Analisis pengaruh angka kelahiran kasar dan angka kematian kasar terhadap laju pertumbuhan penduduk di kecamatan karanganyar. Analisis pengaruh angka kelahiran & kematian kasar terhadap laju pertumbuhan penduduk di Karanganyar. Studi kuantitatif BPS dengan regresi linier ganda.
Tujuan dari penelitian ini adalah untuk mengetahui pengaruh angka kelahiran kasar dan angka kematian kasar terhadap laju pertumbuhan penduduk di Kecamatan Karanganyar beserta model persamaan regresinya. Jenis penelitian ini adalah penelitian kuantitatif yang mana data yang digunakan dalam penelitian ini adalah data sekunder yang diambil dari website badan pusat statistik Kabupaten Purbalingga dari tahun 2010 sampai 2023. Data yang diperoleh berupa data angka kelahiran kasar sebagai , angka kematian kasar sebagai , dan laju pertumbuhan penduduk sebagai Y. Dari data yang diperoleh kemudian dilakukan intepretasi menggunakan metode regresi linier berganda melalui SPSS. Kesimpulan dari empat uji asumsi klasik yaitu uji normalitas, uji multikolinieritas, uji heteroskedastisitas, dan uji autokorelasi adalah (1) data berdistribusi normal, tidak terjadi multikolinearitas, tidak terjadi gejala heteroskedastisitas, dan tidak terjadi autokorelasi. (2) dari hasil uji t diperoleh hasil angka kelahiran kasar tidak berpengaruh terhadap laju pertumbuhan penduduk, sedangkan angka kematian kasar berpengaruh terhadap laju pertumbuhan penduduk (3) dari hasil uji f dengan kesimpulan bahwa secara simultan angka kelahiran kasar dan angka kematian kasar berpengaruh terhadap laju pertumbuhan penduduk. (4) Diperoleh persamaan regresi linier bergandanya yaitu Ŷ=0.343+0.016+0.077
This study, "Analisis Pengaruh Angka Kelahiran Kasar Dan Angka Kematian Kasar Terhadap Laju Pertumbuhan Penduduk Di Kecamatan Karanganyar," addresses a highly relevant demographic topic: the determinants of population growth at a local level. The clear objective to identify the influence of crude birth and death rates on population growth, along with establishing a regression model, is well-articulated. The quantitative approach, utilizing secondary data from a credible source (Badan Pusat Statistik Kabupaten Purbalingga) spanning 13 years (2010-2023), provides a solid foundation for analysis. The application of multiple linear regression and the successful execution of classical assumption tests (normality, multicollinearity, heteroskedasticity, and autocorrelation) demonstrate a sound methodological understanding and robust data preparation. A key point of interest arises from the presented findings regarding the individual and simultaneous effects of the independent variables. While the F-test concludes that crude birth rate and crude death rate *simultaneously* influence population growth, the T-test results indicate that the crude birth rate *does not* individually influence population growth, whereas the crude death rate *does*. This apparent discrepancy warrants further discussion within the main text. The authors should elaborate on why the crude birth rate might not show an individual significant effect despite being part of a jointly significant model. This could be due to confounding factors, the magnitude of its effect being smaller than its standard error, or perhaps interactions that are not fully captured by the abstract's summary. The final regression equation is presented, providing a clear quantitative model for the observed relationships. Overall, the paper presents a straightforward and methodologically sound investigation into local population dynamics. To strengthen the contribution, the authors should delve deeper into the implications of the contrasting t-test and f-test results, particularly concerning the crude birth rate's individual non-significance. Discussing the practical implications of these findings for local policy-making in Kecamatan Karanganyar would also enhance the paper's value. While the study is localized to one sub-district, its systematic approach provides a good foundation for future comparative studies or broader regional analyses. The research is generally well-executed and provides valuable insights into population growth drivers.
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