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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Keteknikan dan Sains (JUTEKS) Indonesian Journal of Statistics and Its Applications JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) ESTIMASI: Journal of Statistics and Its Application
Sri Astuti Thamrin
Departemen Statistika, Universitas Hasanuddin, Indonesia
Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Engineering Mathematics Public Health Other

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STUDI EFEKTIFITAS PROGRAM TENSI TERHADAP KREATIVITAS DAN PSIKOSOSIAL LANSIA DENGAN PENDEKATAN STATISTIKA Khaerati, Rusydah; Rosdiana, Rosdiana; Sumaya, Andi Dewi; Ernasari, Ernasari; Thamrin, Sri Astuti
Prosiding Seminar Nasional Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika (VARIANSI) Vol 1 (2018)
Publisher : Program Studi Statistika, FMIPA, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (773.895 KB)

Abstract

Permasalahan yang sering dihadapi oleh seseorang yang telah memasuki masa lanjut usia (lansia) bukan hanya perubahan secara fisik dan kognitifnya saja, namun juga berpengaruh besar terhadap keadaan psikososial dari lansia itu sendiri. Psikososial lansia yang tidak ditangani secara tepat akan mempengaruhi kualitas hidup baik kesehatan fisik maupun kemampuan kognitif lansia. Oleh karena itu, melalui program “Tensi (Tenda Seni Lansia)” ini, diharapkan masyarakat lansia dapat melakukan suatu aktivitas yang bermanfaat dan menyenangkan sehingga kebutuhan psikososialnya dapat terpenuhi dengan baik. Untuk membuktikan keefektifan program, maka digunakan metode penelitian eksprimen dengan memberikan perlakuan pada lansia berupa aktivitas yang menghasilkan karya seni untuk melihat apakah terjadi peningkatan kreativitas dan interaksi antara masyarakat lansia dengan masyarakat diumur yang berbeda-beda. Jumlah sampel dalam penelitian ini sebanyak 8 lansia, penentuan sampel menggunakan teknik purposive sampling dengan kriteria lansia yang mengikuti kegiatan Tenda Seni Lansia. Teknik pengumpulan data dengan melakukan pre dan post test, wawancara dan observasi. Pengujian data pre dan post test menggunakan uji normalisasi dan uji paired t-test. Hasil yang diperoleh dari pengujian uji normalisasi data menunjukkan bahwa rata-rata nilai sampel pra dan pasca perlakuan memiliki perbedaan atau tidak sama. Hal ini berarti program TENSI efektif dalam meningkatkan kreativitas dan  interaksi sosial antara masyarakat lansia melalui beberapa kegiatan yang terlaksana. Kata Kunci: Psikososial, purposive sampling, tenda seni lansia, uji normalisasi, uji paired t-test.
Peningkatan Kualitas Pembelajaran Matematika Bagi Guru SMA Melalui Media Google Classroom dan Geogebra Aris, Naimah; Erawaty, Nur; Massalesse, Jusmawati; Sirajang, Nasrah; Wahda, Wahda; Kasbawati, Kasbawati; Thamrin, Sri Astuti; Sahriman, Sitti; Ramadhan, Muh. Nur Bahri; Jaya, A. Kresna
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 3 No 2 (2019): JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Forum Dosen Indonesia JATIM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.483 KB) | DOI: 10.36339/je.v3i2.253

Abstract

The involvement of teachers in Bone Regency in using information and communication technology (ICT) to prepare teaching materials is very little or even never said, even though computer facilities and infrastructure are available in the computing lab. This activity aims to provide knowledge to Mathematics teachers about online learning Google Classroom and Geogebra. The use of Google Classroom will make learning more effective for teachers and students because learning is no longer limited by space and time, student can explore learning resources easily and utilize information technology properly. Likewise, Geogebra training is expected to overcome the difficulties of teachers in visualizing concept charts in mathematics dynamically. The target audience for community service is mathematics teachers who are members of the Mathematics MGMP in Bone Regency.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (139.694 KB) | DOI: 10.20956/jmsk.v3i1.3295

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.354 KB) | DOI: 10.20956/jmsk.v4i2.3331

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.213 KB) | DOI: 10.20956/jmsk.v6i2.3356

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (415.772 KB) | DOI: 10.20956/jmsk.v14i2.3551

Abstract

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
KLASIFIKASI FAKTOR-FAKTOR PENYEBAB PENYAKIT DIABETES MELITUS DI RUMAH SAKIT UNHAS MENGGUNAKAN ALGORITMA C4.5 Dewi Rahma Ente; Sri Astuti Thamrin; Samsul Arifin; Hedi Kuswanto; Andreza Andreza
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.83 KB) | DOI: 10.29244/ijsa.v4i1.330

Abstract

Diabetes mellitus (DM) is one of the chronic and deadly diseases that are widely observed in various countries today. This disease continues and is increasing to a very alarming stage. This study aims to identify and see the relationship between factors that influence DM disease. The method used in this research is C4.5 algorithm which is one of the algorithms used to make predictive classifications. Classification is one of the processes in data mining that aims to find patterns in relatively large data that use the representations in the form of decision trees. This method is applied to data from medical records of patients with DM in 2014-2018 taken from the Hasanuddin University Teaching Hospital. The results obtained indicate that there are four factors that influence the prediction of a patient's DM status namely; Fasting Blood Glucose (GDP), LDL Cholesterol, Triglycerides, and Body Weight.
PENENTUAN FAKTOR-FAKTOR POTENSIAL YANG MEMPENGARUHI KEJADIAN MALARIA DI PROVINSI PAPUA DENGAN EPIDEMIOLOGI SPASIAL Siswanto Siswanto; Sri Astuti Thamrin
Indonesian Journal of Statistics and Applications Vol 4 No 3 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v4i3.681

