of use (MEU)) along with its relevant extension including personal factor (digital financial literacy (DFL)), financial risk factor (mobile perceived financial cost (MPFC)), and consequent factors (i.e. use behavior (UB), and digital financial inclusion (DFI)). The moderating impact of gender was also tested. A survey instrument that was self-administered and comprised measurement items adapted from prior research was utilized to gather data from 200 mobile fintech BOP users residing in Makassar, South Sulawesi. According to the results of the PLS-SEM test, seven hypotheses were accepted, while two were rejected. In addition, it was confirmed that men play a more prominent role than women in strengthening mobile fintech use and digital financial inclusion. [ABSTRACT FROM AUTHOR]

Temporary trade barriers, such as safeguards, is a measure to rescue the economy in such a way as to protect domestic industries from foreign competitors. Safeguards provide opportunities for domestic industries to make structural adjustments and reshape their business process to increase their competitiveness during the validity period. Indonesia's government has imposed safeguards for most textile sub-industries, from the upstream industry (yarn and fibres) to the downstream garment industry and other related textile industries. This paper aims to evaluate whether the application of safeguards meets its objectives in improving the competitiveness of domestic industry against its foreign competitors with a long observation period. It is found that the effectiveness of the application of safeguards was limited to rescuing the trade balance. In terms of export competitiveness, safeguards have not been effective in increasing the export competitiveness of the textile industry in the world market. [ABSTRACT FROM AUTHOR]

As start-up companies may leverage information spreading through Instagram's hashtag-setting, algorithms in influence maximization can be encoded. The objective is to find a maximum impact which can activate users in spreading advertisement marketing campaign through social network. This paper contributes an influence analysis on Instagram and reproduces it into a hashtag network by transforming postings with hashtag interdependence. In finding optimal paths such network structure with influence probabilities, we employ Floyd-Warshall algorithm under uncertainty. The technique is simulated on Indonesian FnB unicorn company and demonstrated in numerical example. The result shows that the hashtag #promokopi may impact the most. [ABSTRACT FROM AUTHOR]

Numerous research on stunting supplementation interventions in Indonesia have been published. The information can be extracted through data mining, especially from academic research databases. In this paper, we presented a text mining-based literature review strategy to create a pipeline that researchers can use to accelerate the development of stunting supplementation intervention research in Indonesia. Utilizing various NLP (Natural Language Processing) techniques, data were crawled, processed, and visualized using Python. The crawling dataset used a module from the Pubmed API (Application Programming Interface) to collect literature papers. The NLTK (Natural Language Toolkit) module and itertools were used to process text data. The n-grams model was applied to process tokens into bigrams and trigrams. Text information was visualized using Matplotlib and Word cloud packages. There is an increasing number of publication in stunting supplementation intervention according to our result, which was observed from 2015 to 2021. West Java was the province where most of the stunting research has been conducted, as determined by research abstracts. Top occurrences obtained from the bigram and trigrams models calculation produced different terms. The word pairings that occurred the most frequently in the bigram and trigram model analyses were "child-aged" and "iron-folic-acid," respectively. The findings of this study are expected to help researchers to obtain the latest research topics related to stunting supplementation interventions in Indonesia. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic affected many aspects in global life, the one of aspect is e-commerce. The COVID-19 pandemic changes the general society into having a more consumptive behavior. This research is conducted to identify whether there is a difference in mean/average sales between the period before the COVID-19 pandemic and during the COVID-19 pandemic. This paper used T-Test Paired Samples to analyze the difference of behavior's customer of some e-commerce in Indonesia. Biplot analysis is also used to give visualization of the behavior's change caused by the COVID-19 pandemic. Six variables are used in this paper and purposive sampling is selected to get a sample size. We use 63 respondents are eligible to fulfill the questionnaire. The T-Test paired samples resulted that there is a difference in mean sales for the service or online products, food and beverages, electronics, and cosmetics and skincare. Those aspects are evidence that COVID-19 pandemic could change the customer behavior in E-Commerce. We also illustrate the change of customer behavior through biplot [ABSTRACT FROM AUTHOR]

The prevalence of diabetes mellitus has increased over time. Medicinal plants, including Andrographis paniculata (Burm.f) Nees, are recognized for their use to manage hyperglycemia. Nowadays, plenty of papers are published about A. paniculata as an antidiabetic; however, no bibliometric study about the topic exists. This study examines the existing papers about the preclinical trial of A. paniculata as an antidiabetic agent using bibliometric analysis focusing on countries, institutions, publishers, authors, documents, and keywords. Bibliographic information of relevant research and conference articles were obtained from the Scopus database. In total, 97 articles published between 1994 and 2021 were selected, covering 376 authors and 1270 keywords. Data were analyzed bibliometrically using Vosviewer 1.6.16. A total of 97 published papers occurred from 1994 to 2021 were selected. India, Universitas Gadjah Mada (Indonesia), Journal of Ethnopharmacology, and Agung Endro Nugroho (Universitas Gadjah Mada, Indonesia) were the most productive country, institution, publisher, and author, respectively. The analysis of the most influential papers, co-citation network of the most influential papers, bibliographical coupling network based on authors, and keyword co-occurrence network and overlay demonstrated that the abundance and variety of existing papers about preclinical trials of A. paniculata as an antidiabetic were from phytochemistry, pharmacology, and drug formulation. The findings of our analysis have implications for managerial and theoretical aspects on this topic, such as encouraging research collaborations by analyzing the contributions of countries, institutions, publishers, and authors and revealing research gaps (molecular mechanisms, toxicities and side effects, drug formulations, and clinical trials) to accept a phytomedicine as a therapeutic option. [Display omitted] • The abundance of preclinical trials of Andrographis paniculata as antidiabetic. • India, Universitas Gadjah Mada (Indonesia), Journal of Ethnopharmacology, and Agung Endro Nugroho were the most productive country, institution, publisher, and authors, respectively. • Research mapping is needed to determine the expansion of the research fields. • The related fields were phytochemistry, pharmacology, and drug formulation. [ABSTRACT FROM AUTHOR]

