Acceptance of Toddler Nutrition Decision Support Systems Using the Technology Acceptance Model (TAM) Method
- DOI
- 10.2991/assehr.k.220207.030How to use a DOI?
- Keywords
- Stunting; TAM; Early Detection
- Abstract
One of the Sustainable Development Goals (SDGs) is terminating the malnutrition 1n 2030. Stunting is malnutrition due to lack of nutritional intake for a long time due to feeding that does not match nutritional needs. The toddler nutrition decision support system was created to help parents of toddlers and health cadres to perform early detection of stunting. The researchers intend to obtain an overview of the level of acceptance of the stunting early detection system by residents of the village of Kemuning Lor, Jember Regency. This research was descriptive research, and the number of these community was 20 people who are village officials. Data analysis was conducted through scoring and presented in tables and percentages. The results showed that the level of system acceptance based on the perceived usefulness aspect had the highest value 89.75%, variable perceived ease of use 87,08%, variable behavioral intention to use 86,25%, variable attitude toward using 85,94%. It can be concluded that the community accepts stunting early detection system technology because the system is simple to use and the community feels the benefits. The development of an early stunting detection system is still needed as an effort to reduce stunting cases.
- Copyright
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Gamasiano Alfiansyah AU - Mudafiq Riyan Pratama AU - Selvia Juwita Swari PY - 2022 DA - 2022/02/17 TI - Acceptance of Toddler Nutrition Decision Support Systems Using the Technology Acceptance Model (TAM) Method BT - Proceedings of the 2nd International Conference on Social Science, Humanity and Public Health (ICOSHIP 2021) PB - Atlantis Press SP - 186 EP - 191 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220207.030 DO - 10.2991/assehr.k.220207.030 ID - Alfiansyah2022 ER -