Skripsi/Tugas Akhir
Analisis Forecasting Penjualan Motor & Alat-Alat Trail Kawasaki di Toraja Menggunakan Metode Single Exponential Smoothing (SES) & Double Exponential Smoothing (DES)
ABSTRAK
Analisis Forecasting Penjualan Motor & Alat-Alat Trail Kawasaki Di Toraja Menggunakan Metode Single Exponential Smoothing (Ses) & Double Exponential Smoothing (Des) merupakan penelitian yang bertujuan untuk menganalisis Forecasting (peramalan) penjualan motor dan alat-alatnya dengan menggunakan metode single exponential smoothing (SES) dan Double Exponential Smoothing (DES). Selain itu, penelitian ini juga memiliki output yaitu aplikasi penjualan motor dan alat-alat trail Kawasaki di Toraja sehingga memberikan keuntungan bagi perusahaan Kawasaki. Analisis forecasting dengan menggunakan metode SES dan DES dilakukan dengan perhitungan melalui Microsoft Excel dan SPSS. Diharapkan dengan adanya penelitian ini dapat memantau aktivitas penjualan perusahaan dengan baik.
Kata Kunci: Forecasting, Single Exponential Smoothing, Double Exponential Smoothing
ABSTRACT
Analysis of Forecasting Sales of Kawasaki Trail Motorcycles & Tools in Toraja Using the Single Exponential Smoothing (Ses) & Double Exponential Smoothing (Des) Method is a study that aims to analyze Forecasting (forecasting) sales of motorcycles and tools using the single exponential smoothing (SES) and Double Exponential Smoothing (DES) methods. In addition, this research also has an output, namely the application of motorcycle sales and Kawasaki trail equipment in Toraja so as to provide benefits for the Kawasaki Company. The forecasting analysis using the SES and DES methods is done by calculating through Microsoft Excel and SPSS. It is hoped that this research can monitor the company's sales activities properly.
Keywords: Forecasting, Single Exponential Smoothing, Double Exponential Smoothing
Tidak ada salinan data
Universitas DIPA Makassar
NPP 7371142D1000002
Jln. Perintis Kemerdekaan KM.9
Telp. (0411)587194
Hotline: +6281228221994
WhatsApp Admin: +6281342092072
e-Mail: [email protected]
© 2024 — Perpustakaan UNDIPA Makassar - SLiMS