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Gedung LPPMP Universitas Bhayangkara Jakarta Raya Jl. Perjuangan No.81, Marga Mulya, Kec. Bekasi Utara, Kota Bks, Jawa Barat 17143
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Journal of Students‘ Research in Computer Science (JSRCS)
Published by Universitas Bhayangkara Jakarta Raya
ISSN : -     EISSN : 2722290X     DOI : https://doi.org/10.31599/jsrcs
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal ini berisi tentang karya ilmiah hasil penelitian mahasiswa bidang ilmu komputer bersama dosen pembimbingnya yang bertemakan: Algoritma, Augmented and Virtual Reality, Bahasa Komputasi, Computer Graphics, Game Teknologi, Mobile Computing, Operating Systems, Pengolahan Citra, Robotika, Sistem Pakar, Soft Computing, Software Engineering, Software Process and Life Cycle, Software Testing and Quality Assurance, System Software, User Experience (UX), User Interface (UI), Artificial Intelligence, Blockchain Technology, Business Intelligence, Cloud Computing, Computer Architecture, Computer Vision, Database Systems, Deep Learning, Human Computer Interaction, Digital Forensic, Internet of Things, IT Security, Machine Learning, Networking, Semantic Web, Sistem Terdistribusi, Systems Engineering, dan Wireless Network.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 162 Documents
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Konversi ke Microservices Untuk Peningkatan Layanan Perpustakaan Sumadyo, Malikus; Handayanto, Rahmadya Trias; Setiawan, Ramdhani
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/vr275f23

Abstract

Most web-based applications are applications that provide services to users. The services themselves often change according to policies that are usually based on user satisfaction information. Unfortunately, existing applications are mostly based on open-source which is mostly monolithic. If there is an addition of a new service, it requires development from the beginning again. Especially when there is an imbalance between one service and another where one service requires large resources while other services do not require too many resources such as processors, network speed, or database size. This study tries to propose a system change in the library based on PHP-MySQL to be based on microservices.
Metode Naïve Bayes dan Support Vector Machine untuk Mengolah Sentimen Ulasan dan Komentar di Platform Digital Herlawati; Srisulistiowati, Dwi Budi; Agustin, Syafira Cessa; Syafina, Prilia Hashifah; Rachmatin, Nida; Setiawati, Siti
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/dby15h32

Abstract

This study analyzes sentiment from user Reviews of the FLO app, Taman Mini Indonesia Indah (TMII), and public comments on infidelity cases on Instagram, using Naïve Bayes and Support Vector Machine (SVM) algorithms. FLO, an app that helps users track reproductive health, was analyzed based on 1,393 Reviews on Google Play Store. Of these, 796 Reviews expressed positive sentiment, while 597 were negative. Although both Naïve Bayes and SVM achieved an accuracy of 74%, SVM performed better in recall (74%) and precision (71%). For TMII Reviews, the analysis involved 1,616 Google Reviews, with 1,263 showing negative sentiment, indicating complaints about facilities and services, and 353 expressing positive sentiment. SVM outperformed Naïve Bayes, achieving an accuracy of 85% and an f1-score of 87%, compared to Naïve Bayes’ 82% accuracy and 83% f1-score. Additionally, the analysis of 1,200 public comments on Instagram accounts @lambe_turah and @awreceh.id revealed 918 negative comments and 282 positive ones. SVM once again demonstrated superior performance with an accuracy of 91%, precision of 87%, recall of 96%, and an f1-score of 92%, surpassing Naïve Bayes, which achieved an accuracy of 86%. These findings confirm that SVM is more effective for sentiment classification across various digital Platforms, including social issues and service evaluations. The results can be applied to develop public opinion analysis systems that support strategic decision-making and enhance service quality based on user feedback.
Sistem Monitoring Kekeruhan Air Berbasis Arduino Pada Tangki Penampungan Air Fathin, Imas Sofia Umul; Retnoningsih, Endang; Rofiah, Syahbaniar
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/6adkxy39

