cover
Contact Name
Ramdani Dwi Pamuji
Contact Email
jocsit.publine@gmail.com
Phone
+6285945340977
Journal Mail Official
jocsit.publine@gmail.com
Editorial Address
Jl. Tawak-tawak No.5 Karang Sukun, Kel. Mataram Timur, Kec. Mataram, Kota Mataram - NTB, Indonesia 83121
Location
Kota mataram,
Nusa tenggara barat
INDONESIA
Journal of Computer Science and Information Technology
ISSN : -     EISSN : 3090787X     DOI : https://doi.org/10.70716/jocsit
Core Subject : Science,
Journal of Computer Science and Information Technology (JOCSIT) is a scientific journal in computers that contains research results and literature studies, managed by Lembaga Publikasi Ilmiah Nusantara. JOCSIT journal provides a platform for researchers, academics, professionals, practitioners and students to embed and share knowledge in the form of empirical and theoretical research papers, case studies, literature reviews and book reviews related to computer science and information technology research, and or related to it with a range of themes such as Biomedical Application Computer Network and Architecture, Data Mining, E-Business, E-Commerce, E-Government E-Learning, Embedded Systems, Environmental Systems, Fuzzy Logics, Genetic Algorithms, Geographic Information System, High-Performance Computing, Human-Computer Interaction, Image Processing, Internet of Things (IoT), Computer Vision, Information Security, Information Retrieval, Modeling System and Control, Mobile Technology, Neural Networks, Pattern Recognition, Remote Sensing, Robotics, Signal Processing, Smart Home, Smart Sensor Networks. This journal will process all receipts of the script in a double-anonymized review by Bestari partners.
Articles 10 Documents
Pengembangan Website Responsif untuk Media Informasi Sekolah Menggunakan HTML5 dan CSS3 Jaelani, Muhammad Yusron
Journal of Computer Science and Information Technology Vol. 1 No. 1 (2025): Journal of Computer Science and Information Technology, June 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i1.186

Abstract

Payment of Educational Development Contribution (SPP) is one of the routine activities carried out in the school environment, including at SMK Negeri 1 Sikur. The payment process which is still done manually causes various problems, such as late recording, human error, and lack of transparency of information to parents. This study aims to develop a web-based SPP payment information system to simplify the school financial administration process and increase data efficiency and accuracy. The system development method used is the Waterfall model which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is built using the PHP programming language with a MySQL database and is accessed via a web browser. The test results using the black-box method show that all system functions run well according to user needs. With this system, the SPP payment process becomes more effective and efficient, and provides more transparent access to information to schools and parents. It is hoped that this system can be a digital solution that supports better school financial governance.
Analisis dan Perancangan Sistem Informasi Akademik Berbasis Web pada Perguruan Tinggi Swasta Candra, Alfat Arya Adi
Journal of Computer Science and Information Technology Vol. 1 No. 1 (2025): Journal of Computer Science and Information Technology, June 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i1.187

Abstract

The rapid development of e-commerce demands a recommendation system that can help users find products that match their preferences. This study aims to implement the K-Nearest Neighbor (K-NN) algorithm in a product recommendation system to improve the personalization of e-commerce services. The K-NN algorithm works by finding similarities in behavior between users based on purchase history, then recommending products based on these similarities. The dataset used in this study consists of user transaction data, product categories, and user data, which are then processed through a cleaning and normalization stage before analysis. Testing was carried out using several variations of K values ​​to find the optimal parameters. The experimental results showed that the value of K = 5 gave the best performance with an accuracy of 87% and an F1-score of 84.5%. In addition, the Cosine Similarity method proved effective in measuring similarities between users in sparse data. The system built is able to provide relevant recommendations with efficient computing time, showing the potential to be applied in small to medium-scale e-commerce platforms. However, the system still has limitations in handling new users (cold-start), so further development with a hybrid approach is recommended. This study shows that the K-NN algorithm is a feasible and efficient approach in user behavior-based product recommendation systems.
Perancangan Sistem Pakar Berbasis Web untuk Menentukan Kerusakan Komputer Menggunakan Metode Certainty Factor Jaelani, Andry; Akbar , Rodi
Journal of Computer Science and Information Technology Vol. 1 No. 1 (2025): Journal of Computer Science and Information Technology, June 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i1.188

