000 02261ntm a2200301 i 4500
003 OSt
005 20240224113959.0
008 240224s2023 |||a|||| abm| 00| 0 eng d
040 _aTUPM
_beng
_cTUPM
_erda
050 _aBTH QA 76
_bC36 2023
100 1 _aCañas, Neil Michael D.
245 1 _aSIDetect :
_bA Web-Base Application for Detecting Suicidal Ideations (SI) Using Natural Language Processing and Machine Learning /
_cNeil Michael D. Cañas, Carlo M. Salva, Saeymond Charles N. Serrano, Jihad M. Yusoph.
264 _aManila :
_bTechnological University of the Philippines,
_c2023.
300 _ax, 124 pages :
_billustrations ;
_c29 cm. +
_e1 CD-ROM (4 3/4 in.)
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
500 _aThesis (Undergraduate)
502 _aCollege of Science --
_bBachelor of Science in Computer Science,
_cTechnological University of the Philippines,
_d2023.
504 _aIncludes bibliographical references.
520 3 _aThis thesis introduces SIDetect, a web-based application that uses machine learning (ML) and natural language processing (NLP) methods to identify suicidal ideations (SI). The system uses natural language processing (NLP) to extract pertinent information from user-generated text, which is then examined using machine learning (ML) algorithms to find patterns that suggest the presence of suicidal ideations. A dataset of user-generated text with SI and non-SI instances was used to assess the system. It was developed using Visual Studio Code, Open API, and Python as the programming language. The user interface of the system was also assessed and found to be intuitive and user-friendly. The system was evaluated using ISO 25010 criteria for quality assurance, with a total of 23 respondents consisting of IT/CS, Psychology students, and professionals from the IT and Psychology field. According to the evaluation's findings, SIDetect achieved an overall score of 3.55, indicating a Highly Acceptable rating.--Author's Abstract
650 _aSuicidal behavior
_xComputer programs.
700 1 _aSalva, Carlo M.
700 1 _aSerrano, Saeymond Charles N.
700 1 _aYusoph, Jihad M.
942 _2lcc
_cBTH COS
_n0
999 _c28509
_d28509