K-Means Algorithm and Binary Search on FiBuSI

Abstract

Purpose: Create an application called FiBuSI (Find Business and Stock Investment) using the k-means algorithm and binary search for data search features. This application is intended for entrepreneurs and investors where they can interact with each other to build a joint business.Method: Using the RAD (Rapid Application Development) Method which focuses on system testing based on user experience related to Blackbox Testing using the Katalon Studio tools for testing functions on the FiBuSI application.Result: Based on the results of testing the FiBuSI application which focuses on the success of application functions and algorithm implementation, that each application function is successfully executed (PASSED) based on testing using the Katalon Studio tools. Meanwhile, testing the k-means algorithm (data filter) and binary search (search for letter data) was also successfully carried out by testing it directly by the user on the FiBuSI application and also using the results from the Katalon Studio tools.State of the art: Based on several studies that have been done previously related to the use of the k-means algorithm and binary search that this algorithm is carried out on 2 different features but in 1 application for business data search. In concept, the FiBuSI application focuses on bringing together entrepreneurs and investors in one platform.