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INDONESIA
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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Implementasi Metode Double Diamond Dalam Perancangan UI/UX Aplikasi Halopet Marketplace Layanan Hewan Peliharaan Mahadevi Katarina Sabila; Seftin Fitri Ana Wati; Prasasti Karunia Farista Ananto
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.v5i2.400

Abstract

The rapid growth of the pet care industry in Indonesia has not been accompanied by integrated service systems, resulting in various issues such as limited information, inefficient booking processes, and poor schedule management. This study aims to design the UI/UX of the Halopet application as a pet care service platform using the Double Diamond method to produce user-oriented design solutions. The evaluation was conducted using Heuristic Evaluation and Usability Testing based on the ISO 9241-11 standard. The results show an effectiveness score of 97% and an efficiency score of 97.19%, with a System Usability Scale (SUS) score of 92, categorized as excellent. These findings indicate that the proposed application design is capable of improving usability, efficiency, and user satisfaction in accessing pet care services. This study also contributes by proposing an integrated pet care service platform design through a UI/UX approach focused on user experience and a high level of usability.
Klasifikasi Multi-Label Dan Ekstraksi Entitas Pada Ulasan Aplikasi Blu by BCA Digital Menggunakan IndoBERT Bhagas Satrya Dewa; Eka Dyar Wahyuni; Nur Cahyo Wibowo
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.v5i2.402

Abstract

The growth of digital banking services in Indonesia has heightened the need to understand factors influencing users' application continuance intention. However, prior studies remain limited to single-label classification and general sentiment analysis, lacking the ability to capture the complexity of information in Indonesian-language user reviews in a structured manner. This study aims to perform multi-label classification based on four Expectation-Confirmation Model (ECM) factors—Confirmation, Perceived Usefulness, E-satisfaction, and Perceived Security—and to extract six Named Entity Recognition (NER) entities from Blu by BCA Digital application reviews using IndoBERT. The dataset was collected from Google Play Store and Apple App Store covering January to December 2025, yielding 3,389 Indonesian-language reviews after filtering. The study employs a single-task approach, applying oversampling and Focal Loss for multi-label classification, and token augmentation with Conditional Random Field (CRF) for NER. Annotation validation using Krippendorff's Alpha yielded average values of 0.856 for intent labels and 0.919 for NER entities. Results show that the best classification model achieved an F1-Score of 0.798 with a Hamming Loss of 0.131, while the best NER model achieved an F1-Score of 0.812. This study demonstrates that IndoBERT is effective for analyzing digital banking application reviews in identifying ECM factors and extracting domain-specific entities, thereby offering potential support for developers in automatically understanding user needs.
Perancangan Sistem Asisten Produktivitas Pribadi Cerdas “Prioritas Bot” Menggunakan Large Language Model (LLM) Berbasis N8N dan Telegram Elita Nur Ilahi; Muhammad Encep; Setyono Setyono
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.v5i2.405

Abstract

The complexity of task and workflow management in the digital era necessitates intelligent assistive tools. This study designs an Intelligent Personal Productivity Assistant System by integrating three primary components: (1) A Large Language Model (LLM) GPT-4o serving as the processing core for natural language understanding and contextual response generation; (2) The n8n low-code automation platform, acting as an orchestrator to manage workflows and connect the LLM to external APIs such as Google Calendar; and (3) A Telegram Bot utilized as the primary user interface due to its high accessibility. The design methodology employs a Prototyping approach adapted from Pressman & Maxim (2020), enabling iterative development and functional validation. Black Box Testing was applied for functional evaluation, while the System Usability Scale (SUS) was used to measure usability, involving 20 active university students in the Bogor region selected through Purposive Sampling. The research resulted in a functional prototype capable of managing schedules end-to-end via conversational natural language. The system achieved an average SUS score of 88.5 from 20 respondents, classified as Excellent with a Grade A rating, indicating the significant potential of integrating LLMs and workflow automation to effectively enhance personal productivity.
Analisis Sentimen Berita Keuangan Berbahasa Indonesia Menggunakan IndoBERT dan LSTM untuk Klasifikasi Tren Harga Saham pada Lima Emiten Blue Chip LQ45 Firman Wijaya Kusuma; Ali Alamsyah Kusumadinata; Hilmy Aliy Andra Putra
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.v5i2.407

