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J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Published by Universitas Negeri Jakarta
ISSN : 26204827     EISSN : 26204827     DOI : -
Core Subject : Science,
Computer Science & IT
J-KOMA is an open access journal, with core focus in two aspect: computer science general and information technology. All copyrights are retained by each respective author, but we hold publishing right. Currently, this journal has E-ISSN :2620-4827 published by LIPI which made it as a national journal.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 53 Documents
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Rancang Bangun Sistem Repositori Akreditasi Program Studi Ilmu Komputer di Universitas Negeri Jakarta Kristanto, Aty Lestari; Indiyah, Fariani Hermin; Nurjanah, Siti
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 1 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i1.05

Abstract

This research aims to develop a document repository system for the accreditation of the computer science study program at Universitas Negeri Jakarta. The system is based on 9 criteria aligned with the Program Study Performance Sheet (LKPS), adhering to LAM INFOKOM regulations. This system is developed to facilitate data collection for accreditation, which is currently done manually. The development process follows the Agile Extreme Programming methodology. The system's final version will be tested using Black Box Testing to examine its features and components. The testing includes system functionality and usability assessments. The results indicated that the system's functionality scored 88.33%, and the usability testing scored 85.87%, demonstrating that the developed system is highly viable and meets the expected outcomes. Keywords: Accreditation, Agile, Extreme Programming, Black Box Testing
Development of a Website-Based Learning management system (LMS) at SMAN 52 Jakarta Abdillah, Maldini; Indiyah, Fariani Hermin; Makmuri
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 1 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i1.01

Abstract

The use of information technology in various fields is increasingly developing, one of which is in the field of education. SMAN 52 Jakarta is one of the public high schools in the Cilincing area, North Jakarta, that wants to utilize information technology in the school environment. Researchers conducted surveys and interviews, resulting in 66% of the SMAN 52 community expressing a desire for a website-based learning information system. Based on the interviews, this system is desired to provide a one-stop medium for learning and to ensure the neatness of note-taking in the learning process. Therefore, the researchers designed a Learning Management System (LMS) that manages teacher and student data, as well as supports learning activities such as uploading and downloading learning materials, grading, and discussions. The researchers used the Software Development Life Cycle (SDLC) with a prototype method in their work. This method was chosen for its ease in accommodating changes during the development process. The prototype method was employed with three iterations to serve as a means for evaluation during system development. Using Codeigniter 4 as the framework and PHP as the programming language, the system was developed. The researchers used phpMyAdmin to manage the database. For system testing, they used black box testing with a Likert scale for the entire system, obtaining a score of 96.8% for functionality testing and 96.3% for non-functionality testing. Therefore, it can be concluded that the developed system is highly suitable for use
Tracking Pergerakan Ikan menggunkan model Gaussian Mixture (GMM) dan Kalman Filter Alim, Hafizhun; Muhammad, Eka Suryana; Mulyono
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 1 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i1.04

Abstract

Indonesia Fish industries is one of the large in the world for market capital which covers for both natural growing and intensive culture. One part of the most challenging problem for intensive culture is related to counting when harvesting which been done by hand all this time. In order to be more efficient, we propose this task can be done through automation with Gussian Mixture Model. The proposed system proven been able with low error rate that also resulting close estimate of fish object counting giiven various background videos.
Comparison of PageRank Algorithm Implementations on a Single Computer Herdian Pradana, Farhan; Eka Suryana, Muhammad; Irzal, Med; Resita, Ersa
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 2 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i2.01

Abstract

Pagerank Algorithm is an algorithm used for calculating web page ranking in Google search engine. Problem arises for Pagerank Algorithm due to big main memory usage, thus make it impossible to run in single machine computer with limited main memory. Alternative algorithms will be proposed by comparing the alternative algorithms from other studies with the Original Google Pagerank in terms of speed, main memory usage, and their result similarity. In this study, the Orignal Pagerank, Distributed Pagerank Computation (DPC), Modified DPC, and Random Walker algorithms will be implemented. The implemented algorithms will be run with datasets, and their speed, main memory usage, and result similarity will be compared. For result similarity, Random Walker’s result will be used as a benchmark, since it has been used as base concept of Pagerank. It is concluded that the Original Pagerank is faster and has very similar result with Random Walker, while DPC and MDPC have significantly smaller main memory usage, thus very suitable for single machine computer with limited main memory, but run slower and sacrificing result similarity.
Classification of Yogyakarta Batik Using the K-Nearest Neighbor (KNN) and Gray Level Co-occurrence Matrix (GLCM) Methods Qur’ania, Arie; Dias Saharani, Ananda; Handini, Riri
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 2 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jkoma.v7i2.02

