Predicting Snack Food Production (Pentol) Using Fuzzy Logic

Hindarto (Muhammadiyah University of Sidoarjo, Indonesia)
Moch Gesang Akbar Jani (Muhammadiyah University of Sidoarjo, Indonesia)
Nuril Lutvi Azizah (Muhammadiyah University of Sidoarjo, Indonesia)
Cindy Taurusta (Muhammadiyah University of Sidoarjo, Indonesia)

IJHCS
Vol. 8 No. 2 (2026): International Journal of Human Computing Studies (IJHCS)

Fluctuating market demand and limited inventory are challenges in determining the optimal amount of production, especially for small businesses such as meatball snack production. This study aims to determine the addition of meatball production using the Mamdani fuzzy logic method. This system uses three input variables: income, inventory, and sales demand, and one output in the form of the recommended amount of production. Each variable is modeled with a triangular membership function. The case study shows that with an income of Rp650,000, an inventory of 600 pieces, and a demand of 1,500 pieces, the fuzzy system recommends an additional production of 500 pieces. These results prove that the Mamdani fuzzy method is effective in helping production decision making amidst subjective or vague data uncertainty.