MACHINE LEARNING BERBASIS DESKTOP DAN WEB DENGAN METODE JARINGAN SYARAF TIRUAN UNTUK SISTEM PENDUKUNG KEPUTUSAN - Handayanto, Rahmadya Trias; Herlawati, Herlawati (Jurnal Komtika (Komputasi dan Informatika), 2020)
Machine learning application demand is increased massively because it provides good ability in the classification that is needed by decision makers. Machine learning application uses a programming language with strong characteristics in computing, usually the back-end programming language, such as Matlab, Python, R, etc. The obstacle faced by the decision support system developer is preparing an interface that makes it easy for the user. Some back-end programming languages have provided a good interface. Therefore, in this study they were compared by taking the case of a scholarship decision support system. The language used is Python with two web-based applications including Google Interactive Notebook and Flask framework. Both devices have their respective advantages and are worthy of being the first choice in the design of decision support systems.Python has advantages with framework Flask support and Matlab is easy in interface design.