ANALISIS ELASTISITAS HARGA DAN PERAMALAN DINAMIS PADA KOMODITAS TOMAT DI KABUPATEN GARUT, INDONESIA

Eka Riskawati, Thabed Tholib Baladraf

Abstrak


Abstrak

Fluktuasi harga yang tinggi dan penurunan permintaan konsumsi menjadi tantangan bagi keberlanjutan produksi tomat di Indonesia. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi harga tomat dan menentukan model proyeksi terbaik komoditas tersebut di Kabupaten Garut, salah satu produsen tertinggi di Jawa Barat. Data sekunder dianalisis menggunakan regresi linier berganda untuk mengidentifikasi elastisitas harga dan faktor-faktor yang berpengaruh dan metode autoregressive integrated moving average (ARIMA) untuk memodelkan peramalan harga dinamis. Hasil penelitian menunjukkan bahwa variabel harga wortel, harga cabai merah, dan harga cabai rawit memiliki pengaruh signifikan terhadap harga tomat pada tingkat signifikansi 5%, sedangkan harga kubis berpengaruh signifikan pada tingkat 10%. Faktor produktivitas tomat, harga wortel, dan populasi memiliki efek positif, sedangkan harga cabai merah dan harga cabai rawit memiliki efek negatif terhadap harga tomat. Pemodelan ARIMA menunjukkan bahwa model terbaik untuk peramalan adalah (1,0) (1,0) dengan nilai AIC sebesar 404,375. Model mampu memproyeksikan harga dengan akurat, didukung oleh uji residual dan white noise dengan nilai p lebih dari 0,05.

Kata kunci: Elastisitas, peramalan, permintaan, regresi, tomat.

Abstract

High price fluctuations and declining consumption demand pose a challenge for the sustainability of tomato production in Indonesia. This study aims to analyze the factors affecting tomato prices and determine the best projection model for the commodity in Garut Regency, one of the highest producers in West Java. Secondary data were analyzed using multiple linear regression to identify price elasticity and influential factors, while autoregressive integrated moving average (ARIMA) method to model dynamic price forecasting. The results showed that the price variables of carrots, red chili, and cayenne pepper had a significant effect on tomato prices at the 5% significance level, while cabbage prices were significant at the 10% level. The factors of tomato productivity, carrot price, and population have a positive effect, while the prices of red chili and cayenne pepper have a negative effect on tomato prices. ARIMA modeling shows that the best model for forecasting is (1,0)(1,0) with an AIC value of 404.375. This model can project prices accurately, supported by residual and white noise tests with a p-value of more than 0.05.

Keywords: Demand, elasticity, forecast, regression, tomato.

Teks Lengkap:

134-147

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DOI: https://doi.org/10.24198/agricore.v9i2.59601

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