Implementasi Algoritme C4.5 untuk Prediksi Penanaman Cabai Merah - Muhammad Syam Firdaus; Aji Primajaya; Asep Jamaludin (Universitas Indraprasta PGRI Jakarta, 2021)
Chili has been the most widely grown plant in Indonesia because it can bear fruit and grow in the highlands and the lowlands. Every year the market demand for chili continues to increase, even the annual price of chili tends to increase as a result of reduced chili supply and less fulfilled market demand. Besides, the crop failure experienced by chili farmers cause inflation growth in 2020 as much as 0.31%, resulting from rising prices in the food sector, including the price of cayenne pepper and red chili. The fluctuations in chili prices are strongly influenced by weather, harvest season, trade policies and the accompanying momentum. According to the background, the purpose of this study is to predict chili planting using the C4.5 algorithm. First, the researchers collect weather and price data taken from DISPERINDAG, BMKG, use chili price data on the market as a dataset to be later preprocessed to eliminate missing values, data outliers and imbalance data and then make a model that can predict chili planting. The prediction results using the rule from the decision tree have an accuracy rate of 97.8% based on the calculation of the prediction using validation data as much as 95 data