Article Per Year (5 Year)
p-Index From 2021 - 2026
3.369
P-Index
This Author published in this journals
All Journal Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Science and Technology Indonesia Jurnal Matematika: MANTIK Jurnal Matematika Sains dan Teknologi BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL PENDIDIKAN TAMBUSAI Jurnal Hilirisasi IPTEKS (JHI) Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Matematika UNAND Community Development Journal: Jurnal Pengabdian Masyarakat Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Makara Journal of Health Research Jurnal Natural Multiverse: Open Multidisciplinary Journal
Izzati Rahmi HG
Universitas Andalas
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Veterinary Other

Published : 29 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 29 Documents
Search

 1   2   3 
PENERAPAN MODEL REGRESI COX-WEIBULL UNTUK MENENTUKAN FAKTOR-FAKTOR YANG MEMPENGARUHI LAMA KESEMBUHAN PASIEN TUBERCULOSIS Stepani Burni Safitri; Hazmira Yozza; Izzati Rahmi H.G
Jurnal Matematika UNAND Vol 5, No 4 (2016)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.5.4.62-71.2016

Abstract

Abstrak. Tuberculosis (TBC) merupakan suatu penyakit saluran pernafasan yangdisebabkan bakteri Mycobacterium Tuberculosis dan dapat menyebabkan kematian.Meskipun demikian, dengan perawatan yang tepat, penyakit ini dapat disembuhkan.Penelitian ini bertujuan untuk menentukan faktor-faktor yang mempengaruhi laju kesembuhanpasien penderita TBC di Rumah Sakit dr. M. Djamil Padang serta memodelkanlaju kesembuhan pasien dan mengetahui laju kesembuhannya. Data lama rawatinap pasien penderita TBC di Rumah Sakit dr. M. djamil Padang berdistribusi Weibullsehingga metode analisis yang digunakan adalah analisis survival dengan model regresiCox-Weibull. Diketahui bahwa faktor-faktor yang mempengaruhi laju kesembuhanpasien TBC penderita TBC adalah usia dan jenis kelamin. Dari nilai odds ratio diketahuibahwa pasien dengan jenis kelamin perempuan memiliki resiko sembuh sebesar0,721 kali lebih besar dibandingkan pasien dengan jenis kelamin laki-laki dan diketahuijuga bahwa jika usia bertambah satu tahun maka resiko penderita TBC untuk mencapaikesembuhan bertambah sebesar 1,007 kali dibandingkan pasien lain. Dari penelitianini diketahui juga bahwa kebiasaan merokok berkolerasi dengan variabel jenis kelamin.Sehingga meskipun pengaruh kebiasaan merokok terhadap laju kesembuhan pasien penderitaTBC tidak nyata,namun pengaruh ini dapat dianggap diwakili oleh variabel jeniskelamin.
Applying bootstrap quantile regression for the construction of a low birth weight model Yanuar, Ferra; Yozza, Hazmira; Firdawati, Firdawati; Rahmi, Izzati; Zetra, Aidinil
Makara Journal of Health Research Vol. 23, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Background: Most investigators use ordinary least squares (OLS) methods to model low birth weight. When the data are non-normal or contain outliers, OLS become ineffective. However, the quantile method of forecasting low birth weight has not been fully evaluated, although it has good potential for overcoming problems associated with linear regression. Methods: The present study reports our comparison between the OLS and quantile regression methods for modeling low birth weight when the data are right skewed and outliers are presented. Additionally, we evaluated the performance of the associated algorithm in recovering the true parameter using the bootstrap method. Results: Our study found that a mother’s education level, the number of maternal parities, and the last birth interval significantly impacted low birth weight at any selected low quantile. Based on the bootstrap simulation study, the proposed model was considered to be acceptable since both methods generated nearly identical estimates of the parameter model. An accuracy test proved that the quantile method was an unbiased estimator. Conclusions: The present study found that low birth weight is significantly affected by the mother’s educational level, the number of maternal parities, and the last birth interval.
TEORI DAN PRAKTEK BISNIS MATEMATIKAWAN Susila Bahri; Neng Kamarni; , Riri Lestari; , Izzati Rahmi HG; Haripamyu Haripamyu; Ferra Yanuar; Ahmad Iqbal Baqi
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2022): Volume 3 Nomor 3 Tahun 2022
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v3i3.9867

