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DigiField: Real-Time Smart Farming Monitoring System Using React.js and Express.js for Agricultural Digitalization Permana, Basuki Rahim Setya; Auliana, Sigit; Octavian, Rizqi Kevin
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4160

Abstract

The agricultural sector remains a cornerstone of Indonesia’s economy, yet it faces persistent challenges such as climate change, land degradation, and limited adoption of digital technology among smallholder farmers. One critical issue is the lack of real-time monitoring systems accessible to farmers for tracking essential environmental parameters such as soil moisture and temperature. Traditional manual methods are still widely used, leading to inefficiencies and suboptimal decision-making. This study proposes the development of DigiField, a smart farming monitoring system designed to bridge the technological gap in rural agriculture by leveraging modern web technologies. The system is developed using the React.js framework for the frontend, enabling a dynamic, responsive, and mobile-friendly user interface, and Express.js for the backend to facilitate real-time data processing from sensor devices. The research adopts a technology-based development approach, involving needs analysis from field observations and interviews with local farmers. The DigiField prototype is designed to monitor soil moisture and temperature using sensor data that is transmitted and visualized in real-time through a web interface. The system aims to support data-driven agricultural decision-making and enhance productivity through accessible, low-cost technology. Preliminary testing and user feedback indicate that DigiField is effective in addressing local agricultural monitoring needs, with a user interface that is intuitive for farmers and a backend infrastructure that supports real-time updates. This study contributes to both academic discourse in the field of agricultural informatics and practical efforts to promote digital transformation in Indonesia’s agricultural sector.
Detecting Hoax News with Web-Based SVM Classifier: A Machine Learning Approach to Combat Misinformation Using Support Vector Machine (SVM) Algorithm Auliana, Sigit; Permana, Basuki Rahim Setya; Kalsum, Ummy; Mudofar, Mudofar
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4161

Abstract

The massive spread of hoax news in the digital era has caused various negative impacts, ranging from public misinformation to social unrest. This condition highlights the need for a technological solution capable of automatically and accurately detecting the truthfulness of information. This study aims to develop a web-based application for hoax news detection using the Support Vector Machine (SVM) algorithm. The method involves text preprocessing, feature extraction using Term Frequency-Inverse Document Frequency (TF-IDF), and classification with SVM. The system is designed with a simple and responsive web interface, allowing users to input news content and receive prediction results easily. Testing was conducted using both white-box and black-box methods to ensure that the system's logic functioned as expected. The results show that the system successfully classifies news into two categories—valid and hoax—with good accuracy. This application is expected to serve as a useful tool for the public in identifying the authenticity of news and preventing the spread of false information across digital platforms.
Information System Audit of FIF Mobile Collection at PT Federal International Finance POS Baros Using the COBIT 5 Framework Permana, Basuki Rahim Setya; Aryono, Gagah Dwiki Putra; Aliffito, Sadam Nazar
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav4182

Abstract

This study aims to evaluate the governance and performance of the FIF Mobile Collection information system implemented at PT Federal International Finance POS Baros using the COBIT 5 framework. As mobile-based applications become critical tools in financial operations—particularly in billing and collection activities—ensuring their security, efficiency, and alignment with organizational goals is imperative. The COBIT 5 framework was adopted to assess the maturity and capability of IT processes, with a specific focus on the DSS05 process: Manage Security Services. Data was collected through observation, interviews, and documentation analysis, and evaluated using the COBIT 5 Process Assessment Model (PAM). The results of the audit show that the DSS05 process achieved Capability Level 3, meaning the process is well-defined and implemented but not yet fully measurable or optimized. The assessment revealed that Levels 1 and 2 were fully achieved, while Level 3 was largely achieved (60–66.66%), indicating the need for performance monitoring and continual improvement mechanisms. Several gaps were identified in the areas of risk management, incident response, and user training, which present potential threats to data security and system reliability. The findings also indicate partial alignment of the system with key enterprise goals such as customer service excellence, operational agility, and information-based decision-making. However, the lack of real-time monitoring, formalized response procedures, and predictive controls hinders the organization from achieving higher governance maturity. Recommendations include implementing automated security tools, conducting regular IT risk assessments, and enhancing user awareness programs. This study concludes that while the FIF Mobile Collection system delivers operational benefits, improvements in governance maturity—guided by COBIT 5—are essential to ensuring secure, efficient, and strategically aligned system performance in the long term.