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JuSTISe: Journal Data Science, Technology, Informatics and Security
Published by Universitas Kebangsaan Republik Indonesia
ISSN : -     EISSN : 31634230     DOI : -
Core Subject :
JuSTISe: Journal Data Science, Technology, Informatics and Security adalah jurnal ilmiah nasional yang ditinjau oleh sejawat (peer-reviewed) dan diterbitkan oleh Universitas Kebangsaan Republik Indonesia. Jurnal ini berfokus pada publikasi hasil penelitian berkualitas tinggi di bidang ilmu data (data science), teknologi informasi, rekayasa informatika, keamanan siber, dan sistem digital. JuSTISe bertujuan menjadi wadah yang kredibel bagi akademisi, peneliti, dan praktisi untuk menyebarluaskan hasil penelitian asli serta artikel tinjauan yang berkaitan dengan kecerdasan buatan, analitik big data, rekayasa perangkat lunak, keamanan jaringan, dan sistem informasi. Jurnal ini menekankan pada penelitian teoritis maupun terapan yang berkontribusi terhadap kemajuan teknologi dan inovasi di era digital. Seluruh naskah yang dikirimkan akan melalui proses penelaahan sejawat (peer-review) yang ketat untuk memastikan kualitas dan integritas akademik. JuSTISe menerima naskah dari penulis nasional maupun internasional, dan seluruh artikel diterbitkan dalam bahasa Inggris untuk menjangkau audiens global. Jurnal ini diterbitkan dua kali dalam setahun (Juni dan Desember) dan berkomitmen untuk mendukung pengembangan ilmu pengetahuan serta kolaborasi penelitian di bidang informatika, ilmu data, dan keamanan siber.
Arjuna Subject : -
Articles 39 Documents
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Monitoring Greenhouse dan Penyemprotan Cerdas Berbasis IoT pada Budidaya Kentang Lutfy Fauzy Firmansyah; Yasri; Alkautsar Rahman
Journal Data Science, Technology, Informatics and Security Vol 3 No 1 (2025): Journal Data Science, Technology, Informatics and Security (Juni 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i1.4315

Abstract

Potato productivity is often disrupted by pest attacks, leading to reduced yields. This research implements an IoT-based early warning system for pest detection and automated pesticide spraying on potato plants in a greenhouse. The system utilizes the YOLOv5 algorithm to detect armyworms and aphids using a mobile phone camera, supported by a NodeMCU microcontroller, soil moisture sensors, and the Blynk platform for real-time monitoring. A rule-based decision tree approach is used to regulate automatic spraying when the pest detection confidence level exceeds 70%. Field trials in Cibeureum Village, West Java, demonstrated a detection accuracy of 85% with a response time of 3–5 seconds. These results demonstrate the ability to reduce excessive pesticide use compared to manual methods and increase pest control efficiency. This smart farming system also provides real-time notifications via the Blynk app, facilitating remote monitoring and control by farmers. This implementation supports the concept of precision agriculture by optimally utilizing pesticides, maintaining productivity, and promoting sustainable agricultural practices.
Prototipe Smart Helmet dengan Notifikasi Navigasi Real-Time melalui Koneksi WiFi Adrian Febriansyah; Irman Hariman
Journal Data Science, Technology, Informatics and Security Vol 3 No 1 (2025): Journal Data Science, Technology, Informatics and Security (Juni 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i1.4317

Abstract

The development of wearable technology has brought various innovations to improve rider safety and comfort. One such innovation is a smart helmet capable of displaying real-time navigation notifications. This research aims to design and implement a smart helmet prototype integrating an ESP32 microcontroller and an OLED display, utilizing a Wifi connection to receive navigation data from an Android smartphone. The method used was prototyping, encompassing literature review, system design, hardware and software development, and questionnaire testing. The implementation results showed that the smart helmet successfully displayed turn direction information in the form of symbols in real time, thus helping motorcyclists stay focused while driving. The Wifi connection proved stable in transmitting data, although there were limitations in displaying route details due to software integration constraints. Overall, this research demonstrates that smart helmets have significant potential to improve safety, especially for highly mobile riders.
Penerapan YOLOv4 dan Sensor Laser untuk Keamanan Kebun Anggur Brazil Rizky Muharam; Yasri; Ocsar Hadikaryana
Journal Data Science, Technology, Informatics and Security Vol 4 No 1 (2026): Jurnal Data Science, Technology, Informatics and Security (Juni 2026)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v4i1.4318

