Abstract
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, t he 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
Highlights
Tanaman cabai menjadi tanaman yang paling banyak ditanam di Indonesia, karena tanaman ini dapat berbuah dan tumbuh di dataran tinggi maupun di dataran rendah
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 Keywords : Chili Planting Prediction, C4.5 Algorithm, Classification, Data Mining
Summary
Tanaman cabai menjadi tanaman yang paling banyak ditanam di Indonesia, karena tanaman ini dapat berbuah dan tumbuh di dataran tinggi maupun di dataran rendah. Cabai yang rusak atau busuk dapat mengakibatkan kegagalan panen yang dialami oleh para petani cabai. Kegagalan panen yang dialami para petani cabai menyebabkan pertumbuhan inflasi di tahun 2020 sebanyak 0,31% disumbang oleh naiknya harga di sektor pangan, termasuk di dalamnya cabai rawit dan cabai merah. Perubahan cuaca ataupun iklim dapat mempengaruhi produksi cabai setiap tahunnya seperti penelitian yang telah dilakukan oleh Ridho (2020) dalam penelitiannya pada petani cabai di Kota Malang, Kecamatan Pakis. Cuaca menjadi salah satu penyebab besar yang mempengaruhi keberhasilan dalam budidaya tanaman cabai, pertumbuhan tanaman cabai akan baik jika petani cabai dapat mempersiapkan ladangnya seperti pengairan, bedengan dan jenis cabai sesuai dengan cuacanya. Data cuaca yang digunakan menggunakan data penelitian sebelumnya oleh Rosdiana & Rismayana (2018) yaitu data tahun 2011-2018 dan data terbaru dari tahun 2019 sebagai data tambahan untuk wilayah Bandung. Berdasarkan permasalahan tersebut, penelitian untuk memprediksi penanaman cabai dibutuhkan sehingga diambillah judul penelitian “Implementasi Algoritme C4.5 dalam Memprediksi Penanaman Cabai Merah”
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