Indonesia is a tropical country that experiences forest fires every year. Forest fires occur due to a prolonged summer season. A major effect of forest fires that commonly occurred in Indonesia is the respiratory disorder and the visual impairment caused by the thick smoke that can experienced by the people who lives around the forest. The effects of forest fire fumes when the forest fire spread across the bigger land or area are also experienced by neighboring countries such as Malaysia, Singapore and Brunei Darussalam. Forest is a habitat for many animals, one of which is a bird. Birds are able to communicate with their colonies through sound. The bird sound during communication to the group can be in the form of calls, marriage invitations, and warnings of danger or threat of forest fires. This paper presents bird sounds classification study using one of Deep Learning (DL) algorithms i.e. Convolutional Neural Network (CNN) method. The CNN method is used to classify bird sounds in the two conditions: (1) under normal circumstances or conditions, and (2) under threated or panic condition. The bird sound data used in this study were collected from the local birds in Indonesia. The classification result of two bird sounds based on CNN method achieved up to 96.45%. This paper is a preliminary study for bio inspired early warning of forest fires based on the sound of birds. [ABSTRACT FROM AUTHOR]

This study explores the key determinants of Supply Chain 4.0 (SC4.0) maturity in the context of a developing country by examining the relationships between supply chain ambidexterity, supply chain agility, and the maturity of SC4.0. The study was carried out using the survey method involving 154 managers from Indonesian manufacturing companies. The SC4.0 maturity model was developed and tested using structural equation modeling. From our analysis, it was found that supply chain ambidexterity emphasizing on innovation positively influences the companies' agility and SC4.0 maturity levels, and supply chain agility partially mediates supply chain ambidexterity. This paper contributes to the operationalization of SC4.0 maturity determinants that incorporate innovation and technological aspects and extends the extant literature by empirically elaborating the determinants and antecedents of SC4.0 maturity that may expedite the achievement of SC4.0 maturity. This implies that companies and supply chain professionals aiming at achieving their SC4.0 maturity should do so by being outward-looking and, at the same time, foster supply chain collaboration with external networks. This paper is pioneering the empirical study on SC4.0 and offers a means to achieving SC4.0 maturity through SC ambidexterity and SC agility, particularly in the context of a developing country. [ABSTRACT FROM AUTHOR]

Jakarta City is one of the largest cities in Indonesia, experiencing urban areas development generally intensive and unsustainable. This development impacts directly or indirectly on landscape degradation. Kalijodo is one of the important public open spaces (POS) constructed in the Jakarta Capital Special Region to facilitate different social functions and ecosystem services. This paper aims to describe the non-ideal condition of the Kalijodo area as a POS and to strengthen its functions towards a Public Green Open Space (PGOS). The Kalijodo POS had actually 47.91 % vegetated and 52.09 % of non-vegetated land cover and this area cannot be categorized as PGOS due to its vegetated land cover under a minimum threshold of 75 %. This condition is closely related to other aspects and parameters which indicate that Kalijodo POS has low water absorption ability, low water storage capacity, high average air temperature, high Thermal Humidity Index (THI), and low potential for economic benefits. The ecohydrology principles were taken into consideration for understanding, assessment, and identification of possible efforts to achieve the PGOS level. Several possible actions would be suggested for improvement consisting of increasing vegetated land cover, replacing pavement hardeners, introducing bio pores, constructing water ponds and wetlands, increasing public participation, and adjusting appropriate government policy and regulations. These efforts will probably have positive impacts on average air temperature reduction, increasing water absorption ability and potential economic gain, entering THI to a comfort zone and positive people's perception, as well as increasing people attendance. [ABSTRACT FROM AUTHOR]

China has issued a series of biodiesel-related policies to alleviate energy shortage anxiety and reduce carbon emissions. However, no other provinces or cities in China widely utilize biodiesel except Shanghai. This article firstly conducted a comprehensive estimation of the potential botanical biodiesel capacity in China. Then, we examined why biodiesel advancement in China was stagnated by comparing biodiesel-related policies in pioneer countries such as Malaysia and Indonesia. We found the highest mix ratio will be ∼13 % if all potential botanical oils are added to petrochemical diesel and an addition of 3 % blending ratio can be achieved if waste cooking oils are effectively utilized. We concluded that despite the encouragement from policies, insufficient materials and lack of downstream consumptions may be the major reasons for the sluggish development of biodiesel in China. If microalgae biodiesel production technology is overcome in the future, China can compulsorily mix biodiesel on a large scale. This paper provided a comprehensive review of biodiesel-related policies in Malaysia, Indonesia and China, and figured out the key problems that hinder the promotion of biodiesel, helping to understand the dilemma and drive the potential development of biodiesel in China. • Potential biodiesel capacities were estimated among various provinces in China. • The highest biodiesel mix ratio will be ∼13 % if adding all potential botanical oils. • The southern China is more likely to prioritize blending biodiesel than the north. • Biodiesel-related policies in Malaysia, Indonesia and China were fully reviewed. • Inadequate materials and lacking downstream consumption hindered biodiesel growth. [ABSTRACT FROM AUTHOR]

The government of Indonesia continues to commit to social forestry as one of its cornerstone rural development policies. Social forestry mechanisms aim to grant legal rights/ permits to groups of local communities to manage previously inaccessible state forests, with the dual aims of improving the livelihoods of rural communities and encouraging participation in forest rehabilitation. Explicit policy targets include the allocation of 12.7 million hectares of state forests for local communities through a suite of social forestry project mechanisms. While the number of social forestry licenses have increased markedly over the past few years, current social forestry initiatives still fall short of meeting the ambitious land area targets. More importantly, increasing evidence points to social forestry policy outcomes only partially serving its initial intended promises. This paper helps to explain these partial outcomes and unmet promises from the perspective of social forestry bureaucracy structures and designs. We found that despite the core social forestry bureaucracy undergoing substantial expansion, several other bureaucracies also channeled their interests into the realm of social forestry policy. These other bureaucracies do not necessarily fit within the intended goals of social forestry policy. Indeed, several bureaucracies continue to hold social forestry policy implementation hostage through other forestry mandates, which results in an institutional chokehold on key social forestry interests. These other bureaucracies even introduced models to redirect social forestry initiatives by retrofitting mandates into their own policy priorities. To address these increasing roadblocks to achieving social forestry policy designs, this paper outlines and proposes a more simplified bureaucratic structure to assist in the implementation of a social forestry policy more in line with its intended goals. Specifically, tasks and responsibilities could be transferred to a single bureaucracy that has mechanisms more closely connected to local people, such as those already envisioned and established in the form of forest management units. • The lens of bureaucratic politics is used to explain the unmet objectives of social forestry policy initiatives. • Non-social forestry bureaucracies have increasingly channeled their interests through social forestry policy. • Non-social forestry bureaucracies are holding intended goals hostage by obstructing policy through several means. • Fragmentation of the social forestry bureaucracy hinders intrinsic policy goals of social forestry. [ABSTRACT FROM AUTHOR]

