PERMODELAN REGRESI NONPARAMETRIK SPLINE TERHADAP INFLASI DI PROVINSI KALIMANTAN SELATAN
Abstract
Inflation is a condition of increasing prices continuously for a certain time. One of the factors thought to influence inflation, namely the Consumer Price Index (CPI), the Consumer Price Index (CPI) is an indicator that can be said to be important in determining the level of economic stability of a country. Seeing the relationship between the Consumer Price Index (CPI) and inflation, this study aims to explain how the influence and how the best model of the Consumer Price Index (CPI) on inflation in South Kalimantan Province uses Spline Nonparametric Regression. The use of the Spline Nonparametric Regression method in this study is because the data used has significant fluctuations so that it is estimated that the data is not normal. In the process, the Spline Nonparamteric Regression method is used to obtain the estimated regression curve through a data fitting approach. This method is also very suitable for use with data that changes frequently, spline is a model that has statistical, visual interpretation and has the ability to be generalized to complex and complex statistical models. The result of this research is that the best model is found at one knot point and the Consumer Price Index (CPI) has an effect on the inflation variable by 13.23 percent.
Keywords: Inflation, Consumer Price Index, Spline Nonparametric Regression
Full Text:
PDFReferences
Aghisna, H. (2017). Analisis Faktor-Faktor Yang Mempengaruhi Inflasi Di Indonesia Tahun 2000-2015. Yogyakarta: Universitas Islam Indonesia Yogyakarta.
Agustina, N. (2021). Pengaruh Inflasi, Indeks Harga Konsumen, Pertumbuhan Produk Domestik Bruto Terhadap Nilai Perusahaan (Studi Empiris Pada Perusahaan Sub Sektor Pariwisata dan Perhotelan yang Terdaftar di Bursa Efek Indonesia Tahun 2017-2019). Yogyakarta: Universitas Mercu Buana Yogyakarta.
Ardiansyah. (2019). Permodelan Faktor Yang Mempengaruhi Kemiskinan Di Provinsi Sulawesi Selatan Dengan Regresi Nonparametrik Spline. Makassar: Universitas Islam Negeri (UIN) Alauddin Makassar.
Astuti, E. P. (2017). Pemilihan Titik Knot Optimal Dalam Regresi Nonparametrik Spline Truncated Pada Data Longitudinal (Studi Kasus: Data Pertubuhan Ekonomi di Pualu Kalimantan). Surabaya: Institut Teknologi Sepuluh November.
Eubank, R. L. (1988). Nonparametric Regression And Spline Smoothing. New York: Marcel Dekker, Inc.
Fathurahman, M. (2011). Estimasi Parameter Model Regresi Spline. Eksponensial, 54-58.
Ferdiana, K. (2017). Pengujian Hipotesis Simultan Dalam Regresi Semiparametrik Spline Truncated. Surabaya: Institut Teknologi Sepuluh November.
Prahutama, A., Wahyu U, T., Eko C, R., & Zumrohtuliyosi, D. (2014). Permodelan Inflasi Berdasarkan Harga-Harga Pangan Menggunakan Spline Multivariabel. Media Statistika, 89-94.
Rahim, F. (2019).Permodelan Regresi Nonparametrik Spline Truncated Pada Data Angka Kematian Ibu Di Jawa Timur. Surabaya: Institut Teknologi Sepuluh Nopember.
Rifai, N. A. (2019). Pendekatan Regresi Nonparametrik dengan Fungsi Kernel untuk Indeks Harga Saham Gabungan. Statistika, 53-61.
Sari, L. P. (2009). Analisis Faktor Indeks Harga Konsumen Pada Sub Kelompok Pengeluaran Yang Mempengaruhi Laju Inflasi Kabupaten Kudus Tahun 2007. Semarang: Universitas Negeri Semarang.
Zulaikah, F. (2009). Analisis Faktor Indeks Harga Konsumen (IHK) Pada Sub-Sub Kelompok Pengeluaran Yang Mempengaruhi Laju Inflasi Kabupaten Pati Tahun 2008. Semarang: Universitas Negeri Semarang.
DOI: https://doi.org/10.20527/ragam.v1i1.7337
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
RAGAM: Journal of Statistics and Its Application
Program Studi Statistika, Fakultas MIPA, Universitas Lambung Mangkurat
Jalan A. Yani Km.36, Kampus ULM Banjarbaru, Kalimantan Selatan, Indonesia 70714
e-mail: [email protected]
website: https://ppjp.ulm.ac.id/journals/index.php/ragam
RAGAM: Journal of Statistics and Its Application is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.