Open AccessOptimization of elderly nutrition needs using PSO algorithm: A case study at POSBINDU PTM Sejahtera
Author(s) -
R Rizqullah,
Silvester Dian Handy Permana,
Y Yaddarabullah
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1098/6/062009
Subject(s) - particle swarm optimization , abstinence , calorie , computer science , optimization algorithm , swarm intelligence , environmental health , medicine , algorithm , mathematical optimization , mathematics , psychiatry , endocrinology
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%. The average price of foodstuffs produced by the PSO algorithm is Rp.50,965.