Abstract

Water is the main human need in daily life. Every house has a storage container (water tank). Water that is stored for a long period of time can change the quality of the water in the water tank. Therefore, the aim of the research is to make it easier to control water in water tanks by using an Arduino-based circuit so that water storage remains clean and does not cause disease. The research uses the Prototype methodology for system development including needs analysis, system design, implementation and system testing. The Arduino-based water turbidity monitoring system is designed with a 16x2 i2c LCD module. The results of research on an Arduino-based water turbidity monitoring system make it easier to control water in water tanks. This system also helps to determine the condition of the water tank, where generally controlling water turbidity and checking water quality is still done manually.
Perancangan Aplikasi Augmented Reality 3D Sebagai Media Pembelajaran Rumah Adat Indonesia Dengan Algoritma FAST Corner di SDI Al-Munir Bekasi Widyanto, Abdillah Prayoga; Handayani, Dwipa; Mayadi
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/bkc3ne60

Abstract

Elementary school students still tend to be less interested in learning local culture, one of which is the variety of traditional houses in Indonesia. Students are more interested in global culture that is trending. The main reason is because the learning process that applies is still conventional and monotonous. The teaching methods that are carried out are only delivered verbally and through written media, resulting in low student involvement in the learning process. Many areas that have cultural heritage are at risk of losing valuable cultural assets due to limited interest and preservation efforts. Digital transformation allows for the creation of new innovations in the scope of education. Augmented reality technology can be used as a bridge to connect students with local cultural diversity. AR technology designed on mobile devices is an ideal medium to motivate the younger generation to maintain the sustainability of local culture in a modern way and in accordance with a digital lifestyle. The purpose of this study is to explore the use of 3D Augmented Reality technology collaborated with the FAST corner algorithm in the learning process as an effort to increase student interest in understanding the forms of traditional houses in Indonesia. The development of a waterfall system is a method in developing Android-based applications by utilizing Unity 3D programming. This research produces an Android-based application to recognize various forms of traditional houses in Indonesia which will be applied to 3rd grade elementary school students so that they can experience a more interactive learning experience.
Penerapan Metode EOQ Pada Sistem Informasi Manajemen Stok Bahan Baku Ayam Broiler Berbasis Web Putri, Sabrina; Irawan, Muhammad Dedi; Santoso, Heri
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/w4gdt918

Abstract

The Economic Order Quantity (EOQ) method is an important inventory management to determine the optimal order quantity to minimize total inventory costs, including ordering costs, storage costs, and stockouts. Companies use technology to make data management easier. With the increasing demand for chicken meat, efficient raw material management is very important to reduce production costs and maintain chicken health. This study found problems faced by companies as a result of manual recording systems that are prone to errors and data loss. The study aims to improve the accuracy of feed management, reduce waste, and ensure proper nutrition for broiler chickens through the implementation of this system. The results of the implementation of this system show improvements in raw material efficiency analysis and stock monitoring. In addition to helping improve the productivity and sustainability of the broiler chicken farming industry, this study offers solutions for companies to overcome current management problems. The system uses the PHP programming language, the codeigniter framework and MySQL as a database.
Sistem Informasi Navigasi Wisata Kota Jakarta untuk Menentukan Rute Tercepat Menggunakan Algoritma Dijkstra Berbasis Web Syaumi, Muhammad Rizki; Noeman, Achmad; Setiawati, Siti; Kustanto, Prio; Achmad, Noeman
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/c9by2m49

Abstract

This study aims to design a web-based tourism navigation information system using Dijkstra’s algorithm to determine the fastest rout in Jakarta City. The proposed navigation system assists tourist in planning their trips more efficiently by providing real-time information on the fastest routes, travel distances, and estimated traviel times. By implementing Dijkstra’s algorithm, the system calculates the optimal route based on the starting location from the user’s device and destination data stored in the database. This research employs the waterfall system development method, which inludes the stages of analysis, design, implementation, and testing. The testing results demonstrate that the system accurately provides the fastest routes, enhancing convenience and travel efficiency for tourist.
Visualisasi Data untuk Analisis Musik Digital Menggunakan Power BI pada Data Spotify Ardi, Afifah Risti; Voutama, Apriade
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/qpm0x949

