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PEMODELAN JUMLAH KASUS PNEUMONIA BALITA DI JAWA TIMUR MENGGUNAKAN REGRESI SPATIAL AUTOREGRESSIVE MOVING AVERAGE MADE NARYMURTI WIDYASTUTI; I GUSTI AYU MADE SRINADI; MADE SUSILAWATI
E-Jurnal Matematika Vol 8 No 3 (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.i03.p259

Abstract

The purpose of this study is to model and determine the factors that significantly influence the number of toddler pneumonia cases in East Java Province. Modeling the number of toddler pneumonia cases was conducted using spatial autoregressive moving average (SARMA) regression analysis. The results showed that the best model to modeling was SARMA (1.1) with the AIC value is and the coefficient of determination ( is . The significant factors that affect the number of these cases are the number of toddler receiving complete basic immunization and the number of toddler receiving health services in each district/city.
MODEL ANGKA PARTISIPASI SEKOLAH JENJANG SMA SEDERAJAT DI PROVINSI BALI NI LUH GEDE WIDIADNYANI; NI LUH PUTU SUCIPTAWATI; MADE SUSILAWATI
E-Jurnal Matematika Vol 8 No 3 (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.i03.p250

Abstract

Each distritcs in Bali Province has an uneven high school enrollment rate. The lowest of high school enrollment rate is Bangli Regency in 2012 at 41,99 percent and the highest is Klungkung Regency in 2014 at 91,49 percent. The purpose of this work is to modeling and determine the significant factors that affect the high school enrollment rate in Bali Province by applying panel data regression. The results show the suitable model is fixed effect model (FEM) that is fixed individual effect model and significant affect by HDI, the percentage of poverty, and gini ratio.
FAKTOR–FAKTOR YANG MEMENGARUHI MINAT MAHASISWA ASAL LUAR BALI KULIAH DI FMIPA UNIVERSITAS UDAYANA BALI DAIMATUL KHOIRIYAH; MADE SUSILAWATI; DESAK PUTU EKA NILAKUSMAWATI
E-Jurnal Matematika Vol 2 No 1 (2013): E-Jurnal Matematika
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.2013.v02.i01.p024

Abstract

Tujuan dari penelitian ini adalah untuk mengetahui faktor–faktor yang memengaruhi minat mahasiswa luar Bali kuliah di FMIPA Universitas Udayana Bali. Analisis yang digunakan  dalam  penelitian  ini  adalah  analisis  faktor.  Data  yang digunakan  adalah data primer yang diperoleh dengan menyebarkan kuesioner kepada setiap mahasiswa asal luar Bali yang kuliah di FMIPA Universitas Udayana Bali angkatan 2008-2011. Dalam penelitian ini faktor-faktor  yang digunakan  adalah  lokasi,  faktor  biaya,  produk,  latar  belakang sosial ekonomi,  motivasi,  fasilitas,  referensi,  promosi,  dan  reputasi.  Hasil  penelitian menunjukkan  bahwa,  terdapat  delapan  faktor  yang memengaruhi  minat  mahasiswa luar Bali kuliah di FMIPA Universitas Udayana Bali. Faktor tersebut yaitu: (1) faktor produk yang merupakan faktor dengan nilai eigen paling tinggi yaitu 7,792 dan varian 28,860%, (2) faktor referensi dengan varian 8,732%, (3) faktor reputasi dengan varian 7,808%,  (4)  faktor  biaya  dengan  varian  6,723%, (5) faktor  latar  belakang sosial ekonomi dengan varian 4,921%, (6) faktor motivasi dengan varian 4,430%, (7) faktor lokasi dengan  varian 3,836% dan (8)  faktor promosi  dengan  varian  3,708%, dengan total varian yang dapat dijelaskan adalah sebesar 69,018%.
ESTIMASI MODEL REGRESI SEMIPARAMETRIK MENGGUNAKAN ESTIMATOR KERNEL UNIFORM (Studi Kasus: Pasien DBD di RS Puri Raharja) ANNA FITRIANI; I GUSTI AYU MADE SRINADI; MADE SUSILAWATI
E-Jurnal Matematika Vol 4 No 4 (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.i04.p108

