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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

IoT-based Soil Nutrient Monitoring and Control Using Fuzzy Logic and Multi-Modal Sensor Integration Hakis, Andi Wahyunita; Arda, Abdul Latief; Jalil, Abdul
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10575

Abstract

The decline in soil quality due to inappropriate agricultural practices has become one of the main factors contributing to reduced agricultural productivity. The primary focus of this research is on monitoring and controlling soil nutrient quality, particularly in clay soil used for chili cultivation. This study aims to develop an Internet of Things (IoT)-based monitoring system integrated with multi-modal sensors and fuzzy logic algorithms. The system is designed to support precision agriculture by enabling automated decision-making based on real-time environmental data. The research uses an experimental approach, involving the design of a system based on the ESP32 microcontroller, sensor data processing using the Mamdani fuzzy algorithm, and integration with the Blynk platform for remote monitoring and control. The system responds to changes in environmental conditions to determine optimal timing for irrigation and liquid nutrient application adaptively. The test results show that the system achieved a classification accuracy of 84% and an average F1-score of 88.5%, indicating its effectiveness in handling continuous and uncertain sensor data. Evaluation of the fuzzy logic performance revealed a 75.8% success rate in irrigation control and 99.8% accuracy in nutrient delivery, demonstrating the system’s ability to respond accurately and efficiently to actual soil and environmental conditions. With its stable, adaptive, and resource-efficient performance, this system has the potential to become a practical solution for automating irrigation and fertilization processes in support of technology-driven and sustainable agriculture.
Smart Waste Management Monitoring and Control Analysis Based on Objects Based on Smart Systems and Internet of Things Sarmila, Sarmila; Achmad, Andani; Arda, Abdul Latief
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11281

Abstract

Garbage is a problem that often becomes a trending topic in almost every country.throughout developing countries. The current condition of waste in our environment is still in a mixed condition, because the garbage has not been sorted. The minimum waste management information technology by officers also causes Waste management is slow, so that waste often piles up.The aim of this research is to develop a smart trash can that can sort metal, dry and wet waste automatically via Internet function of Things (IoT). The methodology used is Research and Development which can provide information when the trash can is full. This research was successful designing and implementing a prototype of a smart trash can based onInternet of Things (IoT) with the ability to sort waste into three categories The main components are metal, wet, and dry. The system utilizes proximity sensors inductive, soil sensor, and ultrasonic sensor HC-SR04 integrated with Blynk application for real-time monitoring of waste capacity. Algorithm Fuzzy logic is used so that the system is able to make adaptive decisions according to with the sensor condition. from the performance in the research Where the Accuracy of the system is 97.10%. The calculation is based on the number of correct predictions on the diagonal. main data divided by total data: true = 189 (Dry) + 187 (Wet) + 194 (Metal) = 570 out of a total of 587 samples, so 570/587 = 0.9710 (97.10%), with 17 error (error rate 2.90%). These values describe how much the accuracy and completeness of the model in recognizing each category of waste, with results consistently high (average 0.97).