K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers - Herayati Herayati; Andronias Siregar; Hariyanto Hariyanto (LPPM STIKI MALANG, 2025)
Television remains one of the most influential mass media platforms for disseminating information and entertainment to the public, with one notable example being the I’Murojaah program aired by Muslim TV on MNC Channels. The objectives of this study are to identify the level of viewer satisfaction with the I’Murojaah program, determine the indicators influencing viewer satisfaction, classify viewers based on their satisfaction levels, and provide recommendations to program managers to improve quality and viewer satisfaction. This study employs a qualitative approach using the K-Means Clustering algorithm. The data used in this study were obtained through a survey distributed to 100 respondents, covering several viewer satisfaction indicators such as content quality (6 questions) and program presentation (6 questions). The collected data were then grouped and analyzed. The results of the first cluster iteration distance calculation consisted of 84 viewers who were very satisfied, while the second cluster consisted of 16 viewers with relatively low satisfaction levels. The Davies Bouldin Index values were -0.674 for class 2 clustering, -2.001 for class 3 clustering, -1.961 for class 4 clustering, and clustering class 5 (-2.000). In conclusion, the best clustering performance results were for classes 2, 3, 4, and 5. The smallest Davies Bouldin Index value was for clustering class 2. Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality.