COAL DEMAND PREDICTION MODEL USING MACHINE LEARNING METHODS

Forecasting coal demand needs is important to minimize operational costs. Forecasting will help companies determine the right amount and time to order coal from suppliers. Research on coal forecasting in Indonesia generally uses a statistical approach and has not analyzed the performance of other forecasting models. This research aims to forecast coal demand using statistical and machine learning methods, namely ARIMA, Exponential Smoothing, Support Vector Regression (SVR), Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM). The evaluation methods used to analyze forecasting performance are Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The new coal demand data used is 1097 daily data taken from January 2021 to December 2022 in the form of a timeseries and is stationary which has been tested using Augmented Dickey-Fuller (ADF). The test results show that the ARIMA model has MAPE value of 5.11%, MAE 2.91 and R-Square 0.925, Exponential Smoothing MAPE 1.07%, MAE 0.55 and R-Square 0.997, SVR with MAPE value of 5.48%, MAE 3.16 and R-Square 0.88, RNN with MAPE value of 5.19%, MAE 2.91 and R-Square 0.896, LSTM with MAPE value of 4.83%, MAE 2.84 and R-Square 0.897. From the test results it was found that exponential smoothing had the smallest error values among the other models. With forecasting results that have a small error rate, it can help management in making decisions to minimize costs in coal ordering and warehouse management

Aplikasi Theory Of Planned Behavior Terhadap Niat Beli Produk Skincare Halal Pada Gen Z

The halal industry has a strategic role in improving the economy. Halal certificates are an important factor in skincare products. The aim of the research is to analyze the influence of attitudes, subjective norms and behavioral control on halal skincare products on Gen Z. The population in this study is generation Z in Semarang City and the sample taken was 205 respondents. The sampling technique used was a purposive sampling technique. The analysis technique in the research uses multiple linear regression analysis with the help of SPSS version 26. The results of this research show that attitude has no effect on the intention to buy halal skincare products. Meanwhile, norms and behavioral control have a positive and significant effect on the intention to purchase halal skincare products. Keywords: attitude; subjectivtive norms; behavior control;purchase intentio

OPTIMISME TOKOH UTAMA WANITA DALAM SERIAL METEOR GARDEN

OPTIMISME TOKOH UTAMA WANITA DALAM SERIAL METEOR GARDEN