Development Edge Device Monitoring System Stunting and Malnutrition in Golden age 0–5 years Integrated with AI
DOI:
10.29303/jppipa.v9iSpecialIssue.6397Published:
2023-12-25Issue:
Vol. 9 No. SpecialIssue (2023): UNRAM journals and research based on science education, science applications towards a golden Indonesia 2045Keywords:
Edge Devices, Golde Age, Machine Learning, Malnutrition, StuntingResearch Articles
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Abstract
Golden age is the best period for a child's growth, monitoring of growth and development must be carried out regularly. Growth and development disorders in children are stunting and malnutrition. This incident also prompted the government through the Ministry of Health to create a special program towards a golden Indonesia 2045 to monitor stunting and disease, especially in children. The prevalence of stunting decreased to 21.6% from 24.4% in 2022. Early detection of stunting and malnutrition, where the research object is children aged 0-5 years. This prototype was built using a load cell sensor, a study of the use of optical sensors and ultrasonic sensors to measure body height, and a MAX sensor to detect children's anemia. The integration of this tool combines IoT and AI. The results obtained to validate the use of load cells have a reading error of 0.01% with an accuracy of 99%. Comparison using optical sensors and ultrasonic sensors. Optical sensors have result average error of 0.01, accuracy 98.99%, ultrasonic sensors error was 0. 15 with 85% accuracy. To measure malnutrition, the anemia parameters were processed using the Dense Neural Network (DNN) model with 256 neurons showing an accuracy of 98.03%.
References
Anggorowati, L. (2013). Anemia Terhadap Pertumbuhan Dan Perkembangan Anak Malnutrisi. Jurnal Kesehatan Masyarakat Andalas, 11(1), 87–95.
Bayangkari Karno, A. S. (2020). Analisis Data Time Series Menggunakan Lstm (Long Short Term Memory) Dan Arima (Autocorrelation Integrated Moving Average) Dalam Bahasa Python. Ultima Infosys : Jurnal Ilmu Sistem Informasi, 11(1), 1–7. Https://Doi.Org/10.31937/Si.V9i1.1223
Bitew, F. H., Sparks, C. S., & Nyarko, S. H. (2022). Machine Learning Algorithms For Predicting Undernutrition Among Under-Five Children In Ethiopia. Public Health Nutrition, 25(2), 269–280. Https://Doi.Org/10.1017/S1368980021004262
Bkkbn. (2022). Angka Stunting. Https://Www.Bkkbn.Go.Id/Berita-Indonesia-Cegah-Stunting
Children, U., & New, P. (2023). Machine Learning Algorithms For Predicting Stunting Among Under-Five Children In Papua New Guinea.
Clark, S. (208 C.E.). Iron Deficiency Anemia. Nutrition In Clinical Practice,.
Fenta, H. M., Zewotir, T., & Muluneh, E. K. (2021). A Machine Learning Classifier Approach For Identifying The Determinants Of Under-Five Child Undernutrition In Ethiopian Administrative Zones. Bmc Medical Informatics And Decision Making, 21(1), 1–12. Https://Doi.Org/10.1186/S12911-021-01652-1
Fundrika, B. A. (2022). Menuju Indonesia Bebas Stunting, Bisakah Gerakan Makan Telur Dan Ikan Setiap Hari Jadi Solusi? In Suara.Com. Https://Www.Suara.Com/Health/2022/09/09/070500/Indonesia-Targetkan-Prevalensi-Stunting-14-Persen-Di-2024-Bisakah-Gerakan-Makan-Telur-Setiap-Hari-Jadi-Solusi
Humas Bkpk. (N.D.). Dua Titik Penting Intervensi Stunting - Badan Kebijakan Pembangunan Kesehatan _ Bkpk Kemenkes.
Jahidur Rahman Khan, Jabed H., J. H. T. (201 C.E.). A Machine Learning Classifier Approach For Identifying The Determinants Of Under-Five Child Undernutrition In Ethiopian Administrative Zones. Informatics For Health And Social Care, 46(4), 425–442.
Kemenkes Ri. (2010). 24 Indikator Kesehatan Dalam Ipkm – Sehat Negeriku. Https://Sehatnegeriku.Kemkes.Go.Id/Baca/Rilis-Media/20101210/37636/24-Indikator-Kesehatan-Dalam-Ipkm/
Kemenkes Ri. (2023). Prevalensi Stunting Di Indonesia Turun Ke 21,6% Dari 24,4%. In 25 Januari 2023 (P. 1). Https://Sehatnegeriku.Kemkes.Go.Id/Baca/Rilis-Media/20230125/3142280/Prevalensi-Stunting-Di-Indonesia-Turun-Ke-216-Dari-244/#:~:Text=Standard Who Terkait Prevalensi Stunting,Usia 6 Sampai 2 Tahun.
