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Journal of Applied Science, Engineering, Technology, and Education
Published by PT. Mattawang Mediatama Solution
ISSN : -     EISSN : 26850591     DOI : https://doi.org/10.35877/454RI.asci1116
Core Subject : Science, Education, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Other
Journal of Applied Science, Engineering, Technology, and Education (ASCI) is an international wide scope, peer-reviewed open access journal for the publication of original papers concerned with diverse aspects of science application, technology and engineering.
Arjuna Subject : Umum - Umum
Articles 285 Documents
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PLS-SEM Approach: Validity and Reliability of a Questionnaire on Context, Input, Process and Acceptance of STEM Implementation in Malaysia Bin Amatan, Mohammad Azri; Han, Crispina Gregory K.; Pang, Vincent
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3885

Abstract

This study aims to test the validity and reliability of the context, input, process, and acceptance of STEM implementation questionnaires for secondary school teachers in Malaysia. Partial Least Squares Structural Equation Modelling (PLS-SEM) with SMARTPLS 3.2.3 software was used to do the analysis. The study involved 825 secondary school teachers using stratified random sampling. Based on composite reliability and Cronbach's alpha values, the Reflective Measurement Model showed that there was internal consistency reliability. Convergent validity was also achieved through outer loading analysis and average variance extracted (AVE). It also met the criteria for discriminant validity based on the Fornell-Larcker Criterion, Cross Loading, and the Heterotrait-Monotrait (HTMT) Ratio. The findings of this study demonstrate that this questionnaire is valid and reliable for assessing STEM implementation among secondary school teachers in Malaysia.
Strategic Decision Analysis for Investment Portfolios: Computational Risk Assessment in Transportation Asset Management Sofyanty, Devy; Romadhoni, Romadhoni; Handriadi, Handriadi; Makhsudovna, Istamova Shokhida; Anwar, Zakiyah; Mamadiyarov, Zokir
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3897

Abstract

This study presents a strategic decision-making framework for portfolio investment by applying computational risk assessment methods to the transportation sector in Indonesia. Focusing on two key players—PT. Adi Sarana Tbk (ASSA) and PT. Blue Bird Tbk (BIRD)—the research evaluates their individual and combined risk-return profiles using daily stock return data from December 2023 to November 2024. A hybrid analytical approach is employed, integrating traditional financial metrics with advanced computational techniques such as Monte Carlo simulation and Value at Risk (VaR) modeling to support managerial decision-making. The analysis reveals contrasting performance patterns: BIRD exhibits marginally positive expected returns (0.04%) but higher downside risk exposure, whereas ASSA shows negative average returns (-0.06%) yet demonstrates lower volatility and reduced extreme loss potential. Portfolio optimization results demonstrate that a diversified allocation of 60% ASSA and 40% BIRD generates improved risk-adjusted returns, achieving a positive expected return while maintaining lower overall risk compared to the individual assets. By incorporating monetary VaR estimates, this study enhances the practical relevance of risk analytics for portfolio managers, particularly in navigating volatile emerging markets. The findings underscore the importance of strategic asset allocation, business model differentiation, and quantitative risk modeling in constructing resilient investment portfolios. This research contributes both methodologically and managerially by offering a robust, replicable framework for strategic decision analysis in transportation asset management and beyond.
Downside Risk Measurement of Indonesian Financial and Energy Securities: A Value at Risk Perspective Rony, Zahara Tussoleha; Jefri, Riny; Rusmardiana, Ana; Pramono, Susatyo Adhi; Mamadiyarov, Zokir
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3898

Abstract

This study explores the measurement of downside risk in the Indonesian capital market by applying Value at Risk (VaR) analysis to two representative companies from different economic sectors: PT Asuransi Bina Dana Arta Tbk (ABDA), an insurance firm, and PT ABM Investama Tbk (ABMI), an energy and mining company. Utilizing daily return data from December 2023 to November 2024, we assess both individual and portfolio-level risk profiles through a quantitative framework based on Monte Carlo simulation. Our findings reveal distinct risk-return characteristics between the two stocks. ABDA exhibits a negative average daily return (-0.15%) with relatively low volatility (standard deviation of 1.12%), whereas ABMI shows a positive expected return (0.07%) but higher variability (standard deviation of 2.06%). Interestingly, despite its lower volatility, ABDA records higher VaR values across all confidence levels, indicating greater downside exposure—particularly evident at the 95% confidence level where ABDA's one-day VaR is -2.04%, compared to ABMI’s -1.77%. A cross-sector portfolio consisting of 40% ABDA and 60% ABMI demonstrates meaningful diversification benefits, reducing the standard deviation to 1.02% and improving the VaR to -1.54%. This represents a risk reduction of 24.5% compared to ABDA alone and 13% relative to ABMI alone. For a hypothetical investment of IDR 100 million, these improvements equate to reduced potential daily losses of IDR 508,258 and IDR 233,504 respectively. The results emphasize that strategic cross-sector allocation—even within a simple two-asset portfolio—can significantly enhance risk-adjusted performance in emerging markets like Indonesia. By combining financial and energy assets with differing sensitivities to macroeconomic conditions, investors can better manage downside risk while maintaining exposure to diverse economic drivers. This research provides a practical methodology for risk assessment and portfolio construction, offering valuable insights for asset managers and decision-makers operating in volatile and multi-sector investment environments.
Computational Risk Management for Strategic Investors: An Engineering-Inspired Approach to Portfolio Diversification Hasan, Nonce; Rahim, Robbi; Sapinah, Sapinah; Pramono, Susatyo Adhi; Abroza, Ahmad
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3904

