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Fernando Verdy Sunata
Universitas Buddhi Dharma
Computer Science & IT

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Penerapan Data Mining Untuk Merekomendasikan Seri Produk NAS Kepada Calon Konsumen Toko Storage Menggunakan Algoritma Multinomial Naïve Bayes Fernando Verdy Sunata; Susanto Hariyanto; Dicky Surya Dwi Putra; Hartana Wijaya
ALGOR Vol. 4 No. 1 (2022): System and Engineering
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/algor.v4i1.1498

Abstract

Toko Storage is a trade name used by PT. Distributor Trimitra Indonesia to sell various kinds of Network Attached Storage products. The number of NAS products that are sold with different prices and specifications, sometimes makes it confusing and even makes it difficult for potential consumers to choose the right NAS product. So it is not uncommon for them to ask about NAS recommendations to store admins. The process of providing recommendations is carried out through a question and answer session related to NAS needs. The process of giving recommendations sometimes takes a long time because they have to wait for answers from potential customers. Therefore, a research was conducted that aims to design a system that is able to provide recommendations for NAS product series to potential customers by applying data mining methods and multinomial naïve bayes algorithms. The results of the application of the methods and algorithms used have proven to be successfully implemented on the data used, this is evidenced by the results of tests and evaluations carried out using the help of the Weka application which produces an accuracy value of 95.5556%. The final result of this research is the design of a web-based NAS product series recommendation system that can be used by users to get NAS product series recommendations quickly and precisely, just by entering the NAS criteria they are looking for.
Co-Authors Dicky Surya Dwi Putra Hartana Wijaya Susanto Hariyanto