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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Marsipature Hutanabe: Jurnal Pengabdian Kepada Masyarakat Pascal: Journal of Computer Science and Informatics
Sony Bahagia Sinaga
STMIK Mulia Darma
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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Journal : pascal journal of computer science and informatics

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Development and Performance Evaluation of an IoT-Based Smart Irrigation System for Real-Time Soil Moisture Monitoring and Automatic Irrigation Siti Rubiah; Tasya Halizha Lubis; Haryoko Ichsan Prabowo; Dina Lorensa Sinaga; Sony Bahagia Sinaga
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 02 (2026): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Manual irrigation management often results in watering practices that do not reflect actual soil moisture conditions, leading to inefficient water use and reduced crop productivity. This study aims to design and implement an Internet of Things (IoT)-based Smart Irrigation System capable of monitoring soil moisture in real time while automatically controlling the irrigation process. The research employed a Research and Development (R&D) method using a prototyping approach, including requirement identification, system design, hardware and software implementation, system integration, and performance testing. The proposed system was developed using an ESP32 microcontroller, a capacitive soil moisture sensor, a relay module, a water pump, and an internet-based monitoring dashboard. System performance was evaluated through sensor readings, real-time data monitoring, automatic pump control, response time measurement, and operational stability testing. The results demonstrate that the proposed system successfully monitors soil moisture, transmits data to the dashboard in real time, and automatically controls the irrigation pump based on predefined soil moisture thresholds. The implementation of a threshold with hysteresis mechanism improves pump stability by reducing frequent switching caused by sensor fluctuations. Furthermore, the system exhibits a relatively fast response time and stable operation throughout the testing period. These findings indicate that IoT technology provides an effective solution for developing efficient, practical, and scalable smart irrigation systems suitable for small- and medium-scale agricultural applications.
Optimization of Indoor Navigation Using the A Algorithm and Adaptive Grid (Gridadapte) for Efficient Pathfinding Asia Leny Ritonga; Ega Fransiska; Hafidz Afdillah; Johan Alfredo Nainggolan; Rahmad Imam Sobari; Sony Bahagia Sinaga
Pascal: Journal of Computer Science and Informatics Vol. 3 No. 01 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Optimal path navigation in indoor environments is a crucial problem in the development of robotic systems and location-based services due to complex spatial structures, the presence of obstacles, and limited available pathways. The A* algorithm, as a heuristic-based pathfinding method, is widely used; however, its performance degrades on high-resolution grid maps because of the increasing number of nodes that must be explored. This study proposes the integration of the A* algorithm with an adaptive grid simplification method (Gridadapte) to improve pathfinding efficiency without sacrificing route quality. The research methodology includes grid-based indoor map modeling, the application of Gridadapte to reduce cell density in low-obstacle areas, and the implementation of the A* heuristic function for optimal path search. Performance evaluation is conducted through simulations on several indoor map scenarios by comparing conventional A* and Gridadapte-based A* in terms of the number of explored nodes, path length, and computation time. Simulation results show that the proposed approach significantly reduces the number of search nodes by 30–45% and accelerates computation time by 25–40% compared to A* on regular grids, while the resulting path length remains optimal and does not experience a significant increase. These findings indicate that Gridadapte is effective in reducing the A* search space while preserving the topological structure of the environment. Therefore, the combination of A* and Gridadapte is proven to enhance both the efficiency and accuracy of pathfinding in complex indoor environments. This approach has strong potential for application in autonomous robotic systems, smart building guidance systems, and location-based Internet of Things (IoT) applications in indoor settings such as hospitals, campuses, and shopping malls.
Co-Authors Asia Leny Ritonga Berto Nadeak Chandra Frenki Sianturi Dina Lorensa Sinaga Ega Fransiska Hafidz Afdillah Haryoko Ichsan Prabowo Johan Alfredo Nainggolan Kevin H Hutahaean Rahmad Imam Sobari Siti Rubiah Tasya Halizha Lubis