Online library resources can act as a trusted source to find various references for conducting research or writing research papers. With the increasing number of published papers, the use of online library resources becomes increasingly important for academics, including for university students. This study aims to investigate the factors that lead to the continued use of online library resources among university students in developing countries, especially Indonesia. We investigate the impact of resource quality, confirmation, satisfaction, perceived usefulness, perceived ease of use, and perceived enjoyment of users on their intention to continue using online library resources and the effect on e-WOM intention. This study will enhance the Post-Acceptance Model of Information System (IS) Continuance by adding several other constructs and tested using data from 215 university students in Indonesia who have used online library resources. The method used to analyze the data is Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results of the study indicate that satisfaction and perceived enjoyment have a significant effect on the intention to continue using online library resources. In addition, it was also found that the continuation intention to use online library resources also affects the user's intention to convey it to others (e-WOM intention). This study provides insight to online library resources service providers in making improvements and formulating strategies to increase users' intentions to continue using their online library resources. [ABSTRACT FROM AUTHOR]

This paper presents a model to capture the impact of the Basel III's Liquidity Coverage Ratio (LCR) and the reserves requirement regulation on the banking sector and the real economy. It employs a medium-scale Dynamic Stochastic General Equilibrium (DSGE) model with financial frictions and calibrated to match data for Indonesia. The study shows that the impact of changing the two liquidity requirements on lending and output are relatively similar. However, lowering the LCR has consequences on the decline of demand for government bonds, so that it has a different impact on taxes, household deposits and bank's profit. This paper also found that countercyclical liquidity regulations can improve welfare and reduce the volatility of bank loans. [ABSTRACT FROM AUTHOR]

• We conducted a state-of-the-art RP and SP survey and presented its methodology with a total of 5,143 respondents, which covers 52,731 observations. • The development of On-Demand Transport (ODT) is popular in many cities. Urban Air Mobility (UAM) will become a new alternative mode of transportation. • This paper presents the travel behavior of respondents in each mode of transportation. • We explored willingness to pay (WTP): VTTS, VTAT, elasticity, and the preference of all choice alternatives, including ODT and UAM using pooled SP and RP data sets. The research presented in this paper analyzed two data sets Revealed Preference (RP) and Stated Preference (SP), obtained with a new travel diary and mode choice survey. This survey, called Mobility Jakarta, combined both RP and SP parts and was conducted in the Greater Jakarta region. This is the first survey that collected responses from a substantial sample of the whole metropolitan area population. We estimated the discrete choice model pooling SP and RP data sets. We explored the Willingness To Pay, e.g., the Value of Travel Time Savings, and the elasticity for all mode choice alternatives, including On-Demand Transport and Urban Air Mobility. [ABSTRACT FROM AUTHOR]

• The Indonesian Government failed in disciplining large-scale peatland users. • Major plantation companies steer their worker unions to resist peatland policies. • Corporations actively influence and seek to weaken peatland protection policies. This paper examines new governmental technologies that are emerging in Indonesia to address socio-ecological crises resulting from the conversion of peat forest landscapes to large-scale agricultural plantations. The early implications of Indonesia's 'peatland-fire-free' policy interventions for palm oil and pulpwood industries, including private sector resistance and contestation to this policy, are investigated. Drawing on the Foucauldian concept of disciplinary governmentality, this article analyses the Government of Indonesia's (GoI) failed attempts to render large-scale peatland users governable. The GoI introduced two peatland disciplinary strategies: a spatial and hydro-governance approach to governing palm oil and pulpwood plantations in peatland landscapes. However, significant contestation and opposition arise from these policies as the state attempts to apply disciplinary logics upon powerful and prickly actors. In this context, contestation reflects the complexities of the existing political economy of peatland exploitation in Indonesia, which is decisively shaped through structural and environmental violence. The paper outlines the elements that limit the prospects for fully-fledged disciplinary governmentality over peatland areas and highlights the messy, insecure and unfinished nature of environmental governance. [ABSTRACT FROM AUTHOR]

This paper proposes the development of a markerless augmented reality (AR) application for Indonesian traditional house education. The application aims to provide an immersive and interactive way of visualizing traditional houses from various regions of Indonesia, with the potential to raise public awareness about the importance of preserving traditional culture. The prototyping method was employed as the most appropriate approach to software development, and the ARFoundation platform was used to integrate plane detection into the AR application. The results showed that 80% of tested devices were compatible with ARCore, and the AR plane detection could detect up to 250cm from the device position. In addition, a feedback survey conducted on 17 testers showed that the application design and mechanism brought a good experience to users, with 53% stating that the app is easy to use. This research project contributes to the development of technology-based solutions to promote Indonesian culture and preserve traditional houses, especially for younger generations who may be less familiar with traditional culture. [ABSTRACT FROM AUTHOR]

People with hearing impairments exist in our society, whether we realize it or not. It is not easy for them to communicate with us, the ones without hearing disabilities, and they often receive a lot of mistreatment. Since we don't learn about sign language and don't know where to start, our knowledge about sign language is also limited. This paper explains the making of Deafvoir—a visual novel game about sign language—as well as why it is developed and how it can help the deaf and us learn sign language. By conducting a survey and asking how familiar sign language is to some people and their response about Deafvoir, we can move forward to realize this sign language learning visual novel video game and make it local-based before going international. With this video game, it is hoped to make Indonesia's younger generation, especially Gen Z, understand and be able to use sign language whenever they encounter the deaf in real life. [ABSTRACT FROM AUTHOR]

