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Jurnal Komputer
Published by Gein Rafflesia
ISSN : -     EISSN : 29620651     DOI : -
Core Subject : Science,
Computer Science & IT
Domain Specific Frameworks and Applications IT Management dan IT Governance e-Government e-Healthcare, e-Learning, e-Manufacturing, e-Commerce ERP dan Supply Chain Management Business Process Management Smart Systems Smart City Smart Cloud Technology Smart Appliances & Wearable Computing Devices Robotic Systems Smart Sensor Networks Information Infrastructure for Smart Living Spaces Intelligent Transportation Systems Models, Methods and Techniques Conceptual Modeling, Languages and design Software Engineering Information-centric Networking Human Computer Interaction Media, Game and Mobile Technologies Data Mining Information Retrievel Information Security Image Processing and Pattern Recognition Remote Sensing Natural Language Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 36 Documents
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Implementasi dan Evaluasi REST API dalam Integrasi Sistem Lintas Platform Olivia, Melvina
Jurnal Komputer Vol 3 No 2 (2025): Januari- Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v3i2.108

Abstract

In today's digital era, online games such as Minecraft are rapidly growing as part of the entertainment industry. Arknesia Entertainment Network developed an independent Minecraft server called Reforged World to improve users' gaming experience. However, there are challenges in integrating server data efficiently. This research aims to develop a RESTful API that integrates with the backend using Express.js, the website frontend using Next.js, and the mobile application using Expo. This RESTful API allows real-time management of server status data, player information, and game statistics. The results show that the RESTful API is able to improve service quality and provide a better user experience. Full documentation is provided to make it easier for other developers to implement and further develop the API.
Desain dan Implementasi Sistem Pakar Diagnosa Penyakit Menggunakan Forward Chaining Saputri, Vettyca Diana
Jurnal Komputer Vol 2 No 2 (2024): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i2.109

Abstract

The development of information technology has encouraged the utilisation of expert systems in various fields, including health. An expert system is a computer system designed to mimic the ability of an expert to make decisions. This article discusses the design and implementation of an expert system to diagnose diseases based on the forward chaining method. This method works by tracing the facts provided by the user to the right conclusion. The purpose of this research is to assist the community in making an initial diagnosis of common diseases. The implementation results show that the system is able to provide accurate diagnosis results based on the symptoms entered by the user.
Integrasi Chatbot Berbasis NLP pada Sistem Layanan Akademik Universitas Tarigan, Heskyel Pranata
Jurnal Komputer Vol 3 No 1 (2024): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v3i1.110

Abstract

The advancement of digital technology has driven transformation in the delivery of information services in higher education institutions. One innovation that is being increasingly adopted is the use of Natural Language Processing (NLP)-based chatbots in academic service systems. This chatbot enables natural conversation-based interactions between users and systems, facilitating students in accessing information quickly and efficiently. This paper discusses the basic concepts, benefits, system architecture, and challenges faced in integrating NLP-based chatbots into academic service systems. By adopting this approach, universities can enhance service quality, reduce administrative burdens, and promote the digitalization of academic processes in a comprehensive manner.
Sistem Penjadwalan Otomatis Menggunakan Algoritma Genetika pada Lingkungan Sekolah Pratama, Sutan Abeng
Jurnal Komputer Vol 3 No 2 (2025): Januari- Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v3i2.111

Abstract

Scheduling problems in school environments often present significant challenges due to the involvement of numerous variables and constraints, such as teacher availability, classroom allocation, and balanced subject distribution. Manual scheduling tends to be time-consuming and prone to errors, necessitating a more efficient and adaptive solution. This study aims to design and implement an automatic scheduling system using a Genetic Algorithm. This algorithm is chosen for its capability to solve optimization problems with complex solution spaces. The development process involves representing chromosomes as combinations of schedule elements, selecting based on conflict levels, and applying genetic operators such as crossover and mutation to generate optimal solutions. Test results show that the system is capable of producing high-quality schedules with minimal conflicts and efficient computation time. This approach significantly enhances the speed, accuracy, and flexibility of school scheduling systems
Pengembangan Sistem Rekomendasi Buku Menggunakan Collaborative Filtering Pratama, Sutan Abeng
Jurnal Komputer Vol 2 No 2 (2024): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i2.112

Abstract

In the rapidly evolving digital era, the need for accurate and personalized recommendation systems is increasingly important, particularly in digital libraries and online bookstores. This study aims to develop a book recommendation system using a collaborative filtering approach, which leverages user interaction data to suggest books that align with individual preferences. The system utilizes a user-based collaborative filtering method by calculating similarities between users based on their historical book ratings. The dataset used in this research is a simulated, anonymized dataset from a school library. Testing results indicate that the system is capable of delivering relevant recommendations with good accuracy, demonstrated by a low Mean Absolute Error (MAE) score and positive user feedback. This system allows users to discover books aligned with their interests more efficiently, thereby enhancing the overall reading experience.
Analisis Performa Algoritma CNN dalam Klasifikasi Citra Medis Berbasis Deep Learning Sari, Nely Puspita
Jurnal Komputer Vol 2 No 2 (2024): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i2.113

Abstract

The advancement of artificial intelligence technologies, particularly in the field of deep learning, has driven the application of Convolutional Neural Network (CNN) algorithms in various domains, including medical image classification. This study aims to analyze the performance of CNN in classifying medical images associated with different diseases using a standard CNN architecture. The dataset utilized consists of labeled X-ray and MRI images based on medical diagnoses. Evaluation metrics such as accuracy, precision, recall, and F1-score were used to assess how effectively the model recognizes complex visual patterns. The results demonstrate that CNN achieves high accuracy in identifying objects within medical images, with an average F1-score exceeding 90% on selected datasets. These findings suggest that CNN has significant potential to support automated and efficient medical diagnosis, although further clinical validation is necessary for real-world implementation.

Page 4 of 4 | Total Record : 36

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