cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ansari Saleh Ahmar
Contact Email
journal@ahmar.id
Phone
-
Journal Mail Official
journal@ahmar.id
Editorial Address
http://jurnal.ahmar.id/index.php/asci/about/editorialTeam
Location
Unknown,
Unknown
INDONESIA
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 15 Documents
 1   2 
Search results for , issue "Vol. 7 No. 1 (2025)" : 15 Documents clear
Application of Digital Image Processing for Orchid Image Segmentation in Morphological Plant Analysis Riza, Bob Subhan; Rosnelly, Rika; Haryanto S., Edy Victor
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3772

Abstract

The deployment of digital image processing in orchid image segmentation for plant morphological analysis is investigated in this study. The goal of this study is to increase the accuracy of orchid species identification using color-based segmentation approaches using 90 photos of three different orchid species—Cattleya, Dendrobium, and Onchidium—that were retrieved from Kaggle. Pre-processing is the first step in the process, which involves shrinking the size of the photos, separating them into RGB components, and converting them to HSV color space for additional analysis. Segmentation is done using the K-Means technique, which clusters pixels according to the color features that have been retrieved. Centroid updates are made until convergence is reached. With an identification accuracy of 92%, the binary and RGB segmentation results show how well this method works to distinguish the flower item from the backdrop. By advancing image processing methods in botany, this study aids in the identification of rare orchid species and conservation initiatives.
Sustainable Competitive Advantage in Indonesia’s Bioethanol Industry: Key Variables and Ecosystem Model Rachman, Izmirta
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3784

Abstract

The target for bioethanol fuel-grade blending in Indonesia has yet to be achieved, indicating significant barriers to the development of a sustainable industry. This study aims to identify key variables and develop an ecosystem model that supports Sustainable Competitive Advantage (SCA) in the Fuel-Grade Bioethanol Industry (FGBI) in Indonesia. Adopting the Resource-Based View (RBV) and Institutional Theory (IT) approaches, this study analyzes the interaction between internal and external factors influencing industry sustainability. Utilizing an exploratory inductive qualitative method covering the period 2006 to 2024, the research identifies three key RBV variables: (1) demand, (2) raw materials, and (3) technology as well as three coercive IT variables: (1) price formulation, (2) trade structure, and (3) tariffs and incentives as critical elements in achieving SCA. The findings indicate that coercive IT alone is ineffective in achieving SCA without integration with RBV. As both an academic and practical contribution, this study proposes a sustainable ecosystem model for FGBI in Indonesia. Further quantitative testing is needed to examine inter-element dynamics and evaluate the model’s long-term effectiveness. The implications for stakeholders highlight the importance of integrating policy with RBV principles to ensure the sustainability of the industry.
Paper vs. Digital Assessments: Evaluating Critical Thinking on Ecological Issues in Indonesian Madrasahs Berlian, Zainal; Isnaini, Muhammad; Farwati , Ratna; Metafisika, Kartika; Velina, Yessy; Fitriyanni, Viona
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3785

Abstract

This research aims to determine the difference in the assessment results in the critical thinking skills of State Madrasah Ibtidaiyah (MIN) students or State Islamic schools in Indonesia using paper-based and digital-based tests. Data was collected from 314 participants representing MIN on four large islands in Indonesia, namely MIN Bogor Regency, West Java, MIN Sinjai Regency, South Sulawesi, MIN Palembang City, South Sumatra, and MIN Balikpapan City, East Kalimantan. The research method used a quantitative survey. A total of 24 valid Critical Thinking Skills Items with the Facione Critical Thinking Skills indicator as an instrument for measuring critical thinking skills. Factors such as motivation, technological accessibility, and effectiveness of test formats contribute to differences in results. This study provides new insights into the effectiveness of technology-based assessment in Madrasa education, especially in evaluating critical thinking skills. These findings lead to policy recommendations for improving the Madrasa assessment system in the digital era.
Towards Integrated E-Government Services: Key Contributing Factors from a Whole-of-Government Perspective Othman, Mohamed Hairul; Razali, Rozilawati; Nasrudin, Mohammad Faidzul
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3800

