Alfensi Faruk, Alfensi
Jurusan Matematika, Fakultas MIPA, Universitas Sriwijaya

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Analisis Survival Parametrik Pada Data Tracer Study Universitas Sriwijaya Faruk, Alfensi
Jurnal Matematika Vol 5, No 2 (2015)
Publisher : Jurnal Matematika

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Abstract

In this study, we aimed to (1) show whether the Sriwijaya University tracer study data follow some survival distributions,  (2)  find the best survival distribution to represent the data, and (3) estimate the survival probability and hazard rate of the data. The tracer study was conducted from January 1, 2012 to December 31, 2012. There were 637 alumni who participated in the study. The result showed that the data follow the normal distribution, logistic distribution, and SEV distribution, in which the normal distribution was the best in representing the data. Based on the estimation procedure, the lowest probability of finding the first job was before graduation and the highest probability was about two years after graduation.
Model Survival Nonparametrik Pada Data Rawat Inap Pasien Diare di Puskesmas Indralaya Amran, Ali; Faruk, Alfensi
Jurnal Matematika Vol 5, No 2 (2015)
Publisher : Jurnal Matematika

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Abstract

This research aimed to (1) estimate the survival functions, and (2) investigate the effect of some covariates toward the survival time  from hospitalization time data in Public Health Center of Indralaya. The research subjects consisted of all the diarrhea patients who were hospitalized within the period from January 1, 2014 to June 30, 2014. The patients characteristics were sex, age, job, and disease status. The result showed that the lowest probability of a patient will be out of hospitalization was on the fourth day and the highest probability was on the fifteenth day. In order to find the best model, some statistical tests were also conducted in this research.
Penerapan Regresi Data Panel Komponen Satu Arah untuk Menentukan Faktor-Faktor yang Mempengaruhi Indeks Pembangunan Manusia Sutikno, Bayu; Faruk, Alfensi; Dwipurwani, Oki
Jurnal Matematika Integratif Volume 13 No 1 (April 2017)
Publisher : Department of Matematics, Universitas Padjadjaran

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Abstract

Efek spesifikasi wilayah dan waktu dari data panel dapat menjelaskan perbedaan antar nilai Indeks Pembangunan Manusia (IPM) di setiap wilayah dan periode waktu.  Tujuan dari penelitian ini adalah (1) menentukan model regresi data panel terbaik dengan efek komponen satu arah dalam menjelaskan tingkat keberagaman dari nilai IPM, dan (2) menganalisis faktor-faktor yang berpengaruh signifikan terhadap perubahan nilai IPM. Data yang digunakan dalam penelitian ini adalah nilai IPM  dari seluruh kabupaten dan kota di Provinsi Sumatera Selatan mulai tahun 2007 hingga 2014 yang diperoleh dari Badan Pusat Statistik Provinsi Sumatera Selatan (BPSPSS). Berdasarkan uji Chow, uji Hausman, dan pemilihan efek komponen satu arah, hasil yang diperoleh memperlihatkan bahwa model regresi data panel terbaik dari nilai IPM di Provinsi Sumatera Selatan mulai tahun 2007 hingga 2014 adalah model efek tetap komponen waktu yang diboboti dengan seemingly unrelated regression (SUR). Adapun, faktor-faktor yang berpengaruh signifikan terhadap perubahan nilai IPM di Provinsi Sumatera Selatan mulai tahun 2007 hingga 2014 adalah banyaknya rumah tangga yang dapat mengakses air bersih, angka partisipasi Sekolah Menengah Atas (SMA), angka melek huruf, dan tingkat partisipasi angkatan kerja. Kata kunci: regresi data panel, IPM, uji Chow, uji Hausman, efek komponen satu arah.
Prediction and Classification of Low Birth Weight Data Using Machine Learning Techniques Faruk, Alfensi; Cahyono, Endro Setyo
Indonesian Journal of Science and Technology Vol 3, No 1 (2018): IJoST: Volume 3, Issue 1, 2018
Publisher : Universitas Pendidikan Indonesia

