Early Stress Detection... 288 Runjati, Rahayu Indonesian Journal of Health Administration (Jurnal Administrasi Kesehatan Indonesia) p-ISSN 2303-3592, e-ISSN 2540-9301 10.20473/jaki.v11i2.2023.288-298 Original Research EARLY STRESS DETECTION DURING PREGNANCY USING E-HEALTH IN THE PANDEMIC Deteksi Dini Stres Selama Masa Kehamilan dengan E-Health pada Masa Pandemi *Runjati 1 , Sri Rahayu 2 1 Midwifery Department, Poltekkes Kemenkes, Semarang, Indonesia 2 Poltekkes Kemenkes, Denpasar, Indonesia Correspondence*: Address: Jl Tirto Agung Pedalangan, Tembalang Banyumanik, Semarang, Indonesia | e-mail: runjati@yahoo.com Abstract Background: Women are more prone to stress during pregnancy than during the postpartum period. Stress during pregnancy is correlated with pregnancy and birth outcomes. Early detection using the e-Health system is an alternative to health services during the pandemic. Aims: The research objective was to produce innovation in early stress detection using an information system based on the e- Health system. Methods: This study was conducted in the Ngaliyan Primary Healthcare Centre with 34 pregnant women. This study utilized both qualitative and quantitative research. Qualitative research was done using the System Development Life Cycle (SDLC), while quantitative research was done using an experimental design with a one-shot case study approach. Results: The e-Health system could automatically identify stress during pregnancy with the TAM questionnaire yielding a very effective result of 85.4%. The average time needed to detect pregnant women’s stress was 230.94 seconds. This system can analyze 374 pregnant women within one day (24 hours), provide services, and report pregnant women’s stress detection results. Conclusions: The e-Health system effectively in conserves time and can be used to record and report early stress in pregnant women. Keywords: early detection, information system, pregnancy, smartphone, stress Abstrak Latar Belakang: Stres rentan terjadi pada masa kehamilan dibandingkan selama masa postpartum. Stres selama kehamilan berhubungan dengan luaran kehamilan dan persalinan. Deteksi dini dengan sistem e-Health sebagai alternatif pelayanan kesehatan pada masa pandemi. Tujuan: Penelitian ini bertujuan untuk menghasilkan inovasi upaya deteksi dini stres dengan sistem informasi menggunakan sistem e-Health yang dapat digunakan secara efektif dalam mengidentifikasi stres ibu hamil. Metode: Jenis penelitian ini adalah penelitian kualitatif dan kuantitatif. Penelitian kualitatif menggunakan Sistem Development Life Cycle (SDLC) dan penelitian kuantitatif menggunakan rancangan experimental dengan pendekatan one-shot case study. Hasil: Sistem e-Health secara otomatis dapat mengidentifikasi stress selama kehamilan dengan kuesioner Technology Acceptance Model (TAM) yang menunjukkan hasil yang sangat efektif 85.4%. Rerata kecepatan waktu yang dibutuhkan mendeteksi status stres ibu hamil adalah 230,94 detik. Sistem ini dapat menganalisis 374 orang ibu hamil dalam satu hari (24 jam) dan juga menyediakan layanan dan melaporkan hasil deteksi stress pada ibu hamil. Kesimpulan: Sistem e-Health dapat mendeteksi stress dalam kehamilan secara efektif. Sistem informasi e-Health juga efektif secara waktu pengisian dan dapat digunakan sebagai pencatatan dan pelaporan terkait deteksi dini stress dalam kehamilan. Kata kunci: kehamilan, stres, deteksi dini, sistem informasi, smartphone Indonesian Journal of Health Administration (Jurnal Administrasi Kesehatan Indonesia) p-ISSN 2303-3592, e-ISSN 2540-9301, Volume 11 No.2 2023, DOI: 10.20473/jaki.v11i2.2023.288-298 Received: 2023-02-14, Revised: 2023-11-20, Accepted: 2023-11-22, Published: 2023-12-02. Published by Universitas Airlangga in collaboration with Perhimpunan Sarjana dan Profesional Kesehatan Masyarakat Indonesia (Persakmi). Copyright (c) 2023 Runjati, Sri Rahayu This is an Open Access (OA) article under the CC BY-SA 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/). How to cite: Runjati and Rahayu, S. (2023) “Early Stress Detection During Pregnancy Using E-Health in The Pandemic”, Indonesian Journal of Health Administration, 11(2), pp. 288-298. doi: 10.20473/jaki.v11i2.2023.288-298.