Rusadi, Pradia Ahmad (2025) USULAN PERBAIKAN APLIKASI DISNEY+ HOTSTAR MENGGUNAKAN LATENT DIRICHLET ALLOCATION DAN QUALITY FUNCTION DEPLOYMENT. S1 thesis, Fakultas Teknik Universitas Sultan Ageng Tirtayasa.
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Abstract
Disney+ Hotstar is a popular mobile streaming application that had 149.6 million users globally in 2024. This reflects the large scale of Disney+ Hotstar, but on the Google Play Store platform, its rating is significantly lower compared to other streaming applications. This study aims to investigate why Disney+ Hotstar has a low rating despite its large user base. The research was conducted using Text Mining implementation in the form of Latent Dirichlet Allocation (LDA) and Artificial Neural Network (ANN) processes with the Quality Function Deployment (QFD) method. The study began with data collection of Disney+ Hotstar reviews from the Google Play Store platform. After the data collection stage, pre-processing was carried out before being used for LDA and ANN processes. The LDA method identified nine attributes: OTP code for login, subscription requirement, subscription price, the feature of watching Disney+ on TV, restricted access due to false banning from VPN use, smooth video playback, frequency of new movie additions, video resolution quality, and the app’s tendency to avoid crashes or black screens. The ANN method results showed that positive reviews accounted for 12%, while negative reviews reached 88%. The identified attributes were used to build the House of Quality (HoQ), leading to technical response priorities, including periodic evaluation of streaming performance, providing preview and free versions, offering multiple subscription plans, adding international content, reducing app size, evaluating trending content and popular categories, and offering an email alternative for login authentication.
| Item Type: | Thesis (S1) | |||||||||
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| Additional Information: | Disney+ Hotstar merupakan aplikasi streaming mobile ternama yang pada tahun 2024 memiliki 149,6 juta pengguna secara global. Ini menunjukkan besarnya aplikasi Disney+ Hotstar, tetapi pada platform Google Play Store aplikasi tersebut memiliki rating yang sangat rendah dibanding dengan aplikasi streaming lainnya, sehingga dilakukan penelitian ini untuk mengetahui mengapa Disney+ Hotstar memiliki rating yang rendah padahal banyaknya pengguna yang menggunakannya. Penelitian dilakukan menggunakan implementasi Text Mining dalam bentuk proses Latent Dirichlet Allocation (LDA) dan Artificial Neural Network (ANN) dengan metode Quality Function Deployment (QFD). Penelitian dimulai dengan pengambilan data ulasan Disney+ Hotstar di platform Google Play Store. Setelah dilakukan tahap pengambilan data, dilakukan tahap pre-processing sebelum digunakan untuk proses LDA dan ANN. Metode LDA menghasilkan 9 atribut yaitu, kode OTP untuk login, langganan untuk menonton, harga berlangganan, fitur menonton Disney+ di TV, akses dibatasi karena false banning akun karena VPN, kelancaran berjalannya video, frekuensi penambahan film baru, kualitas resolusi video dan kecenderungan aplikasi untuk tidak crash atau blackscreen. Hasil metode ANN menunjukkan jumlah persentase ulasan positif 12% dan negatif 88%. Atribut yang didapatkan digunakan untuk membangun House of Quality (HoQ) dan didapatkan prioritas respon teknis yaitu evaluasi berkala performa streaming, menyediakan preview dan free version, memberikan opsi beberapa paket berlangganan, penambahan konten dari mancanegara, pengurangan ukuran aplikasi, evaluasi trending dan kategori film, dan alternatif via email. | |||||||||
| Subjects: | T Technology > T Technology (General) | |||||||||
| Divisions: | 03-Fakultas Teknik > 26201-Jurusan Teknik Industri | |||||||||
| Depositing User: | Pradia Ahmad Rusadi | |||||||||
| Date Deposited: | 26 Sep 2025 04:05 | |||||||||
| Last Modified: | 26 Sep 2025 04:05 | |||||||||
| URI: | http://eprints.untirta.ac.id/id/eprint/54516 |
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