Application of Data Mining to Recommend NAS Product Series to Potential Toko Storage Customers Using Multinomial Naïve Bayes Algorithm

Authors

  • Fernando Verdy Sunata Universitas Buddhi Dharma
  • Susanto Hariyanto Universitas Buddhi Dharma
  • Dicky Surya Dwi Putra Universitas Buddhi Dharma
  • Hartana Wijaya Universitas Buddhi Dharma

DOI:

https://doi.org/10.31253/algor.v4i1.1498

Keywords:

Data Mining, Multinomial Naïve Bayes, Network Attached Storage

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.

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Published

2022-09-15

How to Cite

Sunata, F. V., Hariyanto, S., Dwi Putra, D. S., & Wijaya, H. (2022). Application of Data Mining to Recommend NAS Product Series to Potential Toko Storage Customers Using Multinomial Naïve Bayes Algorithm. ALGOR, 4(1), 44–55. https://doi.org/10.31253/algor.v4i1.1498

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