Prediksi Harga Bahan Pokok Nasional Jangka Pendek Menggunakan ARIMA

Clicks: 456
ID: 11772
2017
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #19 of 92 articles by views in journal of information systems engineering and business intelligence

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstrak— Fluktuasi harga bahan pokok yang tidak terkendali dapat menyebabkan kerugian bagi konsumen maupun produsen. Salah satu langkah untuk mengatasi permasalahan tersebut yaitu dengan membuat prediksi harga yang akurat sehingga tindakan preventif dapat dilakukan untuk meminimalkan gejolak harga. Dalam studi ini, ARIMA digunakan untuk memprediksi harga bahan pokok nasional dalam jangka pendek. Data harga harian dari dua belas bahan pokok pada empat horizon prediksi (1 hingga 30 hari ke depan) digunakan untuk menguji kinerja ARIMA dalam memprediksi harga bahan pokok. Hasil eksperimen menujukkan bahwa model ARIMA yang dihasilkan mampu memprediksi harga dengan tingkat error rata-rata sebesar 2.22%.  Kata Kunci— ARIMA, Bahan Pokok, Prediksi, Peramalan Abstract— Uncontrolled price fluctuation of basic commodities can harm both consumers and producers. One way to overcome the problem is by making accurate price prediction so that preventive actions can be conducted to minimize the price fluctuation. In this study, ARIMA is used to make short-term price prediction of national basic commodities. Daily pricing data of twelve commodities in four prediction horizons (1 to 30 days ahead) is used to test the performance of ARIMA in predicting the commodity prices. The experimental results showed that the ARIMA model was able to predict the price quite accurately with an average error rate of 2.22%.  Keywords— ARIMA, Basic Commodities, Forecast, Prediction
Reference Key
rasyidi2017prediksijournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mohammad Arif Rasyidi;
Journal journal of information systems engineering and business intelligence
Year 2017
DOI
10.20473/jisebi.3.2.107-112
URL
https://e-journal.unair.ac.id/JISEBI/article/download/5663/3897
Keywords
arima basic commodities forecast prediction

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.