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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer AKSIOMA Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Journal Of Nursing Practice LENSA (Lentera Sains): Jurnal Pendidikan IPA EDUKATIF : JURNAL ILMU PENDIDIKAN Sehat Masada Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) J-Intech (Journal of Information and Technology) Jurnal Multidisiplin Indonesia
Indriati Indriati
Universitas PGRI Semarang
Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : SITEKIN: Jurnal Sains, Teknologi dan Industri

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Comparison Genetics Algorithm and Particle Swarm Optimization in Dietary Recommendations for Maternal Nutritional Fulfillment Kurnianingtyas, Diva; Daud, Nathan; Indriati, Indriati; Muflikhah, Lailil
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 21, No 2 (2024): June 2024
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v21i2.28937

Abstract

Fulfilling maternal nutrition is an NP-hard problem. Optimization techniques are required to solve its complexity. This issue is crucial as it affects the number of stunted toddlers in Indonesia. Stunting begins in the womb due to inadequate maternal nutrition during pregnancy. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are optimization methods applied to NP-hard problems, including medicine. Their performance has not been compared in this field. This study aims to identify an alternative method for recommending daily menus based on maternal nutritional needs. There are 55 food ingredients used to fulfill five menu parts: staple food (SF), vegetables (VG), plant source food (PS), animal source food (AS), and complementary (CP). Nutritional adequacy for prenatal is determined by Total Energy Expenditure (TEE) based on basal energy, daily activity, and stress levels. Results show PSO outperforms GA in average fitness values, 30.45 to 102.51, while GA excels in execution time, 0.33 to 23.22 seconds. PSO is preferred for effectiveness, and GA for efficiency, but given the problem's urgency, PSO is recommended. Exploring other metaheuristic methods is advised to enhance menu recommendation solutions for maternal nutrition. Additionally, expanding the food database is necessary for more varied maternal menu to support stunting prevention.
Co-Authors Achmad Ridok Arbawa, Yoke Kusuma Arief Andy Soebroto Awalina, Aisyah Bayu Rahayudi Brilliansyach, Raihan Fikri Candra Dewi Daud, Nathan Edy Santoso Fiqri, Miftahul Fitra Abdurrachman Bachtiar Ginting, Rosalina Br. Hendra Darmawan Heni Pujiastuti Ibnu, Mohammad Issa Arwani Karlitasari, Karlitasari Kohei Arai Kurnianingtyas, Diva Lailil Muflikhah M. Hidayat M. Zainal Abidin Marji Marji Mugi Hartoyo Muh Arif Rahman murtanti, Riris Tri Nadia Artha Dewi Nurannisa, Nadhira Nurkolis Nurkolis, Nurkolis Nurul Hidayat Oktaviana, Natasya Eldha Permataningrum, Sandra Elanda Aza Purwaniati, Sulis Ricardo, Muhammad Erico Rizal Setya Perdana Santoso, Andri Satria, Rangga Adi Setyorini, Tri Endah Siregar, Rifki Akbar Sri Utami Dwiningsih Sutrisno, Sutrisno Suyono Suyono Tutik Setyowati, Tutik Vasya, M Azka Obila Yeni Mahwati Yuita Arum Sari Zhafira, Dhaifa Farah