TELKOMNIKA Telecommunication, Computing, Electronics and Control
Prediction schizophrenia using random forest
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Prediction schizophrenia using random forest
Prediction schizophrenia using random forest
Subject
Classification, Machine learning, Random forest, Schizophrenia
Description
Schizophrenia is a mental illness with a very bad impact on sufferers, attacking the part of human brain that disables the ability to think clearly. In 2018, Rustam and Rampisela classified Schizophrenia by using Northwestern University Schizophrenia Data, based on 66 variables consisting of group, demographic, and questionnaires statistics, based on the scale for the assessment of negative symptoms (SANS), and scale for the assessment of positive symptoms (SAS), and then classifiers that used are SVM with Gaussian kernel and Twin SVM with linear and Gaussian kernel. Furthermore, this research is novel based on the use of random forest as a classifier, in order to predict Schizophrenia. The result obtained is reported in percentage of accuracy, both in training and testing of random forest, which was 100%. This classification, therefore, shows the best value in contrast with prior methods, even though only 40% of training data set was used. This is very important,
especially in the cases of rare disease, including schizophrenia.
especially in the cases of rare disease, including schizophrenia.
Creator
Zuherman Rustam, Glori Stephani Saragih
Source
DOI: 10.12928/TELKOMNIKA.v18i3.14837
Publisher
Universitas Ahmad Dahlan
Date
June 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Zuherman Rustam, Glori Stephani Saragih, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Prediction schizophrenia using random forest,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3866.
Prediction schizophrenia using random forest,” Repository Horizon University Indonesia, accessed April 3, 2025, https://repository.horizon.ac.id/items/show/3866.