Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Vol. 6 No. 1 (2026): October 2026

Selection of Toddlers at Risk of Stunting in Binjai City using the MOORA Method

Kelvinsyah Reynaldi (STMIK Kaputama)
Relita Buaton (STMIK KAPUTAMA)
Suci Ramadani (STMIK KAPUTAMA)



Article Info

Publish Date
15 Oct 2026

Abstract

Stunting is a growth and development disorder in toddlers caused by long-term malnutrition, which can occur from pregnancy to 24 months of age. The Binjai City Population Control and Family Planning Office has an important role in efforts to prevent and handle stunting, but the selection of toddlers at risk of stunting still faces obstacles because the assessment process is still carried out manually, so it becomes less effective and takes a long time so that it has the potential to cause errors in decision-making. Therefore, this study aims to build a Decision Support System (SPK) that is able to help the Binjai City PPKB Office determine the selection of toddlers at risk of stunting objectively, quickly, and accurately. The method used in this study is MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) which is a method that has the ability to solve multicriteria decision-making problems through the process of normalization, weighting, and calculation so as to produce alternative rankings based on priority levels. The research data was obtained through observations, interviews, and documentation at the Binjai City Population Control and Family Planning Office. The results of the study show that the MOORA method is able to produce a ranking of toddlers based on the level of stunting risk in a systematic and objective manner, so that it can help the Binjai City PPKB office for decision-makers and increase the effectiveness of prioritizing toddlers who need further handling. The Implementation of the Selection of Toddlers at Risk of Stunting The MOORA Decision Support System Method is expected to support stunting prevention and control programs in a more targeted manner.

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Journal Info

Abbrev

JAIEA

Publisher

Subject

Automotive Engineering Computer Science & IT Control & Systems Engineering

Description

The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering ...