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Statistika
Article . 2021 . Peer-reviewed
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Statistika
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Pemodelan Harga Cabai Merah Menggunakan Model ARIMA (Studi Kasus: Harga Cabai Merah di Kota Padang Periode Januari 2010 – Desember 2020)

Authors: Sherly Aktivani;

Pemodelan Harga Cabai Merah Menggunakan Model ARIMA (Studi Kasus: Harga Cabai Merah di Kota Padang Periode Januari 2010 – Desember 2020)

Abstract

Cabai merah merupakan komoditas sayuran yang memiliki nilai ekonomis yang cukup tinggi, karena peranannya yang cukup besar untuk memenuhi kebutuhan domestik sebagai komoditi ekspor dalam industri pangan. Cabai merah juga merupakan salah satu komoditas yang termasuk dalam volatile food. Kenaikan harga komoditas cabai merah tersebut ketika dihitung secara parsial per komoditas, kontribusinya terhadap inflasi bulanan seringkali lebih unggul jika dibandingkan dengan komoditas lain dalam kelompok yang sama (Badan Pusat Statistik). Penelitian ini terpusat pada Kota Padang sebagai salah satu Kota Inflasi di Indonesia. Informasi naik turunnya harga cabai pada periode terdahulu diperlukan dalam analisis pasar untuk meramalkan harga beli cabai demi mengantisipasi kenaikan dan penurunan harga cabai dimasa mendatang dan kontrol terhadap nilai inflasi. Metode peramalan yang digunakan peneliti dalam meramalkan harga cabai adalah ARIMA Box-Jenkins. Dari tahapan pembentukan model ARIMA harga cabai merah Kota Padang, dapat disimpulkan bahwa data belum memiliki varian yang konstan sehingga perlu dilakukan transformasi data. Model ARIMA terbaik yang diperoleh setelah mean dan varians data stasioner yaitu AR(1,2)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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