Henni Melisa
Universitas Islam Negeri Sumatera Utara, Medan

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Prediksi Hasil Panen Pertanian Salak di Daerah Tapanuli Selatan Menggunakan Algoritma SVM (Support Vector Machine) Rakhmat Kurniawan; Aidil Halim; Henni Melisa
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1246

Abstract

South Tapanuli is an area known for its extensive salak farming. Salak farming in the South Tapanuli area is one of the economic sources of the people in the South Tapanuli area. The South Tapanuli Regional Agriculture Office is an agency engaged in various fields of agriculture, in its annual activity it records the results of salak agricultural production. Salak agricultural production results that are obtained often experience changes, so we need a system to make predictions, the goal is to find out the yield of salak farming. With the application of the SVM (Support Vector Machine) algorithm, it has been successfully carried out with a total of 28 data on salak agricultural yields in the South Tapanuli Region year 2019 - 2020. The error rate obtained from the RMSE (Root Mean Square Error) in making the prediction model is 1,49 while the accuracy level is 44%