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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Mohamad Choirul Zamzami
Politeknik Statistika STIS
Computer Science & IT

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Nowcasting of Chili Pepper (Capsicum frutescens L.) Prices in East Java Province Using Multi-Layer Perceptron Method Mohamad Choirul Zamzami; Nucke Widowati Kusumo Projo
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2023 No. 1 (2023): Proceedings of 2023 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2023i1.274

Abstract

The aims of study is to predict the price of chili pepper at the provincial level in East Java by looking for the best input variable from three types of input variables, price of chili pepper at the regency and city levels, natural factors, and word search index on Google Trends as an approach to the causes of chili pepper price fluctuations. The Multi-Layer Perceptron method, accompanied by a search for the best combination of model parameters is selected to get the model with the best nowcasting ability. The result shows that the best model for nowcasting is characterized by: the input variable is price of chili pepper at the regency and city levels with three hidden layers and 32, 45, and 51 neurons in each hidden layer, maximum iteration is 200 iterations, maximum iteration when the model not increase in performance for applying early stopping is 20 iterations, non-linear activation used is RELU (Rectified Linear Unit), and optimization function used is ADAM optimizer. The accuracy of nowcasting in this study is highly accurated with MAPE smaller than 10%.
Co-Authors Nucke Widowati Kusumo Projo