Abstract. Sales is a major factor in supporting the viability of a company. Therefore, the company must be able to determine policies related to sales activities undertaken by the company. To deal with sales issues to fit the company's target, a sales forecasting is required. One of the methods that can be used is forecasting. This study aims to reduce the error of CCTV sales forecasting using Adjusted Exponential Smoothing method and the smallest error indicator MAD, MSE, MAPE, MAPD, SE, and Tracking Signal. The author in preparing this thesis using this type of descriptive research is powerful. The data used is historical data for 12 months in 2017. Data collection techniques conducted are interviews to the company and conducted a direct observation to the company. The results in this study show that to determine the best α and β based on the smallest error is in the error MAD, MSE, MAPE, and Standard Error. Where from the data the smallest value is at α = 0,1 and β = 0,2 with result of forecasting 558,68 or 559.Keywords: Forecasting, Adjusted Exponential Smoothing. Abstrak. Penjualan merupakan faktor utama dalam menunjang kelangsungan hidup dalam suatu perusahaan. Oleh karena itu perusahaan harus mampu dalam menentukan kebijakan-kebijakan yang berhubungan dengan aktivitas penjualan yang dilakukan oleh perusahaan. untuk menangani masalah penjualan agar sesuai target perusahaan, maka diperlukan adanya sebuah peramalan penjualan. Salah satu metode yang dapat digunakan adalah forecasting. Penelitian yang dilakukan ini bertujuan untuk mengurangi kesalahan peramalan penjualan CCTV dengan menggunakan metode Adjusted Exponential Smoothing dan indikator kesalahan terkecil MAD, MSE, MAPE, MAPD, SE, dan Tracking Signal. Penulis dalam menyusun skripsi ini menggunakan jenis penelitian deskriptif kuatitatif. Data yang digunakan yaitu data historis selama 12 bulan pada tahun 2017. Teknik pengumpulan data yang dilakukan adalah wawancara terhadap pihak perusahaan dan mengadakan observasi langsung ke perusahaan. Hasil yang didapat pada penelitian ini menunjukkan bahwa untuk menentukan α dan β terbaik berdasarkan error terkecil berada pada error MAD, MSE, MAPE, dan Standard Error. Di mana dari data tersebut nilai terkecil berada pada α = 0,1 dan β = 0,2 dengan hasil peramalan 558,68 atau 559.Kata Kunci : Peramalan, Adjusted Exponential Smoothing.
Abstract. Sales is a major factor in supporting the viability of a company. Therefore, the company must be able to determine policies related to sales activities undertaken by the company. To deal with sales issues to fit the company's target, a sales forecasting is required. One of the methods that can be used is forecasting. This study aims to reduce the error of CCTV sales forecasting using Adjusted Exponential Smoothing method and the smallest error indicator MAD, MSE, MAPE, MAPD, SE, and Tracking Signal. The author in preparing this thesis using this type of descriptive research is powerful. The data used is historical data for 12 months in 2017. Data collection techniques conducted are interviews to the company and conducted a direct observation to the company. The results in this study show that to determine the best α and β based on the smallest error is in the error MAD, MSE, MAPE, and Standard Error. Where from the data the smallest value is at α = 0,1 and β = 0,2 with result of forecasting 558,68 or 559.