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Authors: Nesi Syafitri ; Yudhi Arta ; Apri Siswanto and Sonya Parlina Rizki

Affiliation: Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia, Indonesia

Keyword(s): Case Based Reasoning, DASS 42, Expert System

Abstract: Around 5% adolescents in Indonesia suffer from depression at the certain time. To identify the level of depression, direct consultation with an expert like alienist or psychologist is needed. However, the problem is the number of experts in hospital and culture social environment is limited, also the society is not used to do consultation to alienist or psychologist. Therefore, a system that can help the medical to detect early depression disorder is needed, before the adolescents do the next consultation to the medical. The system called as expert system with web based which built by Case Based Reasoning (CBR) and using Simple Matching Coefficient (SMC) method also DASS 42 as the research instrument. Based on the 200 data testing on 500 and 700 case base, this expert system can detect the early disorder with an precision rate more than 90%. So that, with this expert system the early disorder can be done accurately and fast.

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Paper citation in several formats:
Syafitri, N.; Arta, Y.; Siswanto, A. and Rizki, S. (2020). Expert System to Detect Early Depression in Adolescents using DASS 42. In Proceedings of the Second International Conference on Science, Engineering and Technology - ICoSET; ISBN 978-989-758-463-3, SciTePress, pages 211-218. DOI: 10.5220/0009158202110218

@conference{icoset20,
author={Nesi Syafitri. and Yudhi Arta. and Apri Siswanto. and Sonya Parlina Rizki.},
title={Expert System to Detect Early Depression in Adolescents using DASS 42},
booktitle={Proceedings of the Second International Conference on Science, Engineering and Technology - ICoSET},
year={2020},
pages={211-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009158202110218},
isbn={978-989-758-463-3},
}

TY - CONF

JO - Proceedings of the Second International Conference on Science, Engineering and Technology - ICoSET
TI - Expert System to Detect Early Depression in Adolescents using DASS 42
SN - 978-989-758-463-3
AU - Syafitri, N.
AU - Arta, Y.
AU - Siswanto, A.
AU - Rizki, S.
PY - 2020
SP - 211
EP - 218
DO - 10.5220/0009158202110218
PB - SciTePress

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