Classification System for Soil Types Suitable for Food Crops using Naïve Bayes Method

Abstract

Agriculture in Indonesia, especially in Aceh, plays a central role in supporting the economy and food security. The success of agriculture is greatly influenced by the selection of appropriate soil types. This research aims to develop a classification system for soil types suitable for food crops by applying the Naive Bayes algorithm to help farmers choose the right type of soil. The steps taken in this research are literature study, observation, interviews, data collection, system design and system implementation. In this study, the variables / criteria used include pH, humidity, drainage, soil texture, and nutrients, as input to provide recommendations for the most suitable soil type. By dividing the data into 70% training data and 30% testing data, the system achieved an accuracy rate of 83.3%. The results of the testing data used in this study were obtained in areas suitable for planting all three types of food, namely kong, tetinggi, Blangbengkik, Gantung Geluni, Porang Ayu, Anak Reje and Bener Baru. While the area that is only suitable for planting one type of food crop is Cinta Maju.