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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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Evaluasi Pengaruh Parameter Alpha terhadap Akurasi Metode Single Exponential Smoothing pada Data Persediaan Barang Retail Zuli Gultom; Ika Windiarti; Muhammad Andika Wardana
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.v5i2.430

Abstract

This study aims to evaluate the effect of the alpha parameter on the accuracy level of the Single Exponential Smoothing (SES) method on retail inventory data. The evaluation was conducted using the MAD, MSE, and MAPE error values. The study used Toko Murni's retail inventory data from January 2025 to February 2026, consisting of white rice, cooking oil, bread flour, and 60 ml Bango sweet soy sauce. The evaluation process was carried out using a variation of alpha values ​​​​from 0.1 to 0.9. The evaluation results showed that low alpha values ​​​​provide a better level of prediction accuracy than high alpha values. In the white rice data, the use of alpha 0.1 resulted in a MAD value of 75.41, MSE 7167.35, and MAPE 16.86 with a prediction result of 460.43. For cooking oil, alpha 0.1 resulted in a prediction value of 75.66 with a MAPE of 18.6, while for 60 ml Bango sweet soy sauce, it resulted in a prediction of 80.51 with a MAPE of 12.79. Meanwhile, in the bread flour data, the optimal alpha value was obtained at alpha 0.2 with a predicted result of 67.19 and MAPE of 19.71.
Implementasi Sistem Pemesanan Restoran Berbasis Web Menggunakan Kode QR dan Payment Gateway Donny Fauzi; Cyntia Rivatunisa; Hardiansyah Hardiansyah; Athia Saelan
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.v5i2.441

Abstract

Kurangnya koordinasi dan efisiensi waktu yang rendah merupakan hambatan utama dalam model layanan restoran tradisional. Untuk mengatasi masalah ini, penelitian ini mengimplementasikan sistem pemesanan dan pembayaran berbasis web dengan memanfaatkan teknologi Kode QR sebagai instrumen digitalisasi transaksi terintegrasi. Pengembangan sistem mengikuti metodologi waterfall, dengan pengujian dilakukan melalui metode pengujian black box. Hasilnya menunjukkan bahwa sistem yang dikembangkan secara efektif memfasilitasi pelanggan dalam melakukan pemesanan sendiri dan mempercepat aliran informasi pesanan kepada kasir dan staf dapur secara real-time. Berdasarkan pengujian fungsional, semua fitur pembayaran baik tunai maupun digital beroperasi sesuai dengan desain. Studi ini menyimpulkan bahwa implementasi sistem berbasis web dan Kode QR secara signifikan meningkatkan efisiensi operasional restoran sekaligus memberikan pengalaman transaksi yang lebih nyaman dan praktis bagi pengguna.
Analisis Komparatif Embedding Semantik Berbasis Large Language Model Pada Sistem Rekomendasi Buku Serendipitous di Perpustakaan Kampus Rahayu Kartika Sari; Eka Dyar Wahyuni; Amalia Anjani Arifiyanti
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.v5i2.443

Abstract

The phenomenon of information overload in academic libraries often makes it difficult for users to discover relevant books, which may reduce reading interest. Conventional recommender systems are also prone to filter bubbles and tend to perform poorly under cold-start conditions. This study proposes a sequential recommendation system based on the Self-Attention Based Sequential Recommendation (SASRec) model integrated with five semantic embedding models, namely Word2Vec, BERT Multilingual, OpenAI text-embedding-3-small, Gemini-embedding-001, and Qwen3-Embedding-0.6B, to generate accurate and serendipitous recommendations. In addition, the Serendipity-Oriented Greedy (SOG) re-ranking algorithm is implemented to balance recommendation relevance and serendipity. The data set consists of 14,502 book records and 5,445 user interaction histories after the data cleaning process. Evaluation was conducted under three testing scenarios, namely the all-test set, warm test set, and cold test set, by comparing all model variants before and after the re-ranking process. The results show that the integration of Large Language Model (LLM)-based embeddings consistently improves performance compared to the standard SASRec model and traditional embeddings. Qwen3-Embedding-0.6B achieved the best performance, improving HitRate@10 by up to 282.9% and NDCG@10 by up to 387.8%, while maintaining semantic robustness in cold-start scenarios with an UnSerendipity@K score of 0.613. The implementation of SOG re-ranking reveals a direct trade-off between recommendation accuracy and diversity. Lightweight weighting provides the optimal balance, whereas overly aggressive weighting significantly reduces relevance. The main contribution of this study lies in integrating modern LLM embeddings into a sequential recommendation architecture to improve accuracy and cold-start robustness, while also evaluating the impact of serendipity-oriented re-ranking strategies on balancing recommendation relevance and diversity. Overall, this study demonstrates that modern LLM integration can produce a smarter, more adaptive, and more balanced library recommendation system in terms of both accuracy and serendipity.
Multilabel Aspect-Based Emotion Analysis Pada Ulasan Aplikasi IKD: Pengaruh Focal Loss dan Threshold Tuning Menggunakan Indobert Viviana Purba; Eka Dyar Wahyuni; Tri Luhur Indayanti Sugata
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.v5i2.448

