Prediksi Harga Jagung Menggunakan Support Vector Machine dengan Fitur Seleksi Forward Selection di Kabupaten Pohuwato - Drajana, Ivo Colanus Rally; Betrisandi, Betrisandi (Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI), 2024)
Abstrak - Kabupaten Pohuwato yang terletak di bagian paling barat Provinsi Gorontalo merupakan salah satu daerah penghasil jagung terbesar. Menurut Kementerian Pertanian, luas lahan perkebunan di Kabupaten Pohuwato seluas 87.104 hektare dimanfaatkan warga untuk menanam jagung. Jagung merupakan salah satu komoditas tanaman pangan utama sebagai sumber karbohidrat sehingga harga jagung menjadi perhatian penting bagi pemerintah, namun harga jagung berfluktuasi. Solusi yang diberikan pada penelitian ini adalah prediksi harga jagung di masa depan dengan menggunakan Algoritma Support Vector Machine dengan Fitur Forward Selection yang dapat memberikan solusi tepat bagi petani perkebunan, pedagang dan pemerintah. Dari hasil percobaan yang telah dilakukan, prediksi harga jagung menggunakan algoritma support vector machine dengan fitur forward seleksi telah berhasil dilakukan. Hasil RMSE sebesar 0.682 terdapat pada algoritma support vector machine yang menggunakan fitur forward seleksi, hasil ini dinyatakan lebih baik dibandingkan tanpa menggunakan fitur seleksi.Kata kunci: Prediction, Corn Price, Support Vector Machine, Forward Selection Abstract - Pohuwato Regency, which is located in the westernmost part of Gorontalo Province, is one of the largest corn producing areas. According to the Department of Agriculture, the area of plantation land in Pohuwato Regency, which is 87,104 hectares, is used by residents to grow corn. Corn is one of the main food crop commodities as a source of carbohydrates so that the price of corn is an important concern for the government, but the price of corn fluctuates. The solution provided in this study predicts future corn prices using the Support Vector Machine Algorithm with the Forward Selection Feature which can provide the right solution for plantation farmers, traders and the government. From the results of the experiments that have been carried out, the prediction of corn prices using the support vector machine algorithm with the forward selection feature has been successfully carried out. The RMSE result of 0.682 is found in the support vector machine algorithm that uses the forward selection feature, this result is stated to be better than without using the selection feature.Kata kunci: Prediction, Corn Price, Support Vector Machine, Forward Selection