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Jurnal Sisfotek Global
Published by Institut Teknologi dan Bisnis Bina Sarana Global
ISSN : 20881762     EISSN : 27213161     DOI : http://.doi.org/10.38101/jsg
Core Subject : Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering
Jurnal Sisfotek Global is a peer-reviewed open access journal published twice a year (March and September), a scientific journal published by Institut Teknologi dan Bisnis Bina Sarana Global. Jurnal Global Sisfotek aims to provide a national forum for researchers and professionals to share their ideas on all topics related to the field of computer science. It is published in online version (e-ISSN 2721-3161) and printed version (p-ISSN 2088-1762). Jurnal Global Sisfotek has been indexed and abstracted in Index Copernicus, GOOGLE Scholar, BASE (Bielefeld Search Engine), Crossref Search, One Search, PKP-Indexed, Neliti search, Garuda, Dimensions, Scilit. Jurnal Sisfotek Global accepts quality manuscripts produced from research projects within the scope of the field of computer science, which include, but are not limited to the following topics: information systems, image processing, multimedia, mobile computing, artificial intelligence, expert systems, computer systems. The manuscript must be original research and written in English (from 2021).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 359 Documents
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Evaluation of the Impact of 3D Space Building Learning Using Augmented Reality Based on Android Applications Simanullang, Robintang; Kusuma, Syenina Putri; Tullah, Rahmat; Nurmaesah, Nunung
JURNAL SISFOTEK GLOBAL Vol 14, No 1 (2024): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v14i1.10942

Abstract

Mathematics is a subject that is considered difficult by many students, especially geometric materials. Grade 5 students at SDN Bugel 2 had a low average score in learning geometric shapes with an achievement of 40,7. The aim of this research is to increase students' understanding of spatial construction materials in class 5 through learning applications. This research was conducted using the ADDIE (Analysis, Design, Development, Implementation, Evaluation) method. The result of this research is to create a 3D space building learning application based on Augmented Reality which can make it easier for students to understand space building learning. This learning application is effective and can improve student understanding. This is proven by the average quiz score increasing to 81,9.
Optimizing Change Management Using the Analytical Hierarchy Process Method: Analysis with Super Decisions Software Ken Putri, Lulasnov Viola Prameswari; Mahdiana, Deni
JURNAL SISFOTEK GLOBAL Vol 14, No 2 (2024): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v14i2.15661

Abstract

A major challenge in change management lies in selecting unbiased policy alternatives that promote effective decision-making. To overcome this obstacle, this research utilizes Super Decisions software to perform AHP calculations and assess various change management policies. The methodology used includes identifying key criteria affecting change management, structuring the problem into an AHP hierarchy, collecting data through expert surveys or interviews, and analyzing the data using Super Decisions software to determine the criteria weights and optimal policy alternatives. The study revealed that improving Standard Operating Procedures (SOPs) emerged as the most optimal policy alternative. The implementation of AHP demonstrated its ability to provide a systematic and unbiased framework, assisting top management in strategic decision-making. Overall, this study underscores the value of AHP in reducing bias and informing sound change management policies. The study recommends continued adoption and adjustment of the AHP method to suit organizational needs.
Measuring Service Quality and Developing a Roadmap for the E-Science Service Application at the National Research and Innovation Agency (BRIN) Pratiwi, Sinta; Taufik, Tatang Akhmad
JURNAL SISFOTEK GLOBAL Vol 14, No 1 (2024): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v14i1.10871

Abstract

This research investigates the E-Service Science Application (ELSA) of the National Research and Innovation Agency (BRIN). In 2022, 77.41% of service requests through ELSA were unfulfilled, significantly impacting BRIN's Non-Tax State Revenue (PNBP) and ELSA Points. The study aims to evaluate ELSA's service quality using the Servqual method and to understand user behavior and intentions through the Technology Acceptance Model (TAM) 2. Questionnaires based on Servqual and TAM 2 models were utilized, with data analyzed via descriptive analysis of each variable and Structural Equation Modeling (SEM) using SmartPLS-3 software. Findings revealed that service quality attributes – tangibility, reliability, responsiveness, assurance, and empathy – were unsatisfactory, as indicated by negative GAPs. Importance-Performance Analysis (IPA) was employed to prioritize areas for improvement. Most respondents showed high intention to use (Mean 4.18) and usage behavior (Mean 4.09), with similar ratings for other TAM 2 variables. These insights contribute to the development of an ELSA Application Roadmap, guiding service enhancements and positioning BRIN as a hub for scientific collaboration.
Cryptography System Based on SEMT Labeling of Total Path and Its Application for Securing Image File by Using Android Studio Trisha Magdalena Adelheid Januaviani; Bahrirrudin Bahrirrudin; Nikita Nikita; I Wayan Sudarsana; Nasria Nacong; Agusman Sahari; Hajar Hajar; Selvy Musdaifah; Moh Ali Akbar; Tri Prasetia Ningrum
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.15934