Abstract

This study presents an engineering-inspired approach to computational risk management, focusing on portfolio diversification strategies for strategic investors. Utilizing Monte Carlo simulation techniques, we assess the Value at Risk (VaR) of two prominent companies in Indonesia’s entertainment sector: MD Pictures Tbk (FILM) and MNC Studios International Tbk (MSIN). Daily return data from January 2022 to December 2022 are analyzed to evaluate both individual and combined risk-return profiles. The results show distinct characteristics between the two stocks, with FILM exhibiting a higher average daily return (0.42%) but greater volatility (standard deviation of 4.01%), compared to MSIN's more moderate return (0.33%) and lower volatility (3.64%). At a 95% confidence level, VaR estimates indicate potential maximum daily losses of 6.12% for FILM and 5.81% for MSIN. When combined into an equally weighted portfolio, significant diversification benefits emerge, reducing portfolio standard deviation to 2.77% and improving the VaR to 4.58%. This represents a risk reduction of 25.2% compared to FILM and 21.2% compared to MSIN. For a hypothetical investment of IDR 100 million, these improvements translate to reduced potential daily losses of IDR 1,540,482 and IDR 1,229,142 respectively. The findings demonstrate that even within a single industry, effective risk management can be achieved through strategic intra-sector diversification when constituent firms differ in business model and operational focus. This research bridges the gap between financial engineering and strategic portfolio management by offering a quantitative, simulation-based framework that supports informed decision-making for risk-conscious investors.
Modified SIFT-Based Kirsch Edge Detection Approach for Copy-Move Forgery Detection Idris, Bashir; Abdullah, Lili N.; Halin, Alfian Abdul; Selimun, Mohd Taufik Abdullah
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3939

Abstract

The increasing accessibility of digital imaging technology has led to a rise in image forgery, raising concerns about digital content authenticity in forensic and security domains. Copy-move forgery is one the most prevalent and challenging forgery techniques due to its seamless manipulation. We propose a novel passive CMFD (CMFD) approach that leverages a modified Kirsch (mKirsch) edge detector and a modified SIFT-based descriptor (DivSIFT) to accurately identify and localize copy-move forgery (CMF). The mKirsch edge detector enhances edge detection by selectively deleting specific masks, improving keypoint extraction and feature matching. We used MICC-F220, CoMoFoD, and MICC-F8Multi datasets to measure the performance of the new method, under challenging conditions such as rotation, scaling, JPEG compression, and multiple forgeries. The results show that mKirsch-enhanced detection outperforms compared to conventional Kirsch-based methods. Notably, methods with deleted masks (WW_NW and NE_SE) achieved a True Positive Rate (TPR) of 90.91%, precision 100%, and an F-measure of 95.24%. Robust against rotation and scaling attacks, achieving a TPR of up to 96.97% with zero false positives. Additionally, the method is computationally efficient, with an execution time of 2.74 seconds, making it suitable for real-world applications. These findings establish the mKirsch-based CMFD as a highly accurate and efficient solution for image forgery detection in digital images.
Citrus Peel Waste as an Electrolyte Solution for Energy Storage in Bio-Batteries I Wayan Suriana; Ida Ayu Dwi Giriantari; Wayan Gede Ariastina; I Nyoman Setiawan
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3974

Abstract

This study explores the potential of citrus peel waste as an electrolyte solution for energy storage in bio-batteries. This research offers an environmentally friendly solution to obtain clean and sustainable energy by utilizing abundant organic waste as raw material. An experimental method was conducted to analyze the ability of electrolyte solutions from citrus fruit peel waste to support bio-battery performance. The results showed that citrus peel waste has significant potential as an electrolyte solution with competitive capabilities in energy storage. The implications of this research include the development of more sustainable alternative energy technologies and the effective use of unused resources, which could be an essential step in achieving global sustainability goals.
Engineering-Based Investment Modeling in Emerging Markets: Decision Analytics for Portfolio Management in Indonesia Puspitaningtyas, Ayu; Rosdiana, Rosdiana; Hakim, Luqman; Zain, Yuli
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3983

