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All Journal Media Statistika Statistika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Varian Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Abdi Insani ESTIMASI: Journal of Statistics and Its Application International Journal Of Science, Technology & Management (IJSTM) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Jurnal Siger Matematika Journal of Research Applications in Community Services Eksponensial STATISTIKA Journal of Education Technology and Information System

Sifriyani, Sifriyani

Statistics Study Program, Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Mulawarman University, Samarinda

Author-ID : 1591418

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I-Regs (Internet-Regression Analysis) as a Statistical Innovation in Nonparametric Regression Modeling Dani, Andrea; Budiantara, I Nyoman; Nuraini, Ulfa Siti; Yustanti, Wiyli; Sifriyani; Putra, Fachrian Bimantoro
Journal of Education Technology and Information System Vol. 1 No. 02 (2025): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jetis.v1i02.35288

This research develops an information system based on the R-Shiny Dashboard, allowing users to perform nonparametric regression modeling. Internet-Regression Analysis (I-Regs) is the name of a dashboard that has been successfully developed. I-Regs provides a complete model library in regression analysis modeling, including parametric, nonparametric, and semiparametric regression. It is hoped that I-Regs can become a valuable tool for researchers, practitioners, and students in modeling regression analysis and solving various data analysis problems.

PELATIHAN ANALISIS DATA DENGAN SOFTWARE R BAGI SISWA SMA NEGERI 8 SAMARINDA Sari, Nariza Wanti Wulan; Sifriyani, Sifriyani; Suyitno, Suyitno; Wahyuningsih, Sri; Yuniarti, Desi; Purnamasari, Ika; Mahmudah, Siti; Nurmayanti, Wiwit Pura; Widyaningrum, Erlyne Nadhilah; Nugraha, Pratama Yuly; Pangruruk, Thesya Atarezcha; Hidayanty, Nurul Ilma; Kosasih, Raditya Arya; Bahriah, Ayu
Jurnal Abdi Insani Vol 12 No 7 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i7.2136

Students of SMA Negeri 8 Samarinda have received material on statistics since grade X. In the learning process, teachers use Microsoft Office Excel software which is closed source. So through this community service activity, a solution is provided by disseminating data analysis and alternative open source software 'R'. Community service activities are packaged in the form of training. Evaluation of activities in the form of pretest and posttest questionnaires and activity feedback surveys. This activity was carried out on September 11, 2024 in the Computer Laboratory Room of SMA Negeri 8 Samarinda. The number of students who participated in this activity consisted of 36 students. Based on the analysis of the pre-test and post-test data, it was concluded that there was an increase in student understanding after the training. The results of the feedback stated that the training material was easy, the explanations given were considered interesting, and the training activities were considered useful by the participants. Furthermore, participants hope that there will be follow-up activities to hold similar activities again.

REGRESI NONPARAMAETRIK SPLINE PADA DATA LAJU PERTUMBUHAN EKONOMI DI KALIMANTAN Purnaraga, Tirta; Sifriyani, Sifriyani; Prangga, Surya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Economic Growth Rate (EGR) is an important indicator for measuring the success of an economy's development. The welfare and progress of an economy is determined by the amount of growth shown by changes in the quantity of goods and services produced nationally. High economic growth is a goal that is expected to be achieved in a developing country. Many factors affect EGR in Kalimantan, so it is necessary to do modeling to find out the factors that significantly affect EGR. This study uses 6 factors that are suspected to influence EGR, namely the labor force participation rate, the number of large and medium industries, the average length of schooling, regional income and expenditure budgets, general allocation funds and rice productivity. The data is 2017 data obtained from the Central Bureau of Statistics in 5 provinces in Kalimantan. The method used to model the LPE is spline nonparametric regression and the optimal knot point is 3 knot points based on the smallest Generalized Cross Validation (GCV) value of 1.208. The research results, the best model is obtained with a R2 value of 82.15 percent and a Mean Square Error (MSE) of 0.805. The results of the study provide information that the factors that influence the LPE are the level of labor force participation, the number of large and medium industries, the average length of schooling, regional income and expenditure budgets, general allocation funds and rice productivity.

IDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DI KALIMANTAN MENGGUNAKAN REGRESI PANEL Zarkasi, Rifka Nurfaiza; Sifriyani, Sifriyani; Prangga, Surya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Pembangunan merupakan salah satu cara untuk meningkatkan kualitas kehidupan demi terciptanya masyarakat yang sejahtera. Pemerintah terus melakukan pembangunan di segala aspek seperti aspek pendidikan, kesehatan, dan kehidupan yang layak. Untuk mengukur keberhasilan pembangunan salah satu indikator yang bisa digunakan adalah Indeks Pembangunan Manusia (IPM). Dalam perhitungan IPM, telah melibatkan komponen ekonomi maupun non ekonomi. Penelitian ini bertujuan untuk meneliti faktor-faktor yang mempengaruhi IPM Kalimantan pada tahun 2014-2017. Karena data yang digunakan merupakan data panel yaitu gabungan antara data cross-section dan data time-series, maka IPM dimodelkan dengan regresi panel. Untuk mengestimasi model digunakan pendekatan Fixed Effect Model (FEM). Pemodelan IPM menghasilkan nilai sebesar 99,54 persen. Hasil penelitian menunjukkan bahwa untuk meningkatkan IPM dapat dilakukan dengan cara meningkatakan angka harapan hidup, rata-rata lama sekolah, harapan lama sekolah, dan pengeluaran per kapita.

