Arkham, Muhammad Zeinur Rosyid (2024) Peramalan Data Statistik Wisatawan Domestik Kota Malang Menggunakan Metode Single Exponential Smoothing Dan Single Moving Average. Undergraduate thesis, Fakultas Teknologi Informasi Universitas Merdeka Malang.

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Abstract

Malang City, as one of the main tourist destinations in Indonesia, faces challenges in anticipating the number of domestic tourists who will visit. This variability can be caused by many factors, including seasonality, market trends, and government policies. These methods are used to estimate market demand, allowing companies to make more informed business decisions. (Arif et al., 2023). The tourism industry is a field of tourism that plays a large economic role and continues to grow. The number of tourists who come to Malang, one of the most popular tourist destinations in Indonesia, varies every year. This research was conducted to find out how accurate and progress is in predicting changes in data fluctuations that will occur in the future. Variations in the approach used are the Single Moving Average and Single Exponential Smoothing forecasting methods. In this research, the data used comes from the official website of the BPS (Badan Pusan Statistics) Malang City. The data in this research is the number of Malang City Domestic Tourists with a span of 3 years from January 2021 to December 2022. The comparison results show that Single Exponential Smoothing shows a forecasting result with α=0.9 in the next period of 290106 and gets a MAPE of 20 % tends to provide more accurate forecast results compared to the Single Moving Average, resulting in forecasting for the next period of 261103 with a MAPE calculation = 22%. especially in dealing with complex data trends and patterns

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