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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 1,045 Documents
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Development of a Prototype Web-based System for Managing Customer Incoming Letters at PLN ULP Subang using a Design Thinking Approach Febrianti, Valentina; Fauzi, Ahmad
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6291

Abstract

This study was conducted to design and evaluate a prototype web-based system for managing customer incoming letters in order to improve efficiency and user experience. The method employed is Design Thinking, which includes the stages of empathize, define, ideate, prototype, and testing, with a focus on identifying issues in incoming mail management that still rely on manual processes. The resulting prototype was evaluated using the System Usability Scale (SUS) and the User Experience Questionnaire (UEQ). The results indicate that the system demonstrates a high level of usability, with an average SUS score of 80.6 (categorized as excellent), and provides a positive user experience, as reflected in UEQ scores for attractiveness (1.6), perspicuity (1.7), efficiency (1.5), dependability (1.4), stimulation (1.6), and novelty (1.3). Therefore, the developed system is capable of improving the efficiency of customer incoming letter management while supporting the digitalization of administrative processes and enhancing service quality.
Framework for Culinary Entrepreneurship Learning System Integrating Pedagogy and Analytics Putra, Perdana Suteja; Brillianti, Grahita Prisca; Komariah, Kokom; Anugerah, Adhe Rizky; Wahyuni, Rhismah Tri; Ibrahim, Faris Zulfan; Haq, Amar Al; Ginting, Azzuhra Muqaddasa; Nafie, Harun Stephen
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.5737

Abstract

Entrepreneurship education in Indonesian vocational higher education remains constrained by theoretical approaches and generic learning management systems (LMS) that do not fully capture the multidimensional competencies required for entrepreneurial readiness. The culinary sector, which contributes nearly 42% of the creative economy’s GDP and is dominated by micro, small, and medium enterprises (MSMEs), highlights the urgent need for tailored pedagogical and technological solutions. This study proposes a conceptual framework for a culinary entrepreneurship learning information system, designed by integrating Deep Learning pedagogy, Innovation Canvas, and learning analytics. Drawing on preliminary findings from focus group discussions with practitioners and surveys of student competence, the research employed a conceptual design methodology guided by human-centered design principles. The resulting framework maps stakeholder needs into system components, including competency dashboards, e-portfolios, gamified features, and analytics-driven monitoring of five core entrepreneurial competencies: mentality, management, legality, branding, and networking. The framework demonstrates how reflective pedagogy can be operationalized into an information system architecture, bridging the gap between entrepreneurship education and digital innovation. Academically, it extends the literature on integrating pedagogy and information systems, while practically, it offers a replicable blueprint for higher education institutions seeking to enhance graduate employability and entrepreneurial readiness. The novelty of this study lies in integrating deep learning pedagogy, innovation canvas, and learning analytics into a unified conceptual framework for vocational entrepreneurship education—an approach not previously applied in the culinary education context. Future research should focus on prototyping, usability testing, and empirical validation to ensure the framework’s effectiveness and scalability.
Performance Evaluation of a Laravel-based Internship Website using MySQL Master–Slave Replication Pamungkas, Viona Mojang; Suranegara, Galura Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6152

Abstract

Single database architectures often experience performance degradation as user load increases because all read and write operations are processed centrally, causing bottlenecks and limiting the scalability of web systems. To address this issue, this study implements database replication using a MySQL Master–Slave architecture combined with the separation of read and write operations in a containerized Laravel-based web system. A quantitative experimental method was applied by comparing the Single Database and Master–Slave Replication configurations implemented in a Docker environment on Windows Subsystem for Linux 2 (WSL2). Performance evaluation was conducted using Apache JMeter at three workload levels low (10 users), medium (50 users), and high (100 users) based on response time, throughput analysis, latency analysis, and error rate. The results show that the Master–Slave configuration provides more stable performance at medium to high workloads, with latency between 0.20 and 0.26 seconds and an error rate of 0% in all test scenarios. Additionally, the highest throughput of 2.01 requests per second was achieved at medium workload, indicating effective read-write separation and better workload distribution through database replication.
Development of a Flask-based Application for Bank Customer Churn Prediction as a Decision Support Tool Wibowo, Suluh Arif; Rezky, Muhammad; Ibrahim, Ali; Afrina, Mira; Fathoni, Fathoni
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6257

