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Hidra Amnur
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Kampus Politeknik Negeri Padang, Jurusan Teknologi Informasi. Gedung E. Limau Manis, Pauh. Padang - Sumatera Barat. Indonesia
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JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Published by Society of Visual Informatics
ISSN : 27224619     EISSN : 27224600     DOI : 10.30630/jitsi
Core Subject : Science,
Computer Science & IT
The journal scopes include (but not limited to) the followings: Computer Science : Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering : Computer Architecture, Computer Network, Computer Security, Embedded system, Coud Computing, Internet of Thing, Robotics, Computer Hardware Information Technology : Information System, Internet & Mobile Computing, Geographical Information System Visualization : Virtual Reality, Augmented Reality, Multimedia, Computer Vision, Computer Graphics, Pattern & Speech Recognition, image processing Social Informatics: ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT education
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 174 Documents
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Pemilihan Peserta Terbaik pada Sistem Manajemen Bimbingan Belajar Uji Kompetensi dengan Metode Weighted Product dan Simple Additive Weighting Firman Shiddiq Alamsyah; Deni Satria; Yulherniwati
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 1 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.1.555

Abstract

The Competency Test Learning Guidance is a platform for students or nurses who wish to enter the workforce. The learning guidance organized by Appskep Indonesia is held annually in several periods. One of the efforts to improve the quality of the participants is by evaluating them and selecting the best participants for each class period in Appskep Indonesia. The selection of the best participants in the Competency Test Learning Guidance at Appskep Indonesia currently lacks a system capable of conducting effective and efficient evaluations. The criteria for selecting the best participants in the Competency Test Learning Guidance at Appskep include the average exam scores from the Competency Test tryouts taken by the participants, access to materials available to all registered participants, attendance at the start and end of the classes, and each participant's level of activeness. The decision support system for selecting the best participants for this research uses the Weighted Product (WP) and Simple Additive Weighting (SAW) methods, implemented in a website. SAW is a method that involves finding the weighted sum of performance ratings for each alternative across all attributes. In contrast, WP uses multiplication to relate attribute ratings, where each attribute is first raised to the power of its respective weight. The research was conducted to test three class periods starting from July 2023 to March 2024. The study compared the results of the methods in Excel and on the website, achieving 100% accuracy. This research compares the SAW and WP methods for the intensive batch 158, intensive batch 157, and intensive batch 156 class periods. The results for the intensive batch 158 showed that the best participant was Aditya Rizal with WP and SAW scores of 0.01207 and 1.01, respectively. For the intensive batch 157, the best participant was Sarri Qurrotul with WP and SAW scores of 0.01099 and 0.95, respectively. For the intensive batch 156, the best participant was Ari Lani with WP and SAW scores of 0.01707 and 1.01, respectively
Sistem Pakar Diagnosa Kerusakan Smartphone Menggunakan Metode Certainty Factor Ilham Agus Pratama; Aldo Erianda; Ardi Syawaldipa
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 1 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.1.556

Abstract

Smartphones are multifunctional telecommunication devices that have become an essential part of everyday life. However, with the increasing use of smartphones, damage to these devices often occurs and is difficult for lay users to detect. To assist Pagaruyung Ponsel employees or cashiers in diagnosing smartphone damage without needing to rely on expert technicians, this study developed a computer-based expert system. This system combines the Forward Chaining and Certainty Factor (CF) methods to accurately detect smartphone damage. By utilizing expert knowledge, this system provides appropriate solutions based on detected symptoms. The system's accuracy test results showed a value of 85%, which proves the system's effectiveness in providing accurate diagnoses. It is hoped that this system can facilitate independent smartphone diagnosis and repair anytime and anywhere, through a website-based platform. The implementation of this expert system with the Forward Chaining and Certainty Factor (CF) methods is expected to increase the speed and efficiency in handling smartphone damage problems
Federated Retrieval-Augmented Generation for Indonesian-Language Misinformation Detection in Multi-Institutional Environments: A Review Miftahul Azzahra; Rahmat Hidayat
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 1 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.1.568

Abstract

The proliferation of misinformation in the Indonesian digital ecosystem presents a critical challenge for public discourse, democratic integrity, and social cohesion. Conventional centralized detection systems, while effective, impose significant privacy risks upon contributing institutions including media organizations, universities, and government agencies that possess unique and sensitive corpora. This review investigates the emerging paradigm of Federated Retrieval-Augmented Generation (Federated RAG), which synthesizes Federated Learning (FL) with Retrieval-Augmented Generation to enable privacy-preserving, collaborative misinformation detection across multi-institutional environments. The findings reveal that while Federated RAG represents a nascent yet promising frontier, no prior study has applied this paradigm to Indonesian-language misinformation in a cross-silo institutional setting. This review identifies key technical gaps, proposes a novel architectural taxonomy, and provides a roadmap for future empirical investigations. The framework presented herein is designed to be extensible to other low-resource languages across Southeast Asia and beyond
Transformasi Digital Pelayanan Rumah Sakit Melalui Sistem Informasi Rawat Inap dan Rawat Jalan Berbasis Web di Rumah Sakit Umum Daerah (RSUD) Kota Prabumulih Aditya Fersta Alwi; Evi Yulianingsih
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.557

