G-Tech : Jurnal Teknologi Terapan
Vol 8 No 4 (2024): G-Tech, Vol. 8 No. 4 Oktober 2024

Sentimen Analisis & Topik Modeling menggunakan Latent Semantik Indexing (Studi Kasus: Aplikasi Detikcom)

Glenzkovic Samuel Moniharapon (Universitas Papua, Indonesia)
Dedi Iskandar Inan (Universitas Papua, Indonesia)
Ratna Juita (Universitas Papua, Indonesia)
Victor Arie Lambadya Sirait (Universitas Papua, Indonesia)



Article Info

Publish Date
17 Oct 2024

Abstract

The proliferation of digital news platforms has transformed information consumption, making user experience (UX) a key success factor for Detik.com, a leading news application in Indonesia. This research aims to explore the relationship between UX and news through sentiment analysis and topic modelling. The methods include web scraping for data collection, descriptive analysis for sentiment, and Latent Semantic Indexing (LSI) for topic modelling. Out of 14,320 reviews analyzed, 45.6% were positive, focusing on the speed of updates and news quality. Conversely, 41.18% of reviews were negative, highlighting disruptive ads and login issues, while 13.76% were neutral. LSI identified eight main topics, including user experience and ad complaints. Visualizations through heatmaps, distance maps, and word clouds emphasized terms like "news" and "ads." This research recommends that Detik.com developers reduce ad disruptions, fix technical problems, and understand frequently discussed topics to enhance user satisfaction.

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Journal Info

Abbrev

g-tech

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

Description

Jurnal G-Tech bertujuan untuk mempublikasikan hasil penelitian asli dan review hasil penelitian tentang teknologi dan terapan pada ruang lingkup keteknikan meliputi teknik mesin, teknik elektro, teknik informatika, sistem informasi, agroteknologi, ...