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Jurnal Ilmu Komputer dan Sistem Informasi
Published by Unity Academy
ISSN : 28306031     EISSN : 28303954     DOI : -
Core Subject : Science,
Computer Science & IT Library & Information Science
Jurnal Ilmu Komputer dan Sistem Informasi (JIRSI) dikelola secara profesional oleh LKP UNITY Academy dalam membantu para akademisi, peneliti dan praktisi untuk menyebarkan hasil penelitiannya dalam panduan Kemendikbud Ristek Dikti. Jurnal Ilmu Komputer dan Sistem Informasi (JIRSI) Adalah sebuah Jurnal blind peer-review yang didedikasikan untuk publikasi hasil karya ilmiah yang berkualitas di bidang Ilmu Komputer dan Teknologi Informasi (bidang rekayasa perangkat lunak, ilmu komputer, sistem informasi, teknologi informasi dan komunikasi, meachine learning, mikrokontroller, artificial intelligence, computer vision, jaringan komputer). Jurnal Ilmu Komputer dan Sistem Informasi (JIRSI) Terbit 3 kali setahun (Januari, Mei, September).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 149 Documents
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Model Model UTAUT2 dalam Evaluasi Faktor-Faktor yang Mempengaruhi Niat Pembelian pada Konten Affiliate TikTok Shop Devita Fahliza Ulfa; Arista Pratama; Siti Mukaromah
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.361

Abstract

The growth of TikTok Shop’s affiliate program provides opportunities for affiliates to earn commissions from uploaded content. However, the low purchase conversion rate indicates challenges in shaping BI. This study aims to analyze the factors influencing purchase intention in TikTok Shop affiliate content by adapting a modified UTAUT2 model. This research employed a quantitative approach through a survey of 410 respondents selected using purposive sampling, with the criteria of active TikTok users who had interacted with TikTok Shop affiliate content. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships among variables in the research model. The results show that only PV has a significant effect on BI. Although EE and HT significantly affect HM, they do not directly influence BI. In addition, HM, TR, FC, and PE do not show a significant effect on BI. This study contributes by extending the application of the UTAUT2 model to the social commerce context, particularly TikTok Shop affiliate content, and emphasizes the importance of enhancing PV as the main factor in encouraging BI.
Penerapan Arsitektur U-Net pada Segmentasi Cacat Biji Kopi untuk Optimalisasi Inspeksi Kualitas Ami Rahmawati; Ita Yulianti; Ani Oktarini Sari; Siti Nurajizah
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.365

Abstract

Manual visual inspection of coffee bean defects remains prone to subjectivity and inconsistency, necessitating a more accurate and efficient approach. This study proposes a deep learning-based coffee bean image segmentation method using the U-Net architecture to detect the presence of defects in coffee beans using a binary segmentation approach. The dataset consists of 300 coffee bean images evenly divided into 150 images of black coffee and 150 images of insect damage. Annotation was performed using a semi-automatic pseudo-labeling method based on Gaussian filtering, absolute difference, and thresholding to generate ground truth in binary mask format. Training data was enriched through augmentation techniques including horizontal flip, vertical flip, rotation, and brightness-contrast adjustment. The model was trained using a combined loss function of Dice Loss and Binary Cross-Entropy with the Adam optimizer over 15 epochs with an early stopping mechanism. Evaluation results demonstrate excellent performance with a Mean IoU of 0.9240, Precision of 0.9707, Recall of 0.9495, and F1 Score of 0.9600, with an overall correct prediction rate of 97.45% based on pixel-level confusion matrix analysis. These results indicate that the U-Net architecture is capable of segmenting defective coffee bean areas accurately and consistently, making it a promising foundation for the development of an automated coffee quality inspection system.
Perancangan Sistem IoT Untuk Monitoring Getaran dan Stress Pada Kanopi Rumah Berbasis ESP32 Raushan Dhamir; Mhd. Basri
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.366

Abstract

The development of Internet of Things (IoT) enables real-time and continuous monitoring systems. Lightweight structures such as house roofs or canopies are vulnerable to environmental and load changes, yet monitoring is still commonly performed manually, making early detection difficult. This study aims to design and implement an IoT-based canopy structure monitoring system using ESP32 integrated with an MPU6050 vibration sensor, a load cell with HX711 module, and a DHT22 temperature and humidity sensor. Measurement data are transmitted via WiFi to a server for database storage and visualization through a web-based dashboard. Furthermore, the collected data are processed using the Relative Corrosion Potential Index (IPKR), calculated based on normalized parameters including temperature, humidity, vibration, and load variation. The results show that the system is capable of performing real-time data acquisition, transmission, and visualization effectively. The system also provides structural condition indicators based on IPKR values classified into safe, warning, and danger categories. Therefore, the developed system can serve as an effective and informative early monitoring solution for detecting changes in lightweight structure conditions.
Implementasi Smart Home Berbasis IoT: Studi Simulasi Menggunakan Cisco Packet Tracer Ondihon Parlinggoman Munthe; Alz Danny Wowor
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.370

