cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Perani Rosyani
Contact Email
journal.mediapublikasi@gmail.com
Phone
+6288210433859
Journal Mail Official
admin@journal.mediapublikasi.id
Editorial Address
Permata Tangerang, Pasar Kemis Tangerang
Location
Kota tangerang,
Banten
INDONESIA
OKTAL : Jurnal Ilmu Komputer dan Sains
Published by CV. Multi Kreasi Media
ISSN : -     EISSN : 28282442     DOI : -
Core Subject : Science, Social, Engineering,
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences
1. Komputasi Lunak, 2. Sistem Cerdas Terdistribusi, Manajemen Basis Data, dan Pengambilan Informasi, 3. Komputasi evolusioner dan komputasi DNA/seluler/molekuler, 4. Deteksi kesalahan, 5. Sistem Energi Hijau dan Terbarukan, 6. Antarmuka Manusia, 7. Interaksi Manusia-Komputer, 8. Hibrida dan Algoritma Terdistribusi Pemrosesan Informasi Manusia, 9. Komputasi Berkinerja Tinggi, 10. Penyimpanan informasi, 11. Keamanan, integritas, privasi, dan kepercayaan, 12. Pemrosesan Sinyal Gambar dan Ucapan, 13. Sistem Berbasis Pengetahuan, 14. Jaringan Pengetahuan, 15. Multimedia dan Aplikasi, 16. Sistem Kontrol Jaringan, 17. Klasifikasi Pola Pemrosesan Bahasa Alami, 18. Pengenalan dan sintesis ucapan, 19. Kecerdasan Robot, 20. Analisis Kekokohan, 21. Kecerdasan Sosial, 22. Statistic 23. Komputasi grid dan kinerja tinggi, 24. Realitas Virtual dalam Aplikasi Rekayasa, 25. Intelijen Web dan Seluler, 26. Data Besar, 27. Manajemen Informatika, 28. Sistem Informasi, 29. Desain Permainan, 30. Sistem Multimedia, 31. Pemrosesan Gambar, 32. IOT 33. Pemrograman Seluler, 34. Desain Basis Data, 35. Pemrograman Jaringan, 36. Sistem Terdistribusi, 37. Sistem Pendukung Keputusan, 38. Sistem Pakar, 39. Kriptografi, 40. Model dan Simulasi, 41. Jaringan 42. Perhitungan 43. Metematika 44. Kimia 45. Teknik Elektro 46. Robotik 47. Fisika
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,159 Documents
 112   113   114   115   116 
Perancangan Sistem Repositori Digital Berbasis Web untuk Pengelolaan Publikasi pada Kesatuan Press Yanto Hermawan; Sinta Listari; Meilani Kizana
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to design a web-based digital repository system to optimize the management of scientific publications at Kesatuan Press. The main problem currently faced is the management of publication data which is still conventional, making it difficult to search, store, and disseminate information efficiently. The proposed solution is the development of a centralized digital platform with automated archiving features and high accessibility. The system development methodology uses the Waterfall model which includes requirements analysis, design, coding, and testing. The results of the study indicate that the implementation of this digital repository is able to improve the administrative order of publications and facilitate authors and readers in accessing scientific works online. This system is expected to be the main supporting infrastructure for Kesatuan Press in increasing the visibility of academic publications.
Implementasi Sistem Absensi Menggunakan Algoritma Haar Cascade Classifier dengan Bahasa Pemrograman Python di PT Ruragraha Propertindo Muhammad Kiki; Ari Syaripudin
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Conventional attendance systems in companies, including PT Ruragraha Propertindo, still face significant issues such as the potential for fraud (buddy punching), inefficient manual processes, and non integrated data processing. The implementation of face recognition-based biometric technology offers a more practical and secure solution. This study aims to design and implement an automated face recognition-based attendance system at PT Ruragraha Propertindo to improve the accuracy, efficiency, and accountability of employee attendance recording. The system was developed using the Waterfall model of the System Development Life Cycle (SDLC). The Haar Cascade Classifier algorithm from the OpenCV library was used for real-time face detection, combined with Local Binary Pattern Histogram (LBPH) for identity recognition. Software development utilized the Python programming language with the Flask framework for the web interface and MySQL as the database. Functional testing was conducted using Blackbox and Whitebox Testing. The research output is a system prototype expected to automate the attendance process, reduce waiting time, minimize fraud, and provide accurate, integrated attendance data to support managerial decision-making at PT Ruragraha Propertindo.
Rancang Bangun Sistem Data Mining Untuk Analisis Tren Penjualan Dengan Algoritma K-Means (Studi Kasus: Toko Mainan Berkah 3R) Ryan Sugiarto; Nanang
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze sales trends and classify products based on their sales performance using the K-Means clustering method at Toko Mainan Berkah 3R. The main issue addressed is the absence of a structured data analysis system to support decision-making related to stock management and marketing strategies. The research utilized sales transaction data from a specific period, which underwent data cleaning and normalization before the clustering process. The K-Means algorithm was applied by defining three clusters to categorize products into high, medium, and low sales groups. The findings indicate that the clustering results provide a clearer overview of product distribution and sales patterns, enabling store owners to prioritize inventory management and evaluate low-performing products. Therefore, the implementation of the K-Means method proves effective in supporting data-driven decision-making in retail businesses.
