Putro, Amboro (2010) Estimasi Parameter Distribusi Weibull Termodifikasi. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sarhan dan Zaindin (2008) memperkenalkan generalisasi dari distribusi Weibull yang dinamakan dengan distribusi Weibull termodifikasi (Modified Weibull Distribution). Dalam Tugas Akhir ini, akan diselidiki mengenai sifat-sifat dari MWD (Modified Weibull Distribution). Selanjutnya, parameter dari distribusi MWD (Modified Weibull Distribution) akan diestimasi. Proses estimasi ini akan dilakukan berdasarkan data Tipe II dengan menggunakan maximum likelihood estimation dan least square. Masing-masing dari dua metode ini akan menghasilkan beberapa persamaan non linier yang nantinya akan digunakan untuk mencari nilai estimasi dari parameter (a, b, y) . Kemudian, persamaan-persamaan non linier tersebut diselesaikan dengan menggunakan metode biseksi. Dalam prosesnya nanti akan digunakan data yang telah dibangkitkan dengan menggunakan metode acceptance-redjection. Hasil yang diperoleh selanjutnya dibandingkan. Dari perbandingan kedua hasil estimasi diperoleh bahwa metode Least Square mempunyai nilai RMSE (Root Mean Square Error) yang lebih besar daripada metode MLE (Maximum Likelihood Estimator). Hal ini menunjukkan bahwa dalam permasalahan ini, metode MLE (Maximum Likelihood Estimator) memberikan estimasi yang lebih tepat daripada metode Least Square
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Sarhan and Zaindin (2008) introduced a generalization of the Weibull distribution called the Modified Weibull Distribution. In this final project, the properties of the Modified Weibull Distribution (MWD) will be investigated. Furthermore, the parameters of the Modified Weibull Distribution (MWD) will be estimated. This estimation process will be carried out based on Type II data using maximum likelihood estimation and least squares. Each of these two methods will produce several nonlinear equations that will later be used to find the estimated values of the parameters (a, b, y). Then, these nonlinear equations are solved using the bisection method. In the process, data that has been generated using the acceptance-rejection method will be used. The results obtained are then compared. From the comparison of the two estimation results, it is found that the Least Square method has a greater RMSE (Root Mean Square Error) value than the MLE (Maximum Likelihood Estimator) method. This shows that in this problem, the MLE (Maximum Likelihood Estimator) method provides a more accurate estimate than the Least Square method
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSMa 519.24 Put e-1 2010 (weeding) |
| Uncontrolled Keywords: | Maximum likelihood, Least Square, Data Tersensor Tipe II; Maximum Likelihood Estimation, Least Square Procedure, Type II Censored Data |
| Subjects: | Q Science > QA Mathematics > QA273.6 Weibull distribution. Logistic distribution. Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QA Mathematics > QA278.3 Structural equation modeling. |
| Divisions: | Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | EKO BUDI RAHARJO |
| Date Deposited: | 16 Oct 2025 08:44 |
| Last Modified: | 16 Oct 2025 08:44 |
| URI: | http://repository.its.ac.id/id/eprint/128602 |
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