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Jurnal Sisfokom (Sistem Informasi dan Komputer)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Atma Luhur
ISSN : 23017988     EISSN : 25810588     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal Sisfokom merupakan singkatan dari Jurnal Sistem Informasi dan Komputer. Jurnal ini merupakan kolaborasi antara sivitas akademika STMIK Atma Luhur dengan perguruan tinggi maupun universitas di Indonesia. Jurnal ini berisi artikel ilmiah dari peneliti, akademisi, serta para pemerhati TI. Jurnal Sisfokom diterbitkan 2 kali dalam setahun yaitu pada bulan Maret dan September. Jurnal ini menyajikan makalah dalam bidang ilmu sistem informasi dan komputer.
Arjuna Subject : -
Articles 689 Documents
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Business Process Reengineering: Enhancing Efficiency and Data Accuracy Through QR Label Printing in Manufacturing Igo Fatahilah Ilham; Wildan Sudarso
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2588

Abstract

In the manufacturing industry, manual data management and label printing often result in significant time wastage and a high risk of data entry errors. This study aims to reengineer the business processes in a QR label printing and data storage system to achieve greater efficiency and integration. The applied method is Business Process Reengineering (BPR), which includes process analysis using ASME standards, throughput efficiency measurements, and the implementation of an information technology-based system called Ezylabel. The results show that the manual label printing process, which initially took 67 minutes due to excessive typing and manual Excel input, was reduced to only 14 minutes through the implementation of the Ezylabel application. Throughput efficiency increased from 65.67% to 68.49%. This study shows that technology-based BPR effectively eliminates non-value-added activities, accelerates workflows, and ensures data integrity in the production process, providing a scalable solution to modern manufacturing challenges.
Bank Mandiri Stock Performance Prediction Via SVM, LSTM, and Random Forest Rahmat Rambe; Hanif Fakhrurroja; Lukman Abdurrahman
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2589

Abstract

Reliable stock price prediction is critical for effective investment decisions; however, high volatility and nonlinear dynamics continue to challenge forecasting accuracy. Despite the extensive use of machine learning in financial research, short-term comparative studies on Indonesian banking stocks remain scarce. This study evaluates the performance of Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Random Forest models in predicting Bank Mandiri’s stock prices using daily data from Yahoo Finance covering June to December 2024. The data, including price indicators and trading volume, were normalized, transformed into time-series sequences, and divided into training and testing sets. SVM was applied for directional classification, while LSTM and Random Forest were used for regression-based price prediction. Model performance was assessed using accuracy and mean squared error (MSE). The findings show that LSTM achieves the lowest prediction error (MSE = 0.0045), indicating superior ability to model temporal and nonlinear price patterns. In contrast, Random Forest records the highest classification accuracy (0.9932), demonstrating strong performance in predicting price direction. Overall, LSTM is most effective for short-term price forecasting under volatile market conditions, whereas Random Forest remains a robust option for directional classification.
Dropout Prediction Using KNN, Decision Tree, Naive Bayes, and Ensemble Learning: A Comparative Performance Analysis with Synthetic Data Validation Norma Puspitasari; Mochammad Agung Wibowo; Budi Warsito
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2591

Abstract

Student dropout is a critical issue in higher education because it affects institutional performance, resource allocation, and student success. Early identification of students with a high risk of dropout enables institutions to design timely academic and non-academic interventions. However, predicting dropout is challenging due to the complexity of influencing factors and class imbalance in educational data. This study presents a comparative performance analysis of four machine learning algorithms—K-Nearest Neighbor (KNN), Decision Tree (DT), Naive Bayes (NB), and an Ensemble Weighted Voting classifier—to support the development of an effective dropout prediction model. Due to restricted access to complete non-dropout student records, this study integrates real institutional withdrawal data from 2023–2024 to calibrate dropout characteristics and employs a transparently generated synthetic dataset for methodological validation. The dataset consists of 300 instances and is processed using the SMOTE technique to address class imbalance. Model performance is evaluated using accuracy, precision, recall, F1-score, and AUC. The experimental results obtained from synthetic validation indicate that the ensemble model outperforms individual classifiers, achieving an accuracy of 0.97, precision of 1.00, recall of 0.86, F1-score of 0.92, and AUC of 0.93. These findings highlight the potential of ensemble learning as a robust approach for early-warning systems in higher education while providing a transparent framework for predictive modeling under data-access constraints.
Predictive Models Talented Researcher Using Modern Approach Quantum Machine Learning (QML) Lukman Anas; Aghus Sofwan; Iwan Setiawan
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2593

