cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alfian Ma'arif
Contact Email
alfian_maarif@ieee.org
Phone
+6282226375801
Journal Mail Official
alfian_maarif@ieee.org
Editorial Address
Jl. Empu Sedah No. 12, Pringwulung, Condongcatur, Kec. Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta 55281, Indonesia
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
Indonesian Journal of Applied Science and Engineering
Published by Peneliti Teknologi Teknik Indonesia
ISSN : 30309174     EISSN : 30309174     DOI : 10.59247/ijase
Core Subject :
The Indonesian Journal of Applied Science and Engineering is a peer-reviewed, open-access academic journal. The journal is dedicated to advancing knowledge and disseminating high-quality research at the intersection of applied science, engineering, education, and social science, with a strong emphasis on the development and application of knowledge for the benefit of society. The journal serves as a multidisciplinary scholarly platform for academics, researchers, educators, and practitioners to share original work that bridges theoretical foundations with practical applications across diverse fields. The journal recognizes that solving complex real-world problems increasingly requires collaboration across disciplines — from engineering systems and applied technologies to educational innovation and social transformation. Contributions that demonstrate interdisciplinary thinking, innovation, and societal impact are especially encouraged. The journal publishes original research articles, technical reports, systematic literature reviews, expert opinions, and critical responses covering Engineering and Technology, Education and Learning Sciences, and Social Science and Humanities.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "vol. 3 no. 1 (2025)" : 5 Documents clear
Mapping Educational Service Quality Research: A Bibliometric and Science Mapping Analysis of Research Trends and Thematic Evolution (2011–2026) Resky Nuralisa Gunawan; Dwi Mahardiyati; Lamanisa Rasid Saputra; Indah Sari Hamid
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i1.153

Abstract

This study aims to analyze publication trends, thematic structures, collaboration patterns, and emerging research directions in educational service quality studies indexed in the Scopus database between 2011 and 2026. A total of 70 journal articles were selected through a PRISMA-based screening process from an initial dataset of 193 documents. The analysis employed bibliometric and science mapping techniques, including publication trend analysis, co-authorship analysis, bibliographic coupling, and keyword co-occurrence analysis. Bibliometrix (R-package) was used for descriptive bibliometric analysis, while VOSviewer was utilized to visualize thematic relationships and research networks. The findings indicate a significant increase in publication output after 2019, reflecting growing academic interest in educational service quality evaluation. Research in this field is predominantly concentrated within social sciences and management disciplines, with SERVQUAL, student satisfaction, higher education, and service quality emerging as the most dominant themes. The keyword evolution analysis demonstrates a transition from descriptive and perception-based evaluation approaches toward more outcome-oriented research focusing on institutional performance and student experience. The collaboration analysis reveals relatively fragmented research networks among authors and institutions, indicating opportunities for stronger interdisciplinary and international collaboration. The existing literature remains heavily dependent on traditional survey-based methodologies, while advanced analytical approaches such as learning analytics, machine learning, predictive modelling, and intelligent decision support systems remain underexplored within educational service quality research. This study contributes to the literature by providing a comprehensive bibliometric overview of the intellectual structure and thematic evolution of educational service quality research. The findings offer insights for researchers, educational institutions, and policymakers in developing more data-driven, interdisciplinary, and technology-oriented approaches for evaluating and improving educational service quality.
Blockchain-Based Prediction Markets: A Survey of Architectures and Economic Mechanisms Sigit Dani Perkasa; Fachrizal Fikri
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i1.161

Abstract

Prediction markets harness dispersed knowledge to forecast uncertain events. Blockchain technology has enabled a new generation of permissionless, oracle-dependent prediction platforms with diverse architectural and economic designs. To survey the engineering architectures, market microstructure, oracle designs, and economic mechanisms of operational blockchain-based prediction market platforms, using a structured comparative case-study approach. A documented platform-selection protocol (informed by Chong et al. [2019] and Treiblmaier [2019] for blockchain case-study research) was applied across DeFi literature, industry documentation, and technical whitepapers. Six blockchain-native platforms and one centralized regulated benchmark were selected based on market relevance, architectural diversity, and documentation availability. The six blockchain-native platforms—Polymarket, Augur, Gnosis Conditional Tokens/Omen, Azuro, SX Bet, and Overtime Markets—span three dominant architectural paradigms: the centralized limit order book with decentralized settlement, the fully on-chain automated market maker, and the modular conditional token infrastructure. Oracle design emerges as the critical security bottleneck across all platforms, with each adopting distinct trust assumptions and economic security models. Liquidity models range from hierarchical pooled AMMs to competitive order books to parimutuel systems, with no single architecture dominant across applications. Conclusions: The contrast between blockchain-native platforms and the CFTC-regulated Kalshi illustrates the fundamental trade-off between cryptographic trust minimization and regulatory compliance. These findings provide a structured framework for understanding the design space of blockchain-based prediction markets and identify open challenges including oracle security, cross-chain liquidity aggregation, and the integration of prediction market signals with autonomous decision-making systems.
Product Defect Analysis in Almond Cookies using Statistical Quality Control Destia Nur Romadhoni; Safinta Nurindra Rahmadhia; Ainul Mardhiah; Afolabi-Owolabi Oluwafunke Toyin
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i1.164

