Implementasi Algoritma Naïve Bayes untuk Mengevaluasi Reputasi Merek (Studi Kasus: Toko XYZ)

Rizka Putera Suryaresmana; Feri Sulianta

doi:10.55681/jige.v6i3.4016

Authors

Rizka Putera Suryaresmana Program Studi Informatika, Fakultas Teknik, Universitas Widyatama Bandung, Indonesia
Feri Sulianta Program Studi Informatika, Fakultas Teknik, Universitas Widyatama Bandung, Indonesia

DOI:

https://doi.org/10.55681/jige.v6i3.4016

Keywords:

Brand evaluation, brand reputation, classsification, naïve bayes, sentiment analysis

Abstract

Brand reputation assessment is a crucial aspect for companies in maintaining consumer trust and satisfaction. However, evaluating brand reputation is often challenging, especially for companies that lack the resources to perform it manually. This study aims to implement the Naïve Bayes algorithm in evaluating brand reputation, using a case study of Toko XYZ. The Naïve Bayes algorithm is utilized to perform sentiment analysis on text data related to the brand, such as customer reviews, which are then classified into positive, negative, or neutral sentiments. The results of this analysis are expected to provide the company with a deeper insight into consumer perceptions of their brand. This research also aims to support companies in making strategic decisions related to brand reputation management. Based on the findings, the Naïve Bayes algorithm proves to be effective in analyzing customer sentiment, providing companies with a clearer understanding of how their brand is perceived in the market, and enabling them to better respond to consumer needs.

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