Credit scoring models is an important tools in the credit granting process. These models measure the credit risk of a prospective client. This study aims to applied a discriminant model with mixed predictor variables (binary and continuous) for credit assesment. Implementation of the model use debitur characteristics data from a bank in Lampung Province which the used binary variables involve sex and marital status. Whereas, the continuous variables that was considered appropriate in the model are age, net income, and length of work. By using the data training, it was known that the misclassification of the model is 0.1970 and the misclassification of the testing data reach to 0.3753.
Keywords: discriminant analysis, mixed variables, credit scoring
Article Metrics:
Last update:
Comparison of Discriminant Analysis and Adaptive Boosting Classification and Regression Trees on Data with Unbalanced Class
Eva Fadilah Ramadhani, Adji Achmad Rinaldo Fernandes, Ni Wayan Surya Wardhani. WSEAS TRANSACTIONS ON MATHEMATICS, 20 , 2021. doi: 10.37394/23206.2021.20.69Last update: 2025-04-03 19:45:01
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Media Statistika journal and Department of Statistics, Universitas Diponegoro as the publisher of the journal. Copyright encompasses the rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Media Statistika journal and Department of Statistics, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Media Statistika journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form Media Statistika]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Dr. Di Asih I Maruddani (Editor-in-Chief)
Editorial Office of Media Statistika
Department of Statistics, Universitas Diponegoro
Jl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275
Telp./Fax: +62-24-7474754
Email: maruddani@live.undip.ac.id