Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/116022
Title: Peramalan Produksi Bawang Putih di Indonesia Menggunakan Analisis Intervensi
Other Titles: Forecasting Garlic Production in Indonesia Using Intervention Analysis
Authors: Afendi, Farit Mochamad
Silvianti, Pika
Munasyiroh, Ayu Hidayati
Issue Date: 2023
Publisher: IPB University
Abstract: Bawang putih (Allium sativum) merupakan komoditas pertanian yang memiliki nilai ekonomi tinggi. Indonesia merupakan negara importir bawang putih tertinggi di dunia. Kebijakan pemerintah mengenai impor bawang putih menyebabkan penurunan hasil produksi bawang putih di Indonesia pada tahun 2021. Hasil produksi bawang putih mengalami penurunan dan perubahan pola rataan data deret waktu atau yang disebut dengan intervensi. Metode intervensi digunakan untuk menganalisis data deret waktu yang mengalami intervensi. Peramalan produksi bawang putih di Indonesia dilakukan menggunakan analisis intervensi berbasis ARIMA dengan fungsi step. SARIMA merupakan perluasan dari ARIMA. SARIMA (Seasonal Autoregressive Integrated Moving Average) merupakan model yang digunakan dalam peramalan data deret waktu yang memiliki pola musiman. Model intervensi terbaik yang didapatkan pada penelitian ini adalah model intervensi berbasis ARIMA(1,0,0)(1,0,1)12 . Model tersebut layak digunakan karena memiliki performa peramalan MAPE sebesar 36,234%. Hasil peramalan menunjukkan rataan produksi bawang putih lebih kecil dibandingkan tahun sebelumnya dan tahun sebelum intervensi dan mengikuti pola intervensi.
Garlic (Allium sativum) is an agricultural commodity that has high economic value. Indonesia is the highest garlic importing country in the world. The government's policy regarding garlic imports causes a decrease in garlic production in Indonesia in 2021. Garlic production has decreased and changes in the average pattern of time series data or what is called intervention. The intervention method was used to analyze the time series data that experienced the intervention. Forecasting of garlic production in Indonesia is carried out using an ARIMA-based intervention analysis with a step function. SARIMA is an extension of ARIMA. SARIMA (Seasonal Autoregressive Integrated Moving Average) is a model used in forecasting time series data that has a seasonal pattern. The best intervention model obtained in this study is an intervention model based on ARIMA ARIMA(1,0,0)(1,0,1)12. This model is feasible to use because it has a MAPE forecasting performance of 36.234%. Forecasting results show that the average garlic production is smaller than the previous year and the year before the intervention and has intervention pattern.
URI: http://repository.ipb.ac.id/handle/123456789/116022
Appears in Collections:UT - Statistics and Data Sciences

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