Abstract

User reviews of the Identitas Kependudukan Digital (IKD) application contain various emotions toward different service aspects. These reviews not only reflect the level of service satisfaction but also encompass user experiences, complaints, expectations, and public perceptions regarding the quality of the system. This study aims to develop a multi-label Aspect-Based Emotion Analysis (ABEA) model using an end-to-end IndoBERT architecture to identify user emotions across each service aspect of the IKD application. Additionally, it analyzes the impact of implementing Focal Loss and threshold tuning on classification performance under highly imbalanced label distributions. Data were collected from 13,197 user reviews on the Google Play Store spanning from June 2024 to November 2025 using web scraping methods, which were subsequently cleaned and filtered to yield 6,891 data entries. Service aspects were empirically identified using BERTopics. Labeling was conducted by three human annotators and two AI annotators, with the final labels determined through majority voting. The model was developed across 6 experimental scenarios varying in preprocessing, Focal Loss, threshold tuning, and data split ratios. Evaluation was performed using F1 Score Macro, F1 Score Micro, Precision, Recall, and Hamming Loss metrics. BERTopic achieved a Coherence Score of 0.6196 and a Topic Diversity of 0.92 with 5 representative aspects. The most optimal model was obtained using a configuration of Focal Loss, a threshold of 0.4, and a 60:20:20 split ratio, achieving an F1 Score Macro of 0.3916, a 24.1% increase from the baseline, alongside an F1 Score Micro of 0.9134 and a Recall of 0.9423. The selected model was successfully integrated into a web-based system using the Flask framework to visualize the classification results. Anger dominated the reviews concerning the Login & Akses Akun and Scan Barcode ke Dukcapil aspects, whereas the Dokumen & Layanan Digital aspect recorded the highest joy emotion. The combination of Focal Loss and threshold tuning proved effective in handling imbalanced label distributions in Indonesian multi-label ABEA classification.
Analisis Perilaku Adopsi Livin Merchant Pada Pelaku UMKM di Surabaya Raya Menggunakan Model UTAUT2 Medica N Zakiah; Asif Faroqi; Rafika Rahmawati
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.v5i2.451

Abstract

The development of digital technology has encouraged the transformation of financial services in the micro, small, and medium enterprises (MSMEs) sector, one of which is through the use of the Livin’ Merchant by Mandiri application. However, the adoption process of digital services still faces several challenges, such as low technological literacy, risks associated with application usage, and low trust in system security and banking institutions. This study aims to analyze the factors influencing the adoption behavior of Livin’ Merchant among MSME actors in Greater Surabaya using the modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model with the addition of perceived security, perceived risk, institution trust, and technology trust variables. This study employed a quantitative approach through a survey of 521 MSME actors using Livin’ Merchant in Greater Surabaya. The data were analyzed using Partial Least Square-based Structural Equation Modeling (SEM-PLS) with the assistance of SmartPLS 4.0 software. The results indicate that performance expectancy, social influence, hedonic motivation, price value, perceived security, and institution trust have a positive and significant effect on behavioral intention. In addition, facilitating conditions have a positive and significant effect on use behavior, while perceived risk has a negative and significant effect on use behavior. This study concludes that application benefits, social support, system security, and trust in banking institutions are important factors in increasing the adoption of Livin’ Merchant among MSME actors in Greater Surabaya.
Rancang Bangun Website Travel Umroh Berbasis Web Sebagai Media Informasi dan Digital Trust Rahmad Saputra; Muliyono Muliyono; Yassirli Amri; Nurhidayat Nurhidayat
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.v5i2.456

