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Jurnal Komputer dan Teknologi (JUKOMTEK)
Published by Yayasan Pendidikan Cahaya Budaya Indonesia
ISSN : 29631289     EISSN : 29619009     DOI : https://doi.org/10.58290/jukomtek
Core Subject : Science,
Computer Science & IT Library & Information Science
Jurnal Komputer dan Teknologi (JUKOMTEK) e-ISSN 2961-9009 dan p-ISSN 2963-1289 merupakan jurnal ilmiah. Jurnal ini berisi tentang karya ilmiah bersifat open access, dan jurnal ilmiah nasional yang mempublikasikan artikel ilmiah hasil penelitian dalam ruang lingkup bidang ilmu komputer serta aplikasi informatika untuk pengembangan TIK. Frekuensi Terbit: 2 kali setahun (bulan Januari dan Juli).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 68 Documents
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PENERAPAN METODE RAD UNTUK PENGEMBANGAN SISTEM PENGELOLAAN DATA KEPEGAWAIAN Risky, T. Tanzil Azhari; Armansyah
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.548

Abstract

Employee data management at the Medan Religious Training Center includes personal data, employment documents, educational history, work history, performance, and family data, requiring an integrated system for fast and accurate recording, updating, and reporting. This study developed a web-based Personnel Management Information System using the Rapid Application Development (RAD) method through needs analysis, prototyping, user evaluation, and implementation. Research data was obtained through observation, interviews, SOP document studies, and user questionnaires. The results showed that the system was able to integrate all personnel data, provide verification features, and generate PDF and Excel reports. Black Box testing of 10 main functions showed a 100% success rate with an average score of 5.0 (category “Very Good”). The system is considered feasible and effective in improving the efficiency and accuracy of personnel data management at the Medan Religious Training Center.
PERSEPSI PENGGUNA TERHADAP PENERAPAN AI UNTUK ANALISIS KOMENTAR MEDIA SOSIAL Rizkita, Amanda Putri; Octavianta, Nadine; Siregar, Habibah Zahra; Syifa, Salsabilla Khairus; Handayani, Dila
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.552

Abstract

This study examined user views on the use of artificial intelligence (AI) to analyze comments on Indonesian-language social media. Of the 50 respondents, 92% said AI was useful for understanding public opinion, while 8% still doubted the accuracy of the analysis results. While 88% felt AI could speed up the process of recognizing sentiment in comments, 74% felt the technology did not fully understand Indonesian casual language and social context. Furthermore, 81% agreed that the use of AI should be ethically supervised to prevent errors in data interpretation and use. The results showed that users generally held a positive and optimistic view of the future of AI, although adjustments were still needed regarding language and user ethics in Indonesia's digital world.
ANALISIS KEPUASAN PENGGUNA TERHADAP SISTEM INFORMASI AKADEMIK Hastini, Safta; Irawan, Dendi; Isroqmi , Asnurul; Ardius, Enggi
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.559

Abstract

This study was conducted to assess the level of usability and user satisfaction with the Academic Information System of Universitas PGRI Palembang. The evaluation employed the WebQual 4.0 method and was based on survey responses collected from students, lecturers, and staff who actively use the system. The results show that both usability and user satisfaction scored above 75%, indicating that the system is considered easy to use, capable of presenting relevant information, and effective in supporting various academic activities such as course registration (KRS), grade access, and course data management. The research instruments were also proven valid and reliable, making them appropriate tools for assessing the quality of the system’s services. However, several indicators require improvement, particularly those related to interface design and user experience. The indicators for attractive appearance (X1.5) and positive user experience (X1.8) scored lower than others, suggesting the need for interface redesign and more user-friendly guidance materials. Regression analysis further indicates that usability has a significant influence on user satisfaction, meaning that enhancements in navigation, interface consistency, and ease of access will directly contribute to higher satisfaction levels. Overall, this study provides a comprehensive overview of the quality of the Academic Information System and serves as an essential foundation for the development of a system that is more responsive, efficient, and adaptive to the needs of the academic community
PREDIKSI KLAIM ASURANSI MENGGUNAKAN ALGORITMA MACHINE LEARNING DENGAN PEMBANDING GENERALIZED LINEAR MODEL (GLM) Meliyani, Revi; Amin Siregar, Qowiyyul; Rahmah, Hikmah; Musito, M. Hamal; Liana Kacaribu, Tica
Jurnal Komputer dan Teknologi Vol 3 No 1 (2024): JUKOMTEK JANUARI 2024
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v3i1.563

Abstract

Permasalahan prediksi klaim pada industri asuransi merupakan aspek penting dalam proses underwriting, perhitungan premi, dan manajemen risiko. Penelitian ini bertujuan untuk menganalisis performa algoritma machine learning dalam memprediksi klaim asuransi dan membandingkannya dengan pendekatan statistik klasik, yaitu Generalized Linear Model (GLM). Data klaim umumnya memiliki karakteristik yang kompleks seperti non-linearitas, imbalance class, dan variabel interaksi yang sulit ditangkap oleh model linear. Oleh karena itu, penelitian ini menerapkan beberapa algoritma machine learning, yaitu Random Forest, Gradient Boosting, dan XGBoos, untuk memodelkan probabilitas klaim. Evaluasi performa dilakukan menggunakan metrik AUC, F1-score, dan akurasi, disertai analisis feature importance. Hasil penelitian menunjukkan bahwa model machine learning memiliki performa prediksi yang lebih baik dibandingkan GLM, terutama pada masalah data tidak seimbang. XGBoost memberikan nilai AUC tertinggi sebesar 0,063194, sedangkan GLM cenderung memiliki performa lebih rendah pada pola data non-linear. Temuan ini menunjukkan bahwa machine learning dapat menjadi pendekatan alternatif yang efektif dalam mendukung proses pengambilan keputusan aktuaria dan pengembangan sistem pendukung keputusan di industri asuransi
PREDIKSI RISIKO GAGAL BAYAR PREMI MENGGUNAKAN ALGORITMA GRADIENT BOOSTING: STUDI TRAVEL INSURANCE PREDICTION Amin Siregar, Qowiyyul; Meliyani, Revi; Rahmah, Hikmah; Musito, M. Hamal; Claudia Secu, Maria Amelia
Jurnal Komputer dan Teknologi Vol 3 No 2 (2024): JUKOMTEK JULI 2024
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v3i2.565

