ANALISIS SENTIMEN TERHADAP REPRESENTASI LGBT DALAM INDUSTRI GAME MENGGUNAKAN METODE MACHINE LEARNING

Andhika Wahfyudin Majid, 3012110003 (2025) ANALISIS SENTIMEN TERHADAP REPRESENTASI LGBT DALAM INDUSTRI GAME MENGGUNAKAN METODE MACHINE LEARNING. Undergraduate thesis, Universitas Internasional Semen Indonesia.

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Abstract

Industri game mengalami perkembangan pesat, tidak hanya dalam aspek teknologi tetapi juga dalam representasi sosial dan budaya, termasuk isu Lesbian, Gay, Biseksual, dan Transgender (LGBT). Representasi LGBT dalam game sering kali menjadi topik kontroversial yang mendapat tanggapan beragam dari komunitas pemain. Penelitian ini DistilBERTujuan untuk menganalisis sentimen komunitas berdasarkan pengguna di platform steam dan membandingkan performa berbagai model machine learning. Analisis dilakukan terhadap 9.978 ulasan dari 20 game menggunakan lima metode machine learning klasik dan model Transformer, DistilDistilBERT. Hasil analisis menunjukkan sentimen mayoritas adalah netral (87,2%). Hal ini mengindikasikan bahwa sebagian besar pemain fokus pada aspek gameplay dan teknis daripada isu representasi sosial. Sentimen negatif (7,1%) dan positif (5,7%) hanya minoritas. Pada perbadingan model, DistilDistilBERT terbukti sebagai model dengan performa terbaik, dengan tingkat akurasi 83,41 dan F1-score makro 83%, jauh lebih unggul dari model machine learning klasik lain.

Item Type: Thesis (Undergraduate)
Additional Information: Softfile/KK.25/UISI-01/IF
Uncontrolled Keywords: Analisis Sentimen, DistilDistilBERT, Game, Machine learning, Representasi LGBT
Contributors:
ContributionNameEmail
Thesis advisorMohammad Arif Rasyidi, S.Kom., M.Sc., MCEmohammad.rasyidi@uisi.ac.id
Subjects: T Technology > T Technology (General)
Divisions: Department of Informatics
Depositing User: ANDHIKA WAHFYUDIN MAJID
Date Deposited: 04 Aug 2025 12:00
Last Modified: 04 Aug 2025 12:00
URI: https://repository.uisi.ac.id/id/eprint/7923

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