Indonesia is a vast market for talents recruiting, with around 203 million people that count into work age definition (above 15 years) and around 138 million of them are workforce, while 7 percent of the workforce are open for hire. There are several players of job-seeking apps in Indonesia. But most of them are targeting talents with undergraduate degrees and above. Mid to high-level jobs have become such an attractive market for these players. We can see it on several job seeker hub websites, where job seekers proudly post their personal profiles to attract recruiters from top employers. It is not possible for lower-level job seekers to post their profiles on these websites. They will just be under the recruiter's radar. Whereas from the report data released by the Indonesian statistical center bureau regarding the percentage of open unemployment based on education level, the total unemployment rate from diploma education and below is very large compared to the unemployment rate with university education (undergraduate and above). The Covid-19 pandemic also gave a negative impact on the lower job segment, with a decrease in demand and sales resulting in a higher layoff rate which also means an increased percentage of the open unemployment rate. We need a solution to this problem. A solution that can erode a large chunk hidden under an iceberg. This paper offers "Megawe", a mobile application-based solution to assist both job seekers and low-level job recruiters. This segment may have a smaller contract value than upper segments but has a much larger quantity of labor force. Because we are focusing on development speed and accuracy of requirements, we used the prototyping methodology in the implementation of the solution. Moreover, before it is launched publicly, we conducted usability testing to gain a deeper understanding of the user experience directly from users of the targeted segment. [ABSTRACT FROM AUTHOR]

Classification of Indonesian crops is a critical task in developing farming and getting more understanding of agriculture. However, there is no clear task in classifying types of crops in Indonesia. Transfer learning has been used successfully in a variety of image classification applications. Thus, in this paper, we collected images of Indonesian crops from the internet randomly and proposed a classification by using transfer learning of deep learning with four pre-trained models: EffficientNet- B0, ResNet18, VGG19, and AlexNet. In the experiment, augmentation techniques such as random horizontal flip, random vertical flip, and random affine were utilized to prevent the network from overfitting. The result found that EfficientNet-B0 outperformed other models with an accuracy of 82.55. Then, the model struggled to distinguish between crops in the same family. According to the results, although transfer learning can work well to classify images of Indonesian agricultural crops, some improvements are still required to address existing issues. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of the monetary policies undertaken by the central bank on economic growth during COVID-19 uncertainty in case of India and Indonesia. We use an innovative framework of Growth-at-Risk as oppose to standard macroeconomic models, which can predict the growth in a much robust way particularly when an economy is facing shocks like COVID-19. The empirical results based on Growth-at-Risk model clearly reveal that effect of COVID-19 pandemic on economic growth is much adverse in comparison to actual declines. Further, this study shows the effectiveness of monetary and financial policies undertaken by the central banks of both India and Indonesia, which have actually subsided the adverse impact of COVID-19. [ABSTRACT FROM AUTHOR]

This paper examines the importance of legacy as a hidden agenda behind the ambitions and haste attitude of Indonesian state leaders in relocating the capital. It also elucidates the institutional mechanisms employed to achieve this lofty goal. In 2019, President Joko Widodo (Jokowi) issued a controversial declaration on the relocation of Indonesia's capital city from Jakarta to Kalimantan Island. Despite the protracted COVID-19 pandemic and the prevailing global economic and geopolitical uncertainties, he marshalled all necessary means and resources under his command to ensure the capital megaproject could commence and the inauguration could be held before his presidential tenure ends in 2024. As formal and technical arguments for Indonesia's capital relocation have been criticised for inconsistencies, a comprehensive understanding of the real phenomenon necessitates an exploration of the hidden agendas behind this unpopular move. The argument posits that the new capital city serves as a megaproject legacy, signified by the construction of monumental and iconic buildings and structures that will reflect the enduring power and memories of the politicians. Furthermore, the institutional mechanisms of the megaproject legacy tend to be pragmatic, whereby quick, concrete and symbolic actions become the top priority at the expense of the quality of the planning process and outcome. • This paper explores megaproject legacy as a hidden agenda behind capital relocation. • Indonesia's capital relocation can manifest a megaproject legacy. • Official motives for capital relocation are criticized for inconsistencies. • Capital cities reflect state leaders' ambitions and enduring power and memories. • Megaproject legacy building involves pragmatic uses of institutional mechanisms. [ABSTRACT FROM AUTHOR]

Micro-Hydro Power (MHP) is a type of hydroelectric power that typically generates electricity from 5 kW to 100 kW using the natural flow of water. This study investigates the MHP plant as one of the renewable energy projects in rural areas of Indonesia and its benefits to rural women. Implementation of the renewable energy (RE) projects were initiated by local non-government organizations (NGOs) and donor agencies that provide funding, technical assistance, and training for the rural community. The MHP projects discussed in this paper were located in rural areas of West Java and East Java. The empirical data show that MHP not only provides green electricity but also gives benefits to many households. It significantly impacts women's empowerment, gender relations, and their relationship to rural development, including improves their living conditions. The biggest challenges for future implementations of MHP at the national level are maintaining the local's responsibility, networking to connect and motivate practitioners from various institutions and organizations, and developing sustainable and successful Indonesia's energy programs in the long run. • Micro Hydro Power Plant (MHP) is one of the renewable energy projects in rural areas of Indonesia and benefits rural women. • MHP provides green electricity and gives benefits to many households. • MHP brings many positive changes to society, including increasing women's knowledge and skills. • MHP can have a significant impact on women's empowerment, gender relations, and their relationship with rural development, including better living conditions. [ABSTRACT FROM AUTHOR]

Onshore wind potentials are commonly mapped with site selection criteria that either fully include or exclude land for wind farms. However, current research rarely addresses the variability of these criteria, possibly resulting in overly conservative or optimistic potentials. This paper proposes a method to account for the variability of site selection criteria in resource assessments. We distinguish between static and flexible, non-binary criteria and assess onshore wind's technical and economic potential with bias-corrected ERA5 data, 28 turbine power curves, and a turbine-specific cost model. For Indonesia, we show that our flexible mapping approach improves the transparency of resource potential assessments and could contribute to more informed and useful recommendations. These recommendations could address the (1) calibration of site exclusion thresholds, (2) dilemmas of preferring one land type over others, (3) location-specific challenges of wind farm deployment, and (4) more direct support schemes for affected stakeholders and wind farm operators.. We report a technical potential of 207–1,994 TWh/year in Indonesia, which could cover more than 50% of 2030 electricity demand on all islands. LCOEs range between 5.8 and 24.5 US¢(2021)/kWh with an economic potential of 16 TWh/year, which improves to 31–212 TWh/year with a carbon tax of 100 US$(2021)/tCO 2 e. • New method to account for variability of onshore wind site selection criteria. • We differ between static and flexible site selection criteria for resource mapping. • Their use may change onshore wind potentials by several orders of magnitude. • Flexible site selection enables more transparent and informed recommendations. [ABSTRACT FROM AUTHOR]

