PENGEMBANGAN SISTEM KLASIFIKASI SENTIMEN ULASAN APLIKASI MOBILE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (STUDI KASUS: ULASAN ALFAGIFT PADA GOOGLE PLAY STORE)

Adzra Sajida, . (2024) PENGEMBANGAN SISTEM KLASIFIKASI SENTIMEN ULASAN APLIKASI MOBILE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (STUDI KASUS: ULASAN ALFAGIFT PADA GOOGLE PLAY STORE). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The COVID-19 pandemic has changed consumer behavior, increasing online shopping activities. PT Sumber Alfaria Trijaya Tbk responded to this trend with the Alfagift app, which offers affordable products and is integrated with thousands of Alfamart stores in Indonesia. Although the rating of the Alfagift application on the Google Play Store is already quite good, an in-depth understanding of user reviews is still needed. This research uses text mining methods to analyze the sentiment of Alfagift reviews, focusing on the Support Vector Machine (SVM) algorithm. The results show that the review sentiment is almost balanced although it is still slightly more dominant in negative sentiment, but the trend of positive sentiment has increased over time. The SVM classification model built has an average accuracy of 95%. The system developed using Flask as the backend and HTML, CSS, and JavaScript as the frontend, has successfully passed blackbox testing. The conclusion of the analysis shows that Alfagift has great potential to become a better shopping platform by improving service quality, transparency, and responsiveness, as well as expanding promotions and payment methods. This will increase user satisfaction and strengthen Alfagift's position as a trusted online shopping platform.

Item Type:	Thesis (Skripsi)
Additional Information:	[No.Panggil: 2010512049] [Pembimbing 1: Andhika Octa Indarso] [Pembimbing 2: Bambang Saras Yulistiawan] [Penguji 1: Widya Cholil] [Penguji 2: Ika Nurlaili Isnainiyah]
Uncontrolled Keywords:	Text Mining, Sentiment Analysis, Alfagift, Support Vector Machine, Flask
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User:	ADZRA SAJIDA
Date Deposited:	12 Sep 2024 04:11
Last Modified:	12 Sep 2024 04:11
URI:	http://repository.upnvj.ac.id/id/eprint/31958

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