Predicting Chili Pepper Diseases using a Decision Tree in an Android-Based Internet of Things (IOT) Monitoring System

Novenda Putra Linarta  Sitepu; Relita  Buaton; Magdalena  Simanjuntak

doi:10.59934/jaiea.v5i3.2497

Authors

Novenda Putra Linarta Sitepu STMIK Kaputama
Relita Buaton STMIK KAPUTAMA
Magdalena Simanjuntak STMIK KAPUTAMA

DOI:

https://doi.org/10.59934/jaiea.v5i3.2497

Keywords:

Android, CART, Internet of Things, Microclimate, Chili Plants.

Abstract

Chili pepper plants are susceptible to diseases caused by changes in the microclimate, making a data-driven monitoring system essential. This study designed an Internet of Things (IoT) system to monitor the microclimate and predict disease risks in chili pepper plants via an Android app. The system uses an ESP32 connected to a DHT22 sensor, a capacitive soil moisture sensor, a BH1750 sensor, a rain sensor, and a DS3231 RTC. Data on air temperature, air humidity, soil moisture, light intensity, and rainfall conditions are sent to the Firebase Realtime Database via WiFi in real-time. Predictions are made using the CART Decision Tree algorithm with low, medium, and high risk classifications. Test results show that the model achieved an accuracy of 95%, precision of 96%, recall of 95%, and an F1-score of 95%, with 19 out of 20 test data points correctly classified. This system helps farmers make cultivation decisions more quickly and objectively based on actual environmental conditions in chili farming fields.

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