Analisis efek curah hujan dan perbandingan metode ARIMAX-GARCH dan support vector regression berdasarkan prediksi harga beras pada tujuh kota di Pulau Jawa = Analysis of rainfall effects and comparison of ARIMAX-GARCH and support vector regression methods based on rice price forecasting in seven cities on Java Island

Sentosa, Yudiestira Dwi (2023) Analisis efek curah hujan dan perbandingan metode ARIMAX-GARCH dan support vector regression berdasarkan prediksi harga beras pada tujuh kota di Pulau Jawa = Analysis of rainfall effects and comparison of ARIMAX-GARCH and support vector regression methods based on rice price forecasting in seven cities on Java Island. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Salah satu aspek ketahanan pangan yang perlu ditingkatkan di Indonesia adalah dalam ketahanan sumber daya alam yaitu bagaimana cara pemerintah Indonesia melakukan penanggulangan saat terjadi anomali cuaca. Hal ini patut diperhatikan mengingat fakta bahwa Indonesia rentan terhadap perubahan iklim, sehingga dampaknya dapat berpengaruh negatif terhadap industri pertanian di Indonesia yang berakibat pada ketahanan pangan, terutama pada komoditas beras. Meningkatnya harga beras dapat memberikan dampak yang buruk bagi ekonomi dan kesejahteraan di masyarakat. Dalam menyelesaikan permasalahan tersebut, penelitian ini akan melakukan analisis dampak faktor cuaca pada harga beras. Kemudian akan dibuat nilai prediksi harga beras dengan menggunakan data harga beras dan faktor cuaca masa lalu dengan diambil sampel pada tujuh kota di Pulau Jawa. Berbagai metode telah dikembangkan untuk melakukan peramalan harga komoditas agrikultur dimulai dari metode peramalan tradisional sampai ke metode peramalan \textit{intelligent} dan dari model tunggal sampai ke model \textit{hybrid}. Pada penelitian kali ini akan dilakukan perbandingan metode peramalan tradisional menggunakan metode ARIMAX-GARCH dan metode peramalan \textit{intelligent} menggunakan metode \textit{support vector regression} (SVR) untuk melakukan peramalan pada harga beras dan kemudian membandingkan kinerja kedua model. Hasil korelasi yang diperoleh pada pemodelan regresi matematika adalah curah hujan cenderung memiliki pengaruh positif terhadap harga beras. Hasil yang diperoleh dari perbandingan metode prediksi adalah metode SVR lebih baik dalam memprediksi sebagian besar harga beras serta lebih baik dalam mendeteksi pergerakan harga beras. / One aspect of food security that needs to be improved in Indonesia is the resilience of natural resources, namely how the Indonesian government takes countermeasures when weather anomalies occur. This action is noteworthy considering that Indonesia is vulnerable to climate change, so the impact could negatively affect the agricultural industry in Indonesia, which results in food security, especially in the rice commodity. Increasing rice prices can harm the economy and the welfare of society. In solving this problem, this research will analyze the impact of weather factors on rice prices. Then a rice price prediction value will be created using rice price data and past weather factors taken from a sample of seven cities on the island of Java. Various methods have been developed to forecast agricultural commodity prices, from traditional to intelligent forecasting methods and from single to hybrid models. This study will compare traditional forecasting methods using the ARIMAX-GARCH method and the intelligent forecasting method using the support vector regression (SVR) method to forecast rice prices and then compare the performance of the two models. The correlation results obtained in the mathematical regression modeling show that rainfall tends to have a positive effect on rice prices. The results of the comparison of prediction methods are that the SVR method is better at predicting most rice prices and detecting rice price movements.

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