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Archives are a collection of documents that contain information and have useful value for a certain period of time. Every information institution, especially in the archives sector, needs to have archive management, including recording, storage, maintenance and depreciation. The Bandung City Library and Archives Service as an information institution should have good archive management. Therefore, researchers are interested in conducting this research to find out how archives are managed and the obstacles experienced by the Bandung City Library and Archives Service. This research uses descriptive qualitative research methods and data collection methods through observation, interviews and documentation techniques. The research conclusion is that archive management at the Bandung City Library and Archives Service is in accordance with Law Number 49 of 2009 concerning archives, starting from creation, storage, maintenance and depreciation. However, in its management the Library and Archives Service still has obstacles, such as a lack of human resources and a lack of infrastructure in the form of space to accommodate archives.

The Lotka–Volterra predator–prey system for dynamic sea turtle population is solved using r-PINN-Adam method, a novel approach which combines Physics-Informed Neural Network (PINN) with restarting strategy. This method allows us to monitor the loss function values of PINN such that when there is no progress made, we stop the process and pick a good value to be used in the next process. Subsequently, the training time decreases and the accuracy increases. The numerical solutions are compared to the popular Runge–Kutta method in terms of correctness which presented graphically. Simulation results also displayed in terms of trainable parameters and optimal loss function performance. The research highlights the robustness and superiority of the proposed method, positioning it as a valuable tool for sea turtle conservation efforts.

The main objective of research is to ascertain the existing situation of STEAM education research over three decades based on the Scopus database. The entire documents are 256 findings globally data shorted by year, region, and highest cited to 100 documents. The analysis technique used VOSViewer, Microsoft Excel and word cloud generator. The result of document type articel is ranks first in Global and conference paper rank first in South East Asia. The sources that have published the top cited papers are “Journal of Small Business Management” in global and the “Education Sciences” in South East Asia. Meanwhile, the author with the most citations is Jeon M from the U.S.A. Specifically, the country with the most publications is US with 31 articles and 2553 citations. Whereas the majority of Southeast Asian countries have 9 articles and 10 citations. Supported the visualization analysis, VOSViewer's global region is divided into 4 clusters and 62 keywords to assist with the visualization analysis. A pair of clusters containing 14 keywords each for the South Asia region. The terms program, project, environment, model, and implication are frequently used in STEAM throughout the world. The keyword STEAM education appears in analyses conducted in South-East Asia. The outcome of this research can serve as a resource for scholars interested in STEAM and education. Further research into STEAM education trends can be conducted by focusing on a single region or on more specific issues.

Partial differential equations (PDEs) are essential mathematical models for describing a wide range of physical phenomena. Numerically, Physic-Informed Neural Networks (PINNs), a variant of artificial neural networks, present a promising method for solving PDEs. However, due to limitation in accuracy and stability, various adaptive PINN variants have been proposed. We have designed a novel approach that adopted self-adaptive PINN (SA-PINN) with two optimization techniques: the genetic algorithm (GA) and the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. Self-adaptive PINN modifies the weights in the loss function to be fully trainable, enabling the ANN to learn and stabilize the PINN in approximating the difficult regions of the solution. GA initializes the population of ANN trainable parameters to optimize the training process with less number of iterations, while L-BFGS is used to find the best solution accurately. Our proposed approach, named SA-PINN-GA-LBFGS, is tested on solving several benchmark PDE problems including elliptic, parabolic, and hyperbolic types. We compare our results with state-of-the-art methods, demonstrating that SA-PINN-GA-LBFGS provides higher accuracy and greater efficiency.

This study aimed to describe the feasibility of inquiry-oriented electronic student worksheets using live worksheets on chemical equilibrium material to train the analytical thinking skills of class XI students of Senior High School. The feasibility of the Electronic Student Worksheet is viewed from validity, effectiveness, and practicality. This study uses the Research and Development (R&D) method. A limited trial was conducted in April 2023 for 30 students who had received chemical equilibrium material. The results showed that the validity of the electronic student worksheet was stated to be valid based on the results of the validation of the electronic student worksheet, which received a mode of 4. The practicality of the electronic student worksheet was stated to be practical with a percentage of 93.7%. The electronic student worksheet was declared effective based on the t-test results with a significance level of 5% obtained tcount>ttable of 12.294>2.045, which means Ho was rejected, Ha was accepted, and the N-gain score was 0.7. Based on these results, it can be concluded that electronic student worksheet is appropriate to be used to train analytical thinking skills in chemical equilibrium material.