Abstract

Cryptography is one of the mathematical techniques used to address information security issues. The study of information security is essential due to the rapid development of information technology, which increases the risk of unauthorized access to sensitive data. Android smartphones are among the most popular communication devices, offering various features such as text messaging, image sharing, audio, video, and more. Given people use Android widely, data stored on Android devices is highly vulnerable to hacking attempts. Therefore, a cryptographic approach based on graph labeling will be applied to secure images on Android smartphones. This method utilizes the Super Edge Magic Total (SEMT) labeling for total path graphs to encrypt and decrypt image pixels, ensuring the security of images. Furthermore, this technique will be implemented to develop an Android-based application using Android Studio. The study results indicate that total path graphs satisfy the SEMT labeling properties and the developed application functions effectively on Android devices to secure images.
Multi-Sensor Based Remaining Useful Life Prediction of Bearing Motors: A Comparative Study of LSTM and CNN Models Yani Koerniawan; Indrawan Indrawan; Raynaldi Yudha Prasetya; Wingky Kurniawan
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16236

Abstract

Accurate Remaining Useful Life (RUL) prediction is essential for implementing effective predictive maintenance strategies in industrial rotating machinery. Bearing motors are particularly critical components whose unexpected failure may cause severe production losses and safety risks. This study presents a comparative investigation of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) architectures for RUL prediction using multi-sensor monitoring data. The dataset consists of 1000 days of simulated operational data from three bearing motors under varying degradation conditions. Five sensor parameters are considered: vibration (RMS), acoustic emission, temperature, stator current, and rotational speed (RPM). After preprocessing and sliding-window segmentation, 2910 time-series sequences were generated and divided into training, validation, and test sets. Model performance was evaluated using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R²). Experimental results show that LSTM significantly outperforms CNN, achieving an R² of 0.9877 on the test dataset, while CNN achieved R² below 0.34. The findings confirm the importance of temporal dependency modeling in long-horizon degradation prediction and provide guidance for selecting deep learning architectures in predictive maintenance applications.
Student Centric Model for Learning Analytics in Smart Campus Ecosystem: A Systematic Literature Review I Gusti Ngurah Suryantara; Jusia Amanda Ginting; Raphael Benedict Manuel
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16279

Abstract

The development of smart campuses has intensified the use of data-driven technologies to support institutional decision-making in higher education. However, many existing smart campus implementations remain system-oriented, with limited emphasis on learning processes and student needs. This study aims to formulate a student-centric model for learning analytics within digital twin–enabled smart campus ecosystems through a systematic literature review. The review follows the PRISMA 2020 guidelines and analyzes peer-reviewed articles indexed in the Scopus database, focusing on digital twins, smart campuses, learning analytics, and data governance. The findings indicate that digital twins have evolved from static digital representations into integrated platforms that combine real-time data, modeling, and analytics to support proactive decision-making. Nevertheless, the integration of learning analytics that explicitly centers on students is still fragmented. The concept of the student digital twin emerges as a promising approach for modeling learners as dynamic analytical entities, but it also raises critical concerns related to ethics, privacy, transparency, and governance. Based on the synthesis, this study proposes a conceptual student-centric model consisting of data sources, sensing mechanisms, student modeling, learning analytics, feedback and intervention pathways, and governance safeguards. The model provides a structured foundation for designing responsible and sustainable learning analytics in smart campus environments.
Prediction of UFC Lightweight Winners Using Ensemble Machine Learning Praja Anugerah Pratama; Veny Cahya Hardita; Abdul Hadi
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16311