Abstract

Scientific advancement is profoundly shaped by the ability of exceptional individuals to investigate and produce novel insights. Nonetheless, conventional assessment techniques that depend on bibliometric metrics such as the Scopus Score, Sinta, Google Scholar (GS) , and the H-Index—frequently neglect to encapsulate the intricate dynamics associated with research quality. In order to rectify these inadequacies, this study introduces a model aimed at the identification of gifted researchers through a Quantum Machine Learning (QML) methodology. The proposed framework seeks to surmount the constraints of ranking systems that rely exclusively on scientometric indicators by incorporating a reconstructed kernel Hilbert space (RKHS). The research methodology is delineated into four principal phases: (1) data gathering and preprocessing, (2) QSVM model training, (3) researcher score identification and visualization, and (4) performance assessment by comparing actual and anticipated scores. QSVM was tested using a dataset of researchers from various fields. Results show that QSVM accurately predicts researcher performance, with variances between Scores for the whole thing range from -0.25 to 0.05. The plan that was offered congruence with actual performance data supports its robustness. The ranking analysis shows a low mistake rate, proving QSVM's academic performance evaluation accuracy. QML-based categorization models can be scalable and data-driven alternatives to standard research assessment methods, according to this study.
Implementation of a Mamdani Fuzzy Inference System for Assessing Students’ Stress Levels in Final Project Completion (A Case Study of the Informatics Engineering Study Program at UMI) Ririn Melani Asaf; St. Hajrah Mansyur; Siska Anraeni
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2594

Abstract

Academic stress among Informatics Engineering students at Universitas Muslim Indonesia during final project preparation can negatively affect academic performance and mental well being. This study aims to apply the Mamdani Fuzzy method to support the measurement of student stress levels by processing uncertain information through fuzzy sets, rule-based inference, fuzzification, aggregation, and defuzzification. The proposed approach is used to identify student stress levels, classified into Low, Medium, or High, based on several academic variables, including research topic selection, references, time management, consultation with supervisors, data processing, and technical constraints. System testing indicates that the MATLAB implementation produces an output value of 1.66, while manual calculation results in 1.6344, showing a small difference of 0.03. Both results classify the stress level as Low, suggesting that the Mamdani fuzzy approach yields consistent outcomes and demonstrates potential as a supportive tool for assessing academic stress.
Implementation of Digital Archive Management in The Administration of International Missions Police Bureau Rama Dian Syah; Antonius Angga Kurniawan; Mutiara Romana Kusuma; Rizki Ariyani
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2622

Abstract

Advances in information technology have accelerated digital transformation in public sector administration, including archival management systems. However, limited studies have examined the implementation of digital archive systems within high-mobility and security-sensitive governmental units. This study aims to design and implement a digital archive management system for the administrative division of the International Missions Police Bureau (POLRI) to enhance correspondence supervision and operational efficiency. The research adopts the Waterfall development model, consisting of requirements analysis, system design, implementation, and testing stages. System requirements were identified through structured observation, semi-structured interviews, and literature review. The system was designed using use case modeling, database schema design, and flowchart analysis, and implemented as a web-based application using PHP and the CodeIgniter framework with a MySQL database. Functional validation was conducted using black box testing to ensure conformity between system features and specified requirements. The developed system includes modules for managing incoming letters, outgoing letters, official memoranda, archival records, and meeting room scheduling. Testing results indicate that all functional components operate according to expected specifications, demonstrating functional reliability and operational feasibility. The implementation of this system improves document traceability, administrative monitoring, and information accessibility without spatial and temporal limitations. This study contributes to the field of digital governance and information systems by providing an empirical implementation framework for digital archive management in a specialized law enforcement administrative context. The findings demonstrate the practical applicability of structured system development methods in supporting digital transformation within government institutions.
Development and Validation of GIS-Based Multi-Vulnerability Mapping for Floods and Landslides in Parung Panjang Novi Trisman Hadi; Kharisma Wiati Gusti; Rizky Tito Prasetyo; Adita Utami
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2623