Teachers' language assessment literacy (LAL) refers to teachers' ability to perform assessment-related tasks. Despite the significant role of language assessment literacy in English language teaching and learning, many teachers reported to have an inadequate ability to perform assessment-related tasks because of the lack of assessment training programs that prepared them for the tasks. This study aimed at investigating the existing assessment training programs to develop EFL teachers' LAL. A systematic literature review was conducted to observe trends in how assessment training programs were carried out in the past decades. PRISMA model was used for identifying, screening, and selecting. Twenty-eight studies published between 2012 and 2022 were reviewed. The results reveal that the assessment training models comprised theoretical and practical components of language assessments. The results also show that the methods for delivering the content are collaborative and reflective practices. The findings of this study should be considered in the design of EFL teacher training programs on assessment.

Traditionally, partial differential equation (PDE) problems are solved numerically through a discretization process. Iterative methods are then used to determine the algebraic system generated by this process. Recently, scientists have emerged artificial neural networks (ANNs), which solve PDE problems without a discretization process. Therefore, in view of the interest in developing ANN in solving PDEs, scientists investigated the variations of ANN which perform better than the classical discretization approaches. In this study, we discussed three methods for solving PDEs effectively, namely Pydens, NeuroDiffEq and Nangs methods. Pydens is the modified Deep Galerkin method (DGM) on the part of the approximate functions of PDEs. Then, NeuroDiffEq is the ANN model based on the trial analytical solution (TAS). Lastly, Nangs is the ANN-based method which uses the grid points for the training data. We compared the numerical results by solving the PDEs in terms of the accuracy and efficiency of the three methods. The results showed that NeuroDiffeq and Nangs have better performance in solving high-dimensional PDEs than the Pydens, while Pydens is only suitable for low-dimensional problems.

Breast cancer is a serious health concern for women in both developed and developing countries, and early diagnosis is crucial for an effective treatment. One possible approach of detection is by observing abnormal surface temperatures of the breast. To study the thermal behavior of the human breast, this research paper employs the two-dimensional heat equation’s partial differential equation (PDE). In fact, we propose a method called r-PINN-Adam, which uses Physics-Informed Neural Networks (PINN) with a restarting strategy to solve the PDE thermal analysis. PINN is a method that incorporates physical law in each dataset to solve PDE problems, while Adam is used to update the weights of the ANN and minimize the loss function. The restarting process monitors the progress of the loss values, and if no improvement is made, the process is restarted with the best weights as the initial input to the next cycle. This approach ensures that the method finds the smallest value of the loss function, and it is also more efficient as no time is wasted on iterations that do not significantly improve the results. The PDE thermal analysis was solved for normal and tumorous breasts to study the temperature behavior surrounding the cancer. The proposed r-PINN-Adam method was compared to the basic PINN and other optimizers in terms of accuracy and efficiency. The numerical results indicated that our proposed method yields competitive results compared to state-of-the-art methods, while significantly reducing computational time.

Lanczos iterative methods for solving a large sparse linear systems typically face the latent breakdown which strikes every time these methods are deployed. A number of approaches to deal with this issue have been investigated. One of them is by switching between the solvers preemptively breakdown. However, the problem is not fully solved yet. Here, we propose switching models combined with particular Lanczos iterative methods. The first model is by using the last iterate as the switching point with an unlimited number of iterations, the second model is by using the iterate with the minimum residual norm as the initial point and the third model is by using the iterate with the minimum of minimum residual norms as the switching point. These three models lead algorithms of SLULast, SLUMinRes, and SLUMoM, respectively. The parallel version of the proposed algorithms is also provided to speed up their convergence. In this case, we constructed the parallel of SLUMoM and we call it pSLUMoM. The numerical results showed that our switching models performed better than the existing switching strategy in terms of robustness and efficiency. In fact, under a parallel framework, pSLUMoM showed a performance gain of up to 50% in our experiments.

