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MEMODELKAN TINGKAT PENGANGGURAN TERBUKA DI INDONESIA KADEK YUSA MAHENDRA; MADE SUSILAWATI; NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 10 No 1 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i01.p315

Abstract

Unemployment is one of the problems in the field in economic development. To determine the development of open unemployment in a region, an indicator of the open unemployment rate is used. The highest of open unemployment rate is Aceh Province and Maluku Province in 2015 at 9,93 percent and the lowest Bali Province in 2018 at 1,37 percent. The purpose of this work is to modeling and determine the significant factors that affect the open unemployment rate in Indonesia by applying spatial panel data regression. The results show indicate that there is no effect of spatial dependence on the model, so the model chosen to model the open unemployment rate in Indonesia is a panel data model with a fixed time effect and significant affect by head count index, the percentage of illiterate people, the provincial minimum wage, and the number of the workforce.
ANALISIS MODEL REGRESI NONPARAMETRIK SIRKULAR-LINEAR BERGANDA KOMANG CANDRA IVAN; I WAYAN SUMARJAYA; MADE SUSILAWATI
E-Jurnal Matematika Vol 5 No 2 (2016)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2016.v05.i02.p121

Abstract

Circular data are data which the value in form of vector is circular data. Statistic analysis that is used in analyzing circular data is circular statistics analysis. In regression analysis, if any of predictor or response variables or both are circular then the regression analysis used is called circular regression analysis. Observation data in circular statistic which use direction and time units usually don’t satisfy all of the parametric assumptions, thus making nonparametric regression as a good solution. Nonparametric regression function estimation is using epanechnikov kernel estimator for the linier variables and von Mises kernel estimator for the circular variable. This study showed that the result of circular analysis by using circular descriptive statistic is better than common statistic. Multiple circular-linier nonparametric regressions with Epanechnikov and von Mises kernel estimator didn’t create estimation model explicitly as parametric regression does, but create estimation from its observation knots instead.
FAKTOR–FAKTOR YANG BERPENGARUH SIGNIFIKAN TERHADAP INDEKS PEMBANGUNAN MANUSIA DI PROVINSI PAPUA INA AZIZAH KADRI; MADE SUSILAWATI; KARTIKA SARI
E-Jurnal Matematika Vol 9 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2020.v09.i01.p275

Abstract

Geographically weighted regression (GWR) analysis is one of an analysis to resolve the problem with data contains effect of spatial heterogenity. One of the problems which considers spatial heterogeneity is human development index (HDI). HDI is an indicator that used to measure success in building quality of human life. One of the provinces with the lowest HDI in Indonesia is Papua. The purpose of this research is to know the contribution of each HDI factors in Papua using GWR method. The weighting function used is adaptive gaussian kernel. The results of this research showed HDI’s dominant factors in Papua, expected years of schooling and mean years of schooling.
FAKTOR-FAKTOR YANG MEMENGARUHI PDB INDONESIA DENGAN PERSAMAAN SIMULTAN 2SLS NI MADE SRI KUSUMAWARDHANI; I GUSTI AYU MADE SRINADI; MADE SUSILAWATI
E-Jurnal Matematika Volume 1, No 1, Tahun 2012
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2012.v01.i01.p018

Abstract

Economic growth is indicated by an increase in the value of Gross Domestic Product (GDP). The size of GDP is influenced by various factors, including the Household Consumption, Investment, Government Spending, and Net Exports. One of the components that contribute to determine the amount of GDP is investment. According to the concept of macroeconomics, investment is also influenced by the GDP, tax revenue, and Currency. The reciprocal relationship between GDP and the investment is called a simultaneous relationship, therefore this study uses simultaneous equation Two Stage Least Squares (2SLS). 2SLS is one of the statistical methods used to replace the OLS method that can not be used to estimate an equation in a system of simultaneous equations. After analysis, the result shows the variables that influence the investment equation are GDP, tax, and revenue.
IMPLEMENTASI DATA PANEL SPASIAL TERHADAP TINGKAT PRODUK DOMESTIK REGIONAL BRUTO DI PROVINSI BALI NI MADE ARY DHARMA WIDYA ASTUTI; MADE SUSILAWATI; NI LUH PUTU SUCIPTAWATI
E-Jurnal Matematika Vol 10 No 2 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2021.v10.i02.p319

