Optimization of elderly nutrition needs using PSO Algorithm: A Case Study at POSBINDU PTM Sejahtera Rafii Rizqullah (a*), Silvester Dian Handy Permana (a), Yaddarabullah (a)
a) Program Studi Teknik Informatika, Universitas Trilogi
Jl.TMP Kalibata No.1, Jakarta 12760, Indonesia
*rafiirizqullah[at]trilogi.ac.id
Abstract
POSBINDU PTM Sejahtera is a health post that aims to increase awareness of the elderly in preventing non-communicable diseases. According to Departemen Kesehatan, this disease can be caused by food consumption. The food consumed must include vegetables and fruit to enhance the concept of active aging. However, these recommendations are not comparable with the POSBINDU PTM screening data. Screening data mentioned that only 3.5% of 73 elderly people consume vegetables and fruit three times a day. Factors that inhibit the elderly in consuming healthy food are the officers only giving food abstinence advice and expensive food staples. The problem of this optimization model can be solved by the artificial intelligence algorithm, Particle Swarm Optimization (PSO). The results of this study, PSO can provide varied food recommendations at a minimal price (optimization model). The calorie and carbohydrate content gets a value of <10% of the nutritional needs of the elderly, while the protein and fat content produce a greater difference of > 10%. The average price of foodstuffs produced by the PSO algorithm is Rp.50,965.