Kementrian Kesehatan. (2020). Peraturan Menteri Kesehatan Republik Indonesia Nomor 2 Tahun 2020 Tentang Standar Antropometri Anak.
Krishna Kishore, K., Venkata Suman, J., Lakshmi Mnikyamba, I., Rao Polamuri, S., & Kishore Koagnti, K. (2023). Prediction Of Malnutrition In New Born Infants Using Machine Learning Techniques Prediction Of Malnutrition In Newborn Infants Using Machine Learning Techniques. Https://Doi.Org/10.21203/Rs.3.Rs-2958834/V1
Md. Merajul Islam A F, Md. Jahanur Rahman A, Md Moidul Islam A, Dulal Chandra Roy A, N.A.M. Faisal Ahmed B, Sadiq Hussain C, Md Amanullah D, Md. Menhazul Abedin E, M. M. E. (2022). Application Of Machine Learning Based Algorithm For Prediction Of Malnutrition Among Women In Bangladesh. International Journal Of Cognitive Computing In Engineering, 3, 46–57. Https://Doi.Org/International Journal Of Cognitive Computing In Engineering
Nidianti, E., Nugraha, G., Aulia, I. A. N., Syadzila, S. K., Suciati, S. S., & Utami, N. D. (2019). Pemeriksaan Kadar Hemoglobin Dengan Metode Poct (Point Of Care Testing) Sebagai Deteksi Dini Penyakit Anemia Bagi Masyarakat Desa Sumbersono, Mojokerto. Jurnal Surya Masyarakat, 2(1), 29. Https://Doi.Org/10.26714/Jsm.2.1.2019.29-34
Ningsih, E. W., Fajrin, H. R., & Fitriyah, A. (2019). Pendeteksi Hemoglobin Non Invasive. Medika Teknika : Jurnal Teknik Elektromedik Indonesia, 1(1). Https://Doi.Org/10.18196/Mt.010102
Nurlita, A. N., Wigati, M., Hasanbasri, M., Jumarko, J., & Helmyati, S. (2021). Development Of Stunting Early Detection Kit For Children Under Two Years: Validity And Reliability. Jurnal Gizi Dan Pangan, 16(1), 39–46. Https://Doi.Org/10.25182/Jgp.2021.16.1.39-46
P2ptm Kemenkes Ri. (2018). Cegah Stunting Dengan Perbaikan Pola Makan, Pola Asuh Dan Sanitasi - Direktorat P2ptm. In Kemkes.Go.Id. Http://P2ptm.Kemkes.Go.Id/Kegiatan-P2ptm/Subdit-Penyakit-Diabetes-Melitus-Dan-Gangguan-Metabolik/Cegah-Stunting-Dengan-Perbaikan-Pola-Makan-Pola-Asuh-Dan-Sanitasi
Rafaleony Berlian Putri Widodo, Dkk. (2022). E-Stare (Electronic Stunting Care): Inovasi Aplikasi Pencegah Stunting Sebagai Upaya Preventif Dan Promotif Berbasis Iot (Internet Of Things) Untuk Mencapai Indonesia Bebas Stunting. In Indonesian Student Competition (Insco-1) Asosiasi Institusi Pendidikan Ners Indonesia (Aipni) (Vol. 33, Issue 1, Pp. 1–12).
Rezza, M. (N.D.). Perancangan Dan Implementasi Alat Ukur Kadar Hemoglobin Darah Secara Non-Invasive Berbasis Arduino.
Roni, M., Syauqy, D., & Primananda, R. (2022). Rancang Bangun Sistem Deteksi Dini Status Gizi Dan Risiko Stunting Pada Balita Berdasarkan Tinggi Dan Berat Badan Menggunakan Metode Jst Backpropagation. 6(7), 3155–3160. Http://J-Ptiik.Ub.Ac.Id
Unicef. (2022). Malnutrition In Children - Unicef Data. In Unicef. Https://Data.Unicef.Org/Topic/Nutrition/Malnutrition/
Who. (2020). Stunting Prevalence Among Children Under 5 Years Of Age (%) (Model-Based Estimates). In Global Health Observatory Data Repository (P. 35). Https://Www.Who.Int/Data/Gho/Data/Indicators/Indicator-Details/Gho/Gho-Jme-Stunting-Prevalence
Zenit Rohmaningrum, D. (2021). Pengembangan Aplikasi “Anc.Mia Care†Sebagai Upaya Deteksi Dini Dan Pencegahan Anemia Pada Ibu Hamil Dalam Rangka Mewujudkan Indonesia Bebas Stunting (Issue 22020120120008, Pp. 2013–2015).
Author Biographies
Nurdina Widanti, universitas jayabaya
Aditya Alamsyah, Universitas Jayabaya
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Copyright (c) 2023 Nurdina Widanti, Wike Handini, Nur Witdi Yanto, Aditya Alamsyah
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