Abstract

Customer churn prediction is a crucial aspect of the banking industry for maintaining customer loyalty and reducing the cost of acquiring new customers. This study aims to develop a web-based decision support system capable of predicting potential customer churn using the Gradient Boosting Machine (GBM) algorithm. The dataset used is the Bank Customer Churn Dataset, consisting of 10,000 customer records with 14 attributes. The research stages include exploratory data analysis and preprocessing, which involves data cleaning, categorical feature encoding, feature engineering (BalanceSalaryRatio, TenureByAge, CreditScoreGivenAge), and data balancing using SMOTE to address class imbalance. The GBM model was trained on the balanced dataset and evaluated using accuracy, precision, recall, and F1-score metrics. The evaluation results show that the model achieved an accuracy of 83.95%, with a recall of 67.32% for the churn class, indicating a strong capability in identifying customers at risk of churn. Feature importance analysis reveals that Age and NumOfProducts are the most dominant features, contributing approximately 77% to the prediction. The model was then implemented in a Flask-based web application with an HTML and CSS interface, enabling non-technical users to perform real-time churn predictions. This system is expected to assist banking institutions in designing more targeted and data-driven customer retention strategies.
Comparative Analysis of Random Forest and Support Vector Machine Algorithms for Predicting Student Retention at Ibnu Sina University pradipto, dimas; Agastya, I Made Artha; Suryadi, Agus
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6298

Abstract

Student retention is a critical challenge facing higher education institutions, including Ibnu Sina University (UIS), where a significant proportion of students risk not completing their studies. Purpose: This study develops and compares predictive models using Random Forest (RF) and Support Vector Machine (SVM) algorithms to classify student retention into three categories: Active, At-Risk, and Inactive. Methods: Administrative data from 2,389 students across 6 study programs (2021/2022–2023/2024 cohorts) were used, encompassing 18 predictor variables including academic performance (GPA, failed credits), demographic, and socio-economic factors. Class imbalance was handled using SMOTE, and hyperparameter optimization was performed via Grid Search with 5-Fold Cross Validation. Results: RF outperformed SVM across all metrics, achieving accuracy of 92.24%, weighted F1-Score of 92.38%, and macro F1-Score of 82.67%, compared to SVM's 87.63% and 87.79%. Feature importance identified Total Failed Credits (0.2847) and Cumulative GPA (0.2134) as the strongest predictors. Novelty: Unlike prior studies focusing solely on academic data, this research integrates non-academic variables (leave history, parental income) and explicitly addresses class imbalance via SMOTE in a multi-class Indonesian higher education context, providing a practical Early Warning System (EWS) framework.
Instruction-Efficient and Parallelized AES using CUDA and PTX for Data Encryption Daniswara, Raditya Hakim; Astuti, Yani Parti
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.5931

Abstract

This research presents an instruction-efficient and parallelized implementation of the AES-256 encryption algorithm using NVIDIA CUDA with inline PTX to optimize instruction usage and execution performance on GPUs. Conventional AES implementation on CUDA often suffers from redundant instructions and high computational overhead, limiting encryption throughput. To address this, three implementation variants were developed: a baseline version, a parallelized version, and an inline PTX-optimized version. The proposed PTX-enhanced AES reduces instruction redundancy through vectorized memory access, byte permutation, and logical operation consolidation using PTX instructions. Instruction analysis using NVIDIA Nsight Compute and cuobjdump revealed a 66% reduction in executed instructions compared to the baseline, primarily due to optimized AES operations. Performance evaluation of 32 MB plaintext demonstrates a 16-fold improvement in throughput, increasing from 2.73 Gbps in the baseline to 43.9 Gbps in the PTX-optimized version, with cycles per byte decreasing from 2.63 to 0.164. These results confirm that integrating fine-grained PTX control within CUDA enables substantial gains in encryption efficiency while maintaining correctness and security. The proposed approach provides a scalable foundation for high-performance cryptographic operations in GPU-based computing environments.
Analysis of the Provider State Management Pattern for Performance and Maintainability in a Flutter-based Mobile Pharmacy Application Subandri, Muhammad Asep; Putra, Fajri Profesio; Tedyyana, Agus
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6237

Abstract

State management in modern mobile applications is a critical aspect that affects both user interface (UI) rendering performance and code maintainability. Previous studies on Flutter state management have generally used simple catalog applications as test objects and focused on performance comparisons between approaches without quantitatively measuring maintainability aspects. This study aims to analyze the effectiveness of implementing the Provider state management pattern in terms of UI rendering performance and code maintainability, using a real-world business application case study—namely, the Apotek Berkah mobile application. The research adopts an applied research methodology with a case study approach. The application consists of 20 Dart files with a total of 5,899 lines of code (LOC), developed using Flutter with a MultiProvider architecture and dependency injection. Performance measurements were conducted using Flutter DevTools, including widget rebuild count, frame rendering time, and memory usage, with comparisons against setState as the baseline. Maintainability was assessed through nine metric aspects, including code distribution across layers, provider class metrics, provider access patterns, screen complexity, architectural patterns, and dependency graph analysis. The results indicate that the Provider pattern reduces widget rebuild count by an average of 52.3% compared to setState, with frame rendering time consistently below 16 ms. In terms of maintainability, the Provider architecture demonstrates low coupling (all providers depend solely on ApiService), zero inter-provider dependency, and well-structured separation of concerns. The novelty of this study lies in the combined evaluation of performance and maintainability of the Provider pattern within the domain of a pharmacy business application, which involves CRUD operations, inventory management, and point-of-sale (POS) transactions—a domain that has not been extensively explored in prior Flutter state management literature. The main contribution is empirical evidence that the Provider pattern offers an optimal balance between performance, maintainability, and implementation complexity for medium-scale mobile applications.
Comparative Analysis of Accuracy and Performance between Zed Attack Proxy and Burp Suite Community on Website XYZ Pratama, Wendha Alfen; Suranegara, Galura Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6287

