scholarly journals Application of Semiparametric Spline Regression Model in Analyzing Factors that In uence Population Density in Central Java

2017 ◽  
Vol 855 ◽  
pp. 012049
Author(s):  
Y D Sumantari ◽  
I Slamet ◽  
Sugiyanto
Keyword(s):  
Population Density ◽  
Regression Model ◽  
Spline Regression ◽  
Central Java

scholarly journals Modeling of Tuberculosis Case In Central Java 2018 With Three Knot Point

2020 ◽  
Vol 1 (2) ◽  
pp. 53
Author(s):  
Dina Fristantiningtyas Wiliyani Hapsari ◽  
Laelatul Khikmah
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Population Density ◽  
Regression Model ◽  
Resistant Bacteria ◽  
Spline Regression ◽  
West Java ◽  
Tuberculosis Case ◽  
Central Java ◽  
Contagious Disease ◽  
Regression Approach

Tuberculosis is a contagious disease caused by infection with the bacteria Mycobacterium Tuberculosis or known as Acid-Resistant Bacteria (BTA). Central Java is one of the provinces that has a high number of tubuerculosis cases in Indonesia. In 2018, Central Java was in second place after West Java in the highest number of Tuberculosis cases in Indonesia with the number of Tuberculosis cases of all types of 67,941 cases. Many variables can affect the number of TB cases. Therefore, a study was conducted in the form of modeling to determine the variables that affect the number of tuberculosis cases in Central Java. Based on data obtained from the Central Java Provincial Health Office in 2018, it shows that the pattern between the number of tuberculosis cases and the variables that are thought to influence it is not linearly related, then a spline regression approach is carried out. The results of this study indicate that the best spline regression model is to use three point knots with significant variables, namely population density and malnutrition. The value of 𝑅2 obtained is 54.6%.

scholarly journals Survey of the Javan Gibbons (Hylobates moloch) in West and Central Java, Indonesia: Trends in Population Density

2018 ◽  
Vol 07 (01) ◽  
Author(s):  
Entang Iskandar ◽  
Walberto Sinarga ◽  
Septiantina Riendriasari ◽  
Rahmuddin ◽  
Kuswandono Tedjosiswojo ◽  
...  
Keyword(s):  
Population Density ◽  
Central Java ◽  
Hylobates Moloch

scholarly journals PEMODELAN JUMLAH TINDAK KRIMINALITAS DI PROVINSI JAWA TIMUR DENGAN ANALISIS REGRESI SPATIAL AUTOREGRESSIVE AND MOVING AVERAGE

2018 ◽  
Vol 7 (4) ◽  
pp. 346
Author(s):  
NI MADE LASTI LISPANI ◽  
I WAYAN SUMARJAYA ◽  
I KOMANG GDE SUKARSA
Keyword(s):  
Population Density ◽  
Regression Model ◽  
Average Length ◽  
Moving Average ◽  
Spatial Regression ◽  
Higher Order ◽  
Spatial Effect ◽  
Spatial Regression Model ◽  
Spatial Autoregressive ◽  
Total Average

One of spatial regression model is spatial autoregressive and moving average (SARMA) which assumes that there is a spatial effect on dependent variable and error. SARMA can analyze the spatial effect on the higher order. The purpose of this research is to estimate the model of the total crime in East Java along with factors that affect it. The results show that the model can describe total crime in East Java is SARMA(0,1). The factors that influence the total crime  are population density (), poverty total (), average length of education at every regency/city and error from the neigbors.

scholarly journals Is the relationship between population density and body size consistent across independent studies? A meta-analytical approach

2001 ◽  
Vol 61 (1) ◽  
pp. 1-6 ◽  
Author(s):  
L. M. BINI ◽  
A. S. G COELHO ◽  
J. A. F. DINIZ-FILHO
Keyword(s):  
Body Size ◽  
Population Density ◽  
Regression Model ◽  
Phylogenetic Relationships ◽  
Analytical Approach ◽  
Analytical Procedure ◽  
Significant Heterogeneity ◽  
Sampling Variation ◽  
Homogeneity Hypothesis ◽  
The Relationship

