FAHADA, WIDY SANRA (2023) PREDIKSI PENJUALAN PAKAIAN MUSLIM MENGGUNAKAN ALGORITMA C 4.5 DAN REGRESI LINEAR PADA TOKO FARHAN. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This study aims to develop a sales data prediction model using Machine Learning methods. Sales are crucial indicators in the business world as they provide insights into company performance, market trends, and support better decisionmaking. However, accurately and reliably predicting sales data is often a complex challenge. In this study, the researchers collected historical sales data from Toko Farhan, which included information about time, products, categories, and prices. The research also aimed to apply data mining techniques to predict the sales of Muslim clothing at Farhan Store using the Linear Regression algorithm and the C4.5 algorithm. Prediction methods were utilized in this research, and the calculations were performed using Google Collab. The results of the study for predicting the sales of Robes at Farhan Store showed that the best-selling item during the sales period from January to July 2022 was Sabiyan robes, making it the top-selling item or the Best Seller at Farhan Store. The evaluation of prediction performance in this study employed the Mean Absolute Error (MAE), Mean Squared Error (MSE), and R2 Score parameters. For the Linear Regression algorithm, the MAE was found to be 43,633.21, the MSE was 4,005,924,352.66, and the R2 Score was 0.94. On the other hand, the C4.5 algorithm yielded a MAE of 44,823.96, an MSE of 50,233,775.14, and an R2 Score of 0.94. Keywords: Prediction, Data Mining, C4.5 algorithm, Linear Regression algorithm Penelitian ini bertujuan untuk mengembangkan model prediksi data penjualan menggunakan metode Machine Learning. Penjualan merupakan indikator penting dalam dunia bisnis karena dapat memberikan informasi tentang kinerja perusahaan, tren pasar, dan mendukung pengambilan keputusan yang lebih baik. Namun, prediksi yang akurat dan dapat diandalkan mengenai data penjualan sering kali menjadi tantangan yang kompleks. Dalam penelitian ini, peneliti mengumpulkan data historis penjualan dari Toko Farhan yang mencakup informasi tentang waktu, produk, kategori, dan harga. Penelitian ini juga bertujuan untuk menerapkan teknik data mining dalam memprediksi penjualan baju muslim di Toko Farhan menggunakan algoritma C4.5 dan algoritma Regresi Linear. Metode prediksi digunakan dalam penelitian ini, dan perhitungan dilakukan menggunakan Google Colab. Hasil penelitian yang telah dilakukan untuk memprediksi penjualan Baju Gamis di Toko Farhan menunjukkan bahwa item terlaris selama periode penjualan bulan Januari - Juli 2022 adalah Gamis Sabiyan, menjadi item yang paling banyak terjual atau dapat dikatakan sebagai item Best Seller di Toko Farhan. Dalam penelitian ini, digunakan parameter MAE (Mean Absolute Error), MSE (Mean Squared Error), dan R2 Score untuk mengevaluasi performa prediksi. Pada algoritma Regresi Linear, diperoleh nilai MAE sebesar 43,633.21, nilai MSE sebesar 4,005,924,352.66, dan nilai R2 Score sebesar 0.94. Sedangkan pada algoritma C4.5, diperoleh nilai MAE sebesar 44,823.96, nilai MSE sebesar 50,233,775.14, dan nilai R2 Score sebesar 0.94. Kata Kunci: Prediksi, Data Mining, Algoritma C 4.5, Algoritma Regresi Linear
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