Prediksi Kelayakan Seller dalam Penyewaan Gudang Menggunakan Algoritma Decision Tree dan Random Forest Bagas Dwi Prasetya; Atang Susila
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Determining seller eligibility in warehouse rental plays a crucial role in maintaining operational stability and minimizing financial risks. However, the selection process is often conducted manually based on subjective judgment, leading to inconsistent and less accurate decisions. This study aims to implement and compare Decision Tree and Random Forest algorithms in predicting seller eligibility using historical data. The dataset consists of 300 records with attributes including Chat Performance, Membership Duration, Rating, and Total Sales. The research process involves data preprocessing, classification model development using RapidMiner, performance evaluation through cross-validation, and feature importance analysis. The results indicate that Random Forest outperforms Decision Tree with an accuracy of 83.11%, while Decision Tree achieves 80.87%. Feature analysis reveals that Chat Performance is the most influential attribute in determining seller eligibility. This research provides a data-driven approach to support objective and consistent decision-making in warehouse rental management.
Analisis Pengaruh Augmentasi Data Terhadap Performa Transfer Learning MobileNetV2 dalam Klasifikasi Citra Makanan Indonesia Salsabila Aulia Ramadhan; Atang Susila
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Limited training data and high visual variability in Indonesian food images often cause deep learning–based classification models to experience overfitting and difficulties in accurately recognizing new images. To address this issue, this study applies eight data augmentation scenarios to a transfer learning–based MobileNetV2 model for classifying 10 Indonesian food categories, namely Ayam Pop, Bakso, Gado-Gado, Mie Goreng, Nasi Goreng, Rawon, Rendang, Sate, Soto, and Telur Balado. The dataset consists of 500 images used for training, which are divided into 70% training data and 30% validation data, along with 100 additional images used as an independent test set. The applied augmentation techniques include rotation, zoom, brightness adjustment, contrast adjustment, photometric (brightness + contrast), geometric (rotation + zoom), and a combined scenario integrating all augmentation techniques, as well as a baseline scenario without augmentation. Model performance was evaluated using accuracy, precision, recall, F1-score, and confusion matrix. The results indicate that all augmentation techniques improve the model performance compared to the baseline scenario, which only achieved 80.00% validation accuracy and showed signs of overfitting. The rotation scenario achieved the best performance with a validation accuracy of 91.87% and an independent test accuracy of 87.00%. These findings demonstrate that appropriate data augmentation can improve both the accuracy and generalization capability of the MobileNetV2 model in Indonesian food image classification under limited data conditions.
Evaluasi Kepuasan Pengguna Website mcm.madiunkota.go.id Dalam Updating Data Kemiskinan Menggunakan Analisis SWOT Hazel Lahfahukama Masruri; Mei Lenawati
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 04 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to evaluate user satisfaction with the website mcm.madiunkota.go.id as a tool for updating poverty data in Madiun City. The website is utilized by the Regional Development Planning Agency (BAPPEDA) as a data management platform to support regional development planning. This research applies a quantitative descriptive approach with data collection methods including observation, interviews, and questionnaires using a Likert scale. The results indicate that users are generally satisfied with the system, particularly in terms of ease of use and feature completeness. However, several issues were identified, such as system errors, data loss after input processes, and limited user capability in operating the system. Based on the SWOT analysis, the system has strong potential for development, but requires improvements in system reliability, data security, and user capacity. This study is expected to provide recommendations for developing more effective, efficient, and sustainable web-based information systems in managing poverty data.
Pemanfaatan TikTok sebagai Media Informasi Digital pada DPMPTSP Kabupaten Madiun Muha Nanda Sho'im; Sofyan Triono; Mei Lenawati
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 04 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of information and communication technology has encouraged government agencies to adapt in conveying public information, one of which is through the use of social media. TikTok as a short video-based platform is considered effective in attracting public attention and disseminating information quickly, interactively, and easily accessible. The purpose of this internship is to determine the strategy for utilizing the TikTok account of the Madiun Regency DPMPTSP in conveying public service information, increasing interaction with the community, and supporting transparency and openness of information. The method used is the SUS (System Usability Scale) method by distributing questionnaires to DPMPTSP Madiun Regency employees and students of PGRI Madiun University, as well as documentation of social media management activities within the agency. The results obtained indicate that the use of TikTok can increase the reach of information related to licensing services, investments, and DPMPTSP activity programs.
