Analysis and Forecasting of the Training Participants Number Using Time Series Method (A Case Study at XYZ Company)

Analisis dan Peramalan Jumlah Peserta Pelatihan Menggunakan Metode Time Series (Studi Kasus Di Perusahaan XYZ)

Abstract

Forecasting the number of training participants is an important aspect for training service companies in supporting operational planning and achieving annual targets. XYZ Company as a training service provider faces fluctuating participant demand conditions. This case study aims to analyze and determine..the best forecasting method in predicting the number of training participants using a Time Series approach. The methods used include Moving Average, Weighted Moving Average, and Single Exponential Smoothing using POM-QM (Production/Operations Management, Quantitative Methods) software for Windows. The data used is historical data on the number of training participants for 12 months, namely the period December 2024 to November 2025. The performance assessment of the forecasting method is carried out by referring to several error indicators such as MAD (Mean Absolute Deviation), MSE (Mean Squared Error), MAPE (Absolute Percentage Error), and Standard Error. Based on the analysis results, the Moving Average method shows the lowest error rate compared to other forecasting methods, with a MAPE value of 35.557% and the forecasting results for the next period are 843 participants. Thus, the Moving Average method is considered the most effective for use in forecasting the number of training participants at XYZ Company. It is hoped that the forecasting results produced can be used as material for consideration by the company in determining decisions, managing resources, and increasing operational efficiency.