Abstract

Semiparametric regression model estimation is an estimation that combines both parametric and nonparametric regression model. In semiparametric regression, some of the variables are parametrics and the others are nonparametrics. Semiparametric regression is used when relationship pattern between independent and depentdent variables is half known  and half unknown. Regression curve smoothing technique in nonparametric components in this study was using uniform kernel function. The optimal semiparametric regression curve estimation was obtained by optimal bandwidth. By choosing optimal bandwidth, we would obtain a smooth regression curve estimation in respect to data pattern. In choosing optimal bandwidth, we use minimum GCV as a criteria.The purpose of this study was to estimate the semiparametric regression function of dengue fever case using uniform kernel estimator. There were 6 independent variables namely age (in years) body temperature (in Celcius), heartbeat (in times/minutes) hematocryte ratio (in percent), amount of trombocyte (× 103/ul) and fever duration ( in days). Age, body temperature, heartbeat, amount of trombosyte and fever duration are parametric components and hematocryte ration is a nonparametric component. The optimal bandwidth (h) which was obtained with minimum GCVwas 0,005. The value of MSE which was obtained by using multiple linear regression analysis was 0,031 and by using semiparametric regression was 0,00437119.
MODEL LOG-LINEAR FAKTOR-FAKTOR YANG MEMPENGARUHI HIPERTENSI (STUDI KASUS: RSUD ABDOE RAHEM SITUBONDO) IMAMUDDIN KAMIL; MADE SUSILAWATI; I PUTU EKA NILA KENCANA
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.p015

Abstract

The purpose of this study was to determine the effect of the factors age, sex, obesity, family history (heredity), and smoking habits on hypertension status. The research data is secondary data obtained from the medical records of disease in hospitals in East Java Abdoe Rahem Situbondo the data of patients affected by hypertension stage I and II, with a sample size of 137 patients. Methods of data analysis using log-linear regression analysis. The result showed the best log-linear Model are: log mijklmn = U + U134(ikl) + U245(jlm) + U456(lmn) + U1246(ijln) + U12356(ijkmn), explained the factors that influence the risk of hypertension (U6), namely the factors that can not be changed such as gender ((U1), age ((U2), family history ((U3), while factors can be changed such as smoking habits ((U4), and obesity ((U5). Interactions also occur between the factors that influence the risk of hypertension, as shown in the model U134(ikl), namely gender, family history, and smoking habits. In the model U245(jlm) the factors age, smoking, and obesity among interacting factors that influence the risk of hypertension.
PERBANDINGAN REGRESI ZERO INFLATED POISSON (ZIP) DAN REGRESI ZERO INFLATED NEGATIVE BINOMIAL (ZINB) PADA DATA OVERDISPERSION (Studi Kasus: Angka Kematian Ibu di Provinsi Bali) NI PUTU PREMA DEWANTI; MADE SUSILAWATI; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 5 No 4 (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.i04.p132

Abstract

Poisson regression is a nonlinear regression which is often used for count data and has equidispersion assumption (variance value equal to mean value). However in practice, equidispersion assumption is often violated. One of it violations is overdispersion (variance value greater than the mean value). One of the causes of overdipersion is excessive number of zero values on the response variable (excess zeros). There are many methods to handle overdispersion because of excess zeros. Two of them are Zero Inflated Poisson (ZIP) regression and Zero Inflated Negative Binomial (ZINB) regression. The purpose of this research is to determine which regression models is better in handling overdispersion data. The data that can be analyzed using the ZIP and ZINB regression is maternal mortality rate in the Province of Bali. Maternal mortality rate data has proportion of zeros value more than 50% on the response variable.  In this research, ZINB regression better than ZIP regression for modeling maternal mortality rate. The independent variable that affects the number of maternal mortality rate in the Province of Bali  is the percentage of mothers who carry a pregnancy visit, with ZINB regression models and . 
PENGENALAN METODE INQUIRI DALAM PEMBELAJARAN IPA DI SDN 6 UBUNG DENPASAR Nyoman Wendri; Made Susilawati
Prosiding Seminar Nasional MIPA 2013: PROSIDING SEMINAR NASIONAL MIPA UNDIKSHA 2013
Publisher : Prosiding Seminar Nasional MIPA