Cancer is a disease characterized by the uncontrolled growth and spread of abnormal cells in an organ of the human body. Asia is the continent that has the most significant number of new cases of cancer, with a percentage of 49.3% of the number of cancer patients in the world. Preventive action to deal with the spread of cancer is the responsibility of the government to improve the quality of health in the country, so it is necessary to take action to prevent the spread of cancer and help archieve the Sustainable Development Goals (SDGs) at the third point in the field of health. One of them is by determining the characteristics of the cancer and clustering countries in Asia based on their characteristics. This article will discuss the clustering of countries in Asia using fuzzy clustering in the form of fuzzy k-means, fuzzy Gustafson-Kessel babushka and fuzzy k-medoids. the results obtained from the analysis show that using fuzzy k-means will have a more excellent fuzzy silhouette index value compared to fuzzy Gustafson-Kessel babushka and fuzzy k-medoids, which is 0.6313.

One of the factors causing this increase is energy use in the housing sector. Based on reports from the BPS-Statistics Indonesia, there is still a shortage of 12.7 million houses. To meet this shortage, the Indonesian government provides subsidies for the provision of affordable housing as well as design standards for healthy affordable housing for low-income people. One option to optimize energy use in a residential home without incurring large additional costs is through the use of passive design. One of the determining factors in passive building design to reduce energy use is through determining the building orientation. This research will investigate the relationship between orientation and energy use in affordable housing in Indonesia. Through simulations carried out in conjunction with 24 orientations of healthy affordable housing in Indonesia, orientations that provide the best optimization value for energy use will be obtained. This research will only examine one parameter: building orientation. By knowing the optimal orientation and the energy that can be reduced through implementing this orientation, it is hoped that this research can be taken into consideration by the Indonesian government in making regulations regarding the orientation of healthy affordable housing in Indonesia.

Cases of food poisoning often occur due to food contamination caused by pathogenic bacteria. One of the pathogenic bacteria is Vibrio parahaemolyticus which is found in seafood. Thus, a fast, accurate and specific detection method is needed. The purpose of this study was to quickly detect Vibrio parahaemolyticus bacteria in seafood samples targeting the ToxR gene using Real Time PCR. In a previous study, gradient PCR was used to optimize ideal annealing temperature ranges from 53-62°C and revealed that 58°C produced the best outcomes for the ToxR primer with a size of 171 base pairs. Real-Time PCR was utilized to amplify, specify, and test for sensitivity under the ideal conditions from the PCR Gradient. The confirmation results show that the primer pairs could amplify ToxR of Vibrio parahaemolyticus with the amount of concentration as much as 50 ng/µL with Ct 10,69 and 10,32 and melting curve at temperature 82,18°C and 82,23°C. This primer pair can also distinguish non-target bacteria with different Ct and melting curve temperature. The sensitivity assay for this primer can amplify DNA templates at concentration 0,0032 ng/µL. Shrimp samples that are contaminated artificially can still be detected at Ct 13,02 and Ct 13,09. Based on these results, it can be concluded that Real Time PCR with ToxR primer can be applied to develop a detection kit for Vibrio parahaemolyticus in seafood.

Background Abrupt implementation of lockdowns during the coronavirus disease 2019 (COVID-19) pandemic affected the management of diabetes mellitus in patients worldwide. Limited access to health facilities and lifestyle changes potentially affected metabolic parameters in patients at risk. We conducted a meta-analysis to determine any differences in the control of metabolic parameters in patients with diabetes, before and during lockdown. Methods We performed searches of five databases. Meta-analyses were carried out using random- or fixed-effect approaches to glycaemic control parameters as the primary outcome: glycosylated hemoglobin (HbA1c), random blood glucose (RBG), fasting blood glucose (FBG), time-in-range (TIR), time-above-range (TAR), time-below-range (TBR). Mean difference (MD), confidence interval (CI), and P value were calculated. Lipid profile was a secondary outcome and is presented as a descriptive analysis. Results Twenty-one studies enrolling a total of 3,992 patients with type 1 or type 2 diabetes mellitus (T1DM or T2DM) were included in the study. Patients with T1DM showed a significant improvement of TIR and TAR (MD=3.52% [95% CI, 0.29 to 6.74], I2=76%, P=0.03; MD=−3.36% [95% CI, −6.48 to −0.25], I2=75%, P=0.03), while FBG among patients with T2DM significantly worsened (MD=3.47 mg/dL [95% CI, 1.22 to 5.73], I2=0%, P