Abstract

Gross Regional Domestic Product (GRDP) is an economic indicator to see the economic movements of a region during a certain period, whether based on current and constant price. Economic activities in a region use the GRDP calculation based on current prices by industrial base year 2010. In 2019, Bali's economic growth increased by , exceeding national economic growth of . Using spatial panel data in analysis consists of common effect model, fixed individual effect model, fixed time effect model, random effect model, and spatial lag fixed effect model. The best model to modeling GRDP Bali Province is spatial lag fixed effect which has a difference in constant values ??at any time, with of 99.41 percent, the remaining is explained by other variables not examined
PEMODELAN RISIKO PENYAKIT PNEUMONIA PADA BALITA DI PROVINSI JAWA TIMUR DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION EVI NOVIYANTARI FATIMAH; I KOMANG GDE SUKARSA; MADE SUSILAWATI
E-Jurnal Matematika Vol 4 No 2 (2015)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2015.v04.i02.p085

Abstract

This research is aim to determine the comparison of logistic regression models and models Geographically Weighted Logistic Regression and the factors that significantly affect the risk of pneumonia in toddlers in East Java Province. Logistic regression is a statistical analysis that is used to describe the response variable is categorical with the independent variables are categorical or continuous. The main problem of this method if  it’s applied in data that is affected of geographic location or spatial data. One of many method to solve the spatial data is Geographically Weighted Logistic Regression (GWLR). GWLR is a statistical method for analyze the data to account for spatial factor. The results showed that there are no significant differences between the logistic regression model with GWLR model. Factors that significantly affect the risk of pneumonia in toddlers in East Java Province is the percentage of low birth weight, the percentage of  toddlers who get measles immunization, the percentage of toddlers who get vitamin A, and the percentage of toddlers who get DPT+HB immunization.
EFEKTIFITAS PEMBELAJARAN PROBLEM BASED LEARNING DALAM MENGANALISIS DATA STATISTIKA MELALUI PENGGUNAAN LEMBAR KERJA MAHASISWA MADE SUSILAWATI
E-Jurnal Matematika Vol 9 No 1 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2020.v09.i01.p280

Abstract

This study aims to improve students' ability to use software in analyzing Statistics data, especially experimental data with the help of Student Worksheets (LKM). This research was conducted at the Mathematics Study Program at the Faculty of Mathematics and Natural Sciences, Udayana University, on students who were taking the Experimental Design course. The design in this study was a one-group pretest-posttest design, by applying Problem Based Learning. The results of the study showed that the majority of students thought that the use of LKM really helped improve students' understanding of the Experimental Design course. This can be seen also from the average posttest score (82.47) which is higher than the average pretest (65.36). The t test also showed that the increase in the mean pretest to posttest was significant with a p value of 0.000 which was smaller than the 5% significance level. This means that the average student posttest score is higher than the average pretest score.
PEMODELAN ANGKA MORTALITAS IBU DI PROVINSI BALI MENGGUNAKAN METODE REGRESI POISSON NI PUTU NADYA AGUSVIANI; I KOMANG GDE SUKARSA; MADE SUSILAWATI
E-Jurnal Matematika Vol 11 No 1 (2022)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2022.v11.i01.p353

