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Abstract

SOCHI: Child’s Nutritional Status Predictor System using Support Vector Machine

Authors: Ronand D. Almazar, James Bernard M. Manzanero & Laender C. Blanco

The system is a web application that supports machine learning, especially Support Vector Machine. It is developed to assist the health worker of Barangay Cadian, Pill, Camarines Sur, in producing technologically aided relative reports. The said system serves as online storage of the dataset and an automatic determination of the health status of the child.

The descriptive-evaluative and applied research and development using agile software
development methodology were adopted for the development of the SOCHI system in the study. Data collection techniques were used such as surveys, observation, Interviews, and continuous improvement of the software application, furthermore, eight (8) health workers of the aforementioned barangay were respondents of the study determined by the sampling technique that considered the same characteristics in order to be an attester for the system.

Barangay Cadian Pill Camarines Sur is using old methods like paper and pen in gathering child’s information. However, these methods encountered issues such as incorrect data collection and analysis, transferring data from one sheet to another, and other factors that affect the worker’s convenience that leads to misinformation. This leads the researchers to propose and develop a system that will serve as A SOCHI: Child’s Nutritional Status Predictor Using Support Vector Machine, a machine learning algorithm used for assessing the datasets, that can be accessed through computers. The developed system was tested by eight (8) respondents composed of barangay health workers as part of software testing and evaluation under ISO 9126 in terms of functionality.

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