BANADOTAMA, IVAN BONTOR (2023) PERBANDINGAN ALGORITMA C4.5 DAN REGRESI LINEAR UNTUK PREDIKSI DATA PENJUALAN KOPI. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This study uses the C 4.5 algorithm and linear regression in predicting coffee sales at the Ardilia Coffeehouse to ensure stock is always available and customer needs are met. This study aims to apply data mining in predicting coffee sales at Ardilia Coffeehouse using the C 4.5 algorithm and a linear regression algorithm. The method used in this study uses the prediction method. The results of this study were obtained using Google Colab. This study uses the parameters MAE (Mean absolute error), MSE (mean squared error) and R2 score. The test uses the linear regression algorithm and C 4.5 with the MAE, MSE, and R2 Score parameters to get standard results. In the linear regression algorithm, the MAE value is 43391.14, the MSE value is 3325365012.56, and the R2 score is 0.63. Whereas in algorithm C 4.5 the MAE value is 45009.37, the MSE value is 3666775517.61 and the R2 score is 0.60. Keywords: prediction, data mining, linear regression, C4.5. Penelitian ini menggunakan algoritma C 4.5 dan regresi linear dalam memprediksi penjualan kopi pada Ardilia Coffeehouse untuk memastikan stok selalu tersedia dan kebutuhan customer terpenuhi. Penelitian ini bertujuan untuk menerapkan data mining dalam memprediksi penjualan kopi pada Ardilia Coffeehouse menggunakan algoritma C 4.5 dan algoritma regresi linear. Metode yang digunakan pada penelitian ini menggunakan metode prediksi. Hasil penelitian ini didapatkan dengan menggunakan Google Colab. Penelitian ini menggunakan parameter MAE (Mean absolute error), MSE (mean squared error) dan R2 score. Pengujian menggunakan algoritma regresi linear dan C 4.5 dengan parameter MAE, MSE, dan R2 Score mendapatkan hasil yang standar. Pada algoritma regresi linear nilai MAE 43391.14, nilai MSE 3325365012.56, dan R2 Score 0.63. Sedangkan pada algoritma C 4.5 nilai MAE 45009.37, nilai MSE 3666775517.61 dan nilai R2 Score 0.60. Kata Kunci : prediksi, data mining, regresi linear, C4.5.
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