Application of Forecasting Methods to Predict Sukuk Assets in Indonesia

Abstract

This study aims to predict the development of total sukuk assets in Indonesia using a quantitative approach based on time series forecasting. The data used is secondary data on total Indonesian sukuk assets for the period 2002–2018 sourced from the Financial Services Authority (OJK). Three forecasting methods were used, namely Trend Analysis (regress over time), Multiplicative Decomposition, and Exponential Smoothing with Trend, with the help of POM-QM version 3 software. The results show that total sukuk assets in Indonesia experienced a significant growth trend during the observation period. Based on an accuracy evaluation using Mean Absolute Percent Error (MAPE), the Exponential Smoothing with Trend method produced the lowest error rate compared to the other two methods, making it the most reliable method for predicting Indonesian sukuk assets. These findings have important implications for regulators and market participants in formulating policies and strategies for developing the sukuk market in Indonesia.