Analisis Sentimen Suporter terhadap Performa Persijap Jepara Menggunakan Metode Naïve Bayes - M. Rikza Tamyiz; Esti Wijayanti; Ahmad Jazuli (STMIK Banjarbaru, 2026)
Social media has given football fans an open channel to voice unfiltered reactions to their club's performance, and the Instagram account of Persijap Jepara now attracts a large volume of such comments that has never been examined in a structured way. This study applies a Machine Learning technique, specifically the Multinomial Naïve Bayes algorithm, to classify the sentiment expressed by these supporters. A total of 5,493 distinct Instagram comments were collected, cleaned through a text-preprocessing pipeline, and converted into numerical features using TF-IDF weighting. Testing the resulting model produced an accuracy of 74.32%, alongside a precision score of 0.76, a recall score of 0.72, and an F1-score of 0.74. Keywords: Sentiment Analysis; Machine Learning; Naïve Bayes; TF-IDF; Persijap Jepara. Abstrak Kemajuan media sosial membuka ruang bagi suporter sepak bola untuk menuliskan pendapat mereka secara bebas mengenai performa klub. Akun Instagram resmi Persijap Jepara menerima volume komentar yang tinggi, tetapi data teks tersebut belum pernah diolah dan dinilai secara terstruktur. Riset ini berupaya mengukur kecenderungan sentimen suporter dengan memanfaatkan teknik Machine Learning berupa algoritma Multinomial Naïve Bayes. Sebanyak 5.493 komentar unik dikumpulkan dari Instagram, kemudian dibersihkan melalui tahap preprocessing teks serta diubah menjadi fitur numerik menggunakan pembobotan TF-IDF. Hasil pengujian model menunjukkan akurasi 74,32%, presisi 0,76, recall 0,72, serta F1-score 0,74. Kata kunci: Analisis Sentimen; Machine Learning; Naïve Bayes; TF-IDF; Persijap Jepara