ANALISIS SENTIMEN APLIKASI NOICE MENGGUNAKAN METODE NAIVE BAYES

NURFAIDA, INDAH (2024) ANALISIS SENTIMEN APLIKASI NOICE MENGGUNAKAN METODE NAIVE BAYES. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The emergence of many new trends that mark the revolution from conventional to digital, such as audio content, also marks the development of internet users. Audio content consumption has increased in recent years. One audio content platform that offers many types of audio content such aspodcasts, book series (audioseries) or audiobooks (audiobooks) is NOICE. Many users write product and service reviews based on their experiences on the Google Play Store, as was done previously. Sentiment analysis is a methodthat can be used to create a system that can automatically analyze these reviewsand extract the most relevant information for users. Researchers collected NOICE review data from 1000 datasets available on the Google Play store, and will classify it using the Na've Bayes method. The research results show that the sentiment given by users of the Noice application on the Google PlayStore tends to be positive with the amount of data obtained being 633 positivesentiments and 264 negative sentiments. Analysis of user sentiment towards the Noice application using the Naïve Bayes algorithm also produces quite accurate values with an accuracy value of 88%. This shows that NaïveBayes is the right method for conducting sentiment analysis. Keywords: Sentiment Analysis, text mining, audio content, NOICE, NaïveBayes. Munculnya banyak tren baru yang menandai revolusi dari konvensional menjadidigital, seperti konten audio, juga menandai perkembangan pengguna internet. Konsumsi konten audio telah meningkat dalam beberapa tahun terakhir. Salah satu platform konten audio yang meyuguhkan banyak jenis konten audio seperti Podcast, buku series (audioseries) ataupun buku audio (audiobook) adalah NOICE. Analisis sentimen adalah metode yang dapat digunakan untuk membuat sistem yang dapat menganalisis ulasan ini secara otomatis dan mengekstrak informasi yang paling relevan bagi pengguna. Peneliti mengumpulkan data review NOICE dari dataset 1000yang tersedia di Google Play store, dan akan diklasifikasikan menggunakan metode Na've Bayes. Hasil penelitian menujukkan sentimen yang diberikan oleh pengguna aplikasi Noice pada Google Play Store cenderung Positif dengan jumlah data yang didapat sebanyak 633 sentimen positif dan 264 sentimen negatif. Analisis sentimen pengguna terhadap aplikasi Noice menggunakan algoritma Naïve Bayes juga menghasilkan nilai yang cukup akurat dengan nilai akurasi sebesar 88%. Hal ini menunjukkan bahwa Naïve Bayes merupakan metode yang tepat untuk melakukan analisis sentimen. Kata kunci: Analisis sentimen, text mining, konten audio, NOICE, Naïve Bayes.

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