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Prediction of Land Area Harvest, Production, Rice Productivity: A Accuracy Analysis of ARIMA Methods
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Abstract: This study aims to find out the best forecasting model with ARIMA method. The data used by this study is the area of harvest, production and productivity in East Java Province in 2000-2020. Data analysis used is ARIMA method with accuracy parameters used namely MSE, MAPE, and MAD. The results showed that (1) the error rate of ARIMA method in the harvest area, MAD value of 1,013,810,484; MSE value of 16,484,292,627,223; MAPE value of 48.25; (2) ARIMA method error rate in Production, MAD value of 5,975,703,193, MSE value of 5,886,684,845,403,590, MAPE value of 54.60; (3) the last error of ARIMA method in productivity, MAD value of 14,705, MSE value of 39,969, MAPE value of 25.62. The simulation results showed that of the four mathematical models that became the output of G-MFS, the 1st mathematical model became the best model in determining the prediction results due to smaller error parameters with a predicted planting area of 1,728,503 m2, a production rate of 9.609057 tons, and a productivity of 57.145% Abstrak: Penelitian ini bertujuan untuk mengetahui model peramalan terbaik dengan metode ARIMA. Data yang digunakan penelitian ini adalah luas panen, produksi dan produktivitas di Provinsi Jawa Timur Tahun 2000-2020. Analisis data yang digunakan adalah metode ARIMA dengan Parameter akurasi yang digunakan yaitu MSE, MAPE, dan MAD. Hasil penelitian menunjukkan bahwa (1) tingkat kesalahan metode ARIMA di luas panen, nilai MAD sebesar 1.013.810.484; nilai MSE sebesar 16.484.292.627,223; nilai MAPE sebesar 48,25; (2) tingkat kesalahan metode ARIMA di Produksi, nilai MAD sebesar 5.975.703,193, nilai MSE sebesar 5.886.684.845.403,590, nilai MAPE sebesar 54,60; (3) terakhir kesalahan metode ARIMA di produktivitas, nilai MAD sebesar 14,705, nilai MSE sebesar 39,969, nilai MAPE sebesar 25,62. Hasil simulasi menunjukkan bahwa dari empat model matematika yang menjadi output G-MFS maka model matematika ke-1 menjadi model terbaik dalam menentukan hasil prediksi karena parameter error yang lebih kecil dengan hasil prediksi luas tanam sebesar 1.728.503 m2, tingkat produksi 9.609057 ton, dan produktivitas sebesar 57,145%
Universitas Muhammadiyah Mataram
Title: Prediction of Land Area Harvest, Production, Rice Productivity: A Accuracy Analysis of ARIMA Methods
Description:
Abstract: This study aims to find out the best forecasting model with ARIMA method.
The data used by this study is the area of harvest, production and productivity in East Java Province in 2000-2020.
Data analysis used is ARIMA method with accuracy parameters used namely MSE, MAPE, and MAD.
The results showed that (1) the error rate of ARIMA method in the harvest area, MAD value of 1,013,810,484; MSE value of 16,484,292,627,223; MAPE value of 48.
25; (2) ARIMA method error rate in Production, MAD value of 5,975,703,193, MSE value of 5,886,684,845,403,590, MAPE value of 54.
60; (3) the last error of ARIMA method in productivity, MAD value of 14,705, MSE value of 39,969, MAPE value of 25.
62.
The simulation results showed that of the four mathematical models that became the output of G-MFS, the 1st mathematical model became the best model in determining the prediction results due to smaller error parameters with a predicted planting area of 1,728,503 m2, a production rate of 9.
609057 tons, and a productivity of 57.
145% Abstrak: Penelitian ini bertujuan untuk mengetahui model peramalan terbaik dengan metode ARIMA.
Data yang digunakan penelitian ini adalah luas panen, produksi dan produktivitas di Provinsi Jawa Timur Tahun 2000-2020.
Analisis data yang digunakan adalah metode ARIMA dengan Parameter akurasi yang digunakan yaitu MSE, MAPE, dan MAD.
Hasil penelitian menunjukkan bahwa (1) tingkat kesalahan metode ARIMA di luas panen, nilai MAD sebesar 1.
013.
810.
484; nilai MSE sebesar 16.
484.
292.
627,223; nilai MAPE sebesar 48,25; (2) tingkat kesalahan metode ARIMA di Produksi, nilai MAD sebesar 5.
975.
703,193, nilai MSE sebesar 5.
886.
684.
845.
403,590, nilai MAPE sebesar 54,60; (3) terakhir kesalahan metode ARIMA di produktivitas, nilai MAD sebesar 14,705, nilai MSE sebesar 39,969, nilai MAPE sebesar 25,62.
Hasil simulasi menunjukkan bahwa dari empat model matematika yang menjadi output G-MFS maka model matematika ke-1 menjadi model terbaik dalam menentukan hasil prediksi karena parameter error yang lebih kecil dengan hasil prediksi luas tanam sebesar 1.
728.
503 m2, tingkat produksi 9.
609057 ton, dan produktivitas sebesar 57,145%.
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