The Energetic Equivalence Rule (EER) is a controversial issue in ecology. This rule states that the amount of energy that each species uses per unit of area is independent of its body size. Here, we perform a meta-analytical procedure to combine and compare the slopes of population density and body size relationships across independent studies of mammals and birds. We then compared a distribution of 50,000 bootstrap combined slopes with the expected slope (b = -0.75) under the EER. The combined slopes obtained for mammals and birds separately were -0.755 and -0.321, respectively. The homogeneity hypothesis (i. e. within studies the slopes differ by no more than would be expected due sampling variation) was rejected in both cases. So, EER cannot be supported since the use of an exponent of -0.75 is, in fact, an oversimplification. Significant heterogeneity of slopes within each group (mammals and birds) is an indicator of inferential problems related with variation in body size, spatial scale, the regression model adopted and phylogenetic relationships among species. So, we consider that questions regarding the estimation and validity of slopes is the next challenge of density-body size relationship studies.

scholarly journals Regional Factors Influencing Non-Take-Up for Social Support in Korea Using a Spatial Regression Model

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110615
Author(s):  
Gyubeom Park ◽  
Kichan Yoon ◽  
Munjae Lee
Keyword(s):  
Population Density ◽  
Regression Model ◽  
Elderly Population ◽  
Spatial Regression ◽  
The Elderly ◽  
Policy Support ◽  
Unemployment Benefit ◽  
Spatial Regression Model ◽  
Rate Of Increase ◽  
Blind Spots

The purpose of this study is to analyze the influential factors of non-take-up citizens, who do not receive social benefits, to increase their discovery rate. A spatial regression model was used to analyze the variables affecting the discovery rates. As a result of the study, there was a difference in the percentage of welfare blind spots by region. In addition, when the proportion of the elderly population, the number of unemployment benefit recipients, etc. increased, that of welfare blind spots also increased; the lower the population density was, the higher the rate of increase in welfare blind spots became. Accordingly, in order to resolve the welfare blind spots at the local level, it is necessary to reinforce policy support for the elderly population and reduce the unemployment rate. Particularly, the policy will have to be prepared to resolve the welfare blind spots in rural areas with low population density.

Spline Nonparametric Regression Model for Local Revenue in Central Sulawesi

2021 ◽  
Vol 1 (2) ◽  
pp. 31-37
Author(s):  
Mohammad Fajri ◽  
Eka Rizky Wulansari ◽  
Ayu Anggraeni ◽  
Mufitatul Annisa
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Nonparametric Regression ◽  
Local Governments ◽  
Economic Resources ◽  
Spline Regression ◽  
Nonparametric Regression Model ◽  
Local Revenue ◽  
Tax Levies ◽  
Central Sulawesi

Local Own-source Revenue (LOR) is all regional revenue that comes from the region's original economic resources. It is very important to identify it by researching and determining the Regional Local Own-source Revenue (LOR) by properly researching and managing the source of revenue so as to provide maximum results. Central Sulawesi Province itself has Local Own-source Revenue (LOR) in the Regional Revenue and Expenditure Budget of the 2018 Budget Year has reached Rp1 trillion. The increase or decrease in growth of local revenue is influenced by the amount and type of tax, levies collected by local governments and the lack of incentives for the management apparatus to carry out tax collection and levies. This study uses spline regression analysis because the data of the Local Own-source Revenue (LOR) in Central Sulawesi in 2018 does not have a pattern so that it fits perfectly with that method. Then after processing the data obtained the results of spline nonparametric regression modeling using the optimal knots point obtained from the minimum GCV value. The best spline nonparametric regression model is written as follow . It can be concluded that in Central Sulawesi in 2018 the lowest Local Own-source Revenue (LOR) value was Banggai Laut Regency with 21,776 billion rupiahs and the highest Local Own-source Revenue (LOR) value was Palu City at 267,402 billion rupiahs.

scholarly journals Analisis Spasial dan Temporal Persebaran Kasus Baru TB Paru BTA (+) di Kabupaten Batang

2018 ◽  
Vol 17 (2) ◽  
pp. 95
Author(s):  
Arum Siwiendrayanti ◽  
Dyah Mahendrasari Sukendra ◽  
Dwi Arofah
Keyword(s):  
Population Density ◽  
Pulmonary Tuberculosis ◽  
Temporal Analysis ◽  
Population Based ◽  
Specific Pattern ◽  
Cure Rate ◽  
Notification Rate ◽  
Central Java ◽  
Smear Positive Pulmonary Tuberculosis ◽  
Case Notification

Latar belakang: Case Notification Rate (CNR) Kabupaten Batang tahun 2013 sebesar 73,8/100.000 penduduk. Berdasarkan CNR-nya Kabupaten Batang masuk peringkat ke-9 dari 35 kabupaten/kota di Jawa Tengah. Selain itu, pada tahun 2012-2014 tren kasus baru TB paru BTA positif selalu menurun, kemudian meningkat tahun 2015, dan turun kembali di tahun 2016. Namun, tren tersebut tidak menggambarkan tren kasus baru di tiap kecamatan yang ada di Kabupaten Batang. Tujuan dari penelitian ini adalah untuk mengetahui gambaran secara spasial dan temporal persebaran kasus baru Tb paru BTA positif ditinjau dari kepadatan penduduk, ketinggian wilayah, cakupan rumah sehat, dan cure rate tahun 2012-2016.Metode: Jenis penelitian yang digunakan dalam penelitian ini adalah analitik kuantitatif dengan studi ekologis menggunakan pendekatan spasial dan temporal. Sampel dalam penelitian ini adalah semua kasus baru TB paru BTA positif dari tahun 2012-2016. Hasil: Penyebaran kasus baru tidak menunjukkan pola khusus pada pemetaan berdasarkan ketinggian dan kepadatan penduduk. Sebagian penyebaran kasus baru menunjukkan pola penyebaran mengikuti pola cure rate, dan hampir seluruhnya mengikuti pola cakupan rumah sehat. Cure rate tinggi tidak diikuti oleh penurunan jumlah kasus baru pada wilayah dengan cakupan rumah sehat rendah.Simpulan: Persebaran kasus baru TB paru BTA positif dipengaruhi oleh faktor cakupan rumah sehat. Sedangkan faktor yang lainnya tidak mempengaruhi persebaran kasus baru Tb paru BTA positif di Kabupaten Batang Tahun 2012-2016. ABSTRACTTitle: Spatial and Temporal Analysis of AFB Smear-Positive Pulmonary Tuberculosis New Cases Distribution in Batang RegencyBackground: Case Notification Rate (CNR) of Batang Regency in 2013 is 73.8 / 100.000 population. Based on its CNR, Batang regency is ranked 9th of 35 regencies / cities in Central Java. In addition, in 2012-2014, the trend of new AFB smear-positive cases of pulmonary tuberculosis always decrease, then increase in 2015, and decrease again in 2016. However, the trend does not reflect the trend of new cases in each sub-district. The purpose of this research is to descript the spread of new cases of AFB smear positive pulmonary tuberculosis spatially and temporally in terms of population density, altitude, coverage of healthy house, and cure rate of 2012-2016.Method: The type of research used in this study is analytic quantitative with ecological studies using spatial and temporal approach. The samples in this study were all new cases of AFB smear positive pulmonary tuberculosis in 2012-2016. Result: The distribution of new cases did not indicate a specific pattern on mapping based on altitude and population density. Some of the new case distributions showed the pattern of distribution following a cure rate pattern, and almost entirely following the pattern of healthy house coverage. High cure rates were not followed by a decrease in the number of new cases in areas with low coverage of healthy house.Conclusion: The distribution of new cases of AFB smear positive pulmonary tuberculosis is influenced by healthy house coverage factor. While other factors did not affect the distribution of new cases of AFB smear positive pulmonary tuberculosis in Batang Regency in 2012-2016

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