Abstract

This study presents an engineering-based approach to investment modeling in the context of emerging markets, with a focus on portfolio management strategies in the Indonesian equity market. By integrating computational finance techniques and decision analytics, the research develops a structured framework for assessing risk-return dynamics and optimizing asset allocation decisions. Using daily stock return data from two representative companies across different economic sectors—PT Telekomunikasi Indonesia Tbk (TLKM.JK) from telecommunications and PT Petrosea Tbk (PTRO.JK) from energy/mining—the study applies Monte Carlo simulation, Value at Risk (VaR), and statistical decision modeling to evaluate both individual and combined investment performance. Results indicate distinct risk-return profiles, where PTRO.JK offers higher average returns but with significantly greater volatility compared to TLKM.JK. A cross-sector portfolio consisting of 60% TLKM.JK and 40% PTRO.JK demonstrates notable diversification benefits, reducing overall portfolio risk as evidenced by improved VaR estimates. For a hypothetical IDR 100 million investment, the diversified portfolio reduces maximum expected loss by more than 50% compared to investing solely in TLKM.JK. These findings highlight the effectiveness of quantitative, model-driven approaches in supporting strategic investment decisions. By bridging financial engineering methodologies with practical portfolio management needs in Indonesia, this study contributes a replicable framework that enhances decision-making under uncertainty, particularly for investors seeking to balance growth potential with downside risk control in multi-sector allocations.
Perceptions of Students in Relevance of Management Course in Engineering Disciplines: A Higher Education-Implications for a 21st-Century Curriculum Lastimado Jr, Alberto E.
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci4032

Abstract

This study addresses the critical need to understand how engineering students perceive the relevance of engineering management education in preparing them for these multifaceted roles. Specifically, this research evaluates the perspectives of undergraduate engineering students in the Philippines regarding the significance of engineering management in their respective disciplines, its role in skill development, and the challenges encountered. A mixed-methods approach was employed, gathering data from 396 undergraduate engineering students through surveys, brief written responses, and interviews. Findings indicate that a significant majority of students hold favorable impressions, with 86.8% believing the knowledge gained will be valuable and 84.5% affirming that the course develops essential analytical and critical thinking skills. Students generally recognize the importance of engineering management in fostering fundamental abilities crucial for their future careers. However, a notable challenge is the perceived workload, with 52.7% of students finding management-related coursework demanding. The research illustrates the importance of integrating well-designed engineering management education within engineering curricula. The findings highlight the importance of equipping future engineers with the managerial expertise and soft skills the complexities of the 21st-century workforce and inform strategies for curriculum enhancement.
Artificial Intelligence in Educational Measurement: A Bibliometric Review (1997 to 2024) Othman, Nursohana; Mohd. Matore, Mohd Effendi Ewan; Yunus, Farahiyah Wan
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci4126

Abstract

Artificial Intelligence (AI) is increasingly influencing measurement practices across fields such as health sciences, diagnostics, and psychology by enhancing accuracy, efficiency, and personalization. In the educational domain, however, the application of AI in assessment remains relatively underdeveloped, despite its significant potential to support adaptive systems and individualized feedback. This bibliometric review analyzes 921 peer-reviewed articles published between 1997 and 2024 to examine how AI contributes to the evolution of educational measurement. Through citation, co-citation, and keyword co-occurrence analyses, the study identifies influential publications, maps the intellectual structure of the field, and explores emerging thematic directions. Results indicate a substantial growth in research output after 2019, driven by advances in machine learning, natural language processing, and big data analytics. Foundational contributions from health and computer sciences, such as deep learning methods and open-source tools like Scikit-learn, have significantly influenced educational technologies. Three core themes are identified: the technical foundations of AI, cross-disciplinary applications in cognitive and medical diagnostics, and ethical and policy challenges related to AI implementation in education. Global collaboration is prominent, with leading contributions from the United States and China and increasing participation from Malaysia, Pakistan, and Nigeria. The review highlights the interdisciplinary nature of AI in educational measurement and calls for responsible, scalable applications to support inclusive and personalized learning environments
IoT-Based Real-Time Monitoring and Thermal Performance Evaluation of A Box-Type Solar Cooker Panigrahi, Badri N.; Mahanta, Satyam S.; Nayak, Jayashree; Sahoo, Sudhansu S.; Choudhury, Balaji K.
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci4129

Abstract

This work presents the development and evaluation of an IoT-based real-time monitoring system integrated with a box-type solar cooker to assess its thermal performance. The system incorporates an ESP8266 microcontroller interfaced with a DHT11 sensor for ambient temperature and humidity, a DS18B20 sensor for absorber plate temperature, and a MAX6675 with a K-type thermocouple for vessel (water) temperature measurement. All of the sensor data is transmitted to the ThingSpeak cloud platform, enabling real-time visualization and remote analysis. Thermal performance indicators were derived from the recorded data, including the first figure of merit (F₁), second figure of merit (F₂), thermal efficiency (η), and the overall heat loss coefficient (UL). Under clear-sky conditions, the cooker reached a stagnation temperature of approximately 130°C, with ambient conditions near 35°C and solar irradiance around 850 W/m². The calculated F1 (~0.11 °C•m²/W), F2 (~0.41), average thermal efficiency (~30 %), and average heat loss factor (~4.8 W/m²•°C) signify a reasonably efficient solar cooker design. Additionally, real-time insights into heat retention and loss were made possible through continuous monitoring. The integration of IoT with the solar cooker not only improves data acquisition and performance evaluation but also demonstrates the viability of smart sustainable cooking technologies in modern applications. It allows for easy and better evaluation of the cooker by the general user

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