TY - JOUR
T1 - Islamic Banking Third-party Funds Grouping uses the Data Mining Clustering
AU - Hidayat, S.
AU - Irwansyah, R.
N1 - Publisher Copyright:
© 2021 Published under licence by IOP Publishing Ltd.
PY - 2021/5/28
Y1 - 2021/5/28
N2 - Islamic banking as an intermediary institution (intermediary) between people with excess funds and people who lack funds has a very important influence on the Indonesian economy. In this study, the third-party funds discussed were third-party funds of Islamic banking. The purpose of this study is to analyze the grouping of Islamic banking third-party funds on Indonesia's economic growth over the past 11 years, from 2009 to 2019 using the K-means algorithm. The data of this study uses time-series data from Islamic banking statistics, namely data on third-party funds for Islamic banking financing sourced from the official website of the Financial Services Authority. The findings of this analysis are in the context of a clustering of Islamic banking third-party funds containing 2 clusters: low (C1) and high (C2). The results obtained are there are 7 data with low clusters and 4 data with high clusters. The results of calculations carried out manually and testing using Rapid Miner, produce the same data grouping.
AB - Islamic banking as an intermediary institution (intermediary) between people with excess funds and people who lack funds has a very important influence on the Indonesian economy. In this study, the third-party funds discussed were third-party funds of Islamic banking. The purpose of this study is to analyze the grouping of Islamic banking third-party funds on Indonesia's economic growth over the past 11 years, from 2009 to 2019 using the K-means algorithm. The data of this study uses time-series data from Islamic banking statistics, namely data on third-party funds for Islamic banking financing sourced from the official website of the Financial Services Authority. The findings of this analysis are in the context of a clustering of Islamic banking third-party funds containing 2 clusters: low (C1) and high (C2). The results obtained are there are 7 data with low clusters and 4 data with high clusters. The results of calculations carried out manually and testing using Rapid Miner, produce the same data grouping.
UR - http://www.scopus.com/inward/record.url?scp=85108025455&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1899/1/012095
DO - 10.1088/1742-6596/1899/1/012095
M3 - Conference article
AN - SCOPUS:85108025455
SN - 1742-6588
VL - 1899
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012095
T2 - 2nd Workshop on Engineering, Education, Applied Sciences and Technology, WEAST 2020
Y2 - 5 October 2020
ER -