Abstract

Web application security is a critical aspect of protecting the confidentiality, integrity, and availability of data, where Vulnerability Assessment and Penetration Testing (VAPT) serves as a vital method within the system development lifecycle. This study is motivated by the dilemma faced by security practitioners when choosing testing tools between Zed Attack Proxy (ZAP), an open-source solution with full automation capabilities, and Burp Suite Community, an industry-standard tool that imposes throttling limitations in its free version. This study aims to conduct a comparative analysis of the performance of these two tools on Website XYZ, with a particular focus on the accuracy of detecting OWASP Top 10 vulnerabilities, computational resource efficiency, and the effectiveness of fuzzing and spidering in modern web architectures based on JavaScript/AJAX. The research adopts a systematic VAPT approach, including information gathering, vulnerability scanning, and risk analysis, and employs Youden’s Index as a statistical metric to evaluate diagnostic effectiveness. The results indicate that OWASP ZAP achieved a True Positive Rate (TPR) of 75% (6 out of 8 based on Youden’s Index), with a Youden’s Index value of 0.625. In terms of computational efficiency, OWASP ZAP completed the fuzzing process in an average of 4.72 seconds, significantly faster than Burp Suite Community, which required an average of 22.56 seconds due to speed limitations in its free Intruder module. Therefore, this study recommends OWASP ZAP as a more effective tool for penetration testing in environments with limited computational resources, given its superior performance in both endpoint detection accuracy and execution time efficiency.
Development of a Web-Based Extracurricular Activity Monitoring Information System Kusumawardani, Nada; Setiaji, Pratomo; Agus Triyanto, Wiwit
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6286

Abstract

Extracurricular activities play an important role in supporting students’ development, both in academic and non-academic aspects. However, the management of extracurricular activities in many schools is still conducted manually, making it difficult to monitor student participation, record attendance, and document achievements. This study aims to develop a web-based extracurricular activity monitoring information system to improve the effectiveness of activity management at SMP 2 Jati. The system development method used is the Waterfall model, which includes the stages of requirements analysis, system design, implementation, and testing. The system was developed using native PHP and MySQL and can be accessed by administrators, extracurricular supervisors, and students. The results of testing using the Black Box Testing method indicate that all system functions operate as intended. In addition, user evaluation using a Likert-scale questionnaire shows that the system has good usability, improves the efficiency of activity management, and provides a positive level of user satisfaction. The findings of this study demonstrate that the developed system can support a more effective and structured monitoring process for extracurricular activities.
Implementation of a Deep Learning Model for Real-Time Detection and Classification of Toraja Traditional Motifs (Pa’ssura’) for Digital Cultural Preservation Abidin, Ali Asgar Zainal; Ardiansyah, Mursyid; Zahra, Aqilah
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6132

Abstract

Toraja traditional motifs, known as Pa’ssura’, represent an intangible cultural heritage rich in philosophical values and deep cultural identity. However, the authenticity and understanding of the meanings behind these motifs are at risk of erosion among younger generations due to the lack of interactive and technologically relevant learning media. This study aims to bridge this gap through an innovative digital cultural preservation strategy by implementing deep learning technology. Specifically, the research focuses on developing a real-time object detection and classification system using a Convolutional Neural Network (CNN) architecture, particularly the YOLO11s model. The main research stages include constructing an annotated image dataset for seven primary Pa’ssura’ motifs: Pa’ Barre Allo, Pa’ Kapu Baka, Pa’ Tangke Lumu, Pa’ Tedong, Pa’ Ulu Karua, Pa’ Kadang Pao, and Pa’ Papan Kandaure. These data were collected from both planar media (such as textiles) and non-planar media, including wood carvings and stone engravings. The results show that the developed model achieved a precision of 0.7109, a recall of 0.6708, and an mAP@50 of 0.6910 after 100 training epochs. The implementation of data augmentation techniques proved effective in increasing the dataset size—from 1,050 images before augmentation to 2,520 images after augmentation—thereby significantly enhancing the model’s robustness in detecting and classifying motifs across both planar and non-planar media. This study produces an accurate and practical model that can be applied as an educational tool in mobile applications. Furthermore, the model plays an important role in preserving Toraja cultural heritage through digitalization.

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