Perbandingan analisis sentimen ulasan aplikasi ajaib kripto menggunakan metode naive bayes dan k-nearest neighbour

Wendy, Calvin (2024) Perbandingan analisis sentimen ulasan aplikasi ajaib kripto menggunakan metode naive bayes dan k-nearest neighbour. Bachelor thesis, Universitas Pelita Harapan.

Preview	Text (Title) Title.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (15kB) | Preview
Preview	Text (Abstract) Abstract.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (271kB) | Preview
Preview	Text (ToC) ToC.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (551kB) | Preview
Preview	Text (Chapter1) Chapter1.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (631kB) | Preview
	Text (Chapter2) Chapter2.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (1MB)
	Text (Chapter3) Chapter3.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (917kB)
	Text (Chapter4) Chapter4.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (2MB)
	Text (Chapter5) Chapter5.pdf Restricted to Registered users only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (214kB)
Preview	Text (Bibliography) Bibliography.pdf Available under License Creative Commons Attribution Non-commercial Share Alike. Download (457kB) | Preview
	Text (Appendices) Appendices.pdf Restricted to Repository staff only Available under License Creative Commons Attribution Non-commercial Share Alike. Download (2MB)

Abstract

Perkembangan yang terjadi di bidang investasi membuat masyarakat tertarik untuk melakukan investasi. Platform yang sering dipakai adalah aplikasi ajaib kripto pada Google Play Store. Calon pengguna melihat ulasan aplikasi, yang dibuat berdasarkan pendapat pengguna dan digunakan sebagai pertimbangan sebelum memutuskan menggunakan aplikasi tersebut. Sehingga diperlukan analisis data. Salah satu cara menganalisis data disebut analisis sentimen. Terdapat banyak sekali metode yang dapat digunakan untuk analisis sentimen. Sehingga penulis menggunakan metode Naive Bayes dan K-Nearest Neighbor untuk mengetahui metode yang lebih akurat. Data yang diambil untuk penelitian ini merupakan ulasan dari aplikasi ajaib kripto tersebut yang dikumpulkan dari tahun 2022 sampai 2024 dengan data sebanyak 4784. Dataset melalui tahapan pembagian data dengan menggunakan k-fold cross validation dengan k=5, kemudian tahapan preprocessing, transformasi TF-IDF, melatih model Naive Bayes dan KNN dengan data latih. Model tersebut kemudian dicoba pada data uji. Hasilnya adalah metode Naïve Bayes memberikan tingkat akurasi sebesar 82%, presisi sebesar 83%, recall sebesar 98% dan f1-score sebesar 90%. Sedangkan metode K-Nearest Neighbor memberikan tingkat akurasi sebesar 80%, presisi sebesar 84%, recall sebesar 94% dan f1-score sebesar 89%. Kesimpulan dari penelitian ini adalah metode Naïve Bayes memiliki tingkat akurasi yang lebih baik dibandingkan metode K-Nearest Neighbor. / Developments that occur in the investment sector make people interested in investing. The platform that is often used is the crypto magic application on the Google Play Store. Potential users see app reviews, which are based on user opinions and used as consideration before deciding to use the app. So data analysis is needed. One way of analyzing data is called sentiment analysis. There are many methods that can be used for sentiment analysis. So the author uses the Naive Bayes and K-Nearest Neighbor methods to find out a more accurate method. The data taken for this study is a review of the crypto magic application collected from 2022 to 2024 with 4784 data. Dataset through the stages of data division using k-fold cross validation with k=5, then the preprocessing stage, TF-IDF transformation, training Naive Bayes and KNN models with training data. The model was then tested on test data. The result is that the Naïve Bayes method provides an accuracy rate of 82%, precision of 83%, recall of 98% and an f1-score of 90%. While the K�Nearest Neighbor method provides an accuracy rate of 80%, precision of 84%, recall of 94% and f1-score of 89%. The conclusion of this study is that the Naïve Bayes method has a better level of accuracy than the K-Nearest Neighbor method.

Actions (login required)

View Item