Perancangan Strategis Sistem Informasi Financial Planning Management dengan Robo-Advisor

Abstract

The pace of information technology growth in the modern day is so rapid that financial fraud has now spread to renewable technologies. The only approach to guarantee future financial security is to invest. However, the vast array of investment options—including stocks, gold, and other investments—often makes it difficult for people to make the best decision. Many millennials are still apprehensive about investing. This results from a lack of understanding about effective investing. A machine learning information system is necessary to assist in the selection of investment products in order to boost the community's and millennials' interest in investing. The Markowitz and K-Nearest Neighbor algorithms were used in the system's construction. Finding recommendations for investment portfolios that match the risk profile can be aided using the K-Nearest Neighbor approach, which is a machine learning technique. Based on a comparison of the sharpe ratio findings from system calculations and manual calculations, the accuracy level of the Markowitz and KNN approaches, which was set at 99.15%, was established.