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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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Pendeteksian dan Klasifikasi Sampah pada Bank Sampah Berbasis Web Menggunakan YOLOv11 Nabila , Marsyanda Salsa; Hidayat, Agus; Herlawati, Herlawati
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/r5me0z35

Abstract

The problem of poorly managed household waste management can increase the burden on the environment and reduce the effectiveness of recycling. Waste banks in general still rely on manual systems in sorting waste which is prone to errors and requires more labor. This research aims to develop a web-based waste detection and classification system using the You Only Look Once (YOLO) version 11 yolov11n (nano) method. The research method included downloading the main secondary dataset named R1 Test version 15 from the Roboflow Universe platform, collecting other secondary datasets from internet scraping and manual photography, which resulted in a total of 27,400 images of trash with nine different types, namely bottle, cans, cardboard, cup, foil, food, paper, paper_bag, and plastic.The results show that the yolov11n model is able to detect objects with sufficient accuracy and light computational resources by producing a precision value of 91,7%, recall of 89%, mAP50 of 93,2% and mAP50-95 of 75,8% in all classes. The best model results obtained are integrated into the web using the flask framework.
Implementasi Sistem Monitoring Jaringan Mikrotik Dengan The Dude Jaelani, M; Whidhiasih, Retno Nugroho; Handayanto, Rahmadya Trias
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: 10.31599/15w1se86

Abstract

The internet service provider, CV. Sekarjaya Computindo, is currently still using a manual monitoring system. This manual monitoring system relies on the Windows command prompt. As a result, detecting network issues takes longer because the administrator must manually search for and ping IP addresses within the network or wait for user reports when network problems occur. In this study, a Mikrotik network monitoring system using The Dude was developed for CV. Sekarjaya Computindo to assist the administrator in monitoring network devices more efficiently, enabling faster identification and resolution of network disruptions. The results of the study show that The Dude monitoring system can quickly monitor the status of network devices when they are up or down due to damage or network disturbances. These statuses are displayed on The Dude’s network maps and real-time notifications are sent via Telegram.
Analisis Sentimen Masyarakat Terhadap PHK di Indonesia Pada Twitter Menggunakan Naïve Bayes dan Support Vector Machine (SVM) AlHakim, Abdu Malik; Atika, Prima Dina; Herlawati, Herlawati
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: 10.31599/96sfw544

Abstract

The phenomenon of layoffs in Indonesia has led to various public opinions, especially on social media. This research aims to analyze public sentiment on the layoff issue using data from Twitter, and compare the performance of two text classification algorithms, namely Naïve Bayes and Support Vector Machine. The Knowledge Discovery in Databases approach is used as the research framework, which includes the stages of data selection, text cleaning, transformation, classification, and evaluation. A total of 3,458 tweets were collected and processed through the pre-processing stage, then classified into positive and negative sentiments. Performance assessment was conducted with three scenarios of training and test data sharing: 80:20, 70:30, and 90:10. The results showed that Support Vector Machine gave the highest accuracy of 84.93% in the 90:10 scenario, compared to Naïve Bayes with 82.61% accuracy in the same scenario. Visualization through wordcloud was also used to strengthen the interpretation of dominant words in public opinion. The findings show that classification algorithms can be utilized to understand public perceptions of employment issues and support social data-based decision-making. This research can be further developed by expanding data coverage and evaluating more complex methods to improve classification accuracy.
Rancang Bangun Tempat Sampah Otomatis Menggunakan Sensor HC-SR04 Berbasis Arduino Uno Marsharani; Retnoningsih, Endang; Rofiah, Syahbaniar
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/z94b2304

Abstract

The research on automatic trash bins aims to create an innovative solution for maintaining environmental cleanliness by designing an Arduino-based trash bin. This automatic trash bin is expected to reduce the negative impact of a dirty environment on human health and surrounding cleanliness. The trash bin consists of two main components: hardware and software. The hardware includes an ultrasonic sensor that detects objects at a certain distance and a servo motor that operates the lid of the trash bin. The software uses Arduino IDE to control and manage the functions of the hardware. This research employs a Prototype method, which allows for better control over the design and development process. With this method, researchers can quickly iterate and make improvements based on testing results and feedback. The results show that the automatic trash bin functions as expected. When the ultrasonic sensor detects an object at a distance of 20 cm, the Arduino instructs the servo motor to automatically open the trash bin lid. Conversely, if the object is no longer detected, the lid will close again. The implementation of this Arduino-based automatic trash bin is expected to be an effective step in creating a cleane.
Analisis Sentimen Ulasan Produk Sneakers Lokal Pada Tokopedia Menggunakan Algoritma Naïve Bayes dan Support Vector Machine Trisumeikra, I Komang Arya; Herlawati, Herlawati; Hidayat, Agus
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/5wew3w31

Abstract

transformation in various sectors, including the fashion industry, especially sneakers. Sneakers are now a symbol of modern lifestyle and global trends, with brands such as Nike and Adidas dominating the market. However, high prices are an obstacle for many Indonesian consumers. This opens up opportunities for local brands to offer quality products at affordable prices through e-commerce such as Tokopedia, the second highest traffic platform in Indonesia. The research analyzed sentiment from 1,032 consumer reviews of local sneakers from five stores: NAH Project, Aerostreet, Geoff Max, Ventela, and Brodo. The analysis was conducted using Naïve Bayes and Support Vector Machine (SVM) algorithms. The SVM evaluation results produced the highest accuracy of 98%, compared to Naïve Bayes which reached 96%. This best model is implemented in a web-based application to analyze the sentiment of new reviews, to assess the perceived quality and consumer satisfaction of local sneakers products on Tokopedia.
Model Prediksi Kondisi Kesehatan dari Data Medical Check-Up Menggunakan K-Nearest Neighbors dan Decision Tree Cahyaaty, Tata Arya; Herlawati, Herlawati; Setiawan, Andy Achmad Hendhar
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 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/tvt7s936