Abstract

Quality control is an essential aspect of food production because product defects can reduce consumer acceptance, production efficiency, and economic value. Small-scale food industries often face challenges in maintaining product consistency due to limited quality control systems and resources. Therefore, this study aimed to characterize product defects and provide an initial evaluation of production-process variability in almond cookies produced by a small-scale food industry in Yogyakarta using a Statistical Quality Control (SQC) approach. A descriptive observational study was conducted on four production batches comprising 2,125 almond cookies. Data collected included production volume, number of defective products, and defect types identified through visual inspection using a check sheet. The data were analyzed using defect-rate calculations, Pareto analysis, and Statistical Process Control (SPC) using a p-chart. A total of 99 defective products were identified, corresponding to an overall defect rate of 4.66%, while the first-pass conformity rate was 95.34%. Pareto analysis identified shape nonconformity as the dominant defect, accounting for 45.45% of total defects, followed by topping damage (17.18%), color non-uniformity (14.14%), poor dough cohesion (13.13%), and structural breakage (10.10%). The three most frequent defect types accounted for 76.77% of all defects. The p-chart showed that the four observed batch proportions were within the calculated control limits (UCL = 7.40%; LCL = 1.92%). However, because only four production batches were observed, these control-chart results should be interpreted as an initial indication of process variability rather than definitive evidence of long-term statistical control. The findings indicate that shape nonconformity is the primary quality-improvement priority, while further monitoring using a larger number of production batches is required to establish reliable process-control limits and investigate the underlying causes of defects.
Common LMS Log Indicators for Predicting Student Success: A Systematic Literature Review Rugaya Tuanaya; Erna Andriyanti; Edi Istiyono
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i1.175

Abstract

This systematic review synthesizes research on common Learning Management System (LMS) log indicators used to predict student success, addressing challenges of variability and interpretability in leveraging digital behavioral data to forecast academic outcomes. Following PRISMA guidelines, a literature search and screening process using Google Scholar as the primary data source, identified 125 empirical studies for narrative synthesis; no formal meta-analysis was performed, so the ranges reported below reflect the spread of individually reported study findings rather than pooled or averaged effect sizes. The reviewed studies indicate that behavioral indicators such as timeliness of assignment submissions, submission frequency, and regularity of study intervals are repeatedly associated with academic performance, with individual studies reporting correlations as high as r=0.60–0.88, although predictive strength varies considerably by educational context. Tree-based learning models such as Random Forest and Gradient Boosting frequently offer a favorable balance between accuracy (75–96% across studies) and interpretability, while deep learning architectures such as LSTM and GRU are reported to achieve higher accuracy (89–97% in some studies) in capturing non-linear temporal patterns, though these figures are not directly comparable across studies because they were obtained using different evaluation metrics, datasets, and validation procedures. Weekly data aggregation and early engagement metrics (weeks 1–3) are associated with improved timely identification of at-risk students in several studies. Cognitive engagement metrics (e.g., content completion, quiz attempts) are reported to outperform simple frequency indicators in a number of studies, and interpretability techniques such as SHAP values suggest that modifiable behavioral features tend to carry more predictive weight than fixed demographic data. These findings underscore the significant potential of LMS log analysis in understanding student learning behavior. However, the results also highlight methodological differences between studies and limitations in the applicability of the results to other contexts. Therefore, a standardized framework is needed to translate LMS data into applicable, transparent, and equitable educational interventions.
Item Analysis of an English Achievement Test Using Rasch Model and Classical Test Theory Rezkilaturahmi Rezkilaturahmi; Nur Hidayanto Pancoro Setyo Putro; Guldana Begimbetova; Oscar Ndayizeye; Muthmainnah Muthmainnah; Dinda Khaira Latifa
Indonesian Journal of Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/ijase.v3i1.180

Abstract

This study aimed to evaluate the quality of English test items developed by the English Teachers Working Group (MGMP) in Muna District, Indonesia. The study specifically examined the psychometric characteristics of the items in terms of item difficulty, discrimination, distractor effectiveness, and item fit using Classical Test Theory (CTT) and Item Response Theory (IRT). This study employed a quantitative psychometric approach. The data consisted of responses to an English achievement test developed and administered by English teachers participating in the MGMP in Muna District. Item quality was initially examined using Classical Test Theory based on item difficulty, discrimination index, and distractor effectiveness. Further analysis was conducted using the Rasch model of Item Response Theory with the Quest program to evaluate item difficulty and item fit based on INFIT Mean Square (MNSQ) statistics. The results of both approaches were used to determine whether individual items were acceptable, required revision, or should be rejected. The analysis revealed variation in the psychometric quality of the test items. The CTT analysis showed differences in item difficulty, discrimination, and distractor effectiveness, while the Rasch analysis revealed variation in item difficulty and item fit. The combined findings indicated that some items demonstrated acceptable psychometric characteristics, whereas others required revision. In addition, several items could not be evaluated using Quest. These findings indicate that although more than half of the items demonstrated acceptable psychometric characteristics, a substantial proportion still requires improvement before being used as a high-quality English assessment.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 4 No. 2 (2026) Vol. 4 No. 1 (2026) Vol. 3 No. 2 (2025) Vol. 3 No. 1 (2025) Vol. 2 No. 2 (2024) Vol. 1 No. 1 (2023)