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Rezkiani Rezkiani
Institut Digital Bisnis Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Journal : Sistemasi: Jurnal Sistem Informasi

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Naïve Bayes Classification Model for the Producer Price Index Prediction Melisa Winda Pertiwi; Mira Kusmira; Rezkiani Rezkiani; Bambang Kelana Simpony; Yanti Apriyani; Iqbal Dzulfiqar Iskandar; Taufik Wibisono; Imam Amirulloh
Sistemasi: Jurnal Sistem Informasi Vol 11, No 1 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1910.824 KB) | DOI: 10.32520/stmsi.v11i1.1669

Abstract

Producer Price Index is an index number that describes the level of price change at the producer level. Data users can take advantage of the development of producer prices as an early indicator of wholesale and retail prices. In addition, it can also be used to assist in the preparation of the economic balance, distribution of goods, trade margins, and so on. Every year the Badan Pusat Statistika (BPS) updates data on the producer price index to facilitate producer price standards, including rice and grain producers. To determine the Price Prediction Index, a prediction algorithm is needed, namely Naive Bayes based on data from Quarters I and II of 2021. The Naïve Bayes Algorithm, can be used to predict the Producer Price Index. This prediction is made to provide an overview of Quarter III, considering that in 1 year BPS updates the Producer Price Index’s data up to Quarter IV in 1 year. The prediction obtained is an increase for Quarter III with a maximum value between 0.961 – 0.980 based on data from Quarters I and II.
Co-Authors Bambang Kelana Simpony Imam Amirulloh Iskandar, Iqbal Dzulfiqar Melisa Winda Pertiwi Mira Kusmira Taufik Wibisono Yanti Apriyani