Early Detection and Recommendation of Anemia in Adolescent Females Using Artificial Intelligence

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Vol. 11 No. 3 (2023): 2023 Volume -11 - Issue 3

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Published
September 16, 2023
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Early Detection and Recommendation of Anemia in Adolescent Females Using Artificial Intelligence

https://doi.org/10.61096/ijamscr.v11.iss3.2023.325-328
Adinda Navis Nurlailiah
Department of Midwifery Master of Applied Science in Midwifery Program, Semarang Health Polytecnic, Semarang, Indonesia
M. Choiroel Anwar
Semarang Health Polytecnic, Semarang, Indonesia.
Kurnianingsih
Semarang State Polytecnic, Semarang, Indonesia.

Corresponding Author(s) : Adinda Navis Nurlailiah

navisadinda@gmail.com

International Journal of Allied Medical Sciences and Clinical Research, Vol. 11 No. 3 (2023): 2023 Volume -11 - Issue 3

Abstract

Background: The usual detection of anemia is checking by hemoglobin (Hb) levels. But the process requires quite a lot of preparation and implementation stages so the adolescent can not do it independently, in real-time, and anywhere. Therefore, an early detection system for anemia in adolescent females was developed using artificial intelligence. Where in the system will display the results of anemia detection based on signs, symptoms and risk factors as well as recommendations for anemia prevention.


Purposes: Innovate early detection systems and recommendations for anemia in adolescent females using artificial intelligence based on system accuracy values.


Methods: The method in this research is the research and development method. Using 430 data on signs of symptoms, risk factors, and Hb examination results for adolescent females to build a detection and recommendations system.


Results: Based on 4 algorithm tests, the highest system accuracy value is 81.3% using K-nearest neighbors (KNN) and the recommendation accuracy is 90.9%.


Conclusion: The study is proven to be able to build an anemia detection system using artificial intelligence K-Nearest Neighbor with the result of a system accuracy rate of 81,3%, and the recommendation system for anemia uses artificial intelligence forward chaining method with the results of a system accuracy rate of 90,9%.

Keywords

early detection anemia adolescent females artificial intelligence
1.
Adinda Navis Nurlailiah, M. Choiroel Anwar, Kurnianingsih. Early Detection and Recommendation of Anemia in Adolescent Females Using Artificial Intelligence. Int. J. of Allied Med. Sci. and Clin. Res. [Internet]. 2023 Sep. 16 [cited 2025 Sep. 20];11(3):325-8. Available from: https://ijamscr.com/ijamscr/article/view/1403
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