Abstract

In Indonesia malaria is found to be widespread in all islands with varying degrees and severity of infection. Based on the Annual of Parasite Incidence (API) in Eastern Indonesia, Malaria is a disease that has a high incidence rate. The three provinces with the highest APIs are Papua (42.64%), West Papua (38.44%) and East Nusa Tenggara (16.37%). Spatial aspects are considered important to be studied because the spread of disease through mosquitoes is strongly influenced by fluctuating climate. The purpose of this study is to determine the potential factors that influence the incidence of Malaria disease in the province of Papua in 2013 by looking at aspects that are the focus of attention in spatial epidemiology. The methods used in analyzing the area are Simultaneous Autoregressive (SAR) and Conditional Autoregressive (CAR) models with a spatial weighting matrix up to second order. The result shows the average monthly wind velocity, average monthly rainfall, and malaria treatment with government program drugs by getting ACT drugs are substantial factors in determining the incidence number of Malaria in Papua based on the lowest AIC value for the second-order of CAR model. While the SAR model, in this case, has no spatial influence. By knowing the potential factors that influence the incidence of malaria, the Papua Province through the Health Office can take more effective preventive measures to reduce the number of malaria incidents.
Exploration of Obesity Status of Indonesia Basic Health Research 2013 With Synthetic Minority Over-Sampling Techniques: Eksplorasi Status Obesitas Riset Kesehatan Dasar 2013 Indonesia dengan Teknik Synthetic Minority Over-Sampling Sri Astuti Thamrin; Dian Sidik; Hedi Kuswanto; Armin Lawi; Ansariadi Ansariadi
Indonesian Journal of Statistics and Applications Vol 5 No 1 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i1p75-91

Abstract

The accuracy of the data class is very important in classification with a machine learning approach. The more accurate the existing data sets and classes, the better the output generated by machine learning. In fact, classification can experience imbalance class data in which each class does not have the same portion of the data set it has. The existence of data imbalance will affect the classification accuracy. One of the easiest ways to correct imbalanced data classes is to balance it. This study aims to explore the problem of data class imbalance in the medium case dataset and to address the imbalance of data classes as well. The Synthetic Minority Over-Sampling Technique (SMOTE) method is used to overcome the problem of class imbalance in obesity status in Indonesia 2013 Basic Health Research (RISKESDAS). The results show that the number of obese class (13.9%) and non-obese class (84.6%). This means that there is an imbalance in the data class with moderate criteria. Moreover, SMOTE with over-sampling 600% can improve the level of minor classes (obesity). As consequence, the classes of obesity status balanced. Therefore, SMOTE technique was better compared to without SMOTE in exploring the obesity status of Indonesia RISKESDAS 2013.
PENAKSIRAN PARAMETER DISTRIBUSI WEIBULL DENGAN METODE BAYESIAN SURVIVAL DAN MAKSIMUM LIKELIHOOD Sri Astuti Thamrin
Jurnal Keteknikan dan Sains (JUTEKS) Vol. 1 No. 2 (2018): Jurnal Keteknikan dan Sains - Oktober 2018
Publisher : LPPM Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.568 KB)

Abstract

Analisis kelangsungan hidup (survival) merupakan suatu prosedur statistik yang digunakan untuk menganalisis data dimana variabel yang diteliti adalah waktu sampai terjadinya suatu kejadian. Salah satu distribusi yang banyak digunakan dalam menangani masalah survival adalah distribusi Weibull. Distribusi ini memiliki parameter skala (scale) dan bentuk (shape) yang mampu menyajikan keakuratan kegagalan dengan sampel yang kecil. Untuk mendapatkan model Weibull survival, kedua parameter tersebut perlu ditaksir. Menaksir parameter dapat dilakukan dengan dua pendekatan yaitu Bayesian dan klasik (frequentist). Tujuan dari artikel ini adalah untuk mengestimasi parameter distribusi Weibull dengan metode Bayesian dan maksimum likelihood. Kedua metode tersebut dibandingkan dan diaplikasikan pada data simulasi survival yang berdistribusi Weibull.  Hasil yang diperoleh menunjukkan bahwa estimasi parameter dengan menggunakan metode Bayesian memberikan nilai taksiran yang lebih baik dibandingkan dengan metode maksimum likelihood berdasarkan nilai mean squared error (MSE).
Co-Authors Afifah Afifah Ainun Mawaddah Abdal Ainun Utari Budistiharah Andreza Andreza Anisa Anisa Anna Islamiyati Anna Islamiyati Ansariadi Ansariadi Armin Lawi Dewi Rahma Ente Dian Sidik Edy Saputra Rusdi Erna Tri Herdiani Ernasari, Ernasari Hedi Kuswanto I Gusti Agung Komang Diafari Djuni Hartawan Irma Andriani 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 Ramadhan, Muh. Nur Bahri Rosdiana Rosdiana Sahriman, Sitti Samsu Arif Sirajang, Nasrah Siswanto Siswanto Sitti Sahriman Sumaya, Andi Dewi Wahda, Wahda