Evolutionary computing is an exciting sub-field of soft computing. Many evolutionary algorithm based on the Darwinian principles of natural selection are developed under the umbrella of EC in the last two decades. EAs provide a set of optimal solutions in single simulation unlike traditional optimization techniques for dealing with large-scale global optimization and search problems. Teaching Learning based Optimization (TLBO) is one of the most recently developed EA. TLBO employs a group of learners or a class of learners to perform global optimization search process. The framework of the TLBO consists of two phases, including the Teacher Phase and Learner Phase. The Teacher Phase’ means learning from the teachers and the Learner Phase means learning through interaction among learners. In this paper, we have developed a hybrid TLBO (HTLBO) with aim at to further improve the exploration and exploitation abilities of the baseline TLBO algorithm. The performance of the proposed HTLBO algorithm examined upon using recently designed benchmark functions for the special session of the CEC2017 problems. The experimental results of the proposed algorithm are better than some well-known evolutionary algorithms in terms of proximity and diversity.

The purpose of this study was to analyze the scope related to the subject of problem-solving skills based on multiple representation in 2016 – 2020 with 20 documents through bibliometric analysis. The research method used was a literature study through all the articles analyzed in this study. The articles were taken from the Scopus database with sampling in 2003 – 2020, resulting in 29 scientific work data exported in *.ris (RIS) and *CVS formats. Then, those data were processed using VOSviewer and Microsoft Excel. The results of publications in the last five years have increased. Indonesia is the dominant country in publicizing papers about this topic. Institutions from Germany managed to publish most of the documents about multi representation. Meanwhile, Poland is the origin country of the authors with most publications. The visualization of research trends on multi representation resulted in four main clusters: (1) multi representation related to students, representation, and learning processes (2) multi representation as a class (3) multi representation related to the problem (4) multi representation as a model and process. Meanwhile, Indonesian researchers are very active in contributing to this topic, in line with the number of publications by country, namely Indonesia.

This study aims to analyze research trends related to PjBL-STEM topics in 2016-2020 through bibliometric analysis with the Scopus database. Based on the criteria, it obtained 1,169 documents. Microsoft Excel was used to analyze data and VOS viewer as a data visualization. The results showed that PjBL-STEM research is increasing every year. The USA contributes the most research in the world, Indonesia ranks second. Universitas Pendidikan Indonesia, Universitas Negeri Malang, Universitas Sebelas Maret, and Universitas Negeri Semarang are among the top affiliates in PjBL-STEM research in the world. Visualizing the trend of PjBL-STEM research in 2016-2020, there are three clusters, namely 1.) PjBL-STEM as a framework, 2.) PjBL-STEM as self-development, and 3.) Effects of PjBL-STEM research. The results of this study can help researchers related to PjBL-STEM research trends in the world and provide direction in further research.

The quality of education can be improved by developing learning methods, curriculum development, and learning media development. One of them is learning media in the form of comics. This research aims to develop physics comics and analyze the validity of learning media of physics comics on the historical material of atomic development. The research was conducted using the R&D research model (Research and Development) with the 4-D model (Define-Design-Develop-Disseminate). Based on the stages, obtained learning media products that were declared eligible after validation by two high school physics teachers and an expert lecturer gained the average validity in the media component of 90.0%, the display of 89.2%, the material by 90.7%, and the language by 95.4%. In general, the student's responses to the use of physical comic learning media include comic physics can increase motivation in learning (88.6%), students prefer that physics learning uses comic media (88.9%), through comic media, students are introduced to atomic inventors (88.9%), and physics comics can help to understand the historical material of atomic development (83.3%). Based on the study results, learning media of physics comics on the historical material of atomic development deserves to be used in physics. The implication of this study can help other researchers as a reference related to the development of comic physics learning media.

This article describes the impact of postponement of Umrah and Hajj towards Indonesia during Covid-19 pandemic. The bilateral relations between Saudi Arabia and Indonesia have been going on for a long time. Hajj and Umrah visits are one way to establish bilateral cooperation between Indonesia and Saudi Arabia. During pandemic, Saudi Arabia make a foreign policy to postponement Umrah and Hajj, this policy make Indonesian Muslim unable to pilgrimage Umrah and Hajj. This postponement will impact Indonesia in many sectors. The research method used in this study is a descriptive study and library research aims to understand the reasons for a state to make a foreign policy and understand the impact of these policies towards Indonesia. Islamic Jurisprudence (Fiqh) concept, Foreign Policy theory, and Foreign Policy Impact Theory are used to analyze the impact of postponement Hajj and Umrah. The findings confirm that the actors that felt the impact were the government, Hajj and Umrah travel agents, and also the Hajj and Umrah pilgrims from Indonesia.

