Klasifikasi Waktu Pada Dokumen Persetujuan Accounting Voucher

Authors

  • Dinda Nur Octaviany Universitas Muhammadiyah Kalimantan Timur
  • Wawan Joko Pranoto Universitas Muhammadiyah Kalimantan Timur

DOI:

https://doi.org/10.55606/jtmei.v3i1.3215

Keywords:

Naive Bayes, time classification, timely and late classification

Abstract

This research aims to optimize the approval document management process by implementing time classification techniques using Naive Bayes. Naive Bayes classification is a data classification technique that utilizes probability theory and statistics to predict future probabilities based on Accounting Voucher approval document data from January to April 2023. This study focuses on the application of the Naive Bayes algorithm for time classification, aiming to provide innovative solutions for PT. Kideco Jaya Agung in the mining industry. Attributes used in the Naive Bayes classification method include document type, document number, document status, and time difference. The research results indicate that the probabilities of the 'On Time' and 'Late' classes are approximately 0.9737 and 0.0263, respectively, with an accuracy rate of 97.67441860465115% or 98%.

References

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Published

2023-12-22

How to Cite

Dinda Nur Octaviany, & Wawan Joko Pranoto. (2023). Klasifikasi Waktu Pada Dokumen Persetujuan Accounting Voucher . Jurnal Teknik Mesin, Industri, Elektro Dan Informatika, 3(1), 47–60. https://doi.org/10.55606/jtmei.v3i1.3215

Issue

Vol. 3 No. 1 (2024): Maret : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA

Section

Articles

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Copyright (c) 2023 Jurnal Teknik Mesin, Industri, Elektro dan Informatika

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