Abstract

Umrah travel business is a service sector that strongly depends on the trust of prospective pilgrims. Therefore, service providers need an official information medium that is transparent, easily accessible, and able to validate the company’s identity. This study aims to design and develop a web-based umrah travel website as an information medium and a supporting platform for digital trust at Harira Tour and Travel. The system development method used in this study is the prototype method, consisting of requirement gathering, design, implementation, evaluation, and testing stages. The website was developed using WordPress CMS with several main features, including homepage, company profile, umrah packages, gallery, testimonials, contact information, and WhatsApp integration. The results show that the website is able to present service information in a structured manner, provide responsive access on desktop and mobile devices, and help prospective pilgrims obtain official information more easily. Black box testing on 9 main features shows that all features function according to the functional requirements with a success rate of 100%. This website supports digital trust through company identity, transparent package information, activity documentation, testimonials, and official communication channels.
Klasifikasi Lonjakan Ekstrem Nilai Tukar USD/IDR Menggunakan Gaussian Naïve Bayes Meini Syakinah Ritonga; Rita Novita Sari
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.v5i2.457

Abstract

The fluctuation of the Rupiah exchange rate against the US Dollar (USD/IDR) potentially triggers macroeconomic instability. This study aims to classify potential extreme surges in the USD/IDR exchange rate using data mining techniques with the Gaussian Naïve Bayes algorithm. A total of 502 daily historical observation data were extracted into four continuous predictor features: volatility, closing difference, upper bound difference, and lower bound difference. The evaluation was conducted using an 80% training and 20% testing data split. The results show that the model can identify "Normal" and "Extreme" classes with an accuracy of 96.04%, a precision of 62.50%, and a recall of 83.33%. The 5-Fold Cross Validation test yielded an average cumulative accuracy of 95.43%, confirming that the model's performance is stable and does not experience overfitting. In conclusion, the Gaussian Naïve Bayes algorithm is proven to be effective and reliable as an early warning system against the risk of extreme foreign exchange rate surges.
Studi Eksperimental: Efektivitas AI Dalam Meningkatkan Aksesibilitas Informasi PCOS Via Mobile App Ruth Megarini Panjaitan; Miranda Mas Tasya Sitorus; Evta Indra
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.v5i2.472

Abstract

Polycystic Ovary Syndrome (PCOS) is a hormonal disorder commonly experienced by women of reproductive age; however, the level of literacy regarding PCOS remains relatively low. Limited access to clear and easily understandable information has contributed to a lack of awareness of this condition. This study aims to develop an Artificial Intelligence (AI)-based mobile application called OVAI as an educational medium to improve the accessibility of PCOS information. The research was conducted by distributing questionnaires to female respondents aged 18–45 years using a Likert scale. The collected data were analyzed to determine the level of user acceptance and the consistency of the research instrument. The results showed that the OVAI application was successfully developed with interactive chatbot features and user-friendly educational content. The application was considered helpful in enabling users to better understand information related to PCOS and to access information more practically. Therefore, the OVAI application can be utilized as a digital educational medium for women of reproductive age.
Pengembangan Sistem Informasi Manajemen Pemesanan Berbasis Website di UMKM Nenda Print Kunti Eliyen; Abidatul Izzah; Ellya Nurfarida; Lely Indah Kurnia; Agustono Heriadi; Dwi Rahma Fitriani
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.v5i2.479

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the Indonesian economy, but they often face challenges in managing order and financial data due to manual recording. This study aims to develop a website-based order and profit data recording information system for Nenda Print MSMEs to improve business management efficiency. The system development method includes needs analysis, system design, implementation, testing, and evaluation. The developed website-based system is equipped with features for customer data management, order recording, financial transaction recording, automatic profit calculation, and real-time presentation of reports and graphs. Test results show that the system is able to simplify the data recording process, reduce the risk of data loss, and accelerate sales and profit calculations.

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