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Abstract

Machine learning (ML) is a subject that focuses on the data analysis using various statistical tools and learning processes in order to gain more knowledge from the data. The objective of this research was to apply one of the ML techniques on the low birth weight (LBW) data in Indonesia. This research conducts two ML tasks; including prediction and classification. The binary logistic regression model was firstly employed on the train and the test data. Then; the random approach was also applied to the data set. The results showed that the binary logistic regression had a good performance for prediction; but it was a poor approach for classification. On the other hand; random forest approach has a very good performance for both prediction and classification of the LBW data set
Aplikasi Model Proportional Hazard Cox pada Waktu Tunggu Kerja Lulusan Jurusan Matematika Fakultas MIPA Universitas Sriwijaya Faruk, Alfensi; Amran, Ali; Nasir, Nopri
Jurnal Penelitian Sains Vol 17, No 1 (2014)
Publisher : Faculty of Mathtmatics and Natural Sciences

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Abstract

Penelitian ini bertujuan untuk (1) menentukan nilai peluang dari waktu mendapatkan pekerjaan per-tama lulusan, (2) mengetahui bagaimana pengaruh beberapa karateristik terhadap waktu mendapatkan pe-kerjaan pertama lulusan dengan menerapkan model proportional hazard Cox. Subjek penelitian terdiri atas 35 orang lulusan Jurusan Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Sriwijaya yang lulus pada tahun 2012. Karakteristik-karakteristik yang diamati adalah usia, masa studi, IPK, skor TOEFL, pendidikan orang tua, pengalaman organisasi, dan pengalaman kerja. Hasil dari penelitian ini memperlihakan bahwa peluang tertinggi bagi para lulusan untuk mendapatkan pekerjaan pertama adalah mulai awal bulan ketiga sampai akhir bulan keempat setelah wisuda, yaitu sebesar 0,31579. Karakteristik yang berpengaruh sig-nifikan terhadap waktu mendapatkan pekerjaan pertama adalah pengalaman organisasi. Model terbaik yang terbentuk adalah ℎ 𝑡,𝑋 = ℎ0 𝑡 exp(−0,979 𝑋6) dengan nilai rasio hazard sebesar 0,376. Hal ini berarti bahwa lulusan yang memiliki pengalaman organisasi memiliki peluang 0,376 kali lebih besar untuk mendapatkan pe-kerjaan pertama setelah wisuda.
Fitting The First Birth Interval in Indonesia Using Weibull Proportional Hazards Model Faruk, Alfensi; Setyo Cahyono, Endro; Eliyati, Ning
CAUCHY Vol 5, No 2 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

The first birth interval is one of the indicators of women’s fertility rate. Because in most cases the first birth interval contains censored observations, the only appropriate statistical method to handle such data is survival analysis. The main objective of this study is to analyze several socioeconomic and demographic factors that affect the first birth interval in Indonesia using the univariate and multivariate survival analysis, that is Kaplan-Meier method and Cox regression model, respectively. The sample is obtained from 2012 Indonesian Demographic and Health Survey (IDHS) and consists of 28242 ever married women aged 15-49 at the time of interview. The results show that age at the first birth, womens educational level, husband’s educational level, contraceptive knowledge, wealth index, and employment status are the significant factors affecting the first birth interval in Indonesia.
Model Epidemik Tuberkulosis Seir dengan Terapi pada Individu Terinfeksi Faruk, Alfensi
Jurnal Penelitian Sains Vol 18, No 3 (2016)
Publisher : Faculty of Mathtmatics and Natural Sciences

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Abstract

The spread of tuberculosis (TB) among individuals in the population can be described by the epidemic  model, which is a mathematical model that divides the population into four subpopulations i.e. susceptible ( ), exposed ( ), infected ( ), and recovered ( ). The objective of this research is to build an epidemic  model for TB transmission by involving total therapy rate ( ) in infected subpopulation.  To illustrate the effects of , a numerical simulation  with different values of    was also carried out using R software. The results showed that the greater value of the total therapy rate, the decrease in the number of in­dividuals in infected subpopulation  became faster.