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All Journal Jurnal Mantik Penusa Journal of Applied Business and Technology
Eri Yanto
Institut Bisnis dan Teknologi Pelita Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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IMPLEMENTASI ALGORITMA APRIORI DAN FORECASTING PADA TRANSAKSI PENJUALAN Irvan Firnando; Dixsen Dixsen; Tony Tony; Vincent Wijaya; Surianto Surianto; Eri Yanto; Deny Jollyta
Jurnal Mantik Penusa Vol. 3 No. 3 (19): COmputer Science
Publisher : Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (176.206 KB)

Abstract

One of the most important parts of a retail business or product distribution company is inventory management. Transactions with very large amounts in a certain period make the transaction data on sales, prices, and availability of goods must be managed properly. This study was delivered to facilitate the company in determining policies related to sales and availability of goods through the purchase pattern of association rules and sales predictions using the Moving Average method. Association rule is data mining techniques contained in the Apriori algorithm. This algorithm is able to shows random relationships in a number of transactions. The test resulted in three patterns of purchasing goods with the highest frequency namely Milo Activ-go UHT Cmbk 36x115ml, Bear Brand RTD Milk 30x189ml and Milo Activ-Go UHT Cmbk 36x190ml with values of 46.17%, 41.97% and 15.39%. The Moving Average result, sales predictions produce a total of 3669, 3280, and 2619 for each item that can be prepared in the next period. This can be a company's reference in predicting goods that are in demand or not, determine the number of sales and prioritize the procurement of goods based on the rules of the association produced.
APPLICATION OF GENETIC ALGORITHM IN TOURISM ROUTE OPTIMIZATION IN PEKANBARU CITY Eri Yanto; Ramalia Noratama Putri
Journal of Applied Business and Technology Vol. 1 No. 1 (2020): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (773.7 KB) | DOI: 10.35145/jabt.v1i1.22

Abstract

The number of tourist attractions that are not yet well known, reinforced by the release of Pekanbaru City Government data that the tourism sector only accounts for about 0.9% of the national tourism sector. Therefore, this study aims to optimize the determination of Pekanbaru city tourist travel routes by using genetic algorithms or Genetic Algorithms. Genetic algortima process generally consists of several stages, starting from the initial generation, determination of fitness, crossover stage, mutation to the generation of advanced stages. With an accuracy rate of the best offered solutions reaching around 88% and an average solution search of about 19 seconds per iteration on a constant 100x trial, the results of this study can be used to help general users or Tour & Travel businesses in determining travel routes more optimal travel and a better travel experience.
Co-Authors Deny Jollyta Dixsen Dixsen Irvan Firnando Ramalia Noratama Putri Surianto Surianto Tony Tony Vincent Wijaya