SENTIMENT ANALYSIS TO ASSESS CUSTOMER RETENTION ON INSTAGRAM SOCIAL MEDIA USING NAÏVE BAYES CLASSIFIER AND SUPPORT VECTOR MACHINE

-, FANDI RAHMAT HALIM SENTIMENT ANALYSIS TO ASSESS CUSTOMER RETENTION ON INSTAGRAM SOCIAL MEDIA USING NAÏVE BAYES CLASSIFIER AND SUPPORT VECTOR MACHINE. The 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA-2024). (Submitted)

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Abstract

Information technology dominates people's lives and companies' business activities. Customer Relationship Management (CRM) is evolving into Social CRM (SCRM) with the integration of social media, including Instagram. Mr. Cream Puff, a pastry company, actively utilizes Instagram for marketing but has never analyzed customer comments. The comments are important in assessing customer satisfaction which affects customer retention in the company. This research aims to analyze the comments using sentiment analysis methods. Sentiment analysis was conducted using Naïve Bayes and Support Vector Machine (SVM) algorithms, followed by a performance comparison. The results show the accuracy of Naïve Bayes is 74.81% and SVM is 76.59%. From the test results, the SVM algorithm is superior to Naïve Bayes. In addition, the results of social CRM analysis from sentiment data and public opinion show that Mr. Cream Puff has succeeded in retaining its customers.

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