Abstract

Agricultural security is crucial for maintaining productivity and business sustainability, particularly for high-value commodities such as grapes. The threat of theft and disturbance by wild animals, such as wild boar, often causes significant losses in vineyards. This study proposes an intelligent surveillance system integrating laser sensors with the YOLOv4 (You Only Look Once) algorithm to enhance agricultural security through automated, real-time detection. The laser sensor functions as an early motion-detection mechanism, while the ESP32-CAM module captures visual imagery for subsequent analysis using the YOLOv4 model to achieve precise object classification. The system also incorporates Internet of Things (IoT) connectivity via the Blynk platform for real-time remote monitoring. Test results show that the system achieves 85% detection accuracy during daytime and 78% at night, with an average response time of one second from detection to notification.
Implementasi Tanda Tangan Digital untuk Meningkatkan Efisiensi Administrasi Anggota Pramuka Saka Wira Kartika di Kodim 0610/Sumedang Daffa Fadhlurohman; Yasri; Iim Abdurrohim
Journal Data Science, Technology, Informatics and Security Vol 3 No 1 (2025): Journal Data Science, Technology, Informatics and Security (Juni 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i1.4319

Abstract

Membership administration in Scout organizations is still mostly conducted manually, including member data recording, membership card (KTA) issuance, and announcement distribution. Manual processes often lead to issues such as delays in data collection, difficulties in searching for information, and the risk of document loss. Therefore, a digital system is required to manage membership administration more efficiently and securely. This research produces a Web-Based Scout Membership Administration System, developed using Node.js, Express, and Prisma ORM on the backend, and React.js with Tailwind CSS on the frontend. The system provides main features such as member registration and biodata management, KTA issuance in PDF format with an embedded QR Code, member data validation by the administrator, and announcement management. To enhance security, each KTA is embedded with a digital signature using the Ed25519 algorithm, allowing the authenticity of the data to be verified through QR Code scanning. The testing results show that this system is able to simplify the administrator’s tasks in validating and managing member data, while also providing convenience for members in accessing information and obtaining their KTA quickly. The implementation of digital signatures ensures data integrity and security, making the administrative process more effective, efficient, and reliable.
Sistem Monitoring Limbah B3 Rumah Sakit Berbasis Web dan Mobile Vina Nurhotijah; Irman Hariman
Journal Data Science, Technology, Informatics and Security Vol 3 No 2 (2025): Journal Data Science, Technology, Informatics and Security (Desember 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i2.4330

Abstract

The management of hazardous and toxic waste (B3) in hospitals is a crucial aspect to ensure environmental safety and public health. Improper handling of medical waste has the potential to  cause environmental pollution, increase the risk of disease transmission, and create negative impacts on healthcare workers as well as the surrounding community. However, the current  practices of B3 waste management in many hospitals still face several challenges, including error prone manual recording, limited monitoring systems, and a lack of transparency in reporting to relevant stakeholders. This study aims to design and develop a web- and mobile-based monitoring system for B3 waste at Majalaya Regional General Hospital (RSUD Majalaya) to improve efficiency, accuracy, and traceability in waste management processes. The development method applied is Agile with the Scrum framework , enabling the application to be built iteratively and adaptively according to user needs. The developed application is equipped with several main features, including digital waste data recording, waste status monitoring via QR Code, automatic notification when waste accumulation occurs, waste labeling based on categories, and integrated reporting aligned with regulatory standards. The testing results indicate that the system facilitates the recording and monitoring processes, enhances the accuracy of reporting, and supports compliance with government regulations on B3 waste management. With this system, hospital waste  management can be carried out in a more structured, transparent, accountable, and sustainable manner, thereby providing a tangible contribution to environmental protection and public safety.
Implementasi Kios Interaktif Berbasis AI dengan Gemini API dan RAG untuk Optimalisasi Sistem Informasi Kampus Firdaus Rhamadhan; Alkautsar Rahman; Oscar Hadikaryana
Journal Data Science, Technology, Informatics and Security Vol 3 No 2 (2025): Journal Data Science, Technology, Informatics and Security (Desember 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v3i2.4331