The writing of this paper and the creation of this application is a means to improve and add on facilities on the local state-run attraction. This subject matter was picked in conjunction with the decline of tourism in the said historical site due to a pandemic that rankles Indonesia's tourism industry and drives it to the ground. Augmented Reality as a method of deliverance was picked due to its popularity and freshness in the tourism market. The research method was conducted starting with analysis, development, implementation, then evaluation. Analysis was done using sourcing available to the public and a questioner. Implementation was done using Unity, Vuforia, and Maya. And with the positive responses of 66.6 percent of the sample market finding enjoyment in the use of this application in their exploration during User Acceptance testing with the existing prototype. This shows that the resulting use of this application improves user enjoyment in experiencing the state attraction. [ABSTRACT FROM AUTHOR]

In recent years, technology has advanced so much that it is so widespread and the internet is being used by 53.7% of Indonesia's population. This paper reviewed how privacy violations occur, their potential impacts, and their prevention methods personally such as individuals and organizations through literature review. Overall, it can be concluded that in general. There are two methods to prevent privacy violations, which are by using computer security software and end user awareness training. [ABSTRACT FROM AUTHOR]

Technology development has been getting more advanced and greatly facilitated human life. One of them is machine learning automation which has been proven to be consistent for doing various computations against extensive data such as transaction data in the e-commerce area. Seeing this opportunity, we implemented the machine learning approach to detect fraudulent cashback transactions in e-commerce that are currently rife in Indonesia. The training data used to build the machine learning model were the transaction data from one of the leading e-commerce in Indonesia that had been processed. The supervised classification algorithms used were K-Nearest Neighbor (k-NN), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM). In the end, the best steps and methods that could be taken against fraudulent cashback activities in the future are shown in this paper. [ABSTRACT FROM AUTHOR]

The spread of Corona Virus Disease 19 (COVID-19) in Indonesia is still relatively high and has not shown a significant decrease. One of the main reasons is due to the lack of supervision on the implementation of health protocols such as wearing masks in daily activities. Recently, state-of-the-art algorithms were introduced to automate face mask detection. To be more specific, the researchers developed various kinds of architectures for the detection of masks based on computer vision methods. This paper aims to evaluate well-known architectures, namely the ResNet50, VGG11, InceptionV3, EfficientNetB4, and YOLO (You Only Look Once) to recommend the best approach in this specific field. By using the MaskedFace-Net dataset, the experimental results showed that the EfficientNetB4 architecture has better accuracy at 95.77% compared to the YOLOv4 architecture of 93.40%, InceptionV3 of 87.30%, YOLOv3 of 86.35%, ResNet50 of 84.41%, VGG11 of 84.38%, and YOLOv2 of 78.75%, respectively. It should be noted that particularly for YOLO, the model was trained using a collection of MaskedFace-Net images that had been pre-processed and labelled for the task. The model was initially able to train faster with pre-trained weights from the COCO dataset thanks to transfer learning, resulting in a robust set of features expected for face mask detection and classification. [ABSTRACT FROM AUTHOR]

In this paper, we have extended the formula of fuzzy chromatic number (FCN) for the non-disjoint union of two fuzzy graphs. Further, we constructed an algorithm based on the FCN for determining a fuzzy phase system in order to coordinate traffic flow of two paired intersections. By combining the fuzzy phase system and the fuzzy inference system, we were able to construct another algorithm to determine all possible phase timings for coordinating the intersections. Performance of the algorithms was evaluated through a case study at two intersections in Semarang City, Indonesia. The results showed that the proposed phase and timing systems for the two paired intersections could reduce the red and cycle times compared with the control of two intersections separately. The present findings might serve as a feasible proposal for congestion problems in any paired intersections. [ABSTRACT FROM AUTHOR]

COVID-19 severely impacted small industries in Indonesia and many collapsed. Sustainable education is essential to help small industries recover post-pandemic through an open innovation design program to improve small industries' economic, social, and environmental performance. This paper examined the impacts of the sustainable education program implemented and explored open innovations suitable for the sustainability of small industries in developing countries, such as Indonesia, after the pandemic. This research employed a Participatory Action Research (PAR) approach involving academics, government, the community, and four small industries in West Java, Indonesia. Our findings reveal that the sustainable education program through learning activities and direct practice provides valuable knowledge and experience for small industries in designing economic, social, and environmental innovations. Open innovations post-pandemic suitable for small industries in Indonesia include simple business digitalization for company economic growth, the recruitment of people losing their jobs due to the pandemic to achieve social benefits, and innovations in using environmentally friendly packaging and charcoal briquette fuel as an environmental awareness effort. This study recommends that the open innovation designed for small industries be right on target and done using a participatory method to achieve sustainability after the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The objective of this study is to elaborate on the development of micro and small enterprises (MSEs) at the bottom of the economy, where most of them began as unbanked micro-ventures and may continue to be micro-enterprises even after being elevated to higher levels. This study contributes to the field of entrepreneurial finance by identifying the factors that influence the drivers and constraints of MSE upgrading. This paper employed models to show how unbanked MSEs transition to bankable ones, as well as to reveal the dynamics of MSEs' transition to bankability during the COVID-19 pandemic. This study's unit of analysis is MSEs, which initially have little or no access to bank loans. This study employs system dynamics (SD) modeling to investigate and manage the multifaceted response system of MSEs' growth toward bankability in the face of a coronavirus pandemic in Indonesia. This study also simulates a coronavirus pandemic outbreak to fine-tune MSEs' progress toward bankability. The dynamic models in this study reveal a number of variables that are critical in accelerating the bankability status of MSE from un-bankable to bankable, namely entrepreneurial MSE time to bankability, channel business, and MSE NPL. Policymakers can create high leverage policies for MSE bankability progression by changing these values. [ABSTRACT FROM AUTHOR]

