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Al-Muqayyad
Article . 2022 . Peer-reviewed
License: CC BY SA
Data sources: Crossref
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Analisis Komponen Utama dan Biplot untuk Mereduksi Faktor Inflasi Berdasarkan Indeks Harga Konsumen

Authors: Anne Mudya Yolanda; Arisman Adnan; Rustam Efendi; Haposan Sirait; Irfansyah Irfansyah; Okta Bella Syuhada; Rahmad Ramadhan Laska; +1 Authors

Analisis Komponen Utama dan Biplot untuk Mereduksi Faktor Inflasi Berdasarkan Indeks Harga Konsumen

Abstract

Inflation of a region can be measured from the Consumer Price Index (CPI) by spending group. The aim is to look at the factors that influence monthly inflation based on the CPI for 2021. Principal Component Analysis is used to reduce the expenditure group variables in the CPI, followed by biplot analysis to display the visualization of the first two main components of the PCA in a two-dimensional graph. The results of the main component analysis, (1) the primary expenditure component consists of housing, water, electricity and household fuel variables; equipment, tools and household routine maintenance; transportation; information, communication and financial services; recreation, sports and culture, (2) secondary expenditure components include food, drink and tobacco variables; health; education; general, and (3) complementary expenditure components, namely clothing and footwear variables; personal equipment and other services. These three components simultaneously can represent 88.1% of the diversity of the data. Biplot analysis succeeded in describing the similarity and position of the variables with a total variance of 75%

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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