AJITH, AJITH (2024) PREDIKSI TINGKAT PENJUALAN DAN STRATEGI MENGGUNAKAN METODE FORECASTING DENGAN ALGORITMA REGRESI LINEAR BERGANDA UNTUK INTERPRETASI BISNIS. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The fashion industry is one of the business sectors that constantly keeps up with the times. The rapid change in trends and high demand makes this sector extremely dynamic and quick to evolve. Fashion businesses must have the capability to predict these swift trend changes and fluctuating demands. Given these challenges, it is essential to identify key aspects and make predictions and strategies each year. This research utilizes forecasting methods with the Multiple Linear Regression Algorithm. The Multiple Linear Regression Algorithm aims to determine the regression equation values using SPSS 26 tools. After obtaining this equation, manual calculations are performed to find prediction values for the years 2023 and 2024. This research uses four independent variables: Promo Code (X1), Mastercategory (X2), Shipment Fee (X3), and Gender (X4), and one dependent variable: Quantity (Y). Based on the calculations of the Multiple Linear Regression Algorithm, the calculated F-value is 28740.357 with a significant value of 0.000, indicating a significant simultaneous influence between all the independent variables X1, X2, X3, and X4 on the dependent variable Y, with an MAE value of 3427 and a MAPE value of 10.808 or 10%. The results of this study predict sales for the year 2023 to be 286032 and for 2024 to be 260029. The strategy implemented is to add a new promo code "ASIK21" to the category with the lowest sales, which can increase sales by approximately 13% from the previous sales, thus this promo can be applied to all categories to boost sales in the following year. Keywords : Business, Fashion Industry, Linear Regression, Trend changes, Prediction Industri Fashion adalah salah satu sektor bisnis yang selalu mengikuti perkembangan zaman. Perubahan tren dan tingginya permintaan menjadikan sektor ini paling dinamis dan berubah dengan cepat. Bisnis fashion harus memiliki kemampuan dalam melakukan prediksi terhadap perubahan tren yang cepat dan permintaan yang fluktuatif. Dari permasalahan tersebut, maka perlu mencari aspekaspek kunci juga adanya prediksi dan strategi setiap tahunnya. Penelitian ini menggunakan metode forecasting dengan Algoritma Regresi Linear Berganda. Algoritma Regresi Linear Berganda bertujuan untuk mencari nilai persamaan regresi dengan menggunakan tools SPSS 26. Setelah mendapatkan persamaan tersebut dilakukan perhitungan manual untuk menemukan nilai prediksi untuk tahun 2023 dan 2024, dalam penelitian ini menggunakan 4 variabel independen yaitu Promo Code (X1), Masterkategori (X2), Shipment Fee (X3), dan Gender(X4) dan 1 variabel dependen yaitu Quantity (Y). Berdasarkan perhitungan Algoritma Regresi Linear Berganda ditemukan hasil nilai
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