Abstract

Tidak seimbangnya banyaknya lapangan pekerjaan yang tersedia dengan jumlah lulusan perguruan tinggi, membuat para lulusan jurusan matematika perlu memikirkan untuk membuka lapangan pekerjaan sendiri. Salah satu pekerjaan yang memerlukan ilmu matematika sebagai modal dalam menjalankan pekerjaan tersebut adalah bisnis. Untuk sukses dalam berbisnis, seorang pebisnis perlu mengetahui juga teori ekonomi bisnis serta bagaimana ilmu praktik dari bisnis itu sendiri. Pada webinar pengabdian masyarakat ini satu orang narasumber menyajikan berbagai teori yang digunakan dalam bisnis, sedangkan tiga orang narasumber lainnya menjelaskan tentang bagaimana praktik bisnis yang sedang dijalankannya. Pada tahap akhir webinar, kuesioner dengan 11 pernyataan dianalisis untuk melihat pengaruh maatematika terhadap kesuksesan bisnis. Hasil analisis kuesioner menunjukkan bahwa variabel kemudahan, kemanfaatan serta kemampuan dalam matematika sangat mempengaruhi kesuksesan dalam berbisnis.
The Comparison of WLS and DWLS Estimation Methods in SEM to Construct Health Behavior Model Ferra Yanuar; Fadilla Nisa Uttaqi; Aidinil Zetra; Izzati Rahmi; Dodi Devianto
Science and Technology Indonesia Vol. 7 No. 2 (2022): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (536.173 KB) | DOI: 10.26554/sti.2022.7.2.164-169

Abstract

It is unknown how reliable various point estimates, standard errors, and standard several test statistics are for standardized SEM parameters when categorical data used or misspecified models are present. This paper discusses the comparison between WLS and DWLS for examining hypothesized relations among ordinal variables. In SEM, the polychoric correlation is employed either in WLS or DWLS. This study constructs the Health behavior model as an endogenous latent variable in which exogenous latent variables are Perceived susceptibility and Health motivation. All indicators are in categorical types. Thus, data are not multivariate normal, or the model could be misspecified. This study compares the values of standard deviation and coefficient determination to determine a better model. The criteria for the goodness of fit for the overall model are based on RMSEA, CFI, and TLI values. This present study found that the WLS estimator method resulted in better values than DWLS’s.
Spatial Autoregressive Quantile Regression with Application on Open Unemployment Data Ferra Yanuar; Tasya Abrari; Izzati Rahmi HG; Aidinil Zetra
Science and Technology Indonesia Vol. 8 No. 2 (2023): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2023.8.2.321-329

Abstract

The Open Unemployment Level (OUL) is the percentage of the unemployed to the total labor force. One of the provinces with the highest OUL score in Indonesia is West Java Province. If an object of observation is affected by spatial effects, namely spatial dependence and spatial diversity, then the regression model used is the Spatial Autoregressive (SAR) model. Quantile regression minimizes absolute weighted residuals that are not symmetrical. It is perfect for use on data distribution that is not normally distributed, dense at the ends of the data distribution, or there are outliers. The Spatial Autoregressive Quantile Regression (SARQR) is a model that combines spatial autoregressive models with quantile regression. This research used the data regarding OUR in West Java in 2020 from the Central Bureau of Statistics. This study develops to modeling the Open Unemployment Level in all province in Indonesia using modified spatial autoregressive model with the quantile regression approach. This study compares the estimation results based on SAR and SARQR models to obtain an acceptable model. In this study, it was found that the SARQR model is better than SAR at dealing with the problems of dependency and diversity in spatial data modeling and is not easily affected by the presence of outlier data.
The Classification of “Program Sembako” recipients in Payobasung West Sumatra based on the K-nearest neighbors classifier HAZMIRA YOZZA; NINDI MAULA AZIZAH; LYRA YULIANTI; IZZATI RAHMI
Jurnal Natural Volume 23 Number 2, June 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i2.29738