Abstract

Computer device damage is often an obstacle for users, especially for those who do not have the technical knowledge to diagnose the problem. To overcome this problem, a system is needed that is able to provide an initial diagnosis quickly and accurately. This study aims to design and develop a web-based expert system that can help users determine the type of computer damage using the Certainty Factor (CF) method. The CF method is used to calculate the level of certainty of the symptoms entered by the user based on previously formulated expert knowledge. This system is built using the PHP programming language and MySQL database, and is designed to be widely accessible via the internet network. The test results show that the system is able to provide diagnostic results with an adequate level of accuracy and is close to the results of direct analysis by technicians. Thus, this system can be an effective tool in the process of identifying computer damage and providing initial recommendations for handling before users take the device to a professional technician.
Aplikasi Web Pemasaran Produk Makanan UMKM Dengan Fitur Pencarian Menggunakan Algoritma Boyer-Moore (Studi Kasus: UMKM Ombe Baru) Rosita, Selvia
Journal of Computer Science and Information Technology Vol. 1 No. 1 (2025): Journal of Computer Science and Information Technology, June 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i1.189

Abstract

The development of information technology provides great opportunities for Micro, Small, and Medium Enterprises (MSMEs) to expand the reach of their product marketing through digital media. However, many MSMEs still do not have an effective digital platform to market their products independently. This study aims to design and build a web application for marketing MSME food products with a search feature based on the Boyer-Moore algorithm, which can speed up the product search process and increase system efficiency. The system development method used is the Waterfall model, including the stages of needs analysis, design, implementation, testing, and maintenance. The application is built using HTML5, CSS3, JavaScript, PHP, and MySQL technologies, with the Boyer-Moore algorithm implemented in the search feature to speed up keyword matching. The test results show that the application runs well, is responsive, and is able to display search results quickly, especially when the amount of product data increases. Performance testing shows that the Boyer-Moore algorithm has a faster response time than conventional search methods. This application is expected to be a practical and efficient digital solution in helping MSMEs market food products independently and competitively in the digital era.
Pengembangan Sistem Informasi Pembayaran SPP Online Berbasis Web di SMK Negeri 1 Sikur Hidayat, Khaerul
Journal of Computer Science and Information Technology Vol. 1 No. 1 (2025): Journal of Computer Science and Information Technology, June 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i1.190

Abstract

Payment of Educational Development Contribution (SPP) is one of the routine activities carried out in the school environment, including at SMK Negeri 1 Sikur. The payment process which is still done manually causes various problems, such as late recording, human error, and lack of transparency of information to parents. This study aims to develop a web-based SPP payment information system to simplify the school financial administration process and increase data efficiency and accuracy. The system development method used is the Waterfall model which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is built using the PHP programming language with a MySQL database and is accessed via a web browser. The test results using the black-box method show that all system functions run well according to user needs. With this system, the SPP payment process becomes more effective and efficient, and provides more transparent access to information to schools and parents. It is hoped that this system can be a digital solution that supports better school financial governance.
Analisis Performa Jaringan 5G dengan Metode MIMO Satriawan, Hamdani
Journal of Computer Science and Information Technology Vol. 1 No. 2 (2025): Journal of Computer Science and Information Technology, September 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i2.252

Abstract

This study aims to analyze the performance of 5G networks with the implementation of Multiple Input Multiple Output (MIMO) technology through a simulation approach using NS-3 software. Evaluations were conducted on three antenna configurations, namely SISO (1x1), MIMO 2x2, and MIMO 4x4, in two environmental scenarios: urban and rural. The parameters analyzed include throughput, latency, and signal-to-noise ratio (SNR). The simulation results show that the MIMO 4x4 configuration provides the most significant performance improvement compared to SISO, with an average throughput increase of up to 40%, a latency reduction of 25%, and an SNR increase of up to 10 dB. In addition, MIMO is proven to be able to maintain stable performance in dense traffic conditions and high interference, especially in urban environments. Better channel efficiency is also achieved through the utilization of spatial multiplexing and beamforming. These results strengthen the evidence that MIMO is a key technology in the development of 5G networks, especially in addressing the needs of high-speed communications and real-time services. This study concludes that MIMO technology has great potential to be widely implemented in 5G networks in Indonesia, and is an important foundation for the implementation of future communication systems that are smarter, faster, and more reliable.
Penerapan Teknologi Internet of Things (IoT) untuk Monitoring Kualitas Udara dalam Ruangan Aswaldi, Haikal
Journal of Computer Science and Information Technology Vol. 1 No. 2 (2025): Journal of Computer Science and Information Technology, September 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i2.255