Abstract

Blue chip stock price movements within the LQ45 index are non-linear and stochastic, causing conventional statistical approaches to fail in generating reliable predictions. This study develops and evaluates a hybrid deep learning architecture combining IndoBERT—a BERT-based language model pre-trained on Indonesian-language corpora—with Long Short-Term Memory (LSTM) networks to classify daily stock price trend direction (up/down). Trend labels are derived from daily return values: a return greater than zero is labeled Up (1), otherwise Down (0). Sentiment scores were extracted via IndoBERT fine-tuning from 9,819 Indonesian-language financial news articles (CNBC Indonesia) and merged with historical OHLCV data and technical indicators as model features. Experiments were conducted on five LQ45 blue chip equities: BBRI.JK, BBNI.JK, BBCA.JK, BMRI.JK (Financial Sector), and GOTO.JK (Technology). The hybrid model outperformed the baseline on three of five equities, with the highest accuracy improvement on BBCA.JK (+23.21 points, from 33.93% to 57.14%) and BMRI.JK (+12.50 points, from 46.43% to 58.93%). The overall average Relative Error Reduction (RER) reached +9.81%, demonstrating that integrating IndoBERT sentiment significantly enhances LSTM-based stock trend prediction in the Indonesian capital market.
Evaluasi Usability Antarmuka Instagram pada Mahasiswa Arini Sastra Marulafau; Mahda Khairun Nazwa Daulay; Rafika Hadi Siregar; Syukri Falahi Capah; M. Khalil Gibran
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.v5i2.411

Abstract

This study examines the usability of Instagram’s interface among university students since Instagram has become one of the social media platforms most frequently used in daily life and academic activities. The study aims to find out how easy and comfortable Instagram is to use based on Nielsen’s usability dimensions which include learnability, memorability, efficiency, error prevention, and satisfaction. This research used a descriptive quantitative method by distributing a 5-point Likert scale questionnaire to 76 active university students in May 2026. The results showed that the overall usability score reached 3.88 and was categorized as “Good”. The satisfaction dimension obtained the highest score of 3.98 while error prevention received the lowest score of 3.75. The findings also revealed that some students were still confused by the similarity between the Reels and Explore features while the placement of advertisements was considered disruptive to navigation. In addition, many respondents suggested adding a study focus mode to support productivity while using Instagram. Overall, Instagram already provides a good usability experience, although improvements are still needed in navigation consistency, error prevention, and features that better support student needs.  
Implementasi Metode Waterfall untuk Sistem Penjadwalan Perkuliahan pada Universitas Muhammadiyah Bima Iis Muzdalifah; Teguh Ansyor Lorosae; Irma Eryanti 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.v5i2.415

Abstract

Course scheduling is a crucial activity in academic management because it involves organizing lecturers, courses, classrooms, and time allocations in an integrated manner. At Universitas Muhammadiyah Bima, the scheduling process was still conducted manually using spreadsheets, resulting in frequent schedule conflicts, repeated revisions, and inefficient management processes. This study aims to design and implement a web-based course scheduling system capable of overcoming these problems through an automatic constraint-based validation mechanism. The system was developed using the CodeIgniter 4 framework and the Waterfall development method. The main contribution of this research lies in the implementation of real-time automatic validation capable of detecting and preventing conflicts involving lecturers, classrooms, and class schedules before the data are stored in the database, thereby producing a more consistent and reliable scheduling process compared to the previous manual method. System testing was carried out using the Black-box Testing method on 10 testing scenarios covering input validation, schedule conflict detection, data manipulation, and schedule information access. The testing results showed that all scenarios were successfully executed with a success rate of 100%, indicating that all system functions operated in accordance with user requirements. Therefore, the developed system is able to improve the effectiveness of course scheduling management while minimizing scheduling conflicts within the academic environment.
Perancangan Sistem Booking Mini Soccer dengan Payment Gateway dan Dashboard Analitik Menggunakan Metode RAD M. Iwan Setiawan; Irma Eryanti Putri; Teguh Ansyor Lorosae
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.v5i2.416

