Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor

Article History

Submited : June 4, 2020
Published : July 23, 2021

The regression approach can be carried out using three approaches namely parametric, nonparametric and semiparametric approaches. Nonparametric regression is a statistical method used to see the relationship between the response variable and the predictor variable when the shape of the data curve is unknown. Diabetes mellitus (DM) or commonly called diabetes is a disease that is found and observed in various parts of the world today. DM is often marked by a significant increase in blood sugar levels. In this study using blood sugar levels as response variables, body mass index and triglycerides as predictor variables. Data were analyzed using truncated linear spline with one, two and three point knots experiments. The best model is obtained based on the minimum generalized cross validation (GCV) value. The results obtained that the best model is linear spline using three point knots.

References

  1. Budiantara, I.N. Spline dalam Regresi Nonparametrik dan Semiparametrik: Sebuah Pemodelan Statistika Masa Kini dan Masa Mendatang. Pidato Pengukuhan Untuk Jabatan Guru Besar pada Jurusan Statistika, Surabaya: Institut Teknologi Sepuluh Nopember (ITS), 2009.
  2. Eubank, R.L. Spline Smoothing and Nonparametric Regression, Marcel Deker, New York. 1988.
  3. Wahba G. Spline Models for Observational Data. SIAM Pensylvania. 1990.
  4. Ramdhani, Z.A., Islamiyati, A., dan Raupong. Hubungan Faktor Kolesterol Terhadap Gula Darah Diabetes dengan Spline Kubik Terbobot. ESTIMASI: Journal of Statistics and Its Application, 1 (1) : 32-39, 2020.
  5. Islamiyati, A., Fatmawati, and Chamidah, N. Penalized Spline Estimator with Multi Smoothing Parameters in Bi-Response Multi-Predictor Nonparametric Regression Model For Longitudinal Data . Songklanakarin Journal of Sciences and Technology, 42(4): 897-909, 2020.
  6. Putri, W.N.A., Islamiyati, A., dan Anisa. Penggunaan Regresi Kuantil Spline Multivariat pada Perubahan Trombosit Pasien Demam Berdarah Dengue. ESTIMASI: Journal of Statistics and Its Application, 1 (1) : 1-9, 2020.
  7. Aprilia, B., Islamiyati, A., Anisa, dan Ilyas, N. Estimasi Model Regresi Kuantil Spline Kuadratik pada Data Trombosit dan Hematokrit Pasien DBD. ESTIMASI: Journal of Statistics and Its Application, 1 (2) : 58-64, 2020.
  8. Infodatim. Pusat Data dan Informasi Kementerian Kesehatan RI : Hari Diabetes Sedunia, ISSN: 2442-7659, 2019.

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