Abstract

The preservation of Yogyakarta batik motifs as part of Indonesia’s cultural heritage can be supported through digital image classification technology. This study aims to develop an automatic classification system for Yogyakarta batik motifs using the Gray Level Co-occurrence Matrix (GLCM) method for texture feature extraction and the K-Nearest Neighbor (KNN) algorithm for the classification process. The dataset consists of 1,350 digital images of six different batik motif types, sourced from Kaggle. The system was developed and tested on the Google Colab platform through several stages, including preprocessing, feature extraction, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The evaluation results show that the model achieved an accuracy of 60%, with the best performance on the batik-ceplok motif (F1-score of 77%) and the lowest on the batik-kawung motif (F1-score of 46%). The system was then implemented as a web application using the Streamlit framework, allowing users to upload images and receive classification results in real time. This implementation not only contributes to the field of image processing but also aids in cultural preservation through digitization and easy access to batik motif classification  
Design and Development of an Online Catering Ordering Information System Using the Prototype Methodology Fadaniel Herzah, Haby; Peratama Islam, Rizky; Shifa Fauziah, Revi; Kanaya Marlan, Azizah; Indri Wulan Ningsih, Citra
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 2 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i2.03

Abstract

This study develops a web-based online catering ordering system to address issues in traditional catering, such as manual order errors, delayed information delivery, and data inconsistencies. Using the Prototype methodology, the system was iteratively designed with user feedback to ensure functionality and usability. The primary goals are to enhance operational efficiency, improve service accuracy, and deliver a seamless digital experience. Key features include user registration, secure login, interactive menu selection (à la carte or buffet), dynamic order forms for specifying portions and delivery dates, and admin tools for order management and automated sales reporting. The interface is responsive, accessible across devices, with non-functional requirements ensuring data encryption, 24/7 availability, and sub-2-second response times. The development followed the Prototype lifecycle: requirements gathering, system design (using ERD, Use Case, Class, Activity, and Sequence Diagrams), web-based implementation, black-box testing, and ongoing maintenance for bug fixes and performance optimization. Testing validated reliable login, ordering, and payment processes, handling edge cases effectively. This system streamlines catering operations, reduces errors, and enhances customer satisfaction, offering a scalable solution for food services. Future enhancements may include mobile app integration and advanced analytics.
Sentiment Analysis of Indonesia’s Free School Lunch Policy Using LSTM and Word2Vec on YouTube Comments Anderson, Boban; Irzal, Med; Hendarno, Ari
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 2 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i2.04

Abstract

This study analyzes public sentiment toward Indonesia’s free school lunch policy using sentiment classification on YouTube comments. Data were collected from 5,640 videos, resulting in 485,097 comments, with 392,576 comments used for training and testing. The dataset was preprocessed through cleaning, tokenization, normalization, stopword removal, and stemming. Word2Vec was used for word embedding, and sentiment classification was performed using an LSTM neural network. The model achieved 82.56% accuracy on training data but 57.00% on manually labeled test data. The final sentiment distribution shows that negative sentiment slightly dominates, reflecting public skepticism about budget use and program effectiveness. Frequent keywords such as Indonesia, Prabowo, school, and corruption highlight key concerns. These results provide valuable insights for policymakers to improve communication and address public concerns. Future research should expand data sources, refine labeling, and test hybrid deep learning models to enhance classification performance.
Application of Information Retrieval in News Document Search Using Syntax and Semantic Orientation Kurniawati, Anggi; Pradani, Winangsari
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 7 No 2 (2024): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v7i2.05

