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Home > Volume 7, Number 2, December 2024 > Rusyana
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Asep Rusyana
Department of Statistics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University
Jalan Syech Abdurrauf No.3, Kopelma Darussalam, Banda Aceh 23111, Aceh, Indonesia
Email: jda@unsyiah.ac.id
Mobile Phone: +6281360635965

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Identification of Non-Oil and Gas Main Commodity Exports in Indonesia to Major Destination Countries Using PCA Biplot and CVA Biplot

Asep Rusyana, Nurhasanah Nurhasanah, Intan Khalida M, Hizir Hizir

Abstract

Ekspor merupakan salah satu modal suatu negara untuk menambah devisa negara. Penelitian ini difokuskan pada ekspor komoditas nonmigas berdasarkan tujuan utama negara yang memberikan sumbangan laba terbesar bagi Indonesia. Penelitian ini menggunakan biplot principal component analysis (PCA) dan canonical variate analysis (CVA). Penelitian ini bertujuan untuk mendeskripsikan komoditas ekspor nonmigas berdasarkan negara tujuan utama ekspor dan mengidentifikasi kelebihan dan kekurangan kedua metode tersebut. Data yang digunakan meliputi besarnya laba ekspor komoditas nonmigas pada negara tujuan utama. Biplot PCA menggunakan negara sebagai objek, sedangkan biplot CVA menggunakan kelompok negara. Hasilnya meliputi empat kelompok negara tujuan utama berdasarkan komoditas ekspor. Biplot PCA dapat menjelaskan 68,45% data aktual. Kelebihan biplot PCA adalah representasi negara yang baik, sedangkan kelemahannya adalah representasi komoditas ekspor yang buruk. Di sisi lain, kekuatan biplot CVA meliputi representasi variabel ekspor yang lebih baik dibandingkan dengan biplot PCA dan cukup dalam mewakili kelompok negara, sedangkan kelemahannya adalah representasi negara yang buruk.

 

Export is one of the capitals of countries to increase foreign exchange. This study focuses on the export of non-oil and gas commodities based on the main destination countries that contribute the highest profit to Indonesia. The research uses principal component analysis (PCA) biplot and canonical variate analysis (CVA) biplot. This study aims to describe non-oil and gas export commodities based on the main export destination countries and to identify the advantages and disadvantages of both methods. The data include the amount of non-oil and gas commodity export profit on the main destination countries. PCA biplot uses the state as an object, whereas the CVA biplot uses a group of countries. The result includes four groups of main destination countries based on export commodities. The PCA biplot can explain 68.45% of actual data. The advantage of PCA biplot is well representation of a country, whereas its weakness is poor representation of export commodities. On the other hand, the strengths of CVA biplot comprise is the better representation of export variables compared with those of PCA biplot and sufficient in representing country group, and its weakness is poor representation of countries.

 Keywords

Biplot; Countries; CVA; Export; PCA

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References

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DOI: https://doi.org/10.24815/jda.v7i2.43672

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About The Authors

Asep Rusyana
https://fsd.usk.ac.id/asep.rusyana/

Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala
Indonesia

Nurhasanah Nurhasanah
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala
Indonesia

Intan Khalida M
Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala

Hizir Hizir
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala
Indonesia

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Keywords ARIMA Analisis Regresi Banda Aceh Biplot Canonical correlation analysis Computer Network Correspondence Development areas Forecasting Hybrid Kemiskinan Korelasi MANOVA Mean lingkage Multidimensional Nutritonal status Quality of Service Software-defined Network Spatial Regression Stunting Sumatera Island
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