Fedri Ruluwedrata Rinawan, Afina Faza, Ari Indra Susanti, Wanda Gusdya Purnama, Noormarina Indraswari, Didah, Dani Ferdian, Siti Nur Fatimah, Ayi Purbasari, Arief Zulianto, Atriany Nilam Sari, Intan Nurma Yulita, Muhammad Fiqri Abdi Rabbi, Riki Ridwana
Posyandu is an Indonesian mother-child health, community-based healthcare. The provision of the Posyandu data quality map is crucial for analyzing results but is limited. This research aimed to (a) demonstrate data quality analysis on its completeness, accuracy, and consistency and (b) map the data quality in Indonesia for evaluation and improvement. An observational study was conducted using the Posyandu application. We observed data in Indonesia from 2019 to 2021. Data completeness was identified using children’s visits/year. Data accuracy was analyzed using WHO anthropometry z-score and implausible z-score values analyzing the outliers. Cronbach’s α of variables was used to know data consistency. STATA 15.1 SE and QGIS 3.10 was used to analyze and map the quality. Data completeness and accuracy in three years show a good start for the pilot project area, continued with declines in pandemic time, while some other areas demonstrated a small start, then slightly increased. The overall consistency decreased through the study period. A good report on data completeness can occur initially in a pilot project area, followed by others. Data accuracy and consistency can decrease during the pandemic. The app can be promising when synchronized with the government health information system. © 2022 by the authors.
Department of Public Health, Faculty of Medicine, Universitas Padjadjaran, Jalan Ir. Soekarno KM. 21, Jatinangor, Sumedang, 45363, Indonesia; Center for Health System Study and Health Workforce Education Innovation, Faculty of Medicine, Universitas Padjadjaran, Jl. Eyckman No. 38, Bandung, 40161, Indonesia; Indonesian Society for Remote Sensing Branch West Java, Institut Teknologi Bandung, Gedung Labtek IX-C lt.3 Jalan Ganesha 10, Bandung, 40132, Indonesia; Master of Public Health Study Program, Faculty of Medicine, Universitas Padjadjaran, Jalan Eyckman No. 38 Gedung RSP Unpad Lantai 4, Bandung, 40161, Indonesia; Biomedical Engineering Study Program, School of Electrical Engineering, Telkom University, Jl. Telekomunikasi No. 1, Terusan Buahbatu—Bojongsoang, Sukapura, Dayeuhkolot, Bandung, 40257, Indonesia; Informatics Engineering Study Program, Faculty of Engineering, Universitas Pasundan, Jl. Dr. Setiabudi No. 193, Bandung, 40153, Indonesia; Postgraduate Master Study Program of Informatics Engineering, Universitas Langlangbuana, Jl. Karapitan No. 116, Cikawao, Kec. Lengkong, Bandung, 40261, Indonesia; Midwifery Study Program, Faculty of Medicine, Universitas Sebelas Maret, Jl. Ir. Sutami No. 36, Kentingan, Jebres, Surakarta, 57126, Indonesia; Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jalan Ir. Soekarno KM. 21, Jatinangor, Sumedang, 45363, Indonesia; Research Center for Artificial Intelligence and Big Data, Universitas Padjadjaran, Jalan Ir. Soekarno KM. 21, Jatinangor, Sumedang, 45363, Indonesia; Geographic Information Science Study Program, Faculty of Social Sciences Education, Universitas Pendidikan Indonesia, Jalan Dr. Setiabudi No. 299, Bandung, 40154, Indonesia
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