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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi HISTOGRAM: Jurnal Pendidikan Matematika Unisda Journal of Mathematics and Computer Science (UJMC) Journal of Education and Learning Mathematics Research (JELMaR) Al-Khidmah: Jurnal Pengabdian Kepada Masyarakat Tematik: Jurnal Konten Pendidikan Matematika
Putra, Eric Dwi
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Religion Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering

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Journal : Unisda Journal of Mathematics and Computer Science (UJMC)

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Analisis Regresi Linier Berganda Untuk Memodelkan Faktor yang Mempengaruhi Nilai Penambahan Utang Tahunan Negara Indonesia Sulantari, Sulantari; Hariadi, Wigid; Putra, Eric Dwi; Anas, Aswar
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 10 No 1 (2024): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v10i1.6631

Abstract

Indonesia is a one of developing country. After 79 years of independence, Indonesia is not yet free from debt. In 2023, Indonesia's total national debt will reach Rp. 8,144.69 trillion. The debt can cause economic problems in many debtor countries. Regression analysis is a statistical analysis that explains the relationship between the dependent variable (Y) and the independent variable (X). The author is interested in analyzing what factors influence the amount of the annual increase in Indonesia's debt. Using multiple linear regression analysis, the results show that the variables that influence the amount of the increase in Indonesia's national is a variable debt are the GDP growth (X1), variable the GDP value 1 year ago (X2), and variable the debt to GDP ratio 1 year ago (X3). The coefficient of determination (R2) value is 0.89, which means that 89% of the increase in Indonesia's national debt is influenced by variables variable debt are the GDP growth, variable the GDP value 1 year ago, and variable the debt to GDP ratio 1 year ago. The regression model formed is: Y = -60.489 (X1) + 0.046 (X2) + 592.738 (X3) + e. Keywords: Weighted Moving Average, WMA, Inflation. Abstrak. Negara Indonesia merupakan salah satu negara berkembang. setelah 79 tahun merdeka, Indonesia belum lepas dari hutang. Tahun 2023, total utang negara Indonesia mencapai Rp. 8.144,69 triliun. Utang dapat menimbulkan permasalahan ekonomi pada banyak negara debitur. Analisis regresi adalah suatu analisa statistika yang menjelaskan hubungan antara variabel terikat (Y) dan variabel bebas (X). penulis tertarik untuk menganlisis faktor apa saja yang mempengaruhi besaran nilai penambahan hutang tahunan negara Indonesia. Menggunakan analsisi regresi linier berganda, diperoleh hasil bahwa Variabel yang berpengaruh terhadap besar penambahan hutang Negara Indonesia adalah variabel pertumbuhan PDB (X1), variabel nilai PDB 1 tahun yang lalu (X2), dan variabel rasio utang terhadap PDB 1 tahun yang lalu (X3). Nilai koefisien determinasi (R2) sebesar 0.89 yang berarti bahwa sebesar 89% besar penambahan hutang Negara Indonesia dipengaruhi oleh variabel X1, X2, dan X3. Model regresi yang terbentuk adalah: Y = -60.489 (X1) + 0.046 (X2) + 592.738 (X3) + e . Kata kunci: Analisis Regresi, Berganda, Utang Indonesia.
Co-Authors Akbar, Ahmad Maulana Allafa, Anya Birru Anas, Aswar Ardhana, Iqshal Sulton Balila, Jesika Nur Intan Devarigata, Ervatamia Syah Dimas Anditha Cahyo Sujiwo Efendi, Mohammad Rizky HARIADI, WIGID Hasanah, Faizatul Heldiana Ferly, Nonny Zakiyanita Ika Hesti Agustin, Ika Hesti Indah Rahayu Panglipur Ivania, Gissela Putri Lutfiyah Lutfiyah Maulana, Thowil Fikri Mohammad Syafii panglipur, indah rahayu PUTRI WULANDARI Putri, Reta Eksa Ria Amalia Rizqoh, Zidna Saputra, Mohammad Wahyu Dimas Siti Aminah Sulantari, Sulantari Sulisawati, Dwi Noviani Sullystiawati, Lusia Herni Suyitno, Yesica Melia Rani Wardah, Nabilahdhia Rahayu Prima