Abstract

The rapid development of Internet of Things (IoT) technology enables automatic and remote control of home appliances. However, direct hardware implementation often entails high costs and complex configurations. This study aims to design and analyze the performance of a Smart Home system through a simulation approach using Cisco Packet Tracer software. The method encompasses network topology design, core network service configuration, and functionality and Quality of Service (QoS) testing to validate the proposed design. Simulation results demonstrate that the constructed system operates successfully, with the Smartphone effectively controlling electronic devices in real-time. QoS testing recorded 0% packet loss and an average latency of 27 ms, indicating reliable connectivity between user devices and the IoT Server. This study concludes that simulation using Cisco Packet Tracer is effective as a preliminary validation stage in designing Smart Home infrastructure before physical implementation.
Use of Data Visualization Techniques in Bioinformatics for Time-Based Gene Expression Pattern Analysis M. Khalil Gibran; Mhd Ikhsan Rifki; Amir Saleh
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.373

Abstract

This study explores data visualization techniques in bioinformatics for analyzing time-series gene expression patterns. It examines how different visualization approaches support the interpretation of large-scale temporal gene expression data. A dataset comprising 4,381 genes across 24 time intervals was analyzed using heatmaps, Principal Component Analysis (PCA), volcano plots, and dendrograms. Heatmaps were used to observe expression correlations, PCA was applied to reduce dimensionality, volcano plots identified differentially expressed genes between conditions, and dendrograms grouped genes with similar expression profiles. The PCA results showed that the first two principal components accounted for 42.32% of the total variance, indicating that these components captured a substantial but not complete portion of the data structure. Volcano plot analysis detected differentially expressed genes based on log2 fold change > 1 and p-value < 0.05, while dendrogram visualization revealed several major clusters with comparable temporal expression patterns. Overall, the findings suggest that combining multiple visualization methods can improve the exploratory analysis of temporal gene expression data by clarifying patterns, highlighting potentially relevant genes, and supporting further biological interpretation. Rather than serving as standalone evidence for clinical application, these visual approaches provide a useful analytical foundation for subsequent validation, biomarker investigation, and large-scale omics research.  
Analisis Sentimen Publik Terhadap Revisi UU TNI 2025 Menggunakan Algoritma Naïve Bayes Rizky Barus; Rakhmat Kurniawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.380

Abstract

The development of public opinion regarding the revision of the 2025 Indonesian National Armed Forces Law (UU TNI) on social media has generated various responses that are difficult to analyze manually due to the large and unstructured amount of data. This condition requires a computational approach that is able to systematically identify public sentiment trends. This study aims to analyze public sentiment towards the revision of the 2025 TNI Law using the TF-IDF-based Naïve Bayes algorithm and evaluate the performance of the classification model used. The research data was obtained through crawling techniques from YouTube user comments related to the revision of the 2025 TNI Law. The data processing stages include cleaning, case folding, tokenizing, normalization, stopword removal, and stemming before TF-IDF weighting and the classification process using Naïve Bayes. The results of the study of 1826 data show that public sentiment is dominated by the neutral category at 79.8%, while positive sentiment is 13.1% and negative sentiment is 7.0%. The model evaluation yielded an accuracy of 77.11%, but the model showed a bias toward the majority class, resulting in suboptimal classification of positive and negative sentiments. Based on these results, the Naïve Bayes method is quite effective as an initial approach in sentiment analysis, but it still has limitations in handling imbalanced datasets and the complex characteristics of social media language. Therefore, the development of more adaptive methods is needed to improve the quality of sentiment classification results.
Prototype Design of Adaptive Composite Springs As An Anti-Seismic Infrastructure System For Multi-Story Buildings Auni Zahratu Syifa; Naziha Alqiara; Muhammad Fakhri; Muhammad Ghaziyan Faizan; Afryansyah Afryansyah
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.384

