Expert System Quality Analysis: SORTING (Sorong Atasi Stunting) Using WebQual 4.0 - Manuhutu, Melda Agnes; Uktolseja, Lulu Jola; Manurung, Tagor (JOIV : International Journal on Informatics Visualization, 2025)
Stunting is a public health issue that frequently occurs in Indonesia, particularly in Southwest Papua, where it is exacerbated by inadequate maternal nutrition and low parental education. The SORTING's web-based platform was developed to bridge this gap by providing real-time, easily accessible information to pregnant and breastfeeding mothers to improve baby health outcomes. This study assesses the platform's usability quality, information quality, interaction quality, and user satisfaction to increase its effectiveness in underserved areas. The researchers used an explanatory quantitative approach. The structural model formulates that Y = 0.380 X1 + 0.262 X2 + 0.309 X3. The results show the significant positive impacts of these three variables X1 (usability), X2 (information), and X3 (interaction), on variable Y (satisfaction). The p-values are 0.014, 0.034, and 0.043, all below 0.05, indicating statistical significance. The key finding shows that SORTING as an expert system provides good usability, reliable information, and interactive features to enhance user satisfaction. The accessibility of SORTING allows users to assess the risk of stunting in neonates and take necessary preventive measures. The contribution from the research results is that SORTING, which has been built, implemented, and evaluated for quality, can significantly enhance stunting awareness education. This study demonstrates SORTING's ability to improve stunting awareness education in remote locations by increasing user engagement and providing actionable information. Future research should further explore user experiences using a qualitative approach.