2 research outputs found
Pengembangan Aplikasi Berbasis Web untuk Skrining Tingkat Depresi Ibu Pasca Melahirkan Menggunakan Skala EPDS dan PHQ-9
No full textAnxiety and depression are mental health issues that are common in mothers during pregnancy and after childbirth. The prevalence of anxiety and depression among pregnant women is 12.6%, and among postpartum women, it is 10.1%. However, mental health screening is still not an integral part of comprehensive antenatal or postnatal care. This research aims to develop a website-based application for screening postpartum maternal depression levels using the EPDS and PHQ-9 scales. The method used involves application development using the PHP programming language and implementing the EPDS and PHQ-9 scales as assessment instruments. The research findings are a screening application that can help postpartum mothers self-assess their level of depression. The website has been successfully implemented and can be accessed online via the link https://postnatalcare.my.id/. The application is expected to serve as a screening tool for determining the level of postpartum depression in mothers and to assist midwives in monitoring patients\u27 mental health conditions, enabling them to provide appropriate care
The Implementation of Artificial Neural Network (ANN) on Offline Cursive Handwriting Image Recognition
Get PDFIdentifying a writing is an easy thing to do for human, but this does not apply to computers, in particular if it is handwriting. Handwriting recognition, especially cursive handwriting is a research in the area of image processing and pattern matching that is challenging to complete, following the different characteristics of each person's cursive handwriting style. In this study, the use of the ANN model will be implemented in performing offline handwriting image recognition. The cursive handwriting image that has been obtained is then preprocessed and segmented using bounding box rectangle and contour techniques. Evaluation of system performance using global performance metrics in this study resulted in a percentage of 93% where the bounding box and contour succeeded in determining the segmentation point correctly, so that the ANN model worked optimally
