The data used for this visualization was the collected 17 qualitative responses collected from Simon of Cyrene, an organization for people with disabilities, during the deployment at Legazpi City, Albay using the Malasakit toolkit. Data cleaning and filtering methods were performed like the removal of stop words, symbols, numbers, and conversion to lowercase was observed. The data was then preprocessed to count its term frequency and inverse document frequency to gather important feature words. The qualitative responses were experimentally analyzed with different values of k clusters. Silhouette coefficient, an intrinsic evaluation metric for calculating clusters, was used to test the separation between two clusters. The visualizations below shows the clustered 17 Legazpi responses using Tableau software for the scatter plot and WordItOut for word cloud visualization.