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

Abstract

Abstract   Technological developments will not be separated from the development in the field of Natural Sciences (IPA). Development of the field of science is not likely to occur if not accompanied by an increase in the quality of science education, has been teaching science while considered a difficult subject. Inquiri is a learning process based on the search and discovery through systematic thinking process. This activity is done in SDN 6 Ubung Denpasar on fourth grade students. This activity aims to increase the understanding of materials science in the fourth grade students of SDN 6 Ubung Denpasar and increase student interaction in the classroom in the following learning science. IPA materials covered are the parts of the plant. Analysis results obtained mean = 71.79 which indicates that the average student evaluation results for the discussion of the parts of the plants is 71.79, this value is greater than the average value of the specified class, which is 65. T-test results also showed t = 4.40 with p = 0.000 smaller 0.05. This means learning implemented effectively enhance students' understanding and knowledge of the science subjects
METODE ANALISIS REGRESI SPASIAL DALAM MEMODELKAN KASUS COVID-19 DI INDONESIA NI MADE PUSPASARI; NI LUH PUTU SUCIPTAWATI; MADE SUSILAWATI
E-Jurnal Matematika Vol 11 No 3 (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.i03.p377

Abstract

Covid-19 is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2. The transmission of Covid-19 has negative impact on every aspect. This study aimed to determine the factors that significantly affect the number of Covid-19 cases in Indonesia. Spatial regression analysis was used as the research method. The results obtained that on the dependent variable there is a spatial dependence, so the selected model is Spatial Autoregressive Model (SAR) with an AIC value of 759.09 and an value of 58.49%. The significant influencing factor is proportion of the population over 50 years old and open unemployment rate.
FAKTOR-FAKTOR YANG MELATARBELAKANGI KEPUTUSAN BELANJA ONLINE PADA APLIKASI E-COMMERCE NI KADEK DWI ARISYA AFRILIANTI; MADE SUSILAWATI; I GUSTI AYU MADE SRINADI
E-Jurnal Matematika Vol 11 No 3 (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.i03.p382

Abstract

The existence of the COVID-19 Pandemic since 2020 has forced the central government to impose large-scale social restrictions (PSBB) in the various region in Indonesia. This restriction aims to minimize the spread of the COVID-19 virus, but this causes results in many people losing their jobs. This study uses confirmatory factor analysis to examine the factors behind online shopping decisions at stores in e-commerce applications. The results of this study aim to determine what factors are behind the decision of buyers to shop online in e-commerce applications. The research variable consists of eight dimensions: product, price, place, promotion, customer service, convenience, security, and trust, with 33 indicators. The sample in this study was the people of Denpasar City, totaling 232 respondents who had shopped online at least three times in the last six months. The results of the factor analysis obtained that it is true that there are eight factors behind online shopping decisions at shops in e-commerce applications by people in Denpasar City. These results can be considered for online entrepreneurs to increase sales results by sellers and as a reference by buyers in determining what can be regarded as in online shopping.
MEMODELKAN PRODUK DOMESTIK REGIONAL BRUTO DI INDONESIA MENGGUNAKAN REGRESI DATA PANEL SPASIAL NI KADEK AYU PUJI ASTUTI; NI LUH PUTU SUCIPTAWATI; MADE SUSILAWATI
E-Jurnal Matematika Vol 11 No 3 (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.i03.p379

Abstract

Gross regional domestic product (GRDP) is one of the important indicators to determine economic conditions in a region. The magnitude of the growth rate of GRDP is developed by the progress of regional economic development, both carried out by the government and the private sector in order to improve the welfare of the population. The purpose of this study is to examine the business sector that has the most significant influence on GRDP in Indonesia by applying spatial panel data regression. The results show that the best model in modeling GRDP in Indonesia is the spatial lag common effect which has an value of 83,13% while the independent variables that are significant to the increase in GRDP can be divided into two, namely significant positive and significant negative effects. The variables that have a significant and positive effect on GRDP are agriculture, forestry, and fisheries , mining and quarrying electricity and gas supply, water supply, waste management, waste and recycling, construction, financial services and insurance, real estate, and other services. wholesale and retail trade; car and motorcycle repair, transportation and warehousing, company services education services .
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