ANALISIS SENTIMEN ULASAN PENUMPANG MASKAPAI PENERBANGAN DI INDONESIA DENGAN ALGORITMA RANDOM FOREST DAN KNN
DOI:
https://doi.org/10.31849/zn.v6i2.19177Keywords:
Analisis Sentimen, TF-IDF, Natural Language Processing, Random Forest, K-Nearest Neighbor (KNN)Abstract
Penelitian ini mendalam pada analisis sentimen ulasan pelanggan terhadap maskapai penerbangan di Indonesia melalui NLP dan Machine Learning. Dalam prosesnya, data ulasan melibatkan serangkaian teknik, termasuk cleansing, case folding, tokenization, filtering, dan stemming, sementara sentimen diberikan label menggunakan lexicon afinn. Visualisasi kata-kata dominan dari ulasan diwujudkan melalui wordcloud untuk memberikan gambaran yang kaya dan intuitif. Ekstraksi fitur melibatkan metode TF-IDF, diikuti oleh proses klasifikasi menggunakan algoritma Random Forest dan K-Nearest Neighbor (KNN). Hasil evaluasi model menunjukkan tingkat akurasi yang memuaskan, dengan Random Forest mencapai 83% dan KNN mencapai 82%. Temuan ini memberikan wawasan yang dalam tentang preferensi pelanggan dan potensial masalah dalam pengalaman penerbangan di Indonesia, memberikan kontribusi pada pemahaman yang lebih holistik terhadap dinamika industri penerbangan.
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