Rural places throughout the world are frequently sites of amenity-oriented consumption, as much as they are sites of agricultural production, and this is increasingly true for parts of the Global South. The implied assumption, however, has generally been that consumers of rural landscapes are socially or culturally distinct from, and even in conflict with, those living off the land as farmers. This paper, however, presents the phenomena of intra-cultural consumption of an Indonesian rural landscape, whereby place-based cultural identities within a diasporic community are motivating ceremonially-linked remittances and wealth redistribution. This is subsequently supporting a range of non-productivist rural livelihoods. These findings highlight the need to better understand how redistributive practices within spatially dislocated agrarian communities in late-industrializing economies are reshaping processes of contemporary rural change. [Display omitted] • Introduces the phenomena of intra-cultural consumption of rural landscapes. • Rural landscape consumption is linked to a new politics of redistribution. • Non-productivist rural land use is a significant reality in the Global South. • Non-productivist activities increasingly sustain livelihoods in the Global South. • This demands new approaches to contemporary rural development. [ABSTRACT FROM AUTHOR]

Although the colonial era in Indonesia has ended, the legacy of conflict persists. Current conflicts between native and Chinese Indonesians has a colonial underpinning as well. The Dutch classified Chinese Indonesians as middle class, having higher status than natives which changed in the post-colonial era. This classification and the consequent status changes created competitive victimhood beliefs among both groups and impacted each other's perception, which evolved into stereotypes and persisting conflicts. This paper is based on an online survey study conducted among native and Chinese Indonesians (N = 656) who are divided by ethnicity, religion, language, and their different histories of collective victimhood but united by being part of the Indonesian nation. Using structural equation modeling, we hypothesized and found that exclusive victimhood and ethnic identity predicted higher, whereas Indonesian national identity predicted lower prejudice, and in turn, higher prejudice predicted lower support for reconciliation. These findings have theoretical implications for research on social identity and collective victimhood and practical consequences for understanding intergroup relations in multi-ethnic post-colonial contexts. [ABSTRACT FROM AUTHOR]

• Paper rethinks the concept of 'labour risk' by emphasizing workers' perspective. • Firms in labour-intensive sectors outsource economic risks to workers. • Focussing on Indonesian cruise ship worker's resilience strategies. • Workers relying on family, virtual community networks and the local labour market. • Workers' resilience strategies central for reproducing capital accumulation regimes. The collapse of the global industry due to the COVID-19 pandemic has demonstrated how precarious the livelihoods of workers embedded in globalised industries are. In the global production network literature, moments of crisis have been addressed in the debate on 'GPN risk'. While this debate has contributed to our understanding of firms' risk mitigation strategies, much less attention has been paid to workers' resilience strategies in the face of risk. To fill this gap, this paper rethinks the concept of 'labour risk' by including the perspective of the workers. Drawing on concepts from labour geography, the article sheds light on the resilience strategies of cruise ship workers from Indonesia during the COVID-19 crisis. We interviewed twenty-two cruise ship workers, two non-governmental organisations, and two political authorities to analyse how workers used different resilience strategies (coping, adaptive and transformative) to respond to the risk outsourcing practices of cruise ship companies. Our study shows that workers cope with the crisis by relying on family relations, virtual community networks, and the local labour market. In a few cases, workers followed adaptive strategies of opening their own businesses and leaving the cruise industry. These results emphasise that workers' resilience strategies play a central role in reproducing exploitative capital accumulation regimes underpinning global production networks. [ABSTRACT FROM AUTHOR]

• Degraded peatland increases the risk and frequency of peat fires. • Peatland restoration programs faced social and environmental challenges. • We frame peatland programs as distortions to the local actor-network. • The non-human actors reshape actor-networks at different levels. • The peatland programs need to be compatible with non-human actors to survive. This paper studies the survivability of peatland-related programs in Indonesia. Despite an increase in the global and national programs for peatland restoration, many of these programs fail to survive in the long-term. To understand this low survivability, this paper examines how peatland-related programs re-arrange the relationship between the local community and peatland across time and how the new actor-network contributes to the survivability of peatland programs. We develop a multi-level actor-network framework that combines the multi-level perspective from transition studies to capture the stability of actors' relationships and power from actor-network theory to investigate how activities mobilise human and non-human actors to comply with a specific program. Our research shows that non-human actors such as peat, paddy, Acacia, and fire shape peatland-related programs by resisting non-suitable crops, by re-shaping the program, by mobilizing human actors, and by creating pressure to the existing regime. We highlight that the survivability of peatland restoration programs is strongly influenced by how they are adjusted to the materiality of these non-human actors. Given the importance of peatland restoration programs, our study provides an approach in which human and non-human come together to generate plural voices to ensure the survival of peatland restoration programs. [ABSTRACT FROM AUTHOR]

Critical thinking is one of the essential skills for learning in the twenty-first century. One strategy to encourage critical thinking skills in learning is to use a learning model that can educate these abilities. The study's conclusions indicate that the only form of training that can aid students in fostering their critical thinking skills is problem-based learning. The purpose of this research is to review articles from indexed journals that explore how well PBL model foster critical thinking skills. This paper discusses aim to describing the research findings that have been tried and published in good reputation daily articles during the past 5 years (2018 – 2022), while mindful of the importance of critical thinking skills to students and the use of PBL models to develop critical thinking skills. The data in this study is focused on data related to problem-based learning models and critical thinking skills in the field of social science. This study is a particular kind of literature study investigation employing the PRISMA method, which has four parts (identification, screening, eligibility and included). It was discovered from the identification, screening, and eligibility results of hundreds of article journals and twenty one papers were gathered from various journal publications. Based on the study's findings, research on the PBL model and critical thinking skills is mostly conducted in universities among numerous Asian nations, with Indonesia accounting for the biggest share. Science is a subject that is extensively researched utilizing quantitative methods. Additionally, it was discovered that other variables were being included in PBL research, in addition to critical thinking skills. It is clear from the results of the review of journal papers that the PBL model can fostering critical thinking skills. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present and analyze the fractional optimal control model for COVID-19 and diabetes co-dynamics, using the Atangana-Baleanu derivative. The positivity and boundedness of the solutions was shown by the method of Laplace transform. The existence and uniqueness of the solutions of the proposed model were established using Banach fixed point Theorem and Leray–Schauder alternative Theorem. The fractional model was also shown to be Hyers-Ulam stable. The model was fitted to the cumulative confirmed daily COVID-19 cases for Indonesia. The simulations of the total number of hospitalized individuals co-infected with COVID-19 and diabetes, at different face-mask compliance levels, when vaccination strategy is maintained reveals that the total number of hospitalized co-infection cases decreases with increase in face-mask compliance levels, while maintaining COVID-19 vaccination. The simulation results show that to curtail COVID-19 and diabetes co-infections, policies and measures to enforce mass COVID-19 vaccination and strict face-mask usage in the public must be put in place. To further cut down the spread of COVID-19 and diabetes co-infection, time dependent controls are added into the fractional model, and the obtained optimal control problem investigated via the Pontryagin's Maximum Principle. [ABSTRACT FROM AUTHOR]

