Penerapan K-Means pada Segmentasi Pasar untuk Riset Pemasaran pada Startup Early Stage dengan Menggunakan CRISP-DM

Early stage startup would conduct ideation, problem solving, and market research. One of the stages in research is segmentation. Normally, early startups do not have enough resources, thus many processes are done manually. This encourages inacurracies lessen objectiveness evaluating situation which important for growth startups. focuses on developing a machine learning based application The framework used here CRISP-DM, data mining. has six phases, consists business understanding, preparation, modelling, deployment, evaluation, to identify input output process. model this K-Means, common algorithm clustering or dividing set into groups according their attributes. developed able results form visualization segmentation excel format. With this, process segments market. For future research, could be improved efficiency accuracy model. aspects UI/UX design, used, number clusters, analysis dataset, as well adding predictive feature