Abstract

Despite various initiatives introduced to ensure electronic government (e-government) services remain relevant, there are still unresolved issues in its implementation that bring negative perceptions towards the government. One common issue is the existence of duplicated as well as unintegrated services between agencies that mislead citizens and cause bureaucratic red tape. This issue could be resolved by establishing integrated e-government services, which nevertheless require strong collaboration from multiple agencies. One strategy to strengthen cross-agency collaboration is through the Whole-of-Government (WoG) approach. However, studies concerning the WoG approach that specifically focus on collaboration strategies to address service integration issues in e-government are scarce. This study therefore aimed to identify the WoG factors that are important for strengthening cross-agency collaboration, as the effort for establishing integrated e-government services. It adopted the qualitative method approach, consisting of theoretical and empirical studies. The theoretical study was conducted through literature reviews, whereas the empirical study involved semi-structured interviews with relevant informants from public and private sectors as well as statutory body. Both theoretical and empirical data were analysed using thematic analysis. The identified WoG factors were categorised into people, process and technology aspects, which can act as a guideline towards integrated e-government services through cross-agency collaboration.
From Ethics to Impact: Modeling the Role of AI Perception Dynamics in the Relationship Between Ethics AI Practices, AI-Driven Societal Impact, and AI Behavioral Analysis Fakhri, M. Miftach; Jannah, Devi Miftahul; Isma, Andika; Dewantara, Hajar; Nirmala S., Aprilianti
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3802

Abstract

The rapid evolution of Artificial Intelligence (AI) has brought significant changes across various sectors, including healthcare, finance, and criminal justice, presenting both remarkable opportunities and complex ethical challenges. As AI becomes increasingly embedded in decision-making processes, concerns about individual rights, social equity, and public trust are growing, especially in high-stakes contexts. These ethical implications underscore the critical need for robust frameworks that emphasize AI transparency, accountability, and fairness to mitigate risks such as bias and ensure responsible usage. Despite the increased focus on ethical AI practices, there remains a considerable gap in understanding how these frameworks impact societal perceptions and behaviors toward AI. This study seeks to address this gap by investigating the effects of ethical AI practices—specifically transparency, accountability, and fairness—on public perceptions and behaviors. The study employs a quantitative approach, using purposive sampling to select a sample of AI-knowledgeable participants and analyzing the data with Partial Least Squares Structural Equation Modeling (PLS-SEM). This methodological approach allows for a detailed exploration of the relationships between ethical AI practices and societal impacts. Additionally, the study examines the mediated pathways through which these ethical practices influence AI’s societal and behavioral impacts, hypothesizing that transparency and accountability foster trust and positive engagement. By developing a framework that aligns ethical AI practices with societal values, this study aims to advance the broader goals of societal trust, public acceptance, and sustainable social integration of AI technologies. These insights contribute to the growing body of knowledge on responsible AI deployment, supporting ethical alignment in diverse AI applications and promoting trustworthiness in AI-driven systems
Time Series Innovation: Leveraging BetaSutte Models to Enhance Indonesia's Export Price Forecasting Ahmar, Ansari Saleh; Boj, Eva
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3831