Abstract

Information systems play an important role in improving the effectiveness and efficiency of sports facility rental services. S-Soccer Kota Bima still uses a conventional booking system that causes schedule conflicts, delays in confirmation, and unintegrated transaction management. This study aims to design a website-based mini soccer field booking system equipped with a payment gateway feature. The system development applies the Rapid Application Development (RAD) method through the stages of requirements planning, design workshop, and implementation. The system provides features for real-time schedule booking, customer data management, digital payments, and an administrative analytics dashboard. System testing was conducted using the Black Box Testing method on 12 testing scenarios covering registration, login, booking, payment, and data management features. The testing results indicate that all features operated according to user requirements with a success rate of 100%. The developed system is able to improve the efficiency of the booking process, accelerate payment validation, and minimize schedule conflicts compared to the conventional method previously used at S-Soccer Kota Bima.
Analisis Klaster Lagu Indonesia pada Platform Spotify Menggunakan Algoritma K-Means (Studi Kasus: Spotify) Rizki Nur Azim; Sudin Saepudin
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.v5i2.417

Abstract

The growth of streaming platforms like Spotify has revolutionized music consumption in Indonesia, generating complex song performance data from Spotify Charts. This study aims to cluster Indonesian songs by popularity using the K-Means Clustering algorithm. The selected variables—peak, previous, streak, and streams—were chosen because they directly reflect song performance dynamics on the charts, encompassing best position, rank movement, longevity, and play volume, making them more representative of market resonance than audio features alone. A quantitative descriptive approach was applied to Indonesia Spotify Charts data spanning January 2020 to December 2024, with a purposive sample of 5,316 records post-cleaning. The optimal number of clusters was determined via the Elbow Method at k=3, with cluster quality evaluated using a Silhouette Score of 0.4968. Findings reveal three clusters: Cluster 0 (medium popularity, 3.8M average streams), Cluster 1 (low popularity, 569K average streams), and Cluster 2 (high popularity, 54M average streams). The study concludes that K-Means effectively identifies objective popularity patterns to support data-driven promotion strategies.
The Implement’s Steganografi LSB dan Kriptografi AES-256 untuk Pengamanan Data Citra Digital Muhammad Haris; Dedi Irawan; Gunawan Gunawan; Mahardika Abdi Prawira Tanjung
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.v5i2.420

Abstract

Digital data security has become a critical issue in the digital transformation era, particularly in the exchange of digital images that are vulnerable to interception and manipulation by unauthorized parties. This study aims to implement a layered data security method by combining Advanced Encryption Standard (AES) 256-bit cryptography and Least Significant Bit (LSB) steganography on PNG-format digital images. The approach used is encrypt-then-embed, where the secret message is first encrypted using AES-256 in CBC mode, then the ciphertext is embedded into the cover image pixels through LSB bit substitution. Testing was conducted on five test images with varying resolutions (256×256 to 1024×768 pixels) using Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), entropy, avalanche effect, and computation time metrics. The test results show an average PSNR of 70,58 dB and MSE of 0.11, indicating excellent visual quality of the stego images. Security analysis shows an average avalanche effect of 50.29%, approaching the ideal value of 50%, and stego image entropy approaching 7.0545 bits/pixel. The computation time for encryption and embedding processes ranges from 0,005847 to 0,006078 seconds. The combination of AES-256 and LSB has proven effective in providing layered security: AES-256 ensures data confidentiality, while LSB conceals the message existence within the image without significant visual degradation.
Implementasi Sistem QR Code Dalam Meningkatkan Tingkat Kepatuhan Pengisian Checklist Pemeriksaan Kendaraan Harian di PT XYZ: Studi Komparatif Sebelum dan Sesudah Penerapan Muhammad Helmy Ilhamsyah; Felixtianus Eko Wismo Winarto; Lilik Dwi Setyana; Nur Rokhman
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.v5i2.426

Abstract

Daily vehicle inspection is an important component of risk control in occupational safety and health (OSH) management systems. However, manual inspection processes often result in low compliance in checklist completion, reporting delays, and limited monitoring capabilities. This study aims to analyze the effect of implementing a QR Code system on the compliance level of daily vehicle inspection checklist completion at PT XYZ. The study employed a quasi-experimental design with a one-group pretest-posttest approach involving 35 operational vehicles. Data were collected from vehicle inspection checklists before and after the implementation of the QR Code system and analyzed using descriptive and inferential statistics through a paired sample t-test. The results showed that the compliance level increased from 72.2% before implementation to 90.2% after the implementation of the QR Code system. Statistical testing indicated a significant difference in compliance levels before and after implementation with t(34)=26.7 and p<0.001. An effect size value of 4.52 indicated a very large effect on compliance improvement. The implementation of the QR Code system proved effective in improving checklist completion, strengthening monitoring processes, and supporting the digitalization of occupational safety and health management systems in operational environments.

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