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Evaluating Netflix's User Experience (UX) Through The Lens Of The HEART Metrics Method Astriani, Yulia; Indah, Dwi Rosa; Utari, Meylani; Syahbani, M Husni
Journal of Applied Informatics and Computing Vol. 8 No. 2 (2024): December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i2.8727

Abstract

Netflix is one of the most popular subscription video-on-demand (SVoD) platforms, offering a wide range of authentic, high-quality content and features that allow users to select, enjoy, and share their viewing experiences on social media. Despite its popularity, Netflix often receives complaints from users, including issues with accessing the application and various features related to viewing activities. The aim of this study is to evaluate the user experience of the Netflix application and provide recommendations for improvement based on data analysis. To achieve this, the HEART Metrics are utilized, which focus on the user's perspective, and apply the Importance-Performance Analysis (IPA) method to map performance and identify improvement priorities. The research reveals several areas that require enhancement, particularly three priority variables: the Happiness variable (Hp3), indicated by the statement "I like the appearance of the Netflix application"; the Retention variable, represented by "I enjoy using the features of the Netflix application"; and the Task Success variable (Ts4), reflected in "I can save movies in the Netflix application." To improve user satisfaction, Netflix can incorporate both light and dark themes, creating a more user-friendly interface. This update could enhance navigation, increase time spent on the platform, promote recommendations, and encourage subscription renewals.
Implementasi CRISP-DM Pada Analisis Pembangunan Pendidikan Prasekolah Menurut Kabupaten/Kota di Indonesia Iranti, Putri Chandra; Kurniawan, Dedy; Sanjaya, M Rudi; Rifai, Ahmad; Syahbani, M Husni; Hartono Cahyadi, Gabriel Ekoputra; Sari, Purwita
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.5957

Abstract

Preschool education through Kindergarten (TK) plays a crucial role in child development in Indonesia, yet unequal access remains a significant issue. This study evaluates the need for preschool infrastructure development using the K-Means clustering algorithm implemented through RapidMiner. Regional clustering is based on the number of students, number of TK schools, Human Development Index (HDI), poverty rate, population size, and unemployment rate. The CRISP-DM methodology is applied, involving stages of understanding, preparation, modeling, evaluation, and deployment. Data from the Central Bureau of Statistics (BPS) and the Ministry of Education's Dapodik system are utilized, incorporating Z-transformation normalization and data cleansing. The clustering results reveal three main clusters with the lowest Davies-Bouldin Index (DBI) at K=3, scoring 0.205. With a total of 514 districts/cities in Indonesia, the results of the needs of each cluster were obtained, namely Cluster 0 consisting of 402 districts/cities requiring increased participation, Cluster 1 covering 49 districts/cities requiring educational facilities, Cluster 2 covering 63 districts/cities requiring the construction of new schools. This study provides valuable insights into addressing disparities in preschool education access and offers guidance for better resource allocation and policy decisions aimed at improving early childhood education infrastructure.