Abstract

This study introduces a novel application of the Modified Trend-Augmented α-Sutte Indicator (BetaSutte) model for forecasting Indonesia's export prices and compares its performance with the traditional ARIMA approach. Accurate export price forecasting is crucial for economic planning, trade policy formulation, and business strategy development in Indonesia's dynamic and globally connected economy. Using monthly export value data from January 2022 to September 2024 obtained from Indonesia's Central Bureau of Statistics (BPS), we examined whether the BetaSutte model's decomposition of trend and residual components offers enhanced predictive accuracy over the conventional ARIMA methodology. Results show that while the ARIMA(0,1,0) model demonstrated superior in-sample performance (Training MAPE: 7.71% vs. 80.78%), the BetaSutte model achieved better out-of-sample forecasting accuracy (Testing MAPE: 11.22% vs. 11.61%). The BetaSutte model's linear trend component identified a negative slope (coefficient: -158.4), indicating a systematic decline in Indonesia's export values over the study period, which has important implications for trade policy. Furthermore, the model successfully captured the volatility in export prices through its residual forecasting component. These findings suggest that the BetaSutte model's explicit modeling of trend components provides meaningful advantages for export price forecasting, despite its more complex implementation. This research contributes to the growing literature on hybrid forecasting methodologies and offers practical guidance for stakeholders interested in Indonesia's international trade dynamics. For policymakers, the results highlight potential challenges for Indonesia's export competitiveness and suggest the need for targeted interventions to address the identified downward trend in export values.
A Bibliometric Analysis of Complex Problem-Solving Approaches in Engineering Education Azizan, Mohd Fikri; Mohd Matore, Mohd Effendi Ewan; Omar, Marlissa
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3846

Abstract

The evolving landscape of engineering education requires the development of advanced cognitive skills, particularly complex problem-solving (CPS). As engineering challenges grow in complexity, CPS has become a vital competency. However, research on CPS in engineering education remains scattered. This study presents a systematic bibliometric analysis to uncover trends, key contributors, and thematic focuses in CPS-related research. Using the Scopus database and VOSviewer 1.6.20, the study analyzed publications based on co-authorship, co-citation, and keyword co-occurrence. The five-stage bibliometric approach by Masitoh et al. (2021) and Bukar et al. (2023) was adopted, encompassing keyword selection, data retrieval, screening, analysis, and visualization. Findings show a notable rise in CPS publications after 2010, peaking between 2022 and 2024. Dominant keywords include “active learning,” “simulation,” “artificial intelligence,” and “project-based learning,” indicating a shift toward AI-driven, technology-enhanced approaches. China, the United States, and India lead in research output, reflecting global efforts in reforming engineering education. The study highlights the growing emphasis on interdisciplinary and problem-based learning. Despite this momentum, regional disparities remain. Insights from this analysis are valuable for curriculum developers, educators, and policymakers to enhance CPS integration and guide future research toward more holistic and inclusive approaches
The Validity of the Malaysian Teachers’ Global Competency Level Instrument Using Cohen Kappa, Content Validity Ratio and Content Validity Index Analyses Ibrahim, Siti Nurul Aqiedah; Mohd Matore, Mohd Effendi Ewan
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3848

Abstract

Highly competent teachers are vital in developing globally competent individuals. There is a lack of empirical evidence supporting the validity aspect of the Malaysian Teachers' Global Competency Level Instrument. This study aims to evaluate face and content validity. A survey research design with a quantitative approach was conducted. It involves two experts for face validity and eight experts for content validity using purposive sampling techniques. For face validity, the two experts appointed were Malay language teachers with more than five years of teaching experience. To assess content validity, eight experts, including four professionals in measurement, evaluation, and global competency, and four field practitioners: teacher educators, and outstanding teachers. The instrument consists of 73 items with four constructs: self-awareness, global awareness, attitudes & values, and skills. The analysis involved Cohen’s Kappa for face validity, while content validity involved CVR and CVI. The results showed that face validity was (N=2, k=0.640), while for content validity, (N=8, CVI=0.95, and CVR=2 items refined). This instrument demonstrates strong validity as a measurement tool for the global competency level of Malaysian teachers. Further studies are recommended to be conducted: employing an advanced statistical analysis, like the Rasch Model, to enhance higher-quality items.
A Decision-Centric Approach to Risk Management in Aviation Stock Investments Using Value at Risk and Portfolio Optimization Singagerda, Faurani Santi; Pratama, Muh. Riyaldi; Alfairus, M. Qodri; Iskandar, Akbar; Mamadiyarov, Zokir
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3870