PEMODELAN ANGKA HARAPAN HIDUP DAN ANGKA KEMATIAN BAYI DI KALIMANTAN DENGAN REGRESI NONPARAMETRIK SPLINE BIRESPON Padatuan, Aprianti Boma; Sifriyani, Sifriyani; Prangga, Surya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Penelitian ini menggunakan model regresi nonparametrik birespon dengan pendekatan spline truncated. Model tersebut digunakan untuk menyelesaikan permasalahan analisis regresi yang bentuk kurvanya tidak diketahui. Pendekatan spline truncated memiliki fungsi polinomial tersegmen yang memberikan sifat fleksibilitas. Data yang digunakan dalam penelitian ini terdiri dari dua variabel respon yaitu Angka Harapan Hidup (AHH) dan Angka Kematian Bayi (AKB) di Pulau Kalimantan. Tujuan penelitian adalah untuk menentukan model regresi nonparametrik spline truncated birespon pada data AHH dan AKB dan mengetahui faktor-faktor yang mempengaruhi AHH dan AKB. Hasil penelitian diperoleh model terbaik yaitu model regresi nonparametrik spline linier birespon dengan nilai R2 sebesar 80,51 persen dan model spline tiga titik knot dengan nilai Generalized Cross Validation (GCV) minimum 7,1454. Faktor-faktor yang mempengaruhi AHH dan AKB adalah persentase keluarga menerapkan Perilaku Hidup Bersih dan Sehat (PHBS), persentase bayi diberi Air Susu Ibu (ASI) usia 0-6 bulan, laju pertumbuhan ekonomi, persentase persalinan yang dibantu oleh tenaga medis dan persentase penduduk miskin.

NONPARAMETRIK REGRESSION MODEL ESTIMATION WITH THE FOURIER SERIES THE FOURIER SERIES APPROACH AND ITS APPLICATION TO THE ACCUMULATIVE COVID-19 DATA IN INDONESIA Pasarella, Muhammad Danil; Sifriyani, Sifriyani; Amijaya, Fidia Deny Tisna
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

The nonparametric regression model is applied to regression curves for which the regression curve is unknown. Fourier series estimation is an approach in nonparametric regression, which has high flexibility and is able to adjust to the local nature of data effectively. The purpose of the research is to obtain an estimate of the nonparametric regression model with the Fourier series approach with optimal oscillation values and the model suitability of the positive case of Covid-19 in Indonesia. Research on modeling positive cases of Covid-19 in Indonesia using nonparametric regression with the best Fourier series approach is found in the third oscillation by having a minimum GCV of 78969281 with the best model criteria R2 = 97.86% with influencing factors are the percentage of active smokers, the number of health workers, the number of health service facilities, population density and the percentage of the poor population.

IMPLEMENTATION OF THE FUZZY GUSTAFSON-KESSEL METHOD ON GROUPING DISTRICTS/CITIES IN KALIMANTAN ISLAND BASED ON POVERTY ISSUES FACTORS Paradilla, Yunda Sasha; Hayati, Memi Nor; Sifriyani, Sifriyani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Cluster analysis is an analysis that is useful in summarizing data by grouping objects based on certain similarity characteristics. One of the group analysis is Fuzzy Gustafson-Kessel (FGK) which is the development of the Fuzzy C-Means (FCM) method. The FGK method has a good way in adjusting the form of cluster membership function correctly for a data. This study aims to determine the results of the optimal number of groups based on the Partition Coefficient (PC) and Classification Entropy (CE) validity indexes and to find out the results of grouping 56 districts/cities on the island of Kalimantan based on poverty issue factors in 2021. The optimal number of groups using the FGK method based on the validity indexes of PC and CE are two groups. The first group and the second group each consist of 28 districts/cities in Kalimantan Island.

REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL Sari, Ar Ruum Mia; Sifriyani, Sifriyani; Huda, Mohammad Nurul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the nonparametric regression model approaches that is often used is the spline. The truncated spline approach has a segmented polynomial function that provides flexibility. The data used in the study were blood glucose levels in patients with diabetes mellitus, cholesterol levels, and triglyceride levels in 2020. From the results of the study, the best nonparametric biresponse spline truncated regression model with three knot points has been obtained where the minimum GCV value is and has the an value of .

GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) FOR COVID-19 CASE IN INDONESIA Mar'ah, Zakiyah; Sifriyani, Sifriyani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0879-0886

Coronavirus disease 2019 (COVID-19) is a newly emerging infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) which was declared a pandemic by the World Health Organization (WHO) on March 11th, 2020. The response to this ongoing pandemic requires extensive collaboration across the scientific community to contain its impact and limit further transmission. Modeling to see cause-and-effect relationships in an event usually uses the Multiple Linear Regression (Ordinary Least Square) method. But in the case of Covid-19, the spread of the virus occurred from one location to another, so there was an indication that there was a spatial effect on the incident. In this study, we did not only look at spatial perspective but also considered time series data, so the method used was Geographically Weighted Panel Regression (GWPR). This study modeled the number of positive cases of Covid-19 in 34 provinces in Indonesia that occurred from March 2020 to August 2021 and looked at what factors influenced the number of positive cases of Covid-19 in each province. GWPR was performed with the assumption of a Fixed Effect Model (FEM). The FEM assumption was used by considering that the conditions of each observation unit were different. Based on the results, the best GWPR model obtained was the GWPR model with a Fixed Gaussian Kernel. The predictor variables that influenced the number of positive cases of Covid-19 were different at each location and tent to cluster at certain locations.

TUBERCULOSIS CASE MODEL USING GCV AND UBR KNOT SELECTION METHODS IN TRUNCATED SPLINE NONPARAMETRIC REGRESSION Anggraeni, Sitti; Sifriyani, Sifriyani; A'yun, Qonita Qurrota
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1565-1574

The nonparametric regression approach is used when the shape of the regression curve is not known. The advantage of nonparametric regression is that it has a high degree of flexibility. The truncated spline is a method in the nonparametric regression approach, which can overcome changing data patterns at certain sub-intervals with the help of knot points. The purpose of this research is to obtain the best truncated spline nonparametric regression model estimates based on the GCV and UBR knot point selection methodsThe data used in this study came from the publications of the Indonesian Ministry of Health and BPS Indonesia. The response variable used is the percentage of successful treatment of tuberculosis patients in Indonesia with predictor variables namely the percentage of people who smoke over the age of 15 years, the percentage of households that have access to proper sanitation, the percentage of poor people, the percentage of food processing establishments that meet the standard requirements , national health insurance membership coverage and percentage of accredited hospitals. The results showed that the best model came from the GCV method using three knots. This model produces an MSE value of 3.65 with value of 97.04. The value indicates that the predictor variable used in this study affects the response variable by 97.04% while the other 2.96% is influenced by other variables that are not included in this study.

Co-Authors A'yun, Qonita Qurrota Afriani, Nur Alam, Muhammad Zainul Andrea Tri Rian Dani Andrea Tri Rian Dani Anggraeni, Sitti Anisar, Anggi Putri Asnita, Asnita Astafira, Ilyas Aufi, Tresna Restu Bahriah, Ayu Chairunnisa, Nurul Rizky Clemensius Arles Damayanti, Elok Dani, Andrea Dani, Andrea Tri Rian Darnah Andi Nohe Darnah, Darnah Dedi Rosadi Deni Sunaryo Eka Nur Amaliah Erlyne Nadhilah Widyaningrum Etty Puji Lestari Fachrian Bimantoro Putra Fadlirhohim, Rizki Dwi Fatia Fatimah Fauziyah, Meirinda Febriana Rinda Sihotang Febriyani, Eka Riche Fidia Deny Tisna Amijaya Gerald Claudio Messakh Hadi Koirudin Hidayanty, Nurul Ilma Hillidatul Ilmi I Nyoman Budiantara Ika Purnamasari Ilmi, Hillidatul Kesuma, Ahmad Rizky Khotimah, Ariska Khusnul Kosasih, Raditya Arya Lestari, Tri Septi Ayu M. Fariz Fadillah Mardianto Mahmuda, Siti Mar'ah, Zakiyah Mar’ah, Zakiyah Meirinda Fauziyah Memi Nor Hayati Memi Nor Hayati Messakh, Gerald Claudio Mohammad Nurul Huda Muhammad Aldani Zen Muhammad Hunaipi Pratama Mumtaz, Ghina Fadhilla Nabilla, Maghrisa Ayu Nadia Serena NARITA YURI ADRIANINGSIH Nariza Wanti Wulan Sari Novalia, Viona Nugraha, Pratama Yuly Nur, Yumi Handayani Nuraini, Ulfa Siti Nurmayanti, Wiwit Pura Padatuan, Aprianti Boma Pangruruk , Thesya Atarezcha Pangruruk Paradilla, Yunda Sasha Pasarella, Muhammad Danil Purnaraga, Tirta Putra, Fachrian Bimantoro Putri, Asyifa Charmadya Rabiatul Adawiyah Rahman, Athaya Azahra Rahmania Rahmania Rinanda, Farikah Ayu Risti Raihani Rito Goejantoro, Rito Saputri, Marisa Nanda Sari, Ar Ruum Mia Saska, Indria Siti Mahmuda SITI MAHMUDAH Sitohang, Frans Karta Sayoga Sri Wahyuningsih Sri Wahyuningsih Surya Prangga Suyitno Suyitno Suyitno Suyitno Tutik Handayani Tutik Handayani Vita Ratnasari Wasono, Wasono Wianita Noviani Wiyli Yustanti Yuniarti, Desi Zarkasi, Rifka Nurfaiza

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