Abstract

Digital transformation has become an essential necessity in improving the quality of healthcare service, including the management of patient and outpatient services.Rumah Sakit Umum Daerah (RSUD) Kota Prabumulih faces various challenges in managing patient data, administrative record-keeping, and presenting information that is not yet optimally integrated. These conditions affect the efficiency of staff performance and the overall quality of service provided to patients. This study aims to design and implement a web-based inpatient and outpatient information system as part of the hospital’s digital transformation efforts. The system is developed using web-based technology integrated with a database to manage patient data, registration processes, and reporting. The results of study indicate that the developed information system is able to improve the speed, accuracy, and percision of data management, as well as facilitate easier acces to information of the hospital. Therefore, the implementation of web-based inpatient and outpatient information system can support digital transformation and enhance the quality of healthcare services at RSUD Kota Prabumulih.
Analisis Komprehensif Arsitektur Serverless Container dan Edge v8 Isolate pada Penerapan Industri Anla Harpanda; Muhammad Nawaf Akbar; Rahmat Hidayat
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.569

Abstract

This study presents a comparative performance analysis of response times between Serverless architecture (AWS Lambda container-based) and Edge Computing (V8 Isolate-based). The evaluation focused on handling CPU-intensive computational loads using the Hono.js framework via the execution of 1,000 concurrent requests per platform. Measurements were strictly centered on Client-Side Round Trip Time (RTT) to ensure a fair comparison, deliberately bypassing server-side timing due to time quantization security restrictions inherent in the V8 Isolate environment. Empirical results demonstrate that Vercel recorded an average RTT of 432.40 ms, which is 76.29% faster than Cloudflare Workers' average of 762.29 ms. The Mann-Whitney U significance test statistically confirmed this difference (p < 0.05). Furthermore, consistency analysis via the Coefficient of Variation (CV) placed Vercel ahead with a highly stable value of 0.116 compared to Cloudflare's 0.527. Cloudflare also exhibited a larger cold start latency gap during the warm-up phase (28.03 ms difference) compared to Vercel (7.16 ms difference). The conclusion indicates that for REST API applications with heavy computational loads, container-based serverless architecture provides significantly superior stability, lower tail latency, and overall efficiency compared to Edge Isolate, challenging the theoretical assumption of absolute Edge network superiority in industrial scenarios.
Penerapan Augmented Reality Markerless pada E-Commerce Tanaman Hias Berbasis Web dan Mobile Andika Kukuh Prasetyo; Wahyu Sri Utami
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.580

Abstract

This study presents the development of an ornamental plant e-commerce system integrated with Markerless Augmented Reality (AR) technology, supporting both web and mobile platforms. The system addresses two identified problems: SME ornamental plant sales that still rely on informal social media without structured management, and the inability of online buyers to visualize products in their real environment before purchasing. The system was developed using the Waterfall method. The mobile application uses Flutter, the web admin dashboard uses Laravel with Filament, and the AR module uses Unity with ARFoundation and Google ARCore, all connected through a RESTful API with MySQL as the primary database, and integrated with Midtrans for payment and RajaOngkir for shipping. System verification was conducted through Black Box Testing and AR Performance Testing. Black Box Testing confirmed that all 15 mobile and 11 web admin test scenarios produced expected outputs, achieving a 100% success rate. AR Performance Testing on two Android devices showed stable performance on the Infinix GT 30 Pro (Dimensity 8350 Ultimate), while the Xiaomi Redmi Note 13 5G (Dimensity 6080) experienced frame rate fluctuations due to thermal throttling; neither device encountered force close or crash. These results confirm the system functionally addresses both problems: providing a structured digital sales platform for ornamental plant SMEs and enabling buyers to visualize plants in their real environment before purchasing.
Sistem Informasi Manajemen Layanan Rumah Jahit Berbasis Web Menggunakan Model Waterfall dan Framework Laravel Visa Yama; Hanriyawan Adnan Mooduto; Humaira
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.599

Abstract

The rapid growth of small and medium enterprises (SMEs) in the fashion and tailoring industry demands high operational efficiency to maintain customer satisfaction. One Tailor, a boutique tailoring service in Bukittinggi, conventionally managed its daily operations using manual paper-based logs. This approach created significant vulnerabilities, including data loss risks, tedious customer body measurement retrieval (taking 5–10 minutes per record), financial accounting discrepancies, and delayed garment completions due to disorganized production scheduling. This study aims to design and implement a web-based management information system specifically tailored to resolve these operational bottlenecks. Adopting the software development life cycle (SDLC) Waterfall model, the system was developed using PHP with the Laravel 10.x framework and MySQL as the relational database management system. Security measures such as Bcrypt hashing, Cross-Site Request Forgery (CSRF) protection, and role-based middleware were incorporated to protect customer confidentiality. The developed system features digital body measurement archiving, an automated notification scheduler for production deadlines, integrated financial auditing modules, and automated readiness alerts for customers. Functionality and validation testing confirmed that the system eliminates data redundancy, accelerates record retrieval to under three seconds, organizes production tracking, and eradicates cash-flow calculation discrepancies. This research demonstrates how the transition from manual ledger systems to localized web frameworks significantly optimizes workflows and service reliability within micro-enterprises
the Patrick Tshimanga Kapuba; Donking Nsidiovova Kialanda; Jean Teddy Nzinga Tene; Simon Badibanga Ntumba; Eugene Mukendi Mbuyi
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.601

