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Yudha Prahara
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Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences

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PREDIKSI PERSEDIAAN BAHAN BAKU PEMBUATAN PEMPEK MENGGUNAKAN METODE NAIVE BAYES (STUDY KASUS : HOME INDUSTRY PEMPEK YURA) Yudha Prahara; Sewaka
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Pempek Yura is one of the home industries that produces several types of pempek, namely Pempek Kapal Selam, Pempek Lenjer, Pempek Kulit, and Tekwan having the addresses at Jelupang, Tangerang Selatan, Banten. There are frequent stockouts of raw material for Mackerel, Sago and Eggs which prevent the production of goods and disappoint consumers resulting in cancellations, so raw material predictions are needed to determine the plan for supplying raw material stocks. To determine the future raw material requirements. This research focuses on predicting the stock of pempek raw materials so that production continues, and raw materials are always available. Stock prediction analysis is adjusted from production and sales data, from production and sales data data processing is carried out using the Knowledge Discovery in Database stage, namely by selecting the data needed in data mining, then processing the data by deleting empty sales data, changing the numerical data cannot be processed by naïve Bayes data mining, then data mining uses the Rapid Miner Application Version 9.10 with the naïve Bayes method. The operators used in rapidminer are Retrive, Cross Validation, Naïve Bayes, Apply Model and Performance. Accuracy results with the rapid miner in this study showed 99.57% with details of Prediction Results for raw materials Enough 207 data while raw materials lacked 22 data.
Co-Authors Sewaka