This study aims to map the landscape of the importance of previous research on computational thinking (CT) in mathematics learning over the last decade. This research is a literature review research, there are 113 publications collected from the Scopus database which are then analyzed using the bibliometric analysis method assisted by the Vosviewer application. The data taken from the Scopus database was refined so that it became 113 publications. The results of the study show that publications are spread across various continents, including America, Asia, Africa, and Europe. The United States and the United Kingdom are the most influential countries and have high cooperation with other countries in this field. The main conclusion from this study is that computational thinking has an important role in learning mathematics and STEM. The integration of computational thinking in the mathematics curriculum can improve students' understanding of mathematics and help them face the challenges of the digital age. In addition, the development of effective training methods for mathematics teachers as well as the assessment of good computational thinking learning tools and platforms can help improve the effectiveness of computational thinking teaching in mathematics contexts. These innovations will help better understand how computational thinking can be effectively integrated in mathematics learning and prepare students for a future filled with digital technologies.

In this paper, one dimensional mathematical model of convective-conductive-radiative fins is presented with thermal conductivity depending on temperature. The temperature field with insulated tip is determined for a fin in convective, conductive and radiative environments. Moreover, an intelligent soft computing paradigm named as the LeNN-WOA-NM algorithm is designed to analyze the mathematical model for the temperature field of convective-conductive-radiative fins. The proposed algorithm uses function approximating ability of Legendre polynomials based on artificial neural networks (ANN’s), global search optimization ability of Whale optimization algorithm (WOA), and local search convergence of Nelder-Mead algorithm. The proposed algorithm is applied to illustrate the effect of variations in coefficients of convection, radiation heat losses, and dimensionless parameter of thermal conductivity on temperature distribution of conductive-convective and radiative fins in convective and radiative environments. The experimental data establishes the effectiveness of the design scheme when compared with techniques in the latest literature. It can be observed that accuracy of approximate temperature increases with lower values of $N_{c}$ and $N_{r}$ while decreases with increase in $\lambda $ . The quality of solutions obtained by LeNN-WOA-NM algorithm are validated through performance indicators including absolute errors, MAD, TIC, and ENSE.

ASEAN, include Indonesia, Malaysia, Philippines, Singapore, and Thailand, are the countries with ongoing transmission of SARS-COV-2, the virus that causes COVID-19. The confirmed cases in Indonesia and Philippines are the highest ranks among other ASEAN countries such as Malaysia, Thailand, and Singapore. To reduce the spread of the pandemic COVID-19, each country has implemented the lock-down policy differently, depending on its economic situation. Therefore, the study of the impact of lock-down across the world, particularly in ASEAN countries, is still relevant to do. In this study, we developed the lock-down model in ASEAN countries by using hybrid ARIMA-SVR and hybrid SEIR-ANN. The first hybrid is based on the time series model ARIMA, with the revision of the error is by using SVR. The second hybrid is based on the classical model of infectious diseases, SEIR, which we revise on the prediction part by using ANN. The hybrid is intended to revise the individual prediction model. The data collected per country was started from January 20, 2020 to August 5, 2020. The periods of lock-down in this study are divided into three, namely no lock-down, implemented lock-down, and the new normal periods. The strictness levels of lock-down were predicted for 60 days ahead. The results showed that the hybrid ARIMA-SVR had smaller RMSE compared with individual ARIMA, similarly, hybrid SEIR-ANN predicted S, E, I, and R more accurately compared with individual SEIR model. It has been also found that the lock down was most effectively implemented in Thailand, Singapore, and Malaysia, whereas Indonesia and Philippines were inefficient countries to enforce the restriction. It is indicated by the number of cases increased significantly during the restriction periods in both countries.

In the present article, mathematical analysis of drilling system with reverse air circulation is presented by a novel hybrid technique of feedforward artificial neural network (ANN) and biogeography based cuckoo search (BHCS) algorithm. A series solution is constructed with unknown weights for the differential equations representing the drilling problem. Five numerical cases are analysed to show the effectiveness of our method for the solution of differential equations. From the experimental outcomes, it is investigated that our soft computing procedure has a better rate of convergence to the best solution as compared to state-of-the-art techniques. From solution graphs, it is established that our results are in agreement with the reference solutions. It is noted that our technique is easy to implement and can be used for any mathematical model containing nonlinear differential equations. The graphical abstract of this article is given in Figure (1). FIGURE 1.Graphical illustration of the soft computing procedure followed in this paper.