Abstract

Medical Check-Up (MCU) is an essential procedure for the early detection of health disorders. However, manual analysis of MCU results requires time and may be subject to the interpretation of medical personnel. This study aims to develop an automatic classification system to predict health conditions based on MCU results using the K-Nearest Neighbors (KNN) and Decision Tree algorithms. The MCU data used includes blood pressure, body temperature, heart rate, as well as heart and blood pressure assessments. The models were trained and evaluated using the CRISP-DM methodology. The results show that the Decision Tree achieved an accuracy of 91.31%, while KNN achieved an accuracy of 89.75%. This system is implemented as a web-based application with a simple user interface to support the early diagnosis process at RS EMC Cibitung.
Implementasi Algoritma Apriori pada Sistem Informasi Penjualan Web Pujiono, Krisna Dimas; Mugiarso; Handayani, Dwipa; Rasim, Rasim
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 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/kjhjrc12

Abstract

This study focuses to implementing a web-based sales information system leveraging the Apriori algorithm to analyze consumer purchasing patterns at PT. Mura Mitra Sejati. Adopting the Waterfall development methodology, the project progressed systematically through the analysis, design, implementation, testing, and maintenance stages.The system was developed using a native PHP architecture based on the MVC pattern, supported by a MySQL database and Bootstrap for the front-end. Key functionalities of the system include sales transaction recording, real-time inventory management, and powerful association rule mining. Comprehensive black-box testing across all modules—Login, Stock Management, Transactions, Apriori Analysis, and Reporting—confirmed the intended performance of every system function, achieving a 100% success rate.The Apriori algorithm effectively identified strong association rules from 10 transaction datasets, notably revealing the frequent co-purchase of White Paint and 1-inch Brushes, with 40% support and 80% confidence, respectively. Ultimately, the resulting system delivers an efficient, well-structured, and data-driven solution that significantly improves sales management and supports strategic decision-making.
Sistem Pakar Berbasis Whatsapp Bot Dengan Metode Forward Chaining Untuk Diagnosis Dini Gangguan Mental Pada Perkembangan Anak Fadhilah, Rayhan; Revansa , Muhammad Fahri; Fakhriza, Giffari Ahmad; Sutinah, Entin; Kusumo, Aryo Tunjung
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/4b27ra56

Abstract

Mental disorders in children can hinder their development if not detected early. Limited public awareness and a shortage of professionals often lead to undiagnosed cases. This study developed an expert system based on a WhatsApp Bot using the Forward Chaining method to support early diagnosis of children's mental disorders. Built with Node.js and MySQL, the system can identify seven types of disorders: ADHD, anxiety, depression, autism, OCD, eating disorders, and PTSD. Black box testing showed the system functions well and provides accurate results. It is expected to assist parents and educators in early detection and awareness of mental health issues in children.
Implementasi Internet of Things (IoT) pada Sistem Pemantauan Kelembapan Udara di Perpustakaan UBSI Anwar, Rian Septian; Agustina, Nani; Indriyani, Novita
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/3c074h77

Abstract

Libraries, particularly academic libraries like those at UBSI, store valuable collections of books, manuscripts, and digital archives. The preservation of these physical assets is constantly threatened by environmental factors, primarily fluctuating temperature and humidity. Uncontrolled high humidity accelerates the growth of mold and mildew, leading to irreversible damage to paper-based materials. Manual monitoring systems are often inefficient, costly, and susceptible to human error. This research aimed to develop and implement a real-time, Internet of Things (IoT)-based air humidity monitoring system to ensure optimal environmental conditions for collection preservation in the UBSI Library. The system utilizes the NodeMCU ESP8266 microcontroller and the SHT30 sensor, chosen for its high accuracy and stability, to continuously collect humidity data. This data is transmitted via Wi-Fi to a Firebase real-time database and visualized on a dynamic web dashboard. The prototype was tested for accuracy and reliability, showing minimal deviation (less than 3%) compared to commercial hygrometers. The results confirm that the IoT system successfully provides remote, continuous, and highly accurate monitoring, enabling prompt intervention by library staff when humidity levels exceed the safe threshold (50%–60%). This innovative approach significantly enhances collection preservation efficiency and reduces potential conservation costs. The system built not only successfully collects data, but also processes it into easily understood information, thus fulfilling the initial objective of overcoming the inefficiency of manual monitoring.
Sistem E-Payroll pada Karyawan Yayasan Pendidikan Islam An-Nadwah Menggunakan Algoritma Advanced Encryption Standard (AES) Berbasis Web Fitriyani, Linda; Handayani, Dwipa; Lestari, Tyastuti Sri; Hidayat, Agus
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 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/n7qt5a13

Abstract

The rapid development of information technology encourages educational institutions to improve efficiency and security in administrative management, including payroll systems. This research aims to design a web-based E-Payroll system implemented at the Islamic Education Foundation An-Nadwah by applying the Advanced Encryption Standard (AES) algorithm to ensure the confidentiality of employee salary data. The system was developed using the Rapid Application Development (RAD) method to enable fast and user-responsive development. The implementation results show that the system can effectively encrypt and decrypt salary data, as well as provide real-time and secure payroll reports. System testing using the blackbox method demonstrates that all system functionalities work as expected. This system is expected to enhance efficiency, accuracy, and security in the payroll process within the foundation.

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