Search

The presence of volatility in residential property market prices helps investors generate substantial profit while also causing fear among investors since high volatility implies a high return with a high risk. In a financial time series, volatility refers to the degree to which the residential property market price increases or decreases during a particular period. The present study aims to forecast the volatility returns of real residential property prices (RRPP) in Malaysia using three different families of generalized autoregressive conditional heteroskedasticity (GARCH) models. The study compared the standard GARCH, EGARCH, and GJR-GARCH models to determine which model offers a better volatility forecasting ability. The results revealed that the GJR-GARCH (1,1) model is the most suitable to forecast the volatility of the Malaysian RRPP index based on the goodness-of-fit metric. Finally, the volatility forecast using the rolling window shows that the volatility of the quarterly index decreased in the third quarter (Q3) of 2021 and stabilized at the beginning of the first quarter (Q1) of 2023. Therefore, the best time to start investing in the purchase of real residential property in Malaysia would be the first quarter of 2023. The findings of this study can help Malaysian policymakers, developers, and investors understand the high and low volatility periods in the prices of residential properties to make better investment decisions.

Public health is an important aspect of community activities, making research on health necessary because it is a crucial field in maintaining and improving the quality of life in society as a whole. Research on public health allows for a deeper understanding of the health problems faced by a population, including disease prevalence, risk factors, and other determinants of health. This work aims to explore the potential of hospital patient data analysis as a valuable tool for understanding community implications and deriving insights for effective community health interventions. The study recognises the significance of harnessing the vast amount of data generated within hospital settings to inform population-level health strategies. The methodology employed in this study involves the collection and analysis of deidentified patient data from a representative sample of a hospital in Indonesia. Various data analysis techniques, such as statistical modelling, data mining, and machine learning algorithms, are utilised to identify patterns, trends, and associations within the data. A program written in Python is used to analyse patient data in a hospital for five years, from 2018 to 2022. These findings are then interpreted within the context of public health implications, considering factors such as disease prevalence, socioeconomic determinants, and healthcare utilisation patterns. The results of the data analysis provide valuable insights into the public health implications of hospital patient data. The research also covers predictions for the patient data to the hospital based on disease, age, and geographical residence. The research prediction shows that, in the year 2023, the number of patients will not be considerably affected by the infection, but in March to April 2024 the number will increase significantly up to 10,000 patients due to the trend in the previous year at the end of 2022. These recommendations encompass targeted prevention strategies, improved healthcare delivery models, and community engagement initiatives. The research emphasises the importance of collaboration between healthcare providers, policymakers, and community stakeholders in implementing and evaluating these interventions. [ABSTRACT FROM AUTHOR]

The use of the smart office concept in security has increased significantly recently. One of the areas of concern is the use of facial finger biometric technology for authentication systems, for example, authentication to enter a particular room in an office. This paper aims to describe a new prototype for office door automation and security that combines facial biometric technology and NodeMCU. Hopefully, this system will help increase the safety and comfort of office employees with easy installation and low cost. This system automatically controls (opens or closes) the door based on the biometrics of the user’s face registered in the database on the NodeMCU microcontroller. The main system comprises a NodeMCU microcontroller, face sensors, and a door lock system. [ABSTRACT FROM AUTHOR]

Global warming is raising the earth's temperature, and resulting in increased forest fire events, especially in tropical regions with locations that are at high risk of wild and forest fires. Indonesia is a country in Southeast Asia that has experienced a severe number of wildfires, which have dangerous impacts on neighboring countries due to the emission of carbon and haze to the free air. The objective of this research is to map and plot the locations that consist of a significant number of fire hotspots and forecast the possible forest fire disasters in Indonesia based on the collected data of forest fires. The results of forecasting data are beneficial for the government and its policymakers to take preventive action and countermeasures regarding this wildfire issue. The Long Short-Term Memory (LSTM) algorithm, a deep learning method, was applied to analyze and then forecast the number of wildfire hotspots. The wildfire hotspot dataset from the year 2010 to 2022 is derived from the National Aeronautics and Space Administration's (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS). The total number of collected observations is more than 700,000 wildfire data in Indonesia. The distribution of wildfire hotspots as shown in the results is concentrated mainly on two big islands, Kalimantan and Sumatra, Indonesia. The main issue is the peat type of land that is prone to spreading fire. Forecasting the number of hotspots for 2023 has achieved good results with an average error of 7%. Additionally, to prove that the proposed algorithm is working well, a simulation has been conducted using training data from 2018 to 2022 and testing data from 2021 to 2022. The forecasting result achieved a similar pattern of the number of fire hotspots compared to the available data in 2021 and 2022. [ABSTRACT FROM AUTHOR]