• Reducing modifiable risk factors could prevent the onset of cognitive decline. • Physical multimorbidity–cognitive function association was mediated by depression. • Routine screening for depression in multimorbidity patient may delay dementia onset. This paper explores the role of depressive symptoms (mediator/moderator) in the association between physical multimorbidity (exposure) and cognitive function (outcome) among older adults in the three most populous middle-income countries. This study used cross-sectional data from China (2015 China Health and Retirement Longitudinal Study), India (2017/2018 Longitudinal Ageing Study in India), and Indonesia (2014/2015 Indonesian Family Life Survey), with a total sample of 73,199 respondents aged ≥ 45 years. Three domains of cognitive tests were harmonised across surveys, including time orientation, word recall, and numeracy. The four-way decomposition analysis assessed the mediation and interaction effects between exposure, mediator/moderator, and outcome, adjusted for covariates. The mean age of the respondents (in years) was slightly younger in Indonesia (56.0, SD = 8.8) than in China (59.5, SD = 9.3) and India (60.0, SD = 10.5). The proportion of male respondents was 49.3 % in China, 47.3 % in India, and 47.5 % in Indonesia. Respondents in China had the highest mean cognitive function z scores (54.7, SD = 19.9), followed by India (51.1, SD = 20.0) and Indonesia (51.0, SD = 18.4). Physical multimorbidity was associated with lower cognitive function in China and India (p < 0.0001), with 48.4 % and 40.0 % of the association explained by the mediating effect of depressive symptoms ('overall proportion due to mediation'). The association was not found in Indonesia. Cognitive functions were lower among individuals with physical multimorbidity, and depressive symptoms mainly explained the association. Addressing depressive symptoms among persons with physical multimorbidity is likely to have not only an impact on their mental health but could prevent cognitive decline. [ABSTRACT FROM AUTHOR]

Harvest strategies, also referred to as management procedures, are foundational to evidence-based fisheries decision making. Together with closed-loop simulation testing, termed Management Strategy Evaluation, of potential harvest strategies, they are considered to be best practice. However, the use of these approaches is still mostly limited to a small minority of high-value, data-rich stocks in developed economies. The Indonesian tropical tuna fisheries provide a rare real-world experience where formal empirical harvest strategies were being developed for data-limited fisheries within a developing economy as an operational management tool. The Harvest Strategy Framework is a departure from a previously open-access fishery for tropical tuna in Indonesian archipelagic waters. It outlines the necessary actions to operationalize the harvest strategy, including fisheries monitoring, harvest control rules, associated management measures to meet the management objectives, and immediate actions to reduce the levels of catch as a precautionary measure until the harvest strategy is fully implemented. It was developed over a 9-year national consultative process, commencing in 2014 and culminating in the official adoption of the framework in June 2023. This paper outlines key processes and challenges encountered in stakeholder engagement and technical capacity development within the intricate governance context of Indonesia. We argue that the engagement processes have cemented a future direction towards sustainable and best practice fisheries management in Indonesia and the effective co-production process has potential to show the way for other fisheries in coastal developing states who face similar challenges in managing their national and internationally shared stocks. • Rare example of formal harvest strategies in a developing economy. • Complex multi-species, multi-gear, multi-scale fisheries. • Changes in key personnel, institutional structure caused major disruptions. • Knowledge co-production processes led to institutional capacity development. • Lack of secure funding for resource monitoring remains as key challenge. [ABSTRACT FROM AUTHOR]

As a rapidly developing country, Indonesia faces a challenge in improving air quality that is made more difficult by frequent forest fires linked to deforestation and volcanic eruptions. This paper analyses the link between development and air pollution in 30 Indonesian cities from 2002 to 2019. Air quality is measured using two novel regional air quality indicators (AQIs) for PM 2.5 and PM 10 estimated from weather observations and NASA satellite data on Aerosol Optical Depth (AOD). Results from an Environmental Kuznets Curve (EKC) analysis, based on a dynamic panel data model, show that forest fires and volcanic activity have significantly worsened regional air quality in Indonesia. The model also shows that the EKC hypothesis is rejected for Indonesia as cities have followed a monotonically increasing trend in air pollution with respect to economic growth. An additional 1% of economic growth increased long run pollution as measured by AQI PM 2.5 and PM 10 by 0.35% and 0.46%, and forest fire events by 0.11% and 0.06%. A partial Benefit-Cost Analysis (BCA) of forest fires shows that particulate matter pollution is excessive. Decreasing the frequency of forest fires by 1% would generate a net benefit of between US$17 million to 145 million. The lower estimate of the health benefits exceeds the agricultural benefits of forest fire without accounting for other non-market costs due to forest fires. Our results imply that, as Indonesia grows economically, air quality is likely to continue deteriorating. Further, regions affected by regular volcanic activity and wildfires should apply tighter emission standards to controllable point source emissions from industry and non-point source emissions such as agricultural forest fires. [ABSTRACT FROM AUTHOR]