Abstract

The increasing complexity of analytical workloads in banking systems challenges traditional query scheduling mechanisms, particularly in OLAP environments where MDX queries exhibit heterogeneous computational costs and business criticality. This study proposes a semantic-aware scheduling framework based on incremental machine learning to dynamically prioritize MDX queries in real time. The approach models query prioritization as a classification problem, integrating both technical features and business-driven criticality. A Hoeffding Tree algorithm is employed to enable continuous learning from streaming query data without requiring retraining. The model is evaluated using a simulated dataset of 10,000 MDX queries reflecting realistic banking scenarios, including risk monitoring and regulatory reporting. Experimental results show that the proposed approach achieves a classification accuracy of 94.1% and significantly reduces processing latency for high-priority queries, with improvements reaching 42.4% compared to FIFO scheduling. The inference overhead remains negligible, ensuring compatibility with real-time system constraints. These findings demonstrate the effectiveness of integrating incremental learning into query scheduling and highlight the potential of semantic-driven optimization in decision support systems. The study contributes to bridging the gap between learned database systems and business-aware query management.
Deteksi Malware pada File Executable Menggunakan Machine Learning Random Forest M. Cakra Adhana; Alde Alanda; Hidra Amnur; Febrian Kasmar
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.602

Abstract

The pervasive expansion of digital infrastructure has triggered an exponential surge in cyber threats, with malicious software (malware) posing a paramount risk to information security systems. Traditional signature-based and heuristic detection methods demonstrate severe limitations in mitigating zero-day exploits and multi-variant obfuscated malware due to their rigid dependency on existing signature repositories and susceptibility to high false-positive rates. To transcend these boundaries, this study introduces an adaptive and robust static detection framework for Portable Executable (PE) files leveraging the ensemble machine learning technique of Random Forest. Utilizing a structured dataset comprising PE files harvested from public malware repositories including Malware Bazaar alongside verified benign applications, static analysis was performed without code execution to preserve environment safety. A total of 75 distinctive structural features spanning COFF headers, section characteristics, data directories, and configuration markers were systematically extracted using the Python pefile library. The model was trained using an 80:20 data split ratio. Experimental evaluation achieved an exceptional internal generalization capability with an Out-of-Bag (OOB) score of 97.43%. Independent validation on a test suite of 332 unseen files yielded a balanced confusion matrix comprising 160 True Positives, 164 True Negatives, 5 False Positives, and 3 False Negatives, establishing a high precision, recall, and F1-score of approximately 98%. Feature importance analysis highlighted that parameters such as MajorOperatingSystemVersion, MajorSubsystemVersion, and DllCharacteristics serve as critical discriminators. Finally, the optimized predictive model was integrated into a web-accessible application architecture powered by Flask and MySQL to facilitate user-driven file uploading and real-time inference reporting, offering an scalable complementary defense layer for modern cybersecurity ecosystems
Arsitektur Sistem Point of Sale (POS) Multi-Cabang Berbasis Web untuk Perusahaan Ritel Terdistribusi: Studi Kasus pada Raffi Collection Mardhatillah; Aldo Erianda; Ronal Hadi
JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Vol 7 No 2 (2026)
Publisher : SOTVI - Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/jitsi.7.2.606

Abstract

In the modern retail ecosystem, managing distributed store operations through manual interventions presents critical vulnerabilities regarding data consistency, synchronization delays, and operational inefficiencies. This research addresses these systemic limitations by designing and implementing a web-based, centralized Multi-Branch Point of Sale (POS) system tailored for Raffi Collection, a retail enterprise managing three geographically dispersed branches in Bukittinggi. Adopting the structured Waterfall development methodology—encompassing requirements analysis, system design, implementation, testing, and maintenance—the platform was engineered utilizing the Laravel MVC framework and a centralized MySQL relational database management system. The system architecture incorporates a robust Role-Based Access Control (RBAC) mechanism defining distinct operational permissions for Super Admins and Branch Admins. Key functional workflows feature real-time transaction processing with automated cryptographic-like receipt string generation, an advanced cross-branch stock transfer approval workflow, and dynamic multi-criteria reporting engines covering sales, expenditures, inventory mutations, and net profit-loss analytics. Empirical system testing validated absolute data synchronization across all nodes, strict enforcement of security policies (demonstrated by automated 403 Access Denied responses to unauthorized routing), and precise financial auditing capability. The implementation effectively eliminates data redundancy, mitigates recording latencies, and provides business stakeholders with real-time, data-driven decision support tools

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