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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.18 No.4
- 발행연도
- 2024.12
- 수록면
- 203 - 213 (11page)
- DOI
- 10.5626/JCSE.2024.18.4.203
이용수
초록· 키워드
오류제보하기
Stunting is a significant health issue in Indonesia, affecting the growth of children under five due to chronic malnutrition. Traditional methods for early identification of at-risk children often fall short, highlighting the need for advanced predictive models like machine learning (ML). This study compares the performance of support vector machine (SVM) and Decision Tree algorithms using data from Bandarharjo Community Health Centers. Initial results show poor performance for SVM models with linear and polynomial kernels, achieving F1-scores between 0% and 54%. The decision tree algorithm performed slightly better with an F1-score of 64%. To improve detection accuracy, the Synthetic Minority Over-sampling Technique (SMOTE) was applied as a data balancing technique to address class imbalance. After applying SMOTE, the decision tree achieved an F1-score of 97%, proving to be the most effective model. The SVM with the radial basis function (RBF) kernel also improved significantly, achieving an F1-score of 94%. These findings demonstrate that data balancing techniques like SMOTE are crucial for enhancing the accuracy and effectiveness of ML models in detecting stunting, enabling more timely and accurate health interventions.
목차
Abstract
I. INTRODUCTION
II. MODEL
III. RESULTS AND DISCUSSION
IV. CONCLUSION
REFERENCES
참고문헌 (19)
참고문헌 신청
C. R. Titaley, I. Ariawan, D. Hapsari, A. Muasyaroh, and M. J. Dibley, “Determinants of the stunting of children under two years old in Indonesia: a multilevel analysis of the 2013 Indonesia basic health survey,” Nutrients, vol. 11, no. 5, article no. 1106, 2019. https://doi.org/10.3390/nu11051106
J. Mayneris-Perxachs and J. R. Swann, “Metabolic phenotyping of malnutrition during the first 1000 days of life,” European Journal of Nutrition, vol. 58, no. 3, pp. 909-930, 2019. https://doi.org/10.1007/s00394-018-1679-0
J. Aurima, S. Susaldi, N. Agustina, A. Masturoh, R. Rahmawati, and M. T. M. Madhe, “Faktor-faktor yang berhubungan dengan kejadian stunting pada balita di Indonesia [Factors associated with stunting in toddlers in Indonesia],” Open Access Jakarta Journal of Health Sciences, vol. 1, no. 2, pp.43-48, 2021. https://doi.org/10.53801/oajjhs.v1i3.23
M. G. Daffa and P. H. Gunawan, “Stunting classification analysis for toddlers in Bojongsoang: a data-driven approach,” in Proceedings of 2024 2nd International Conference on Software Engineering and Information Technology (ICoSEIT), Bandung, Indonesia, 2024, pp. 42-46. https://doi.org/10.1109/ICoSEIT60086.2024.10497515
P. Webb, H. Luo, and U. Gentilini, “Measuring multiple facets of malnutrition simultaneously: the missing link in setting nutrition targets and policymaking,” Food Security, vol. 7, pp. 479-492, 2015. https://doi.org/10.1007/s12571-015-0450-0
J. Mayneris-Perxachs and J. R. Swann, “Metabolic phenotyping of malnutrition during the first 1000 days of life,” European Journal of Nutrition, vol. 58, no. 3, pp. 909-930, 2019. https://doi.org/10.1007/s00394-018-1679-0
J. Aurima, S. Susaldi, N. Agustina, A. Masturoh, R. Rahmawati, and M. T. M. Madhe, “Faktor-faktor yang berhubungan dengan kejadian stunting pada balita di Indonesia [Factors associated with stunting in toddlers in Indonesia],” Open Access Jakarta Journal of Health Sciences, vol. 1, no. 2, pp.43-48, 2021. https://doi.org/10.53801/oajjhs.v1i3.23
M. G. Daffa and P. H. Gunawan, “Stunting classification analysis for toddlers in Bojongsoang: a data-driven approach,” in Proceedings of 2024 2nd International Conference on Software Engineering and Information Technology (ICoSEIT), Bandung, Indonesia, 2024, pp. 42-46. https://doi.org/10.1109/ICoSEIT60086.2024.10497515
P. Webb, H. Luo, and U. Gentilini, “Measuring multiple facets of malnutrition simultaneously: the missing link in setting nutrition targets and policymaking,” Food Security, vol. 7, pp. 479-492, 2015. https://doi.org/10.1007/s12571-015-0450-0
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