Integration of a larger stiff system of initial value problems emerging from chemical kinetics models requires a method that is both efficient and accurate, with a large absolute stability region. To determine the solutions of the stiff chemical kinetics ordinary differential equations that help in explaining chemically reactive flows, a numerical integration methodology known as the 3-point variable step block hybrid method has been devised. An appropriate time step is automatically chosen to give accurate results. To check the efficiency of the new method, the numerical integration of a few renowned stiff chemical problems is evaluated such as Belousov–Zhabotinskii reaction and Hires, which are widely used in numerical studies. The results generated are then compared with the MATLAB stiff solver, ode15s. [ABSTRACT FROM AUTHOR]

The widespread presence of contaminants in water demands reliable and practical analytical methods to monitor them. However, before their determination, a sample pretreatment step is necessary. This has conventionally been performed using liquid-liquid extraction (LLE) or solid-phase extraction (SPE). Advances in material sciences have since been capitalized on, with new adsorbents used in conjunction with new sample pretreatment techniques based on microextractions. In this mini-review, we showcase some of our previously reported work that demonstrates how advanced materials such as graphene, molecularly imprinted polymers (MIPs), and polymeric cyclodextrins can be used as adsorbents for the determination of contaminants such as bisphenol A, steroids, sulfonamide antibiotics, and antimicrobial agents. These adsorbents formed an important component in the micro-solid phase extraction that was used for the pretreatment of the sample. A brief introduction to the adsorbents studied and evolution of extractions is provided. The distinctive features of the analytical methods used in the real sample analysis of the stated contaminants are highlighted. [ABSTRACT FROM AUTHOR]

The development of Battery Management System (BMS) standards in Indonesia has been carried out causing the FACTS approach. That's approach makes it possible to accommodate all stakeholder requirements. However, the approach has not yet considered a technical review of the regulated standards. Based on this, this study undertook a comprehensive review of BMS performance parameters set out in the standard. In order that the regulated standard s not only accommodate the needs of stakeholders but also consider BMS technical studies in order not to impede the future development of BMS. [ABSTRACT FROM AUTHOR]

Standardization is one of the important things before to deploy a product. Regulation such as national standard has important roles in industry. The roles of standard such as ensuring safety for consumer and producer, increasing product competitiveness, and reducing trade berries. Indonesia is currently in the stage of developing industry of electric vehicle, so that standard which is related to electric vehicle, one of it is standard for the electric vehicle battery. Besides that, Indonesia does not have a relevant standard to regulate. This study is intended to make a framework for standardization of lithium-ion battery module product using A Framework for Analysis, Comparison, and Testing of Standard (FACTS) approach. There are three stages in FACTS approach, they are analysis, comparison, and testing. Based on the result of this research, the framework of lithium-ion battery module product standard consists of 8 parameters. [ABSTRACT FROM AUTHOR]

In general, the process of developing new standards had problems in early the development process. In particular to identify what steps are necessary to develop new standards. Methodology of writing this article was conducted using the methodology of Framework for Analysis, Comparison and Testing of the Standard (FACTS). The results of this paper are the new standard for the Indonesian National Standard of Lithium-ion Battery Cell Ferro Phosphate for Electric Vehicle Alications. The standard of development data is can be use by automotive industrial and also for the government to decide new policy on electric vehicle especially in Indonesia. [ABSTRACT FROM AUTHOR]

The growth of world economic and increasing of trading in most of countries has impact to the number of containers export and import between countries. Some of container terminal is very busy to handle high volume of container movement. Conventional operational procedures have difficulties to handle containers movement then make slow and some issues in terminal operation for container clearance. This paper discus on proposing new algorithm to the current container terminal management system used RFID technology for fast processing and clearance. Container Terminal Management System (CTMS) is a system for port management and interface to the RFID system that used to identify container e-seal, truck and driver identity. Lack of communication and interfacing protocol made slow response during request or reply of message to the gate operator. Proposed algorithm with new procedure of request to CTMS made faster response and avoid inaccuracy of detecting container e-seal. Results of implementation new algorithm have improved to the productivity and efficiency of container terminal. Testing and implementation of this proposed system conducted in a private container terminal in Malaysia. [ABSTRACT FROM AUTHOR]

Increasing numbers of wireless local area networks (WLAN) replacing wired networks have an impact on wireless network systems, causing issues such as interference. The smart antenna system is a method to overcome interference issues in WLANs. This paper proposes an artificial immune system (AIS) for a switch beam smart antenna system. A directional antenna is introduced to aim the beam at the desired user. The antenna consists of 8 directional antennas, each of which covers 45 degrees, thus creating an omnidirectional configuration of which the beams cover 360 degrees. To control the beam switching, an inexpensive PIC 16F877 microchip was used. An AIS algorithm was implemented in the microcontroller, which uses the received radio signal strength of the mobile device as reference. This is compared for each of the eight beams, after which the AIS algorithm selects the strongest signal received by the system and the microcontroller will then lock to the desired beam. In the experiment a frequency of 2.4 GHz (ISM band) was used for transmitting and receiving. A test of the system was conducted in an outdoor environment. The results show that the switch beam smart antenna worked fine based on locating the mobile device. [ABSTRACT FROM AUTHOR]