Post-mining land usage (PMLU) is a critical concern in Indonesia as the country needs to figure out alternatives for repurposing mined land into productive activities which could utilize the available potential. This paper analyzed the technical feasibility, economic viability, socioeconomics, and environmental impact of building a solar power plant as a post-mining land use option. Solar energy generation potential near the equator line can complement the land availability after coal mining operations cease. The technical analysis, financial model, and Monte Carlo simulation were conducted for the techno-economic analysis. The 300 MWp project was estimated to be able to generate 464 gigawatt-hours annually with a setup cost of around 3.1 trillion Rupiah (USD 200 million). The base case net present value (NPV) was 437 billion rupiah (USD 28 million), while the discounted payback period (DPP) was 13 years, suggesting the viability of the project. The simulation results returned 93.99 % certainty that the NPV would be positive, and 94.71 % certainty the DPP would be <25 years. The sensitivity analysis revealed that the top financial risk factors are loan interest, tax rate, feed-in tariff, operating cost, structure cost, array efficiency, solar irradiance, and inflation rate. Solar irradiance and inflation rate are systematic risks that cannot be controlled internally, and array efficiency is limited by 100 %. Five risk factors could be internally managed: loan interest, tax rate, feed-in tariff, operating cost, and structure cost. Furthermore, this system would offer additional socio-economic and environmental benefits such as job creation, biodiversity preservation, and pollution reduction. The system would generate 281,780 tCO 2 annual GHG emission savings. • Post-mining land usage analysis for renewable energy plant is an essential part of the mining plan. • The techno-economic analysis of the solar plant for post mining land usage was investigated. • The optimization combinations are obtained through financial model and Monte Carlo analysis. [ABSTRACT FROM AUTHOR]

Several studies have focused on generating seismic vulnerability maps for earthquake-prone areas, particularly in Indonesia. Building typologies are a key factor in determining vulnerability to earthquakes. However, conducting large-scale field surveys to determine the spatial distribution of building typologies in a city is uneconomical. This paper explores the use of a convolutional neural network (CNN) to automatically detect building typologies from diverse regions in Indonesia, utilizing both conventional and automated building image acquisition processes. In this study, datasets from three distinct image acquisition methods are trained with four unique CNN architectures to identify the best-performing model to classify building typologies. The sample size effect on CNN performance is also investigated. The results showed that randomly sampled Google Street View (GSV) images are the most effective dataset for the CNN model, achieving an f1-score of 84.33%. Among the network architectures tested, MobileNet demonstrated superior performance on the majority of evaluated datasets. As the sample size increases by about 350% in the dataset, there is a positive correlation with up to 2.3% f1-score improvement. Using the best-performing CNN model, two building vulnerability models were employed to assess the spatial distribution of building damage in the urban area of Bandung, considering a hypothetical scenario of an M7 earthquake. Incorporating local construction data, one of the generated maps estimated that approximately 55% of buildings in Bandung would experience moderate to severe structural damage. This study showcases the potential of CNN models in automating regional seismic assessments and providing valuable insights for comprehensive seismic mitigation strategies. • A decision tree to label building typology objectively in Indonesia was developed. • CNN model trained with randomly sampled GSV dataset outperforms other models. • The CNN and probability model generated a city-scale building vulnerability map. [ABSTRACT FROM AUTHOR]

• Tree age is introduced for global and national oil palm suitability assessment. • Other regions have lower proportion of suitable area than Southeast Asia. • Differences in industrial and smallholder oil palm are less obvious than expected. • Market factors and local policies play important role in oil palm production. Oil palm is the dominant global oil crop due to its high productivity and diversified usage in many sectors. Since the late 20th century, oil palm cultivations proliferated in Southeast Asia, West Africa, and Latin America. However, global market factors, different national and regional policies, and smallholder versus commercial planting regimes in different areas lead to significant differences in economic benefits and environmental problems from deforestation and loss of biodiversity. We investigated changes in global and national distributions against suitability and indices of tree age distribution change for industrial oil palm (IOP) and smallholder oil palm (SOP). Spatial and temporal change analyses show that: i) For most tree ages, the proportion of global oil palm planting in suitable areas was less than 50%, but the impact of temporal regimes, from possible market factors and local policies, on planting structure should not be neglected; ii) Central America, South America, and West Africa were less suitable for oil palm cultivation compared to Southeast Asia. While, as two dominant oil palm planting countries, Indonesia and Malaysia had relatively low planting suitability, with 39.23% of Indonesia's IOP, 44.85% of Indonesia's SOP, 30.90% of Malaysia's IOP and 18.77% of Malaysia's SOP in highly and most suitable intervals; iii) There exist clear differences between IOP and SOP in terms of suitability, planting structure and spatial expansion patterns; iv) Hysteresis effect exists between latecomers (countries in West Africa and Latin America) and forerunner (Indonesia and Malaysia) in terms of spatial expansion; v) The spatial expansion patterns of oil palm planting centers have obvious scale effects for both IOP and SOP, with clear inter-country and intra-country differences. This paper reinterprets the global distribution of tree age and spatial expansion pattern and recommends scientific strategies to guide site selection and planting structure that enable oil palm cultivation for sustainable development. [ABSTRACT FROM AUTHOR]

The majority of problems in managing maritime transport originate from fragmented governance. The practice of coordinating decisions across different ports or between port and hinterland can pose a significant challenge in many countries. A related issue is that suggestions for maritime transport governance in the current literature are less clearly focused on the Global South. The present study aimed to identify challenges in improving the governance of maritime transport systems. This paper presents a case study focused on Indonesia to serve as an example from the Global South. We conducted a content analysis of policy and implementation documents to paint a comprehensive picture of contemporary governance practices and the challenges encountered in maritime transport. Here, maritime transport is defined as a system that consists of three main subsystems: port-to-port, within-port, and port-to-hinterland connectivity. Our study illustrates that the same maritime transportation system in the Global South can have different governance patterns with different strengths and weaknesses. We point to the importance for transportation planners and policy makers in the Global South to be aware that fragmentation must be understood in view of these interrelated subsystems, but also that coordination requires a focus on practicalities and thus that less-comprehensive forms of integration may well be legitimate in policy formulation. In improving maritime transport systems, transportation planners and policymakers in the Global South must be aware of the challenge that changes in one sub-system will define other sub-systems while no universal one-fits-all solution for the whole system exists. [ABSTRACT FROM AUTHOR]