000			02155nam a22002417a 4500
003			FT8773
005			20251106125124.0
008			251106b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58.64 E83 2025
082			_a.
100	1		_aEscoto, Louis Mariae C.; Maranan, Gerwin Marie V.; Panajon, Karyll Kaye B.
245			_aEminder: Mental health companion bot for daily monitoring and notification
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: Anxiety and depression have become increasingly prevalent in the Philippines, especially after the COVID-19 pandemic, with the Department of Health estimating that 3.6 million Filipino suffer from these issues. Individuals often find it challenging to express their emotions or seek help, leading to challenges in emotional regulation and communication. In response, researchers from Pamantasan ng Lungsod ng Maynila (PLM) developed Eminder: Mental Health Companion Bot for Daily Monitoring and Notification, a mobile application aimed at assessing emotional states and offering support. The study involved 150 respondents who experienced anxiety, stress, and depression and applied the ISO/IEC 25010 standard to evaluate functional suitability, performance efficiency, reliability, and security. Results indicate high ratings across all categories. The mean per category is as follows: 3.99 for functional suitability, 4.02 performance efficiency, 4.11 for reliability, and 4.04 for security, all rated as “Very Good.” These findings suggest Eminder’s potential to enhance emotional well-being. However, the Support Vector Machine (SVM) model used for emotion detection achieved only 48% accuracy, and the decision tree had an accuracy of 50%. Both models misclassify “fear” and “surprise” as other emotion, indicating the need for further improvements.
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37040 _d37040