Akbar, Muhammad Aulia Akbar and Luqman, Luqman (2024) ANALISIS SENTIMEN E-COMMERCE SHOPEE PADA GOOGLE PLAY MENGGUNAKAN METODE NAIVE BAYES. Diploma thesis, ITPLN.
![[thumbnail of 202031194_Muhammad Aulia Akbar_Revisi_Skrips_Muhammad Aulia Akbar.pdf]](https://repository.itpln.ac.id/style/images/fileicons/text.png)
202031194_Muhammad Aulia Akbar_Revisi_Skrips_Muhammad Aulia Akbar.pdf
Restricted to Registered users only
Download (3MB)
Abstract
Di era digital saat ini, e-commerce telah menjadi bagian integral dari kehidupan masyarakat, dengan Shopee menjadi salah satu platform terkemuka di Asia Tenggara, termasuk Indonesia. Ulasan pengguna di platform seperti Google Play memberikan informasi berharga yang membantu calon pembeli membuat keputusan yang tepat. Studi ini menggunakan algoritma Naive Bayes untuk analisis sentimen ulasan pengguna Shopee. Naive Bayes dipilih karena kesederhanaan dan efisiensi komputasinya, meskipun dengan asumsi independensi kata dalam teks. Hasil penelitian menunjukkan bahwa Naive Bayes dapat mengklasifikasikan sentimen ulasan dengan akurasi 85%, mencapai precision, recall, dan F1-score yang tinggi untuk sentimen positif maupun negatif. Temuan ini mendukung efektivitas Naive Bayes dalam analisis sentimen ulasan e commerce. Analisis ini dapat membantu Shopee memahami persepsi pengguna dan mengidentifikasi area yang perlu diperbaiki. Namun, analisis sentimen memiliki keterbatasan dan sebaiknya dikombinasikan dengan metode lain untuk mendapatkan pemahaman yang lebih komprehensif tentang persepsi pengguna terhadap Shopee.
In today's digital era, e-commerce has become an integral part of people's lives, with Shopee being one of the leading platforms in Southeast Asia, including Indonesia. User reviews on platforms like Google Play provide valuable information that helps prospective buyers make informed decisions. This study employs the Naive Bayes algorithm for sentiment analysis of Shopee user reviews. Naive Bayes was chosen for its simplicity and computational efficiency, despite assuming the independence of words in the text. The study's results demonstrate that Naive Bayes can classify review sentiments with an accuracy of 85%, achieving high precision, recall, and F1-scores for both positive and negative sentiments. These findings support the effectiveness of Naive Bayes in sentiment analysis of e-commerce reviews. This analysis can help Shopee understand user perceptions and identify areas for improvement. However, sentiment analysis has its limitations and should ideally be combined with other methods to gain a more comprehensive understanding of user perceptions of Shopee.
Item Type: | Thesis (Diploma) |
---|---|
Uncontrolled Keywords: | E-commerce, Shopee, Ulasan Pengguna, Analisis Sentimen, Naive Bayes, Google Play, Klasifikasi, Persepsi Pengguna. E-commerce, Shopee, User Reviews, Sentiment Analysis, Naive Bayes, Google Play, Classification, User Perception. |
Subjects: | Skripsi Bidang Keilmuan > Teknik Informatika |
Divisions: | Fakultas Telematika Energi > S1 Teknik Informatika |
Depositing User: | Sudarman |
Date Deposited: | 01 Oct 2025 06:36 |
Last Modified: | 01 Oct 2025 06:36 |
URI: | https://repository.itpln.ac.id/id/eprint/1661 |