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ANALISIS CREDIT SCORING TERHADAP STATUS PEMBAYARAN BARANG ELEKTRONIK DAN FURNITURE MENGGUNAKAN BOOTSTRAP AGGREGATING K-NEAREST NEIGHBOR

BAREKENG: Jurnal Ilmu Matematika dan Terapan · Vol. 15 No. 4 (2021) · pp. 735–744

DOI
10.30598/barekengvol15iss4pp735-744
ISSN
2615-3017, 1978-7227
Published
2021-12-01
Publisher
PATTIMURA UNIVERSITY
Language
eng

Abstract

Classification is the process of grouping objects that have the same characteristics into several categories. This study applies a combination of classification algorithms, namely Bootstrap Aggregating K-Nearest Neighbor in credit scoring analysis. The aim is to classify the credit payment status of electronic goods and furniture at PT KB Finansia Multi Finance in 2020 and determine the level of accuracy produced. Credit payment status is grouped into 2 categories, namely smoothly and not smoothly. There are 7 independent variables that are used to describe the characteristics of the debtor, namely age, number of dependents, length of stay, years of service, income, amount of payment, and payment period. The application of the classification algorithm at the credit scoring analysis is expected to assist creditors in making decisions to accept or reject credit applications from prospective debtors. The results showed that the accuracy obtained from the Bootstrap Aggregating K-Nearest Neighbor algorithm with a proportion of 90:10, m=80%, C=73, and K=5 was the best, which was 92.308%.

Collaboration network of the authors

18 authors · 31 co-authorship links

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Co-authorOrganisationJoint articles
Nur Annisa FitriAffiliation unknown2
Hairi SeptiyanorAffiliation unknown1
Syaripuddin SyaripuddinAffiliation unknown1
Reni PratiwiAffiliation unknown1
Surya PranggaAffiliation unknown1
Sifriyani SifriyaniAffiliation unknown1
Yunda Sasha ParadillaAffiliation unknown1
Sri WahyuningsihAffiliation unknown1
Kartika RamadaniAffiliation unknown1
Fidia Deny Tisna AmijayaAffiliation unknown1
Dwi Indra YunistyaAffiliation unknown1
Suyitno SuyitnoAffiliation unknown1
Ineu SintiaAffiliation unknown1
M. FathurahmanAffiliation unknown1
Ardiman WiranataAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://ojs3.unpatti.ac.id/index.php/barekeng/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">ANALISIS CREDIT SCORING TERHADAP STATUS PEMBAYARAN BARANG ELEKTRONIK DAN FURNITURE MENGGUNAKAN BOOTSTRAP AGGREGATING K-NEAREST NEIGHBOR</dc:title>
	<dc:creator>Astuti, Putri Sri</dc:creator>
	<dc:creator>Hayati, Memi Nor</dc:creator>
	<dc:creator>Goejantoro, Rito</dc:creator>
	<dc:description xml:lang="en-US">Classification is the process of grouping objects that have the same characteristics into several categories. This study applies a combination of classification algorithms, namely Bootstrap Aggregating K-Nearest Neighbor in credit scoring analysis. The aim is to classify the credit payment status of electronic goods and furniture at PT KB Finansia Multi Finance in 2020 and determine the level of accuracy produced. Credit payment status is grouped into 2 categories, namely smoothly and not smoothly. There are 7 independent variables that are used to describe the characteristics of the debtor, namely age, number of dependents, length of stay, years of service, income, amount of payment, and payment period. The application of the classification algorithm at the credit scoring analysis is expected to assist creditors in making decisions to accept or reject credit applications from prospective debtors. The results showed that the accuracy obtained from the Bootstrap Aggregating K-Nearest Neighbor algorithm with a proportion of 90:10, m=80%, C=73, and K=5 was the best, which was 92.308%.</dc:description>
	<dc:publisher xml:lang="en-US">PATTIMURA UNIVERSITY</dc:publisher>
	<dc:date>2021-12-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4195</dc:identifier>
	<dc:identifier>10.30598/barekengvol15iss4pp735-744</dc:identifier>
	<dc:source xml:lang="en-US">BAREKENG: Jurnal Ilmu Matematika dan Terapan; Vol 15 No 4 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan; 735-744</dc:source>
	<dc:source>2615-3017</dc:source>
	<dc:source>1978-7227</dc:source>
	<dc:source>10.30598/barekengvol15iss4year2021</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4195/3580</dc:relation>
</oai_dc:dc>