Abstract

This study explores an information retrieval system for news document search, leveraging both syntactic and semantic approaches. The Word2Vec model, utilizing the skip-gram architecture, is employed to capture semantic relationships between words, transforming news articles into vector representations. Semantic similarity is measured using Word Mover’s Distance (WMD) and Cosine Similarity, while a syntax-based method employs regular expressions for keyword matching. The dataset comprises 2,813 news articles from Liputan6.com and Tempo.co, collected between 25–31 August 2019, containing 25,951 unique words. Preprocessing steps include case folding, filtering, tokenization, stopword removal, and stemming to enhance data quality. The system was evaluated using six user queries, with performance assessed through Precision@k and Mean Average Precision (MAP). Results indicate that Word2Vec with Cosine Similarity achieved the highest MAP score of 76.86%, outperforming WMD (75.65%) and regular expressions (72.06%). This demonstrates the effectiveness of semantic-based retrieval for news documents. Future work should focus on larger datasets and advanced models like Doc2Vec to improve retrieval accuracy and contextual understanding. 
Application of Monte Carlo Simulation in Predicting Stock Prices at PT Bank Syariah Indonesia Tbk Kamila, Isti; Anggraeni, Fidela; Ramadhany Rumengan, Novia; Dwi Puji Ramadhani, Novira; Fatanah Zetafahrul, Philant; Ananda Br Pelawi, Riva; Mawar Desember, Natalie
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 8 No 1 (2025): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v8i1.01

Abstract

Stock investment has become a popular choice for individuals seeking financial returns, although it comes with high risks due to market price volatility. This study aims to apply the Monte Carlo Simulation method to predict the stock price of PT Bank Syariah Indonesia Tbk (BRIS) and assess the accuracy of its predictions. BRIS was selected as it represents the largest Islamic bank in Indonesia and is attractive to investors focused on sharia-compliant finance. The research uses historical daily closing prices from January 2023 to December 2024, which are processed into daily returns and volatility as inputs for the simulation model based on Geometric Brownian Motion (GBM). The simulation was run three times to generate a variety of potential price paths. The predicted results were then compared with actual stock prices, and the Mean Absolute Percentage Error (MAPE) was used to evaluate prediction accuracy. The MAPE result of 39.75% indicates a moderate level of forecasting error. Although not perfectly precise, the model provides a valuable insight into possible price movements. The Monte Carlo method proves useful in capturing the uncertainty of the stock market and serves as a supportive tool for better investment decisions, especially in the Islamic banking sector. This research is expected to offer useful guidance for investors and stakeholders in managing portfolios using a quantitative approach.
Design and Implementation of a Web- Based Vessel Daily Report Information System for Optimizing Operational Efficiency and Accounting in the Shipping Industry Rama Putra, Gustian; Fajar Ilmiyono, Agung; Rafif, Raid; Munggaran Akhmad, Dinar
J-KOMA : Jurnal Ilmu Komputer dan Aplikasi Vol 8 No 1 (2025): J-KOMA : Jurnal Ilmu Komputer dan Aplikasi
Publisher : Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/j-koma.v8i1.02

Abstract

The rapid development of information technology has provided solutions to various operational challenges in the shipping industry, particularly in daily reporting systems that are still performed manually using spreadsheets. PT. LSM currently faces inefficiencies, data inaccuracy, and lack of real-time access in reporting vessel daily activities. To address these issues, this study aims to design and implement a Web-Based Vessel Daily Report Information System using PHP (Laravel Framework) and MySQL as the database. The research adopts the System Development Life Cycle (SDLC) methodology, which consists of planning, analysis, design, implementation, and testing phases. Data were collected through observation, interviews with company staff, and literature study. The system was designed with features such as vessel daily report management, vessel data management, inventory management, user management and automated report generation in PDF/CSV formats. The testing results, which include structural, functional and validation tests, show that the system operates in accordance with its design and successfully resolves the problems of the previous manual reporting process. The system enables real-time, accurate, and secure reporting that supports both operational monitoring and accounting-related decision-making. In conclusion, the developed system significantly improves the efficiency, accuracy and effectiveness of vessel daily reporting processes at PT. LSM. For future development, the system can be enhanced with additional features such as online crew attendance and ship requisition modules to further strengthen operational and accounting integration.

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