PERBANDINGAN ALGORITMA K-NEAREST NEIGHBOUR DAN NAÏVE BAYES DALAM ANALISIS SENTIMEN PRODUK INFINIX NOTE 40 - Arya Aji Pradana; fitria (Innotech: Jurnal Ilmu Komputer, Sistem Informasi dan Teknologi Informasi, 2026)
Abstract: Infinix Note 40 is a popular product with high specifications yet affordable, complemented by an attractive purchase package. This product has gained attention on social media and review platforms, including the Gadgetin YouTube channel. This study aims to compare two data mining algorithms, K-Nearest Neighbour (KNN) and Naïve Bayes, in sentiment analysis. From 8,323 comment data on videos from the GadgetIn channel, the results show that Naïve Bayes outperforms KNN with an accuracy of 69% compared to KNN's accuracy of 59%. The detailed metrics for Naïve Bayes are as follows: Precision of 68.9%, Recall of 69%, and F1-Score of 68.5%. This finding highlights the superiority of Naïve Bayes in analyzing sentiment towards Infinix Note 40 from reviews on the Gadgetin YouTube channel, with the interpretation leaning towards the negative, where the model classified 39% of sentiments as negative, 26% as neutral, and 34% as positive. Keywords: Data Mining, Text Classification, Sentiment Analysis, K-Nearest Neighbor, Naïve Bayes, YouTube.