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primary topic: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY)

PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY)
type: Thesis
type: Article
abstract: Binary logistic regression is an analytical technique to see the relationship between predictor variables and response variables. Meanwhile, Classification and Regression Trees (CART) is a flexible decision tree method, capable of handling non-linear relationships and interactions between variables automatically. In 2020, there has been a COVID-19 pandemic that has an impact on the global economy, including MSMEs in Indonesia, where some MSMEs have succeeded in increasing revenue by utilizing digital platforms. This study compares the performance of binary logistic regression and Classification and Regression Trees (CART) in classifying factors that influence the increase in online business income using SUSENAS data from BPS in 2021. The research method used is quantitative analysis with a statistical approach. The results show that binary logistic regression has a classification accuracy of 76.29% with an APER of 23.71%, while the Classification and Regression Trees (CART) have a classification accuracy of 72.16% with an APER of 27.84%. In conclusion, binary logistic regression shows better results in classifying factors that increase online business income, especially if the relationship pattern in the data is relatively linear and the model assumptions are met.
date: 2025-05-21
status: published
author list: authors
type: EPrint
type: ThesisEPrint
is part of: repository
has document: http://digilib.uin-suka.ac.id/id/document/1006420
has version: http://digilib.uin-suka.ac.id/id/document/1006420
has published: http://digilib.uin-suka.ac.id/id/document/1006420
has document: http://digilib.uin-suka.ac.id/id/document/1006421
has version: http://digilib.uin-suka.ac.id/id/document/1006421
has published: http://digilib.uin-suka.ac.id/id/document/1006421
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has document: http://digilib.uin-suka.ac.id/id/document/1006462
has document: http://digilib.uin-suka.ac.id/id/document/1006463
has document: http://digilib.uin-suka.ac.id/id/document/1006464
has document: http://digilib.uin-suka.ac.id/id/document/1006465
subject: 510 Mathematics (Matematika)

http://digilib.uin-suka.ac.id/id/document/1006420
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Text)
has file: 21106010040_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
has part: 21106010040_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf

http://digilib.uin-suka.ac.id/id/document/1006421
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Text)

UIN SUNAN KALIJAGA YOGYAKARTA
type: Organization

FAKULTAS SAINS DAN TEKNOLOGI, UIN SUNAN KALIJAGA YOGYAKARTA
type: Organization

NIM.: 21106010040 Faiqotul Muna
type: Person
given name: NIM.: 21106010040
family name: Faiqotul Muna

http://digilib.uin-suka.ac.id/id/document/1006458
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006459
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006460
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label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006461
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label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006462
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006463
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006464
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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http://digilib.uin-suka.ac.id/id/document/1006465
type: Document
label: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY) (Other)
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https://digilib.uin-suka.ac.id/id/eprint/71770/
title: HTML Summary of #71770 PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY)
format: text/html
primary topic: PERBANDINGAN MODEL REGRESI LOGISTIK BINER DAN METODE CLASSIFICATION AND REGRESSION TREES (CART) (STUDI KASUS: STATUS PENINGKATAN PENDAPATAN USAHA ONLINE PADA TAHUN 2020 TERHADAP TAHUN 2019 DI DIY)

510 Mathematics (Matematika)
type: Concept