Abstract

Prediksi risiko gagal bayar premi merupakan salah satu aspek penting dalam pengelolaan risiko perusahaan asuransi. Ketepatan model prediksi memungkinkan perusahaan mengidentifikasi calon tertanggung yang berpotensi menunggak pembayaran premi sehingga langkah mitigasi dapat dilakukan sejak awal. Penelitian ini bertujuan menerapkan algoritma Gradient Boosting Classifier (GBC) dalam memprediksi risiko gagal bayar dengan menggunakan dataset publik Travel Insurance Prediction. Variabel target direlabel menjadi Default Risk sebagai representasi risiko gagal bayar. Proses penelitian meliputi pre-processing data, encoding variabel kategorik, penyeimbangan data dengan SMOTE, dan evaluasi model menggunakan metrik AUC, akurasi, precision-recall. Hasil penelitian menunjukkan bahwa Gradient Boosting menghasilkan performa terbaik dibandingkan Logistic Regression dan Random Forest, dengan nilai AUC tertinggi dan stabilitas prediksi yang baik pada data tidak seimbang. Penelitian ini memberikan kontribusi pada pengembangan model risiko berbasis machine learning di industri asuransi.
PEMANFAATAN GOOGLE SITES UNTUK PUBLIKASI WEBGIS INFORMASI KETAHANAN PANGAN PETERNAKAN IKAN AIR TAWAR Purbasari, Yuntari; Wijaya, Khana; Panglipur , Phinton; Suhartini, Suhartini; Sayuti , Akhmad
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.566

Abstract

The utilization of web-based Geographic Information System (WebGIS) technology is a strategic solution for presenting and publishing spatial data interactively. However, the development of WebGIS generally requires high costs and advanced technical expertise, which are not always available, particularly in regions with limited information technology resources. This study aims to design and implement a simple WebGIS using the Google Sites platform as a medium for publishing food security information in the freshwater fish farming sector in Prabumulih City. The system development method employed in this study is the Waterfall method, which consists of requirements analysis, system design, implementation, testing, and maintenance stages. The research data include spatial data on the locations of freshwater fish farmers and attribute data related to production potential, which are presented in the form of interactive thematic maps. The results indicate that Google Sites is effective as a medium for publishing simple WebGIS due to its ease of access, free usage, and minimal requirement for advanced programming skills. The developed WebGIS is capable of presenting interactive information on the locations and production potential of freshwater fish farming, thereby enhancing data transparency and facilitating information access for local governments and the community. Therefore, the use of Google Sites as a WebGIS publication medium can serve as an economical alternative solution to support the strengthening of local food security in Prabumulih City.
KLASIFIKASI JENIS PENYAKIT BUAH MANGGA BERBASIS DEEP LEARNING MENGGUNAKAN ARSITEKTUR RESNET DAN MOBILENET Cornelis Rasyid, Nanda; Karman, Joni; Toyib Hidayat, Asep; Lingga Wijaya, Harma Oktavia
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.570

Abstract

Mango plantations in Indonesia face significant challenges due to pests and diseases that reduce productivity and cause economic losses for farmers. Manual identification of these issues requires expert knowledge and is often time-consuming and inaccurate. This study aims to develop a classification system for detecting various mango leaf diseases using deep learning models, specifically ResNet and MobileNet architectures. Deep learning, particularly Convolutional Neural Networks (CNNs), enables automatic disease detection from plant images by learning patterns without explicit programming. The proposed system focuses on identifying common diseases such as leaf blight, whiteflies, and leaf caterpillars efficiently and accurately. By leveraging image-based recognition, the system allows for early diagnosis and timely intervention. The results of this research are expected to provide a technological solution that supports modern agriculture and empowers farmers with better disease management tools.
APLIKASI PEMBELAJARAN IQRO BERBASIS MULTIMEDIA sidiq, ahmad fajar; Nasirudin, Nasirudin; Subana, Bambang; Sitomo, Rizky; Fachri, Mohamad
Jurnal Komputer dan Teknologi Vol 5 No 1 (2026): JUKOMTEK JANUARI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i1.606

Abstract

Information lovers are truly pampered by the advancement of ever-more-modern information technology. Because of this, people appear to be inseparable from time and space. As technology advances, people are capable of producing a variety of tools and equipment to boost productivity by carrying out different tasks. A formula is created so that teachers can deliver instruction using suitable ways because the efforts made by teachers to enhance Qur'anic reading and writing are not at their best. more diversified based on the child's aptitudes in order to strengthen the Qur'anic reading and writing skills at TPQ. A system development methodology, such as the System Develop Life Cycle (SDLC) with the waterfall model, is required based on the current constraints. The classic life cycle, which describes a methodical and methodical approach to software development, starting with the user requirements specification and progressing through the planning, modelling, building, and deployment phases before ending with support for the complete project. In addition to making it easier for teachers to instruct pupils, the multimedia-based Iqro learning application was developed to assist users in learning correct and proper iqra' and makharijul letters.

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