Naïve Bayes Classification Model for the Producer Price Index Prediction

Melisa Winda Pertiwi (UNIVERSITAS NUSA MANDIRI)
Mira Kusmira (Universitas Nusa Mandiri)
Rezkiani Rezkiani (Institut Digital Bisnis Indonesia)
Bambang Kelana Simpony (Universitas Bina Sarana Informatika)
Yanti Apriyani (Universitas Bina Sarana Informatika)
Iqbal Dzulfiqar Iskandar (Universitas Bina Sarana Informatika)
Taufik Wibisono (Universitas Bina Sarana Informatika)
Imam Amirulloh (Universitas Bina Sarana Informatika)

Sistemasi: Jurnal Sistem Informasi
Vol 11, No 1 (2022): Sistemasi: Jurnal Sistem Informasi

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.