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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Keteknikan dan Sains (JUTEKS) Jurnal Matematika UNAND Jurnal Varian JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) ESTIMASI: Journal of Statistics and Its Application Indonesian Journal of Statistics and Its Applications

Sri Astuti Thamrin

Departemen Statistika, Universitas Hasanuddin, Indonesia

Author-ID : 402902

Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 22 Documents Claim Missing Document

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Title

Penggunaan Data Mining Saat Ini Dan Tantangannya Di Masa Depan Sri Astuti Thamrin
Jurnal Matematika, Statistika dan Komputasi Vol. 3 No. 1: July 2006
Publisher : Department of Mathematics, Hasanuddin University

This paper begins by describing the main activities involved in the data mining process and highlight the two major styles of data mining: supervised and unsupervised. It then describes two “hot” areas where data mining applications are being used successfully business database systems and the Internet. Finally, it concludes by examining the challenges and research issue data mining will face in the future

Analisis Data Survival Menggunakan Metode Proportional Hazard dan Accelerated Failure Time Sri Astuti Thamrin
Jurnal Matematika, Statistika dan Komputasi Vol. 4 No. 2: January 2008
Publisher : Department of Mathematics, Hasanuddin University

This paper describes survival data analysis using proportional hazard method and accelerated failure time method to determine the factors that influence survival times of patients’ Diabetes Mellitus in Dr. Wahidin Sudirohusodo hospital in Makassar. Besides that, we compare the results of these methods. The results show that among eight tested variables, three of them are affected factors.

Aplikasi Kalman Filter pada Data Survival Erna Tri Herdiani; Nuravia Nuravia; Sri Astuti Thamrin
Jurnal Matematika, Statistika dan Komputasi Vol. 6 No. 2: January 2010
Publisher : Department of Mathematics, Hasanuddin University

Kalman Filter merupakan metode untuk memprediksi nilai suatu peubah di masa yang akan datang dengan mempertimbangkan data-data sebelumnya yang senantiasa di up-date. Metode ini selanjutnya akan diaplikasikan pada data survival penderita penyakit Tuberculosis (TB) dari penduduk Amerika Serikat. Metode ini sangat menarik untuk digunakan karena Tan (2004) hanya memanfaatkan metode state space saja dalam memprediksi nilai peubahnya. Oleh karena itu, pada paper ini akan memanfaatkan metode Kalman Filter dalam memprediksi nilai suatu peubah dari data survival penderita TB di Amerika Serikat.

Methods for Estimating Survival Time of Treatments for Renal Dialysis Sri Astuti Thamrin
Jurnal Matematika, Statistika dan Komputasi Vol. 14 No. 2 (2018): January 2018
Publisher : Department of Mathematics, Hasanuddin University

This papes discusses the theory and application of statistical methods for describing and analyzing survival times of the renal dialysis patients : a) from the first diagnosis until the time of death, and b) on each mode of given treatment. The paper also tries to predict the variables significantly effecting the survival time of renal dialysis patients. The paper makes use of and focuses on the data sets containing patient hospital records, patients’ identity and hospital code centre. To meet the desired aims, the paper uses two prominent methods of survival analysis including the Kaplan-Meier and Cox Proportional Hazard model. The result shows that survival time on the first treatment depends on mode of treatment and it quite low approximately 18 days for median time on hospital outpatient CAPD. Similarly, survival time on the second treatment is quite low about 24 days for the median time on hospital outpatient CAPD. It was also indicated that the survival time of renal dialysis patient depends on the number of treatments, the number of treatment changes, place of treatment, age and the first treatment

Determining Factors that Influence Unmet Need For Family Planning Using Geographically Weighted Logistic Regression With LASSO: Dian Ayu Permata Sari Rusdy; Sri Astuti Thamrin; Anna Islamiyati
Jurnal Matematika, Statistika dan Komputasi Vol. 21 No. 2 (2025): JANUARY 2025
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v21i2.35081

Binary logistic regression is a regression used for categorical response variables with two possibilities: success or failure. This regression is a global model, making it inappropriate for spatial data. Binary logistic regression was then developed into geographically weighted logistic regression (GWLR). GWLR considers location factors into the model through a weight function. Nevertheless, GWLR is unable to overcome multicollinearity issue. Multicollinearity can cause the estimated parameters to be insignificant, thus it needs to be solved. A method to deal with multicollinearity is least absolute shrinkage and selection operator (LASSO). LASSO is applicable to various areas, including health, namely in the case of unmet need for family planning (FP). Unmet need for FP refers to productive-age women who do not wish to have more children or wish to postpone having children without using contraceptive methods. This study aims to obtain GWLR model with LASSO and influential factors, and acquire the performance of GWLR model with LASSO on unmet need for FP in South Sulawesi. The AIC value of the GWLR with LASSO model, which is 31,918, is less than the AIC value of the GWLR without LASSO, which is 38,879. This implies that GWLR with LASSO method is able to model unmet need for FP better than GWLR model. In addition, it was obtained that the status of unmet need for FP in 22 districts/cities was affected by the percentage of women with junior high school education or equivalent or lower, number of high-fertility women, percentage of husbands/families who refuse family planning, and number of KB staffs, while there were 2 districts/cities where the status of unmet need for KB was determined by the number of high-fertility women, percentage of husbands/families who refuse family planning, and number of FP staffs.

Co-Authors Adhel, Fadilah Amirul Afifah Afifah Ainun Mawaddah Abdal Ainun Utari Budistiharah Al Anshory, Fadhil Amil, Sri Indriani Andreza Andreza Anisa Anisa Anna Islamiyati Anna Islamiyati Anna Islamiyati Ansariadi Ansariadi Armin Lawi Armin Lawi Dewi Rahma Ente Dian Ayu Permata Sari Rusdy Dian Sidik Edy Saputra Rusdi Ernasari, Ernasari Hedi Kuswanto Herdiani, Erna Tri I Gusti Agung Komang Diafari Djuni Hartawan Inayah, Ika Irma Andriani Iwan Kurniawan Jaya, A. Kresna Jusmawati Massalesse Kasbawati Kasbawati Khaerati, Rusydah Muralia Hustim Naimah Aris Naimah Aris Najhah Aris Nur Erawaty Nur Erawaty Nuravia Nuravia Nurdin Nurdin Okta Nofri PRANANDA, ADHIYAKSA Ramadhan, Muh. Nur Bahri Rezki, Nurul Rombe, Yoris Rosdiana Rosdiana S Siswanto Sahriman, Sitti Samsu Arif Siddik, A. Muh. Amil Sirajang, Nasrah Siswanto Siswanto Sitti Sahriman Sumaya, Andi Dewi Utami, Mamik Wahda, Wahda

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