Abstract

This study aims to design and formulate earthquake dampers composed of carbon fiber and epoxy resin, employing a specialized configuration to produce anti-seismic devices that are corrosion-resistant, adaptively flexible, and capable of supporting building loads effectively. A quantitative design-based methodology was applied, encompassing prototype design, material selection, and performance testing against vertical loads and seismic vibrations. Evaluation was conducted using a hydraulic press to determine maximum vertical load capacity and a shake table to simulate horizontal and vertical seismic activity according to the Richter scale. The results indicate that the composite dampers can absorb seismic energy bidirectionally, maintain structural integrity without significant material degradation, and require minimal maintenance. These findings demonstrate the potential of carbon fiber and epoxy resin-based dampers as adaptive seismic isolation systems that are robust, durable, and suitable for multi-story buildings, while meeting the demands for economical, efficient, and sustainable infrastructure solutions.
Integrasi Algoritma DBSCAN Dengan Sistem Informasi Geografis Untuk Mengidentifikasi Cluster Wilayah Rawan Kebakaran Provinsi Riau Chairun Nas; Khairul Fajri Ilahi; Boy Sandy Dwi Nugraha
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.386

Abstract

Riau Province is one of the regions in Indonesia that is prone to forest and land fires (karhutla), especially during the dry season. Accurately identifying the distribution patterns of fire-prone areas is crucial in supporting disaster mitigation and management efforts. This study aims to identify the spatial patterns (Cluster) of forest and land fire-prone areas (karhutla) in Riau Province using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm integrated with a Geographic Information System (GIS). This study uses NASA-MODIS data taken from 2020 to 2024 with 840 data records. The analysis results show that DBSCAN is able to effectively group hotspots, with Cluster 2 being the largest cluster covering 297 karhutla points in Bengkalis, Rokan Hilir, and Dumai. The large number of points in this cluster is due to the high frequency of forest and land fires between 2020 and 2024. However, Cluster 7 shows the best density quality with a Silhouette Coefficient value of 0.872, surpassing Cluster 2 which has a value of 0.638. The overall average Silhouette Coefficient value is 0.683, indicating that the cluster modeling is quite optimal. A total of 57 hotspots are categorized as noise, but still provide a picture of the distribution of forest and land fires. GIS-based map visualization reveals that most fire hotspots are located in peatlands and dry vegetation areas that are consistent from year to year. The results of the study confirm that the use of appropriate DBSCAN parameters (epsilon and minPts) produces accurate spatial visualization and supports more effective and targeted mitigation strategies and fire monitoring based on priority areas.    
Geo-Insight MBG: Sebuah Platform Geospasial untuk Mengukur Dampak Program Makan Siang Gratis terhadap Status Gizi Anak Ashabul Kahpi; Harianto Harianto; Ariastuti Rahman
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.394

Abstract

The Free Nutritional Meal Program (MBG) is a strategic national policy designed to improve the nutritional status of school-aged children. However, impact evaluation remains largely manual and administrative, hindering the identification of priority areas and integrated monitoring of anthropometric changes. This study aims to develop Geo-Insight MBG, a web-based geospatial platform to measure the program’s impact on children’s nutritional status. The methodology employs the Waterfall software development model and quantitative descriptive analysis of height, weight, and body mass index data collected before and after the intervention. System testing demonstrates that the platform successfully visualizes beneficiary distribution, automatically calculates nutritional categories based on z-scores, and generates interactive dashboards and regional heatmaps. Preliminary results from a pilot sample of 15 children indicate that 73.3% showed nutritional improvement, with an average z-score increase of +0.83. While these findings suggest the platform’s potential for enhancing location-based monitoring and data-driven decision-making, the limited sample size necessitates cautious interpretation of the program’s effectiveness. Future studies with larger, multi-regional cohorts are needed to validate these results. Nonetheless, Geo-Insight MBG demonstrates promise as a scalable digital evaluation tool that could support optimized resource allocation and targeted interventions in national school nutrition programs.
Rancang Bangun Sistem Informasi Enterprise Resource Planning (ERP) Pada Dinas Kesehatan Kota Medan Feby Hasanah Ritonga; Raissa Amanda Putri
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.398

Abstract

The Medan City Health Office faces various challenges in managing human resources and inventory due to manual administrative processes, resulting in data inaccuracies, delays, and low operational efficiency. This study aims to design and implement an Enterprise Resource Planning (ERP) system using Human Resource Management (HRM) and Inventory Management (IM) modules. The research employed a qualitative method with data collection techniques consisting of observation, interviews, and literature study. System development used the Rapid Application Development (RAD) method, which includes requirement planning, workshop design, and implementation stages. The results indicate that the ERP system is capable of integrating employee management, attendance, payroll, training, inventory, and stock management processes. The developed system improves data accuracy, accelerates administrative processes, and supports more effective decision-making. Therefore, the implementation of ERP at the Medan City Health Office can enhance efficiency, transparency, and the quality of healthcare services.

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