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All Journal Jurnal Rekayasa elektrika Journal of Electrical Engineering, Energy, and Information Technology
Muhaimin, Ahmad Dzakiyuddin
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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LoRa and IoT Based Monitoring System for Detecting Ganoderma Disease Attacks on Oil Palm Plants Muhaimin, Ahmad Dzakiyuddin; Hadary, Ferry; Suswanto, Iman
Journal of Electrical Engineering, Energy, and Information Technology (J3EIT) Vol 11, No 3: December 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/j3eit.v11i3.68713

Abstract

This research develops a monitoring system based on LoRa and IoT to detect ganoderma disease attacks on oil palm plants, aiming to detect ganoderma disease early. The method used involves the use of MQ-138 and TGS 2611 sensors to detect the level of volatile organic compounds gas emitted by palm trunks affected by ganoderma disease. The research results show that this system is capable of detecting ganoderma disease with a range of increased values on healthy palm plant samples: 0 - 5 values; moderate oil palm plants: 8 - 22 values; and on sick oil palm plants: 28 - 32 values. The system can also transmit data up to a range of 757.92 meters with an RSSI value of -105 dBm in conditions with minimal obstacles, and send and receive information from LoRa devices to Blynk IoT with an average time difference of 0.695 seconds for LoRa devices and 0.701 seconds for Blynk IoT.
Pre-Symptom Detector of Root Disease Palm Oil (Ganoderma) Trunk Based on LoRa and IoT Hadary, Ferry; Saziati, Ochih; Muhaimin, Ahmad Dzakiyuddin
Jurnal Rekayasa Elektrika Vol 20, No 2 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v20i2.35120

Abstract

The stem rot disease caused by the Ganoderma boninense is a type of disease that is deadly to oil palm plants and can cause a significant reduction in oil palm productivity. Difficulty in detecting disease infected oil palm plants is cause of the high risk of plan death due to the condition and risk of oil palm plants being affected by disease as early as possible. The system used is Long Range (LoRa) technology which utilizes radio frequencies as signal transmission between transmitter and receiver devices. The transmitter device is equipped with TGS 2611, MQ-138, MS1100 and TGS822 sensors as a tool for detecting ganoderma disease and is also equipped with a GPS sensor which functions to map trees affected by the disease. Meanwhile, the receiver as the recipient of the data that has been sent by the transmitter via LoRa will be forwarded to BIynk Apps via the internet network, thus forming an IoT (Internet of Things) system. This technology helps monitor oil palm plantations more efficiently because it can be monitored in real time on a smartphone application. The research results show that the four sensors can detect levels of volatile organic compounds (VOC) from ganoderma fungi with three classification; healthy, moderate and sick.
Co-Authors Hadary, Ferry Iman Suswanto Saziati, Ochih