Metode Regresi yang Tepat Untuk Meramalkan Permintaan Minyak Solar di Kabupaten Sumbawa
Abstract
Abstract. This study aims to find the proper regression method to predict the amount of demand for fuel oil in the form of diesel fuel in Sumbawa Regency. The data needed for this research are data on the amount of monthly diesel oil demand in 2018. The data were analyzed by various regression methods to predict the number of requests as the dependent variable ( ) influenced by the month of demand as a independent variable ( ). The four methods chosen for analysis are linear, quadratic, cubic, exponential and logarithmic regression. The selection of the proper regression method predicts the case in this study based on the coefficient of determination ( ) and the data processing using SPSS. The results of the study show that the right method for forecasting diesel oil demand in 2019 is to use cubic regression methods.
Keywords: Forecasting, Regression Method, Determinant Coefficient, Solar Oil.
Abstrak. Penelitian ini bertujuan untuk menentukan metode regresi yang tepat untuk meramalkan jumlah permintaan bahan bakar minyak (BBM) berupa solar di Kabupaten Sumbawa. Data yang diperlukan untuk penelitian ini adalah data jumlah permintaan minyak solar perbulan pada tahun 2018. Data tersebut dianalisis dengan berbagai metode regresi untuk meramalkan jumlah permintaan sebagai variabel terikat ( ) dipengaruhi oleh bulan permintaan sebagai varibel bebas ( ). Empat metode yang dipilih untuk dianalisis adalah regresi linier, kuadratik, kubik, eksponensial dan logaritmik. Pemilihan metode regresi yang tepat meramalkan kasus pada penelitian ini berdasarkan nilai koefisien determinasi ( ) dan pengolahan datanya menggunakan SPSS. Hasil penelitian menunjukkan bahwa metode yang tepat untuk meramalkan permintaan minyak solar pada tahun 2019 adalah dengan menggunakan metode regresi kubik.
Keywords: Peramalan, Metode Regresi, Koefisien determinan,Minyak Solar.
References
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