Abstract

Maternal Mortality Rate (MMR) is a metric used to assess a region's maternal health status. Maternal death occurs when a woman dies during pregnancy or until 42 days after to the pregnancy itself or its handling. It does not count if the death occurred as a result of an accident or injury. There are number of factors that cause maternal death, one of which is the direct factor that still dominates up to now on. In this study, MMR modeling in Bali was conducted in 2019 by using 6 factors that are thought to be influential. Poisson Regression method is used to determine the factor that cause maternal death. Based on this study of maternal death rate in Province of Bali, it shows that the percentage of pregnant mother visits K1 (X1) and the percentage of obstetric complication cases (X2) are significant towards the variable.
PEMODELAN NILAI KURS TERHADAP HARGA SAHAM PADA DATA LONGITUDINAL MENGGUNAKAN REGRESI NONPARAMETRIK SPLINE MILATUS SHOLIKHA; MADE SUSILAWATI; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 8 No 4 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2019.v08.i04.p262

Abstract

The purpose of this study was to obtain the models between currency value and stocks in longitudinal data. The models were obtained by using nonparametric truncated spline regression. The data consisted of stocks from three companies namely PT. Mandom Indonesia, PT. Unilever Indonesia and PT. Akasha Wira Internasional and currency value of AUD to IDR. The data were splitted into two sub samples which were “in sample” data from January 2013-December 2017 that were used to generate the models and “out sample” data from January 2016-December 2018 to validate the models, MAPE was used as measurement in validation. This resulted in three distinctive models which were model with order and 3 knots for PT. Mandom Indonesia and PT. Unilever Indonesia, model with order and 4 knots for PT. Akasha Wira Internasional stock, all with there own respective knot points and MAPE value of 9.62%, 15.61% and 48.8% sub sequently.
ANALISIS STABILITAS HASIL GENOTIPE JAGUNG MENGGUNAKAN METODE FIXED AMMI MODANA LOLITA; I KOMANG GDE SUKARSA; MADE SUSILAWATI
E-Jurnal Matematika Vol 8 No 1 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2019.v08.i01.p229

