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Design of Fresh Vegetable Quality Monitoring System Based on the Internet of Things (IoT) Amri, Syahputra; Bukhori, Alan Akbar; Zahro, Annisa; Pasaribu, Filemon Agustinus; Fragastia, Vidi Agung
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 3 (2024): October 2024
Publisher : LPPM Universitas Potensi Utama

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Abstract

In the fresh vegetable distribution industry, maintaining product quality during transportation is a significant challenge, especially since vegetables are vulnerable to changes in temperature, humidity, and vibrations. This research developed an Internet of Things (IoT)-based vegetable quality monitoring system that utilizes sensors to measure temperature, humidity, vibrations, and GPS location during the distribution process. The system was designed using the Software Development Life Cycle (SDLC) method, which includes stages of analysis, design, development, testing, and maintenance. The monitoring tools consist of the GPS Neo 6m sensor, temperature and humidity sensor (DHT11), vibration sensor (SW-420), as well as the Node MCU ESP32 microcontroller and GSM SIM800L V2 modem. Data was collected during the distribution from Berastagi, Karo Regency, to Pusat Pasar Medan. The monitoring results showed a lowest temperature of 23.6°C and a highest humidity of 93% RH, which are within the safe range. The detected vibration was 94.22%, indicating a low vibration level, which did not cause mechanical damage to the vegetables. Therefore, this monitoring system is effective in maintaining vegetable quality during distribution, and the data obtained validates that transportation conditions did not negatively impact the horticultural products.
Development of a Geographic Information System–Based Palm Tree Census Tool for Oil Palm Plantations (Case Study: Langkat Regency) Fragastia, Vidi Agung; Batubara, Rini Oktari; Putra, Armansyah; Afilla, Muhammad Rizky
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 3 (2024): October 2024
Publisher : LPPM Universitas Potensi Utama

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Abstract

Oil palm plantations require accurate and timely plant census data to support effective management decisions related to productivity, replanting, and maintenance activities. However, conventional manual census methods are constrained by long processing times, inconsistent data quality, and high susceptibility to human error. These limitations hinder the early identification of abnormal or missing palms and delay operational planning. To address these challenges, this study developed an integrated digital census system using a Web-based Geographic Information System (WebGIS), GPS-enabled Android mobile applications, and drone-based photogrammetry. The research employed the Waterfall Software Development Life Cycle (SDLC), consisting of requirement analysis, system design, implementation, testing, and maintenance. Spatial and non-spatial data were collected through field observations, interviews, GPS coordinates, and UAV imagery. The system was developed using PHP, MySQL, and GIS-based visualization tools, while mobile components utilized GPS navigation to guide field staff in locating abnormal trees. Analysis of census data revealed that 799 out of 47,404 trees (1.68%) were classified as abnormal or missing, a population loss that can significantly reduce potential yield. The GIS-based system demonstrated substantial efficiency improvements, reducing census duration from 7–8 months to 1–2 months in Observation Area 1 and from 4–5 months to 1 month in Observation Area 2. Drone photogrammetry enabled more accurate detection of canopy gaps and validated field measurements. System testing showed that all functional modules performed correctly, and User Acceptance Testing yielded a Cronbach’s Alpha value of 0.821, indicating strong user acceptance and instrument reliability. Overall, the integrated system enhances data accuracy, accelerates census operations, and supports site-specific management in alignment with precision agriculture principles. The results highlight the system’s potential to significantly improve operational efficiency and sustainability in oil palm plantation management.