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All Journal JSAI (Journal Scientific and Applied Informatics) The Indonesian Journal of Computer Science
Rizka Rahmadhani
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Evaluasi User Experience Pada Aplikasi Disney+ Hotstar Menggunakan Metode MeCUE Questionnaire (2.0) Allsela Meiriza; Rizka Rahmadhani; Putri Eka Sevtiyuni; Nabila Rizky Oktadini; Pacu Putra
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3540

Abstract

Aplikasi Disney+ Hotstar sebagai penyedia layanan penyaluran audio dan video menggunakan jaringan internet (Over-The-Top) mendapatkan penilaian yang rendah pada Google Play Store, sehingga perlu diperhatikan mutu dari pengalaman pengguna aplikasi dengan cara mengevaluasi pengalaman pengguna. Penelitian ini bertujuan agar pengalaman pengguna Disney+ Hotstar dapat dievaluasi dengan menggunakan metode MeCUE Questionnaire (2.0). Hasil metode meCUE 2.0 yang terdiri dari modul Persepsi Kualitas Instrumen Produk variabel Kebergunaan (5,43) dan Kemudahan Penggunaan (6,02). Modul Persepsi Kualitas Non-Instrumen Produk variabel Tampilan Estetika (5,74), Status (3,73), dan Komitmen (2,88). Modul Emosi variabel Emosi Positif (5,27) dan Emosi Negatif (2,19). Modul Konsekuensi variabel Niat Menggunakan (4,17) dan Loyalitas Produk (3,76). Serta modul Global dengan nilai 3,8. Yang mana responden penelitian ini adalah masyarakat Kota Palembang. Dari hasil tersebut variabel kemudahan penggunaan memiliki nilai tertinggi dan variabel emosi negatif sebagai nilai terendah.
Analisis Sentimen Aplikasi MPStore Menggunakan Algoritma Logistic Regression dan LDA Tia Arlin Dita; Ali Ibrahim; Rizka Rahmadhani; Mira Afrina
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9557

Abstract

The rapid growth of the digital economy encourages user satisfaction as the key to successful application innovation. Within technopreneurship, understanding user sentiment is essential for sustainable product development. This study aims to analyze sentiment and identify the deter-minants of user satisfaction regarding the MPStore application based on reviews from the Google Play Store. Review data were collected via scraping and analyzed using Logistic Regression (LR) for sentiment classification (positive, negative, neutral) also Latent Dirichlet Al-location (LDA) for satisfaction topic extraction. The result shows that the LR model achieved an accuracy of 88.5%. The LDA analysis also successfully revealed eight main topics, includ-ing ease of use, transaction speed, and technical obstacles (errors, login, balance issues). Over-all, a majority of users hold a positive perception of MPStore's efficiency and ease of transac-tions. This study concludes that the combination of sentiment analysis and topic modeling is effective for explaining the level of user satisfaction and providing a strategic foundation for digital application developers.
Co-Authors Ali Ibrahim Allsela Meiriza, Allsela Mira Afrina Oktadini, Nabila Rizky Pacu Putra Putri Eka Sevtiyuni Tia Arlin Dita