Abstract

Efficient and accurate information access is a fundamental challenge in higher education environments. This research aims to develop an interactive kiosk application based on artificial intelligence (AI) as a solution to optimize the information system at Universitas Kebangsaan Republik Indonesia (UKRI). The system is designed by integrating the Gemini Multimodal API with the Retrieval-Augmented Generation (RAG) framework to provide intelligent and efficient information services. The methodology includes building a campus-specific knowledge base from internal documents, which are processed into vector embeddings and stored in a Qdrant vector database. The RAG framework ensures that every response generated by the AI model is grounded in factual data from this knowledge base, thereby significantly improving accuracy. The implementation results show that the kiosk prototype successfully provides a natural and responsive multimodal (voice and text) interaction. Functional testing proves that the RAG mechanism dramatically outperforms a generic AI model in delivering relevant and accurate answers regarding campus information. In conclusion, this interactive kiosk has great potential to transform conventional information dissemination methods, making them more accessible and user-centric.
Sistem Rujukan RS Terdekat Berbasis Model-Driven DSS (A*) di Kota Bandung Salma Rahayu; Irman Hariman
Journal Data Science, Technology, Informatics and Security Vol 3 No 2 (2025): Journal Data Science, Technology, Informatics and Security (Desember 2025)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop a model-driven Decision Support System (DSS) designed to determine hospital referrals in Bandung City by considering the nearest distance as the primary criterion. The motivation for this research is the growing demand for efficient referral mechanisms that can assist both patients and healthcare providers in making objective, fast, and location-based decisions. The proposed system integrates Global Positioning System (GPS) coordinates as user input and applies the A search algorithm to calculate the most optimal route between the user’s position and the selected hospital. The dataset consists of a graph-based map of Bandung nodes combined with a hospital database containing detailed information on available polyclinics. The system generates recommendation tables that present hospital names, types, addresses, distances, statuses, and classes, allowing users to compare referral options more comprehensively. Experimental evaluation shows that the A* algorithm consistently produces valid distance calculations compared with manual measurements, confirming the reliability of the system in processing spatial data and generating accurate recommendations. Therefore, the model-driven DSS proposed in this study provides a practical and effective solution to improve the efficiency of medical decision-making processes in Bandung City, particularly in referral determination.
Sistem Pendukung Keputusan Gaya Belajar Siswa Berbasis Website Menggunakan Metode WASPAS Salik Elhanan; Mochzen Gito Resmi; Ismi Kaniawulan
Journal Data Science, Technology, Informatics and Security Vol 4 No 1 (2026): Jurnal Data Science, Technology, Informatics and Security (Juni 2026)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v4i1.5007

Abstract

Determining students' learning styles is an essential aspect of optimizing the information absorption process in learning activities. However, the learning style identification process at SMP Fullday Al-Muhajirin Purwakarta is currently still carried out through manual recapitulation which takes time and has the potential to cause subjective bias in decision making by Guidance and Counseling (BK) teachers. This research provides a solution by developing an integrated website-based Decision Support System (DSS) using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The aim is to automate the classification of students' learning styles into Visual, Auditory, or Kinesthetic (VAK) categories quickly and precisely. The software engineering method used is Prototype, which focuses on iterating user needs directly. This system was built using the Laravel 10 framework and MySQL database. The results of this research prove that the WASPAS method is able to process questionnaire instrument data into a stable decision matrix, producing structured ranking accuracy. Software testing shows that all application modules run smoothly, so this system has practically succeeded in accelerating the duration of identifying student learning styles and assisting BK teachers in designing targeted academic approach strategies.
Penerapan Rule-Based System Berbasis Data Temporal pada Sistem Monitoring Masa Kerja dan Proyeksi Pensiun Annisa Azzahra; Ismi Kaniawulan; Mochzen Gito Resmi
Journal Data Science, Technology, Informatics and Security Vol 4 No 1 (2026): Jurnal Data Science, Technology, Informatics and Security (Juni 2026)
Publisher : Universitas Kebangsaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31848/justise.v4i1.5015

Abstract

Personnel data management at BKPSDM Purwakarta Regency still faces challenges in monitoring employee service periods and identifying personnel approaching retirement due to the lack of automated data processing. This study aims to develop the JAPEL personnel information system by implementing a temporal data-based Rule-Based System for employee service period monitoring and retirement projection. The system was developed using the prototyping method with PHP, the Laravel Framework, and MySQL. Temporal data was applied to calculate employee age, remaining service period, and estimated retirement date, while the Forward Chaining inference method was used to classify employee status based on predefined rules. The results show that the system can monitor employee service periods, identify employees approaching retirement, project position vacancies, and generate reports automatically. Functional testing using Blackbox Testing with the Equivalence Partitioning technique confirmed that all system functions operated as expected. The developed system improves personnel data management and supports decision-making in workforce planning.

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