A Decision Support System for Selecting Beneficiaries of the Free Nutritious Meal Program Using Fuzzy Possibilistic C-Means

M. Husen Al Farisy (Department of Mathematics Education, Universitas Nahdlatul Ulama Sunan Giri, 62115, Indonesia)
M. Ivan Ariful Fathoni (Department of Mathematics Education, Universitas Nahdlatul Ulama Sunan Giri, 62115, Indonesia)
Anisa Fitri (Department of Mathematics Education, Universitas Nahdlatul Ulama Sunan Giri, 62115, Indonesia)
Nabila Alisa Rohmah (Department of Mathematics Education, Universitas Nahdlatul Ulama Sunan Giri, 62115, Indonesia)
Siti Nur Laili Zuhri (Department of Mathematics Education, Universitas Nahdlatul Ulama Sunan Giri, 62115, Indonesia)

Zero : Jurnal Sains, Matematika, dan Terapan
Vol 10, No 1 (2026): Zero: Jurnal Sains Matematika dan Terapan

The Free Nutritious Meal Program (MBG) aims to improve students’ nutritional status, but beneficiary selection is challenged by data uncertainty and overlapping criteria. This study proposes a decision support system based on the Fuzzy Possibilistic C-Means (FPCM) algorithm. The dataset consists of 200 students from Bojonegoro Regency using five indicators: nutritional status, household income, family size, participation in social assistance, and distance to school. The methodology includes data standardization, clustering using Fuzzy C-Means (FCM) and FPCM, and evaluation using Partition Coefficient, Silhouette Score, and Dunn Index. The results classify students into three groups: 52% not eligible, 18.5% moderately eligible representing borderline cases requiring further verification, and 29.5% eligible. FPCM achieves higher cluster clarity with a Partition Coefficient of 0.84 compared to 0.74 in FCM, while other evaluation metrics indicate comparable structural quality between methods. These findings indicate that FPCM provides a more interpretable and robust framework for decision-making under uncertainty.