Abstract

Indoor air quality plays a crucial role in the health and comfort of occupants, especially in enclosed environments such as homes, offices, and public spaces. Decreased air quality can lead to various health problems, including allergies, respiratory problems, and decreased work productivity. With the advancement of technology, the Internet of Things (IoT) has become an innovative solution for real-time air quality monitoring. This research aims to design and implement an IoT-based air quality monitoring system capable of detecting environmental parameters such as temperature, humidity, carbon dioxide (CO₂) concentration, and dust particles (PM2.5). This system consists of environmental sensors integrated with a microcontroller and connected to a cloud platform for online data storage and visualization. Test results show that the system can provide accurate data and is responsive to changes in air conditions. The system is also equipped with an automatic notification feature that alerts users when air quality decreases below normal thresholds. With this approach, users can take early preventative measures against health risks caused by exposure to polluted air. This research shows that the application of IoT in air quality monitoring is very effective and can be applied on a household and commercial scale.
Sistem Deteksi Wajah Berbasis Deep Learning Menggunakan Convolutional Neural Network (CNN) Anwar, Khairil
Journal of Computer Science and Information Technology Vol. 1 No. 2 (2025): Journal of Computer Science and Information Technology, September 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i2.258

Abstract

Face detection is an important technology in the field of pattern recognition and digital image processing that is widely used in various applications such as security systems, surveillance, and identity recognition. This study aims to develop a deep learning-based face detection system using the Convolutional Neural Network (CNN) architecture. CNN was chosen because of its ability to automatically extract important features from images through an in-depth training process. This system is designed using a diverse facial dataset to ensure model generalization to various lighting conditions, viewing angles, and facial expressions. The training process is carried out by applying data augmentation and parameter optimization techniques to improve detection accuracy. The evaluation results show that the developed CNN model is able to detect faces with a high level of accuracy, and demonstrates stable performance against input variations. The advantage of this method lies in its ability to detect faces in real-time with low latency and resilience to background noise. With the results obtained, this system is expected to be applied in various computer vision-based applications such as automatic attendance systems, intelligent surveillance, and biometric authentication. This research contributes to the development of more reliable and efficient face detection technology with a modern deep learning approach.
Penerapan Algoritma Deep Learning untuk Deteksi Dini Penyakit dari Citra Medis Munadi, Muhammad
Journal of Computer Science and Information Technology Vol. 1 No. 2 (2025): Journal of Computer Science and Information Technology, September 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i2.259

Abstract

Advances in artificial intelligence technology, particularly in the field of deep learning, have made significant contributions to medical image processing for the early detection of various diseases. This study aims to apply deep learning algorithms, specifically Convolutional Neural Networks (CNNs), in the process of classifying and identifying diseases through the analysis of medical images such as X-rays, MRIs, and CT scans. The use of CNNs enables automatic and efficient feature extraction, thereby improving the accuracy of disease detection compared to conventional methods. The dataset used consists of thousands of medical images that have been manually classified by medical professionals. The model training process was carried out using transfer learning techniques using pre-trained architectures such as VGG16 and ResNet50. Performance evaluation was carried out by measuring the values of accuracy, precision, recall, and F1-score. The results showed that the developed CNN model was able to achieve a detection accuracy level of up to 95.3% on the test dataset. The application of this technology is expected to support computer-based diagnostic systems (CDI) as an aid for medical personnel in clinical decision-making. In addition, this system has the potential to accelerate the screening process and reduce the risk of misdiagnosis. These findings indicate that deep learning technology has enormous potential for improving the quality of healthcare services, particularly in the areas of disease prevention and early detection more effectively and efficiently.
Penggunaan Cryptography dalam Keamanan Pesan Digital Setiawan, Adi Bima
Journal of Computer Science and Information Technology Vol. 1 No. 2 (2025): Journal of Computer Science and Information Technology, September 2025
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/jocsit.v1i2.261

Abstract

The rapid development of information technology has facilitated digital communication processes, but on the other hand, it increases the risk of data leakage and misuse. One solution widely used to secure digital messages is the application of cryptography technology. Cryptography plays a crucial role in maintaining the confidentiality, integrity, and authenticity of information by converting messages into a format that cannot be read without the appropriate key. This study aims to analyze the use of cryptographic methods in maintaining the security of digital messages, with a focus on symmetric and asymmetric encryption techniques. The research method used is a literature review from various scientific sources and simulation implementation to test the effectiveness of cryptographic algorithms against cyberattacks. The results show that symmetric cryptography has a higher processing speed, while asymmetric cryptography excels in key management and authentication. The combination of the two through a hybrid encryption mechanism has been proven to increase the level of security without sacrificing performance. The proper application of cryptography not only protects messages from unauthorized access but also supports trust in digital communication. This study recommends the integration of modern cryptographic algorithms such as AES and RSA in digital messaging applications to achieve optimal protection.

Page 1 of 1 | Total Record : 10