(deposit) A Counseling Expert System to Reduce Trauma for Orphans During The Covid-19 Pandemic on Natural Language Processing

Megadiningrum, Regita (2022) (deposit) A Counseling Expert System to Reduce Trauma for Orphans During The Covid-19 Pandemic on Natural Language Processing. Undergraduate thesis, Universitas 17 Agustus1945 Surabaya.

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Abstract

As a result of the Covid-19 pandemic that has occurred in the past two years, the death rate, especially in Indonesia, is quite significant. Many of our people have lost their relatives and friends, including children who have lost both their parents due to this pandemic. As a result of losing parents, children will experience trauma or what is often called Post Traumatic Stress Disorder (PTSD). This trauma condition, if allowed to continue, will reduce the quality of the child itself. This study aims to build an expert counseling system to assist children in overcoming the trauma they are experiencing. Children can have conversations like an expert and tell their complaints. In this expert system requires two methods in it. Where the Natural Language Processing method is used to process the text of the complaint submitted by the child. Then the text will be processed using the Forward Chaining method to get a solution or suggestion that fits the child's condition. This study resulted in an accuracy of 73% by conducting 30 keyword testing experiments with input sentences. Not only that, the expert system is also able to produce conclusions / solutions to the symptoms of trauma experienced by children in accordance with expert conclusions with an accuracy rate of 93%. Keyword : Expert System, Natural Language Processing, Counseling, Trauma

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Expert System, Natural Language Processing, Counseling, Trauma
Subjects: Q Science > QP Physiology
T Technology > T Technology (General)
Divisions: Fakultas Teknik > Program Studi Teknik Informatika
Depositing User: 1461800160 Regita Megadiningrum
Date Deposited: 05 Sep 2022 01:58
Last Modified: 08 Nov 2022 02:15
URI: http://repository.untag-sby.ac.id/id/eprint/18032

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