Abstract

The "Sembako Program" is a program carried out by the Indonesian government to improve the welfare of low-income communities. The purposes of this study are: (a) to determine the classification of households that deserve to receive basic-food assistance in Koto Panjang Payobasung, West Sumatra, using the KNN classifier and (b) to determine the optimal number of nearest neighbors used in the classification process. The measure of proximity between objects used is the Gower dissimilarity coefficient. This research used primary data consisting of 175 households collected purposively in a survey conducted on all households in Payobasung.  The optimal K value is determined by implementing a 5-fold cross-validation procedure. The result showed that the best classification process is when K = 3 nearest neighbors are used since it produces the highest accuracy coefficient and Mattews correlation coefficient (MCC). Therefore, for further work, in deciding the eligibility of a household to receive the Sembako Program in Payobasung, KNN can be used by considering its 3 nearest neighbors
Comparison Between SARIMA Model and Artificial Neural Network On Forecasting Foreign Tourist in Batam City Fadila Rasyid; DODI DEVIANTO; IZZATI RAHMI HG
Jurnal Matematika UNAND Vol 12, No 3 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.3.282-290.2023

Abstract

Batam City is one of the tourist attractions in Indonesia with the number of foreign tourist arrivals increasing every year. As one of the impacts of increasing the number of foreign tourist visits, the provincial government must improve the existing facilities in the tourism area, both in quality and quantity. In order for these facilities to be adequate to serve foreign tourists visiting Batam City in the future, it is estimated that the number of tourist visits to Batam City in the future is expected. This study aims to model foreign tourist arrivals using the SARIMA method and Neural Networks and compare the accuracy of the two methods with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The best SARIMA model for data on the number of foreign tourist arrivals to Batam City is SARIMA (2, 1, 0)(1, 1, 0)12 with MSE = 2,672,774,359 and MAPE = 21,4487%. The Neural Network Model is ˆy = max(0, 0.03208266 + 0.48310924V1 +...+ 0.46732363V8) with MSE = 171.279.990 and MAPE = 7.1404%. Thus, modeling with Artificial Neural Networks in these cases provides a better model than SARIMA in modeling data on the number of tourist visits to Batam City.
PEMILIHAN CARA PERKULIAHAN YANG EFEKTIF BAGI MAHASISWA JURUSAN MATEMATIKA UNIVERSITAS ANDALAS DENGAN METODE ANALYTICAL HIERARCHY PROCESS Rahmat Fajri; Izzati Rahmi HG; Hazmira Yozza
Jurnal Matematika UNAND Vol 13, No 2 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.2.106-118.2024

Abstract

Perkuliahan adalah kegiatan antara dosen dan mahasiswa di perguruan tinggi sesuai dengan pokok bahasan mata kuliah. Cara pelaksanaan perkuliahan di zaman sekarang dapat dilakukan melalui dua cara yaitu tatap muka dan daring. Untuk Menentukan cara pelaksanaan yang efektif maka dibutuhkan suatu metode pengambilan keputusan. Salah satu metode yang dapat digunakan adalah Analitycal Hierarchy Process (AHP). AHP adalah sebuah metode pengambilan keputusan untuk menghadapi permasalahan yang kompleks dalam menentukan pilihan ataupun prioritas terhadap alternatif pemecahan masalah yang ada. Data yang digunakan adalah data hasil dari kuesioner yang disebarkan pada mahasiswa Jurusan Matematika Universitas Andalas angkatan 2018 dan 2019. Dari hasil analisis didapatkan, mahasiswa lebih memilih tatap muka dengan nilai prioritas 83; 05%.
PERBANDINGAN METODE FUZZY TIME SERIES MARKOV CHAIN DAN FUZZY TIME SERIES CHENG DALAM MERAMALKAN NILAI TUKAR RUPIAH TERHADAP DOLAR AMERIKA SERIKAT (AS) M.PIO HIDAYATULLAH; HAZMIRA YOZZA; IZZATI RAHMI HG
Jurnal Matematika UNAND Vol 12, No 2 (2023)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.12.2.121-134.2023

