ANALISIS SENTIMEN PADA ULASAN PENGGUNA APLIKASI SHOPEE DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

Rohanda Selia Pangaribuan, . (2023) ANALISIS SENTIMEN PADA ULASAN PENGGUNA APLIKASI SHOPEE DI GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The rapid development of technology can make things easier, faster and more practical. Technological developments are currently growing rapidly and affecting all aspects of life, including in the field of goods and services. The use of technology does not only benefit one party but also all parties. Currently there are many services that use online buying and selling applications. One of these applications is Shopee. Shopee is the largest online shopping application in Indonesia, due to frequent and varied promotions, and the many ways used to entice users to be interested in using the Shopee application. The more people who are interested in using the Shopee application, the more diverse the level of consumer satisfaction is. And the more Shopee application users, the more users share their experiences in the form of giving satisfaction or complaints in reviews on the Google Play Store. This review will be used as material for analysis in the form of input or feedback so that it can be used as future improvement by the company. In conducting sentiment analysis, this study uses the Support Vector Machine Algorithm in modeling. This study aims to find out how public sentiment is towards the Shopee application. The stages start from collecting review data on the Shopee application. Then the data is labeled positive or negative. Then it will be pre-processed and followed by classification using the Support Vector Machine algorithm.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 1910511009] [Pembimbing: Didit Widiyanto] [Penguji 1: Ermatita] [Penguji 2: Anita Muliawati]
Uncontrolled Keywords: Shopee, Sentiment Analysis, Support Vector Machine.
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: Rohanda Selia Pangaribuan
Date Deposited: 31 Jul 2023 04:57
Last Modified: 31 Jul 2023 04:57
URI: http://repository.upnvj.ac.id/id/eprint/25261

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