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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
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Journal : Jurnal Varian

 1 
Comparison K-Means and Fuzzy C-Means In Regencies/Cities Grouping Based on Educational Indicators Gerald Claudio Messakh; Memi Nor Hayati; Sifriyani Sifriyani
Jurnal Varian Vol 7 No 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i1.2879

Abstract

Cluster analysis is an analysis that aims to classify data based on the similarity of specific characteristics. The methods used in this research are K-Means and Fuzzy C-Means (FCM). K-Means is a partition-based non-hierarchical data grouping method. FCM is a clustering technique in which the existence of each data is determined by the degree of membership. The purpose of this study is to classify regencies/cities in Kalimantan based on education indicators in 2021 using K-Means and FCM and find out which method is better to use between K-Means and FCM based on the standard deviation ratio so it can be used efficiently and effectively for decision making by the government to advance the level of education on the island of Kalimantan. Based on the results of the analysis, it's concluded that K-Means is the better method with the ratio of the standard deviation within a cluster against the standard deviation between clusters of 0.6052 which produces optimal clusters of 2 clusters, namely the first cluster consisting of 14 Regencies/Cities, while the second cluster consists of 42 Regencies/Cities in Kalimantan.
Stunting Prevalence Modeling Using Nonparametric Regression of Quadratic Splines Tutik Handayani; Sifriyani Sifriyani; Andrea Tri Rian Dani
Jurnal Varian Vol 7 No 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.2916

Abstract

The nonparametric regression approach is used when the shape of the regression curve between the response variable and the predictor variable is assumed to be of unknown shape. The advantages of nonparametric regression have high flexibility. A nonparametric regression approach that is often used is truncated spline which has an excellent ability to handle data whose behavior changes at certain sub-sub intervals. The purpose of this study is to obtain the best model of multivariable nonparametric regression with linear and quadratic truncated spline approaches using the Generalized Cross Validation (GCV) and Unbiased Risk (UBR) methods and to find out the factors that influence the prevalence of stunting in Indonesia in 2021. The data used were the prevalence of stunting as a response variable and the predictor variable used was the percentage of infants receiving exclusive breastfeeding for 6 months, the percentage of households that have proper sanitation, the percentage of toddlers who get Early Initiation of Breastfeeding (IMD), the percentage of poor people, and the percentage of pregnant women at risk of SEZ. The results showed that the best quadratic truncated spline nonparametric regression model in modeling stunting prevalence was quadraic truncated spline using the GCV method with three knot points. This model has a minimum GCV value of 7.29 with an MSE value of 1.82 and a R2 value of 94.07%.
Stunting Prevalence Modeling Using Nonparametric Regression of Quadratic Splines Handayani, Tutik; Sifriyani, Sifriyani; Rian Dani, Andrea Tri
Jurnal Varian Vol. 7 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.2916

Abstract

The nonparametric regression approach is used when the shape of the regression curve between the response variable and the predictor variable is assumed to be of unknown shape. The advantages of nonparametric regression have high flexibility. A nonparametric regression approach that is often used is truncated spline which has an excellent ability to handle data whose behavior changes at certain sub-sub intervals. The purpose of this study is to obtain the best model of multivariable nonparametric regression with linear and quadratic truncated spline approaches using the Generalized Cross Validation (GCV) and Unbiased Risk (UBR) methods and to find out the factors that influence the prevalence of stunting in Indonesia in 2021. The data used were the prevalence of stunting as a response variable and the predictor variable used was the percentage of infants receiving exclusive breastfeeding for 6 months, the percentage of households that have proper sanitation, the percentage of toddlers who get Early Initiation of Breastfeeding (IMD), the percentage of poor people, and the percentage of pregnant women at risk of SEZ. The results showed that the best quadratic truncated spline nonparametric regression model in modeling stunting prevalence was quadraic truncated spline using the GCV method with three knot points. This model has a minimum GCV value of 7.29 with an MSE value of 1.82 and a R2 value of 94.07%.
Co-Authors A'yun, Qonita Qurrota Abda Abda Adhitya Ronnie Effendie, Adhitya Ronnie Afif Nurdiansyah, Mochamad Afriani, Nur Alam, Muhammad Zainul Andrea Tri Rian Dani Angeline Seru, Indra Anggraeni, Sitti Anisar, Anggi Putri Asnita, Asnita Astafira, Ilyas Atarezcha Pangruruk, Thesya Aufi, Tresna Restu Aulia, Nabila Bahriah, Ayu Chairunnisa, Nurul Rizky Christian, Diego 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 Fadlirhohim, Rizki Dwi Fatia Fatimah Fauziyah, Meirinda Febriana Rinda Sihotang Febriyani, Eka Riche Fidia Deny Tisna Amijaya Gerald Claudio Messakh Hardina Sandariria Hidayanty, Nurul Ilma Hillidatul Ilmi I Nyoman Budiantara Ika Purnamasari Ilmi, Hillidatul indarsih, Indarsih Kesuma, Ahmad Rizky Khoiruddin, Ahmad Zulfikar Khotimah, Ariska Khusnul Koirudin, Hadi Kosasih, Raditya Arya Lestari, Tri Septi Ayu M. Fariz Fadillah Mardianto Mahmuda, Siti Mar'ah, Zakiyah Mar’ah, Zakiyah Memi Nor Hayati Memi Nor Hayati Messakh, Gerald Claudio Mohammad Nurul Huda Muhammad Hunaipi Pratama Mulyadi, Taqriri Kamal Mumtaz, Ghina Fadhilla Nabilla, Maghrisa Ayu Nadia Serena NARITA YURI ADRIANINGSIH Nariza Wanti Wulan Sari Nasywa, Syarifah Novalia, Viona Nugraha, Pratama Yuly Nur, Yumi Handayani Nuraini, Ulfa Siti Nurmayanti, Wiwit Pura Nurul Istiqomah 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 Raihani, Risti Rian Dani, Andrea Tri Rinanda, Farikah Ayu Rito Goejantoro, Rito Salsabila, Adellia Saputri, Marisa Nanda Sari, Ar Ruum Mia Saska, Indria Shalihatunnisa, Shalihatunnisa SITI MAHMUDAH Sitohang, Frans Karta Sayoga Solikhah, Arifatus Solikhatun, Solikhatun Sri Wahyuni Sukamto, Ika Sumiyarsi Surya Prangga Suyitno Suyitno Syaripuddin Syaripuddin Tamba, Felicia Joy Rotua Tandi Kala, Ezra Alfrianto Tutik Handayani Tutik Handayani, Tutik Uha Isnaini Vita Ratnasari Wahyujati, Mohamad Fahruli Wasono, Wasono Wianita Noviani Wiyli Yustanti Yuniarti, Desi Zarkasi, Rifka Nurfaiza Zen, Muhammad Aldani