Analisis Regresi Bayesian Untuk Penentuan Parasetamol dan Ibuprofen Simultan Menggunakan Spektrofotometri UV

Fahma, Fatma Syifa Izzul (2021) Analisis Regresi Bayesian Untuk Penentuan Parasetamol dan Ibuprofen Simultan Menggunakan Spektrofotometri UV. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian terhadap penerapan regresi multilinear Bayesian untuk penentuan parasetamol dan ibuprofen simultan menggunakan sistem kerja probabilistik telah dilakukan. Regresi nonparametrik Bayesian diimplementasikan menggunakan metode Markov Chain Monte Carlo (MCMC) menggunakan PyMC3 dalam software Phyton. Prosedur uji statistik digunakan untuk melakukan perbandingan empiris pendekatan regresi Bayesian menggunakan teknik regresi multilinier konvensional. Hasil penelitian ini menunjukkan bahwa nilai prediksi akar kuadrat kesalahan (RSME) sebesar 6,48 dan nilai R2 sebesar 0,998. Sehingga dapat disimpulkan bahwa regresi Bayesian mampu menunjukkan peningkatan kerja analisis yaitu dengan memberikan informasi berupa ketidakpastian dan sebaran eror. ================================================================================================
Research on the application of Bayesian multilinear regression for the simultaneous determination of paracetamol and ibuprofen using a probabilistic system has been carried out. Bayesian nonparametric regression was implemented using the Markov Chain Monte Carlo (MCMC) method using PyMC3 in Python software. The statistical test procedure was used to make an empirical comparison of the Bayesian regression approach using conventional regression techniques. From this research, the predictive value of the Root Square Mean Error (RSME) is 6.48 and R2 value is 0.998. So it can be concluded that Bayesian regression is able to show an increase in analytical work by providing information in the form of uncertainty and error distribution.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Interferensi Bayesian, Markov Chain Monte Carlo (MCMC), Regresi Multivariat, Kalibrasi Spektroskopi, Bayesian Interference, Multivariate Regression, Calibration Spectroscopy
Subjects:	Q Science > QD Chemistry > QD117.S64 Spectrophotometry Q Science > QD Chemistry > QD75.2 Chemistry, Analytic
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Chemistry > 47201-(S1) Undergraduate Thesis
Depositing User:	Fatma Syifa Izzul Fahma
Date Deposited:	28 Aug 2021 14:16
Last Modified:	28 Aug 2021 14:16
URI:	http://repository.its.ac.id/id/eprint/90277

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