Abstract

Nilai tukar mata uang atau yang sering disebut dengan kurs merupakanharga satu unit mata uang asing dalam mata uang domestik atau dapatjuga dikatakan harga mata uang domestik terhadap mata uang asing.Nilai tukar rupiah terhadap dolar Amerika Serikat memainkan peranan sentraldalam perdagangan internasional, karena nilai tukar rupiah terhadap dolarAmerika Serikat memungkinkan seseorang untuk membandingkan harga-hargasegenap barang dan jasa yang dihasilkan berbagai negara. Pertumbuhan nilaitukar mata uang yang stabil menunjukkan bahwa negara tersebut memilikikondisi perekonomian yang stabil. Oleh sebab itu perlu dilakukan peramalannilai tukar rupiah terhadap dolar Amerika Serikat untuk beberapa waktu yangakan datang sebagai dasar pengambilan keputusan bagi pemerintah. Beberapametode peramalan yang dapat dilakukan untuk meramalkan data time seriesnilai tukar rupiah terhadap dolar Amerika Serikat adalah metode fuzzy timeseries markov chain dan fuzzy time series Cheng. Kedua metode ini akan ditentukanhasil peramalannya kemudian dibandingkan tingkat akurasinya menggunakanMSE, MAE, dan MAPE sehingga diperoleh metode peramalan yangpaling tepat untuk meramalkan nilai tukar rupiah terhadap dolar AmerikaSerikat. Pada penelitian ini diperoleh metode terbaik untuk meramalkan nilaitukar rupiah terhadap dolar Amerika Serikat adalah metode fuzzy time seriesmarkov chain.
The Classification of “Program Sembako” recipients in Payobasung West Sumatra based on the K-nearest neighbors classifier HAZMIRA YOZZA; NINDI MAULA AZIZAH; LYRA YULIANTI; IZZATI RAHMI
Jurnal Natural Volume 23 Number 2, June 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i2.29738

Abstract

The "Sembako Program" is a program carried out by the Indonesian government to improve the welfare of low-income communities. The purposes of this study are: (a) to determine the classification of households that deserve to receive basic-food assistance in Koto Panjang Payobasung, West Sumatra, using the KNN classifier and (b) to determine the optimal number of nearest neighbors used in the classification process. The measure of proximity between objects used is the Gower dissimilarity coefficient. This research used primary data consisting of 175 households collected purposively in a survey conducted on all households in Payobasung.  The optimal K value is determined by implementing a 5-fold cross-validation procedure. The result showed that the best classification process is when K = 3 nearest neighbors are used since it produces the highest accuracy coefficient and Mattews correlation coefficient (MCC). Therefore, for further work, in deciding the eligibility of a household to receive the Sembako Program in Payobasung, KNN can be used by considering its 3 nearest neighbors
Co-Authors Admi Nazra Alfiaturrahmi, Alfiaturrahmi Arrival Rince Putri Bahri, Susila Baqi, Ahmad Iqbal Budi Susetyo Citra Komang Sari Devianto, Dodi Efendi, Riswan Fadila Rasyid Fadilla Nisa Uttaqi Febriyuni, Rahmi Firdawati, Firdawati Haripamyu Haripamyu Hazmira Yozza Helmi, Monika Rianti Indahwati Indahwati Jenizon Jenizon Kamarni, Neng Khairunnisa, Latifa Lestari, Sarima M.PIO HIDAYATULLAH Maiyastri, Maiyastri Mega Susanti Mutiara Fara Nabilla Nadya Putri Alisya Narwen Narwen NINDI MAULA AZIZAH Qistina, Nurul Ain Rahmat Fajri Rahmat Fajri Riri Lestari Samat, Nor Azah Stepani Burni Safitri Suci Rahma Nio Syafwan, Mahdhivan Syamsiah, Syamsiah Tasya Abrari WULANDARI, FRILIANDA Wulandari, Yana Yanita Yanita Yanuar, Ferra Yulianti, Lyra Yulmiati Yulmiati Zahra, Latifah Zetra, Aidinil