Abstract

The Ultimate Fighting Championship (UFC) lightweight division presents significant prediction challenges due to factors including knockout variability, injuries, and fluctuating fighter momentum. This study develops an intelligent prediction system for UFC lightweight fight outcomes using ensemble machine learning, deployed as a web-based platform. Historical data from UFCStats.com comprising 6,000 fights and 675 fighters were collected and preprocessed. Feature engineering generated 63 differential attributes, including stance compatibility, recent performance metrics (last five fights), win streak differential, age difference, reach difference, and striking/takedown statistics. Multiple models, including XGBoost, LightGBM, and Logistic Regression, were optimized using Bayesian hyperparameter tuning, with Synthetic Minority Over-sampling Technique (SMOTE) applied to address class imbalance. The soft voting ensemble classifier achieved 79.25% accuracy and 88.67% ROC-AUC on time-based test data, representing a 13.7% to 14.2% improvement over previous state-of-the-art approaches. The primary contributions of this study include: (1) development of 63 domain-specific engineered features with quality adjustments and temporal weighting, (2) achievement of state-of-the-art prediction accuracy through optimized ensemble architecture, and (3) deployment as an accessible web application providing real-time predictions with confidence scores and market odds comparison—transforming academic findings into a practical decision-support tool. Validation against betting market odds demonstrated 76% agreement with market favorites and 82.1% accuracy in consensus cases, confirming alignment with domain expertise while identifying value betting opportunities.
Analysis of the Influence of System QuaAnalysis of the Influence of System Quality, Information Quality, and Service Quality on User Satisfaction of Payment Systems Using Virtual Accountslity, Information Quality, and Service Quality on User Satisfaction of Payment Systems Using Virtual Accounts Azrul Azmani; Tutik Lestari; Muhammad Dzakky Ikhwani Imaduddin; Ajinarasena Hermanu; Gandung Triyono
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16034

Abstract

This study aims to analyze the influence of system quality, information quality, and service quality on user satisfaction in virtual account payment systems implemented at Pesantren Darunnajah. The increasing adoption of digital payment solutions in educational institutions underscores the need for reliable systems that ensure convenience, security, and efficiency. Using the Technology Acceptance Model (TAM) as a theoretical framework, data were collected through a survey of 36 respondents, including guardians and staff, and analyzed using multiple linear regression. The findings reveal that system quality, information quality, and service quality all have a significant positive effect on user satisfaction, with service quality emerging as the most influential factor. These results highlight the importance of responsive support and accurate information in enhancing user experience. The study contributes to the literature on digital payment adoption in Islamic educational institutions and provides practical insights for improving service delivery. Future research should explore additional factors such as security, interface design, and user trust to broaden understanding of technology acceptance in similar contexts.
Artificial Intelligence (AI) Ethics in Fintech and Startup Ecosystems: A Systematic Literature Review Analysis Aditya Rawasaputra; Rahmat Tullah; I Ketut Sudaryana; Jan Everhard Riworuhi
JURNAL SISFOTEK GLOBAL Vol 16, No 1 (2026): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v16i2.16229

Abstract

Artificial intelligence (AI) is reshaping the fintech and startup ecosystem, offering efficiency in credit scoring, fraud detection, investment personalization, and customer service. Yet, its adoption raises pressing ethical challenges, particularly in Indonesia and Southeast Asia. This study conducts a systematic literature review (SLR) using the PRISMA protocol, analyzing over 80 scholarly articles, industry reports, and regulatory documents to examine key ethical issues in AI-driven finance. Findings highlight concerns around algorithmic transparency, data bias, privacy protection, accountability in automated decision-making, and regulatory compliance. Case studies of Indonesian fintech firms reveal emerging best practices, including explainable AI, fairness audits, compliance with the Personal Data Protection Law (UU PDP), and ethics committees. Regulatory frameworks from OJK and international standards such as GDPR and the EU AI Act provide critical guidance, though implementation challenges persist. The review concludes that embedding ethics into AI development lifecycles, strengthening cross-sector collaboration, and enhancing digital literacy are essential to building an inclusive, transparent, and sustainable fintech ecosystem.

Page 36 of 36 | Total Record : 359

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