Penerapan Metode Hybrid AHP-TOPSIS Dalam Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Tsalatsatus Sa’adah; Herwis Gultom
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 04 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The selection of the best employees conducted manually and subjectively has the potential to cause calculation errors and unfairness in decision-making. Therefore, a system is needed to provide recommendations that are objective, fast, and accurate. This study aims to develop a web-based Decision Support System (DSS) for the process of selecting the best employees. The method used is a hybrid approach combining the Analytical Hierarchy Process (AHP) to determine criteria weights and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank alternatives. The system was tested using actual case data to evaluate the effectiveness of the applied method. The results show that the employee named La Ode Raditya Sambaga achieved the highest preference value of 1.0000 and ranked first. Thus, the web-based hybrid AHP-TOPSIS decision support system is proven to assist management in making decisions more objectively, quickly, and accurately in selecting the best employees.
Sistem Informasi Monitoring Kegiatan Pembelajaran Santri Berbasis Website Pada Pondok Pesantren Tahfidzul Qur’an Nurul Fatikhah Mubarok Ali Makhzumi; Niki Ratama
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 5 No 04 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study is to make it easier for guardians of students to monitor students' learning activities at Islamic boarding schools and make it easier for Islamic boarding schools to record administrative data for students who still use manuals, so that there are no delays, errors, and errors in reporting. Tahfidzul Qur'an Nurul Fatikhah Islamic Boarding School was founded in 1996 by KH Ahmad Sahudi. Currently, several obstacles and shortcomings are found in the student learning monitoring system, including the administrative system which is still done manually, causing problems in managing payment data, student data, and rote. For problems in managing payment data, they still use books to enter data for students who make payments for Madrasah Diniyah Education or students who have deposited memorization. It is the same with the monthly payments for Islamic Boarding Schools, which currently still use paper. Although the process used today uses a computer / laptop, but only uses Microsoft office. The method used for the development of information systems using the waterfall model and using the programming language PHP, HTML and MySQL database.

Page 116 of 116 | Total Record : 1159

 112   113   114   115   116 

Filter by Year

2022 2026


Reset
Filter By Issues
All Issue Vol 5 No 04 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS) Vol 5 No 03 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 5 No 02 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 5 No 01 (2026): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 11 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 10 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 09 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 08 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 07 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 06 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 05 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 04 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 03 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 12 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 10 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 08 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 07 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 06 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 05 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 04 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 03 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 02 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 12 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 11 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 10 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 09 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 08 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 07 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 06 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 05 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 04 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 03 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 02 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 01 (2023): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 12 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 11 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 10 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 09 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 08 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 07 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 06 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 05 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 04 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 03 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 02 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 01 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains More Issue