Abstract

The development of digital technology has transformed the music industry with the emergence of streaming platforms such as Spotify. This study analyzes digital music data on Spotify using Power BI to identify music trends and user consumption patterns. The dataset consists of 6,300 songs with attributes such as artists, Genres, duration, popularity, and explicit status. Data visualization is employed to determine the artists with the most songs, the most popular Genres, the distribution of song duration, and the proportion of explicit and non-explicit songs. The results show that Metallica has the most songs, rock is the most popular Genre, most songs last between 2 and 6 minutes, and non-explicit songs are dominant. These findings provide insights for musicians, record labels, and streaming platform developers in designing music strategies aligned with listener preferences. 
Algoritma SMART dalam Sistem Penilaian Karyawan Terbaik Berbasis Web Sukaesih, Fitri; Mugiarso; Mukhlis; Rasim
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/2nmc4618

Abstract

PT Sinar Perkasa Engineering is a leading engineering and manufacturing company that considers employee evaluation a critical component of human resource management. Manual evaluation processes are often time-consuming and prone to human error, potentially leading to inaccuracies in selecting the best employees. This study aims to design a decision support system based on the SMART algorithm to enhance the efficiency and accuracy of employee evaluations. The system was developed using the Waterfall model and designed with the Unified Modeling Language (UML). The results indicate that the implementation of a web-based decision support system significantly improves the speed and accuracy of the evaluation process, reduces the risk of human error, and provides a transparent and objective assessment tool. This research is expected to serve as a foundation for further development of decision support systems, either through collaborative efforts or by comparing alternative decision-making methods.
Optimalisasi Pemilihan Laptop Kerja Terbaik dengan Pendekatan Metode AHP dan TOPSIS Sya’Roni; Sutinah, Entin; Agustina, Nani
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ev7t4c98

Abstract

The components found in laptops are generally the same as those in personal computers (PCs), but they are designed to be smaller, lighter, and more energy-efficient. As technology has advanced, laptops have also undergone many improvements, including in design, processor speed, memory capacity, feature additions, and efficiency in terms of time and space. Additionally, the prices of laptops today are relatively affordable. PT. Varsindo Kimia Abadi is a company engaged in the chemical industry. Currently, the company is facing a challenge in selecting the right laptop for new employees, considering the many brands and specifications available. Therefore, the author aims to provide the best recommendations for laptop selection. In the data analysis process of this research, two methods are adopted: AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The research results indicate that the best choice for a work laptop is the Asus X441MA with a score of 0.6717, followed by the Lenovo Ideapad IP V130 with a score of 0.5913, and the Asus X407MA as the third alternative with a score of 0.5458.
Implementasi K-Means Clustering pada Citra Digital Tomat untuk Identifikasi Kondisi Segar dan Busuk Aznawi, Nasrul Mahruf; Setiadi, Muhammad Irham; Aina, Zarifah; Manullang, Setti; Rahmadiyah, Shafira Nur
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/srtqmw49

Abstract

The manual identification of fresh and rotten tomatoes has still relied on human visual observation, which tends to be inconsistent and time-consuming. This study aimed to develop a tomato image classification system using the K-Means Clustering method based on color, shape, and texture features to automatically identify fresh and rotten conditions. The Dataset consisted of 500 tomato images for training and 60 tomato images for testing, equally representing fresh and rotten conditions. The process involved converting the images into L*a*b and grayscale formats, performing segmentation using K-Means, and extracting shape and texture features for the classification process. The testing results showed that the system successfully classified fresh and rotten tomatoes with an accuracy rate of 95%, with both precision and recall exceeding 93% for each class. These findings indicated that the K-Means method could be effectively applied in tomato image processing to support the sorting process of agricultural products. This research contributed to the development of a digital image-based classification system that could be integrated into smart agriculture systems.

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