Abstract

Additive Main Effect and Multiplicative Interaction (AMMI) is a method that is used in research to study interaction between genotype and location. The aim of this research is to apply fixed AMMI in examining the production of corn genotype data and to explore yield stability of its based on biplot picture and AMMI Stability Value (ASV). This research uses six corn genotypes, eight trial locations, and three repetitions. The Interaction Principal Component Analysis (IPCA) that are significant to entered in the model based on analysis of variance fixed AMMI are IPCA1, IPCA2, and IPCA3 with total diversity interaction as much as 92,16%. The biplot picture and ASV should the stable genotype in all location are genotype KUI Carotenoid Syn FS. 17-3-2-B-B T01 and genotype CML 305-B-B T01. In addition, corns that are able to adapt only in certain location is: genotype KUI Carotenoid Syn FS. 5-1-5-B-B T01, genotype KUI Carotenoid Syn FS. 25-3-2-B-B T01, genotype KUI Carotenoid Syn FS. 17-3-1-B T01, and genotype CML 130-B-B T01.
Co-Authors AA Sudharmawan, AA Ade Widyaningsih Adelia Yuniarti Adinda Audy Sita Mayzandy ALEXANDER JOSEPH RIADI Andini Ni Kadek ANNA FITRIANI Anresangsya Pria Satvika Antesty, Sella Asmara Santhi, Ni Kadek Wulanda As’ady, Mustofa Bagus Hari Sugiharto Bakkara, Bonica Nisra Br Barus, Eka Valencia Chandra, Johnny Chrisna Anzella Jacob Citra Annisa Rahmania DAIMATUL KHOIRIYAH DESAK AYU WIRI ASTITI Desak Putu Eka Nilakusmawati DEWA AYU DWI ASTUTI Dewa, Saroja Sari Diana Anggraini Kusumawati Diana Diana Diva, Made Tresia Pramasta Duffin DWI LARAS RIYANTINI Eddy Silamat, Eddy EKA N. KENCANA Eko Nur Hermansyah EVI NOVIYANTARI FATIMAH Fadil Mas’ud Fatmasari, Ria Kristia Febriyanti, Ni Wayan Atik FELINA CHANTIKA PUTRI G. K. GANDHIADI G. K. GANDHIADI G.K. GANDHIADI GUSTI AYU RATIH ASTARI Hartono Hartono Hellena Hendarta Hiras Pasaribu Hugo Prasetyo Winotoatmojo I Gusti Ayu Made Srinadi I GUSTI AYU MADE VALENTINA DEWI I GUSTI NGURAH SENTANA PUTRA I KOMANG GDE SUKARSA I PUTU ARISTA YASA I Putu Eka Nila Kencana I Putu Winada Gautama I WAYAN RIAN PRATAMA I WAYAN SUMARJAYA I Wayan Sumarjaya I.G.A. DIAH SULASIH IDA AYU SRI PADMINI IMAMUDDIN KAMIL INA AZIZAH KADRI IRA INDRIYANTI IYOS ALFRANTA SURBAKTI Jamaluddin Majid Johannes P Kumagaya Judijanto, Loso Juliani Tandi Tumbiri KADEK YUSA MAHENDRA Kartika Sari Kastini, Ni Wayan Ketut Jayanegara Kharisma Dewi, Ni Putu Dian KOMANG CANDRA IVAN KOMANG KOKOM SUCAHYATI DEWI P Kosasih, Eva Kundori Kusiyah LUH GEDE UDAYANI LUH PUTU IDA HARINI LUH PUTU SAFITRI PRATIWI Luluk Sarifah M ARRIE KUNILASARI ELYNA Made Ayu Asri Oktarini Putri MADE AYU DWI OCTAVANNY MADE NARYMURTI WIDYASTUTI Masnoni, Masnoni Meilandri, Detti MILATUS SHOLIKHA Miltiades Dewifortuna Pulo MIRA AYU NOVITA SARI MODANA LOLITA Muhamad Risal Tawil Naswan Hadilia Neneng Widayati Nggandung, Yeheskial NI KADEK AYU PUJI ASTUTI NI KADEK DWI ARISYA AFRILIANTI NI KADEK ENDAH YANITA UTARI Ni Ketut Tari Tastrawati Ni Komang Jeni Frika Yanti NI LUH GEDE WIDIADNYANI NI LUH PUTU RATNA KUMALASARI Ni Luh Putu Suciptawati NI LUH WIWIN YUNIARTI NI MADE ARY DHARMA WIDYA ASTUTI Ni Made Deviani Prisilia NI MADE PUSPASARI NI MADE SRI KUSUMAWARDHANI NI MADE SRI SUGIANTARI NI MADE SUKMA PERTIWI NI MADE SURYA JAYANTI NI NENGAH RIKA PUSPITA NI NYOMAN UTAMI DEWI Ni Nyoman Widiasih NI PUTU IIN VINNY DAYANTI NI PUTU NADYA AGUSVIANI NI PUTU PREMA DEWANTI NI WAYAN ARI SUNDARI NI WAYAN DIAH SIHMAWATI NI WAYAN WIDYA EKARANI NI WAYAN YUNI CAHYANI Nilakusmawati, DPE ningrum, dedah - Ningrum, Endah Prawesti Nurhanimah Nurul Ilma Nurul Iman, Nurul Nyoman Wendri Octavanny, Made Ayu Dwi PALUPI PURNAMA SARI Parlindungan Dongoran PRISCELLA PURBA PUTRI DAMEYANTI Putu Edi Dimas Saputra PUTU OKA SURYA ARSANA Putu Rama Hari Bagaskara P. Rinovian Rais Sahri, Yulian Sari Purnamayanti, Ni Gusti Ayu Kadek Selan, Dwi Dersmi Siti Hawa SITTI HAJAR Srinadi, I Gusti Ayu Srinadi, IGAM Suciptawati, NLP Syunikitta, Mirwanti Thalib, Najdah Tita Safitriawati Tubagus, Munir Ulfatun Farika Novitasari Usmany, Paul Utami, Eva Yuniarti Wagiyo Widianti, Nyoman Widyatmike Gede Mulawarman Yasir Maulana, Yasir ZAKIAH NURLAILA Zein Ghozali