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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 : JTAM (Jurnal Teori dan Aplikasi Matematika)

 1 
Implementation of Data Mining and Spatial Mapping in Determining National Food Security Clusterization Sifriyani, Sifriyani; Budiantara, I Nyoman; Mardianto, M. Fariz Fadillah; Febriyani, Eka Riche; Chairunnisa, Nurul Rizky; Putri, Asyifa Charmadya
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 3 (2024): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i3.19912

Abstract

This study proposes a cluster analysis of provinces based on national food security data. The research objective is to determine provincial clusters based on food indicators which include rice harvest area, distribution of rice stocks, percentage of trade margin and transportation of rice distribution, percentage of average per capita expenditure, and total per capita consumption of rice. The source of observation data for the Rice Harvested Area by Province variable is the Ministry of Agriculture, Central Bureau of Statistics and Agriculture Services throughout Indonesia. This study uses data mining techniques in data processing with the K-Medoids algorithm. The K-Medoids method is a clustering method that functions to break down data sets into several groups. The advantage of this method is that it can overcome the weakness of the K-Means method which is sensitive to outliers. Another advantage of this algorithm is that the results of the clustering process do not depend on the order in which the dataset is entered. The k-medoids clustering method can be applied to food security data by province. From grouping the data obtained three clusters, with silhouette coefficient values for cluster 1, cluster 2, and cluster 3 respectively 0.33; 0.32; and 0.44. With the largest silhouette coefficient value obtained in cluster 3 and the cluster has entered into a strong cluster structure. The research results can provide information to the government about food security grouping data in Indonesia which has an impact on the distribution and availability of food in Indonesia.
Geographically Weighted Panel Regression Modelling of Dengue Hemorrhagic Fever Data Using Exponential Kernel Function Raihani, Risti; Sifriyani, Sifriyani; Prangga, Surya
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 4 (2023): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i4.16235

Abstract

Geographically Weighted Panel Regression (GWPR) model is a panel regression model applied to spatial data. This research takes the Fixed Effect Model (FEM) panel regression as the global model and GWPR as the local model for dengue hemorrhagic fever (DHF) in East Kalimantan Province data over the years 2018-2020. DHF is a disease that has the potential to become an extraordinary event which is accompanied by death. In comparison to Indonesia, East Kalimantan Province's DHF Incident Rate (IR) was high in 2020. East Kalimantan's IR is 60.6 per 100,000 population, compared to Indonesia's IR of 40.0 per 100,000 population. This research aims to obtain the GWPR model, as well as to acquire factors that affect DHF in East Kalimantan Province over the years 2018-2020 based GWPR model. The parameter of the GWPR model was estimated on each observation location using the Weighted Least Square (WLS) method, which is an Ordinary Least Square (OLS) with the addition of spatial weighting. The spatial weighting on the GWPR model was determined by the best weighting function between fixed exponential and adaptive exponential. The optimum weighting function with a minimum cross-validation (CV) value of 1.7317×106 is adaptive exponential. Based on GWPR parameter testing, factors that affect DHF are local and diverse in each 10 regencies/municipalities in East Kalimantan Province. These factors are population density, number of health facilities, percentage of proper sanitation use in the household, percentage of household with qualified drinking water sources, and percentage of health services. The coefficient of determination of the GWPR model obtains a higher value than the FEM, which is 95.33%. Based on the measurement of goodness using the coefficient of determination value, it can be concluded that GWPR is the best method to model the DHF data rather than the FEM.
Nonparametric Spline Truncated Regression with Knot Point Selection Method Generalized Cross Validation and Unbiased Risk Handayani, Tutik; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 3 (2023): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i3.14034

Abstract

Nonparametric regression approaches are used when the shape of the regression curve between the response variable and the predictor variable is assumed to be unknown. Nonparametric excess regression has high flexibility. A frequently used nonparametric regression approach is a truncated spline that has excellent ability to handle data whose behavior is variable at certain sub-intervals. The aim of this study was to obtain the best model of multivariable nonparametric regression with linear and quadratic truncated spline approaches using Generalized Cross Validation (GCV) and Unbiased Risk (UBR) methods and to find out the factors influencing stunting prevalence in Indonesia in 2021. The data used are the prevalence of stunting as a response variable and the predictor variable used by the percentage of infants receiving Exclusive breastfeeding for 6 months, the percentage of households with proper sanitation, the percentage of toddlers receiving Early Childhood Cultivation (IMD), the percentage of the poor population, and the percentage of pregnant womenIt's a risk. Results show that the best linear and quadratic nonparametric spline truncated regression model in modeling the stunting prevalence is linear truncated spline using the GCV method with three knot points. This model has the minimum GCV value of 7.29 with MSE value of 1.82. Factors influencing the incidence of stunting in Indonesia in 2021 include the percentage variable of infants receiving Exclusive breastfeeding for 6 months, the percentage of households with proper sanitation, the percentage of poor people, and the percentage of pregnant women at risk of KEK. 
Co-Authors A'yun, Qonita Qurrota Afriani, Nur Alam, Muhammad Zainul 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 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 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 Raihani, Risti Rian Dani, Andrea Tri Rinanda, Farikah Ayu 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, Tutik Vita Ratnasari Wasono, Wasono Wianita Noviani Wiyli Yustanti Yuniarti, Desi Zarkasi, Rifka Nurfaiza Zen, Muhammad Aldani