Background: Physical exercise has a lot of benefit for health. However, the effect of cognitive function such as concentration in teenagers has yet been known. Aims: The objective of this study was to analyze the effect of a single bout or acute moderate intensity physical exercise on the level of concentration in teenagers. Methods: The subjects of this study were 32 16-18 years old teenagers, divided into two groups, control (C) and exercise (E) groups. Each group consisted of 8 boys and 8 girls. The E group did a single bout of moderate exercise using ergocycle. Physical exercise duration was 15 minutes, preceded by 5 minutes of warming up and then followed by 5 minutes of cooling down exercise. The concentration level was measured using the response period to sound stimulation (in second), measured with reaction time machine pre- and post-treatment. Faster response showed better concentration level and vice versa. Data were analyzed using paired T test, Wilcoxon Signed Ranks Test, independent T test, and Mann-Whitney test. The significance level was 5%. Result: There were significant differences of concentration level between pre- and post-exercise in E group (p= 0.004) and post-exercise concentration level between groups (p = 0.01). Exercise group had faster reaction time than C group (0.555±0.2 vs. 0.793±0.3, respectively). Conclusion: A single bout of moderate intensity exercise can improve the cognitive function showed by increased concentration level in teenagers.

The technological disruption and conventional health services that required consumers to meet directly with health practitioners can now be accelerated through health service technology known as digital healthcare applications. In Indonesia, the use of digital healthcare applications increased rapidly when the Covid-19 pandemic hit the world. Therefore, the conventional health care service no longer suits the current market of health care. This study aimed to examine the factors in determining their influence on consumer reuse intentions in using digital healthcare applications. The methodology used is a quantitative method, with data collected by an electronic survey of customers using health care applications. Data is analyzed using SEM PLS. The finding showed that perceived usefulness, trust, privacy, and PEOU have and provide a positive influence on re-usage intention in reusing digital healthcare applications. However, this study did not test the mediation or moderation of the variables. Therefore, external variables limited to trust and privacy need to be explored further so that other external variables that might affect the use of digital healthcare applications can be obtained.

Gold can now be invested digitally through e-commerce platforms. However, Indonesian people generally invest in gold traditionally in physical form. This study aims to identify the intentions and behavior of investors in investing in gold on e-commerce platforms by proving the effect of Attitude, Subjective Norms, Perceived Behavioral Control, Perceived Usefulness, and Perceived Ease of Use variables on Intention to invest. The research uses quantitative methods with data collected through online surveys. The sample was selected using a purposive sampling method, with 261 respondents contained. The study’s results prove that Attitude, Perceived Behavioral Control, and Perceived Usefulness are significantly and positively related to the Intention to Invest. Perceived Usefulness is also demonstrated to have a significant and positive relationship with Attitude. On the other hand, Subjective Norms and Perceived Ease of Use are not significant to Intention to Invest. Perceived Ease of Use also does not demonstrate a substantial Attitude. This study reveals that variables of attitude, perceptions of behavioral control, and perceptions of use value are proven to increase investor intentions in investing in gold digitally. This research can also add to the knowledge in the study of gold investment, especially those carried out digitally through e-commerce platforms.

The goal of writing this article is to convey the efforts of SMK Negeri 3 Pamekasan to contribute to the revitalization of the local knowledge of Pamekasan Regency, namely batik, by participation in a competition. This article draws on a variety of literatures, including those pertaining to design thinking methodologies, digital innovation, and stakeholder approaches. The scenario analysis method was used in the production of this paper. The most of the information comes from Google. Once the data had been collected, it was subjected to an analysis process that included steps such as data selection, data processing, and data assessment that were deemed important to the aim of the writing. The findings of this paper demonstrate the importance of digital innovation in resurrecting Pamekasan batik via the Teaching Factory of Visual Communication Design, as shown in this article.