Abstract

This study applies Monte Carlo simulation to analyze and compare the Value at Risk (VaR) of two Indonesian airline stocks—PT Garuda Indonesia (full-service carrier) and PT AirAsia Indonesia (low-cost carrier)—using daily return data from January to December 2023. The research examines risk-return characteristics at individual stock and portfolio levels across different confidence intervals (99%, 95%, and 90%). Results reveal that PT Garuda Indonesia exhibits higher expected returns (0.5168%) but also higher volatility (3.5980%) compared to PT AirAsia Indonesia (0.2412% return, 2.4868% volatility), reflecting their different business models. Remarkably, an equal-weight portfolio demonstrates extraordinary diversification benefits, with positive VaR values across all confidence levels, indicating robust downside protection even in adverse market conditions. At 99% confidence, the monetary VaR for a Rp100,000,000 investment shows potential maximum losses of Rp7,984,331 for Garuda and Rp5,460,951 for AirAsia, while the portfolio generates a minimum gain of Rp1,886,373. This study highlights the effectiveness of Monte Carlo VaR in capturing complex risk dynamics, demonstrates significant intra-sector diversification benefits challenging conventional diversification wisdom, and provides insights into how different airline business models translate into distinctive risk-return profiles. These findings have important implications for investment decision-making and risk management in specialized industry contexts, particularly in emerging markets.
Cryptocurrency Risk Management through Decision Engineering: Evaluating XRPUSD and ADAUSD Portfolio Performance Litamahuputty, Jacomina Vonny; Amiruddin, Erwin Gatot; Rahim, Robbi; Rahman, Abdul; Mamadiyarov, Zokir
Journal of Applied Science, Engineering, Technology, and Education Vol. 7 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.asci3871

Abstract

This research examines the risk profiles of XRPUSD and ADAUSD cryptocurrencies through Value at Risk (VaR) analysis with Monte Carlo simulation, providing quantitative risk assessments for both individual assets and a diversified portfolio. Analyzing historical price data from January 2016 to November 2024, the study identifies distinctive risk characteristics between these cryptocurrencies: ADAUSD exhibited marginally higher historical returns (1.44% monthly) compared to XRPUSD (1.42%), but with notably higher volatility (standard deviation of 5.41% versus 4.65%). The Monte Carlo simulation with 1,000 iterations generated VaR estimates at multiple confidence levels, revealing that XRPUSD consistently demonstrated lower downside risk than ADAUSD across all confidence thresholds. At the 99% confidence level, ADAUSD showed a Mean VaR of -10.97%, indicating potential monthly losses exceeding $10.97 million on a hypothetical $100 million investment, while XRPUSD's lower Mean VaR of -9.52% translated to potential losses of approximately $9.52 million. The most striking finding emerged from the portfolio analysis, which revealed dramatic risk reduction through diversification—the equally-weighted portfolio achieved a Mean VaR of merely -2.22% at the 99% confidence level, representing an approximately 80% reduction in potential losses compared to ADAUSD alone. These results demonstrate that cryptocurrency diversification can substantially mitigate extreme downside risk while maintaining exposure to the digital asset class. The significant risk reduction achieved through a simple two-asset allocation validates the application of modern portfolio theory principles to cryptocurrency investments despite their unique characteristics and underscores the critical importance of diversified approaches rather than concentrated positions for risk-conscious cryptocurrency investors. This research contributes to both theoretical understanding of cryptocurrency risk dynamics and practical portfolio construction approaches, providing quantitative evidence for the value of diversification strategies in navigating the substantial volatility inherent in digital asset markets.

Page 1 of 2 | Total Record : 15

 1   2 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 7 No. 3 (2025) Vol. 7 No. 2 (2025) Vol. 7 No. 1 (2025) Vol. 6 No. 2 (2024) Vol. 6 No. 1 (2024) Vol. 5 No. 2 (2023) Vol. 5 No. 1 (2023) Vol. 4 No. 2 (2022) Vol. 4 No. 1 (2022) Vol. 3 No. 2 (2021) Vol. 3 No. 1 (2021) Vol. 2 No. 2 (2020) Vol. 2 No. 1 (2020) Vol. 1 No. 2 (2019) Vol. 1 No. 1 (2019) More Issue