Abstract

Rapid peri-urban development in Indonesia, particularly in metropolitan buffer areas such as Bogor Regency, has intensified land use change and increased vulnerability to hydrometeorological disasters. Parung Panjang Subdistrict faces significant environmental pressure from settlement expansion, industrial activity, and mining, which contribute to increased surface runoff, reduced infiltration capacity, and land instability. This study aims to develop and validate a Geographic Information System (GIS)-based model for flood and landslide vulnerability mapping to support sustainable spatial planning at the subdistrict scale. The analysis integrates remote sensing, topographic, and climatic data, while vulnerability weights were determined using the Analytical Hierarchy Process (AHP) and combined through a weighted overlay approach to produce flood, landslide, and multi-hazard vulnerability maps. Model validation was conducted using a confusion matrix, resulting in an Overall Accuracy of 88.4% and a Kappa coefficient of 0.84, indicating strong agreement. The developed flood vulnerability map was further implemented in a web-based GIS platform and functionally tested, achieving a 95% success rate. The findings show that high flood vulnerability is concentrated in low-elevation areas with high moisture indices and dense built-up land use, while multi-hazard zones identify priority areas for mitigation. This study demonstrates the integration of validated multi-hazard spatial modeling with web-based implementation, providing a practical decision-support tool for local disaster mitigation and spatial planning.
Descriptive¬¬–Interpretative Evaluation of SIMONEVA Palu Usability and User Experience Using Cognitive Walkthrough (CW) and User Experience Questionnaire (UEQ) Aisyah Syahskiah Sunandar; Deny Wiria Nugraha
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2628

Abstract

The Monitoring and Evaluation Information System (SIMONEVA) plays an important role in supporting regional development, but it often generates user complaints and has not been systematically evaluated. This research evaluates the usability and user experience of SIMONEVA Palu and analyzes the descriptive-interpretative relationship between the severity of usability issues and user experience scores. The usability evaluation was conducted using the Cognitive Walkthrough (CW) method, involving 10 respondents, consisting of 5 long-term users and 5 new users, while the user experience measurement used the User Experience Questionnaire (UEQ) with 41 long-term users. The results of the descriptive-interpretative relationship analysis indicate that Attractiveness and Efficiency have critical usability issues (severity level = 4) with very low UEQ scores (0.04 and 0.20), while Dependability and Perspicuity have moderate issues (severity levels = 2.22 and 2.38) with low UEQ scores (0.09 and 0.12). The pattern found indicates that the higher the severity level of usability issues, the more negative the users' perception of the system. These findings emphasize that system evaluation needs to consider both operational barriers and users' subjective perceptions. Thus, the resulting recommendations are able to highlight interface areas that require improvement more specifically. This research is expected to contribute to the literature on government information system evaluation, particularly at the regional implementation level, which is still relatively limited.
Acceptance and Use of the MyASN Application Among Civil Servants: An Integration of TAM and IS Success Model in South Central Timor Regency Merlyn Gizella Nifu; Wiwin Sulistyo; Hendry Hendry
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 02 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2639

Abstract

The MyASN application is a mobile-based mandatory system designed to support Civil Servants (ASN) in accessing personnel-related information. However, its implementation still faces challenges, including data inconsistencies and system integration issues. This study analyzes the factors influencing the acceptance and actual use of the MyASN application among civil servants in South Central Timor Regency. The research integrates the Technology Acceptance Model (TAM) and the DeLone and McLean Information Systems Success Model. A quantitative survey involved 250 respondents, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS. The results reveal a distinct adoption pattern for mandatory government systems. Service quality has no significant impact on user perceptions, indicating that users prioritize independent system functionality over technical support. System quality acts as a baseline expectation that significantly enhances perceived ease of use and perceived usefulness, but it does not significantly influence user satisfaction. Conversely, information quality emerges as the application's true core value; while it does not affect ease of use, it strongly drives perceived usefulness and user satisfaction. Furthermore, user satisfaction acts as the strongest predictor of users’ intention to continue using the application, which directly drives actual system use. Practically, these findings recommend that the National Civil Service Agency (BKN) and regional governments prioritize data accuracy to achieve user satisfaction and maintain system stability to prevent user dissatisfaction, rather than solely focusing on support services.

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