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All Journal Coreid Journal Jurnal Accounting Information System (AIMS)
Yogi Saputra
Universitas Kebangsaan Republik Indonesia
Computer Science & IT Economics, Econometrics & Finance Education Other

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Classification of Health and Nutritional Status of Toddlers Using the Naïve Bayes Classification Yogi Saputra; Nurfitria Khoirunisa; Syauqi Arinal Haqq
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.8

Abstract

Life is characterized by the presence of symptoms of growth and development. The growth and development of the degree of health of each individual are different. In this case, one of the efforts to improve health status is to improve nutritional status. Nutritional status is the state of the body related to food consumption patterns and the use of nutrients that are tailored to the body's needs. Improving nutritional status is useful for increasing body resistance and promoting normal growth. In the daily actualization of the nutritional status of toddlers at the posyandu, it is usually obtained through anthropometric measurements, namely by using the weight/age index or weight-for-age to determine nutritional status. However, in measuring with anthropometry, there was confusion in determining nutritional quality, so to get accurate results, a data mining method is needed, namely the Naive Bayes Classification (NBC) Algorithm, which will be implemented in research. With this research, it is hoped that it can help posyandu cadres in the Baros sub-district, Cimahi sub-district, and Cimahi city determine the level of health and nutritional status of toddlers better and more accurately.
Perancangan Strategis Sistem Informasi Financial Planning Management dengan Robo-Advisor Yogi Saputra; Ela Siti Nurpajriah; Siti Kustinah; Novianti Indah Putri
Jurnal Accounting Information System (AIMS) Vol. 6 No. 2 (2023)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v6i2.787

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.
Co-Authors Ela Siti Nurpajriah Novianti Indah Putri Nurfitria Khoirunisa Siti Kustinah Syauqi Arinal Haqq