Problem-solving skills are the skills essential for students to have. This research aimed to analyze the problem-solving skills of senior high school students in biology learning of excretory system topics. The method used was descriptive-quantitative. The data were collected using a problem-solving essay test. The subjects were the eleventh-grade students of senior high schools in Surakarta, who were divided into A category (upper class) and B category (low level). Based on the analysis result, it can be seen that the problem-solving skill achievement of the eleventh grade of A group includes: defining the problem (50.78%), examining the problem (40.62%), planning a solution (19.53%), implementing the solution (37.50%), and evaluating (40.62%); while that of B category includes: Defining the problem (46.35%), examining the issue (34.67%), planning a solution (18.54%), implementing the solution (20.96%), and evaluating (32.25%). The lowest percentage in both categories was found in planning the solution and evaluating. Based on the result, the average problem-solving skills in A group is 37.81% and B Category 32,26%. Based on the data, it can be concluded that students' problem-solving skills in A and B categories are still low. The skills can be improved by conducting problem-solving based learning and familiarizing students to solve problems according to problem-solving stages.

Previous research which found that adolescent tend to involve in radicalism make interesting to find out the relationship between identity status and religious tolerance in adolescence. This research involved 157 participants whose ages ranged from 11 to 24 years. The variable of identity status was conceptualized based on Erikson’s exploration and commitment aspects, and was measured using Ego Identity Process Questionnaire (EIPQ). Meanwhile, religious tolerance was measured using a rating scale adapted from van der Walt’s religious tolerance scale. This study found negative relationship between commitment and religious tolerance, and there is no a relationship between exploration and religious tolerance. From four identity status tested, it is found that most participants are in the category of identity diffusion which means that most participants have no specific commitment and interest in ideology. The result also shows that identity moratorium has the highest mean in religious tolerance, and it is found significantly different with identity achievement and identity foreclosure. Based on the commitment aspect, participants with achievement and foreclosure identity status tend to be religiously intolerance, while those with identity moratorium are found most open to the others’ worldviews. Keywords: Identity status, religious tolerance, adolescent Abstrak: Adanya survei yang menunjukkan besarnya kecenderungan remaja untuk melakukan tindakan radikalisme melandasi dilakukannya penelitian ini yang bertujuan untuk melihat korelasi antara status identitas dan toleransi beragama pada remaja. Responden pada penelitian ini sebanyak 157 remaja dengan rentang usia 11-24 tahun, yang dimasukkan dalam 4 kategori status identitas. Status identitas diukur dengan menggunakan dua kriteria utama pembentukan identitas dari Erikson, yaitu exploration dan commitment, serta diukur menggunakan skala Ego Identity Process Questionnaire (EIPQ). Toleransi beragama diukur menggunakan skala toleransi agama yang diadaptasi dari skala yang disusun van der Walt. Hasil analisis menunjukkan bahwa ada hubungan negatif antara dimensi komitmen dengan toleransi beragama, sedangkan dimensi eksplorasi dengan toleransi beragama tidak terbukti berhubungan. Hasil uji terhadap 4 kategori status identitas menunjukkan bahwa sebagian besar partisipan berada dalam kategori identitas diffusion yang berarti tidak memiliki komitmen ideologis. Selain itu, identity moratorium memiliki rerata yang paling tinggi dalam toleransi beragama dan berbeda signifikan dengan identity achievement dan identity foreclosure. Berdasarkan pada tingginya dimensi komitmen dan karakteristik masing-masing kategori status identitas, identity achieve-ment dan identity foreclosure merupakan kategori yang memiliki kecenderungan untuk bersikap intoleran, sedangkan identity moratorium masih memiliki keterbukaan terhadap perbedaan agama atau ideologi.

This article discussed about globalization that eliminated physical borders between coun- tries in the world so that it considered a variable of social change in various fields. One of the important issues related to globalization was whether globalization related to things that were typical of a group, namely the value of the dominant group and has advantages in various aspects of life. Indonesian society has a distinctive value, namely Pancasila. The study method used Pearson correlation analysis to test two significance of two variables, knowing the strong-weak relationship, and knowing the amount of retribution and to explain the degree of relationship between indepen- dent variables with dependent variables. This article also discussed about the measurement the relationship between values formulated in Pancasila and correlated with the global identity. The results obtained that the higher score of Pancasila equal with the person global identity score. This happens to all values of Pancasila. These results could be a marker that the value of Pancasila relevant for Indonesian people in the face of globalization.

Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms (EAs) were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark functions and various real-world problems. In general, the developed evolutionary algorithms (EAs) belong to nature-inspired algorithms (NIAs) and swarm intelligence (SI) paradigms. Differential evolutionary algorithm is one of the most popular and well-known EAs and has secured top ranks in most of the EA competitions in the special session of the IEEE Congress on Evolutionary Computation. In this paper, a customized differential evolutionary algorithm is suggested and applied on twenty-nine large-scale bound-constrained benchmark functions. The suggested C-DE algorithm has obtained promising numerical results in its 51 independent runs of simulations. Most of the 2013 IEEE-CEC benchmark functions are tackled efficiently in terms of proximity and diversity.

Coccinia grandis or ivy gourd is an edible plant. Its leaves and fruits are used as vegetable in many countries. Many works on antidiabetic activity of a crude extract of C. grandis, i.e., in vitro, in vivo, and clinical trials studies, have been reported. Profiles of the antidiabetic compounds were previously proposed by using LC-MS or GC-MS. However, the compounds responsible for antidiabetic activity have rarely been isolated and characterized by analysis of 1D and 2D NMR data. In the present work, UHPLC-ESI-QTOF-MS/MS analysis and GNPS molecular networking were used to guide the isolation of α-glucosidase inhibitors from an extract of C. grandis leaves. Seven flavonoid glycosides including rutin (1), kaempferol 3-O-rutinoside (2) or nicotiflorin, kaempferol 3-O-robinobioside (3), quercetin 3-O-robinobioside (4), quercetin 3-O-β-D-apiofuranosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-glucopyranoside (5) or CTN-986, kaempferol 3-O-β-D-api-furanosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-glucopyranoside (6), and kaempferol 3-O-β-D-apiofuranosyl-(1→2)-[α-L-rhamnopyranosyl-(1→6)]-β-D-galactopyranoside (7) were isolated from C. grandis leaves. This is the first report of glycosides containing apiose sugar in the genus Coccinia. These glycosides exhibited remarkable α-glucosidase inhibitory activity, being 4.4–10.3 times more potent than acarbose. Moreover, they also displayed virucidal activity against influenza A virus H1N1, as revealed by the ASTM E1053-20 method.

In this study, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering. The mathematical models of the problems are exploited by the intelligent strength of Euler polynomials based Euler neural networks (ENN’s), optimized with a generalized normal distribution optimization (GNDO) algorithm and Interior point algorithm (IPA). In this scheme, ENN’s based differential equation models are constructed in an unsupervised manner, in which the neurons are trained by GNDO as an effective global search technique and IPA, which enhances the local search convergence. Moreover, a temperature distribution of heat transfer and natural convection porous fin are investigated by using an ENN-GNDO-IPA algorithm under the influence of variations in specific heat, thermal conductivity, internal heat generation, and heat transfer rate, respectively. A large number of executions are performed on the proposed technique for different cases to determine the reliability and effectiveness through various performance indicators including Nash–Sutcliffe efficiency (NSE), error in Nash–Sutcliffe efficiency (ENSE), mean absolute error (MAE), and Thiel’s inequality coefficient (TIC). Extensive graphical and statistical analysis shows the dominance of the proposed algorithm with state-of-the-art algorithms and numerical solver RK-4.

The study aims to investigate the English presentation self-efficacy of ESP undergraduate students through a longitudinal-experimental research design. Rooted in Bandura's social cognitive theory, it addresses two research problems: how Indonesian ESP undergraduate students' English presentation self-efficacy developed when they were exposed to mastery experience in the form of presentation tasks, and how individual and group presentation tasks affected the English presentation self-efficacy development. Three groups of ESP undergraduate students (n = 107) taking ESP English for Management were purposively selected as the participants for the study. Each group was exposed to one of the three forms of interventions: individual presentation tasks, homogeneous-group presentation tasks, and heterogeneous-group presentation tasks. A Likert-type presentation self-efficacy questionnaire validated by exploratory factor analysis (EFA) was utilized to collect the data in Weeks 3, 8, 12, and 16 of the semester. The study found that the Indonesian ESP undergraduate students' English presentation self-efficacy developed significantly as they completed the presentation tasks. The homogeneous-group presentation task outperformed both the heterogeneous-group and individual presentation tasks in enhancing English presentation self-efficacy. Implications for the teaching practices, study limitations, and future research recommendations are presented.