Grid transformation method of population data combining geographic factors and simulated township boundary adjustment

2009 ◽  
Author(s):  
Jiafu Han ◽  
Hongsheng Li ◽  
Liuqing Ma
Keyword(s):  
Population Data ◽  
Transformation Method ◽  
Geographic Factors

scholarly journals Patterns of Population and Urban Growth in Southwest Europe: 1920-2010

2017 ◽  
Vol 43 (6) ◽  
pp. 1021-1040 ◽  
Author(s):  
Cathy Chatel ◽  
Mateu Morillas-Torné ◽  
Albert Esteve ◽  
Jordi Martí-Henneberg
Keyword(s):  
Regression Model ◽  
Social Organization ◽  
Iberian Peninsula ◽  
Urban Growth ◽  
Local Level ◽  
Population Data ◽  
Population Geography ◽  
Urbanization Process ◽  
Geographic Factors ◽  
Population Concentration

This work seeks to measure, locate, and explain changes in the distribution of population and urban growth in the territory formed by France, Italy, and the Iberian Peninsula between 1920 and 2010. This is based on population data of more than fifty-six thousand local units obtained from population censuses: the Geokhoris database that we built. Our starting viewpoint is that it is only possible to understand the extent of the urbanization process within the context of the evolution of all of the municipalities. The description of the distribution and growth of population at the local level shows the population concentration in the various urban agglomerations, and, since 1970, a relative deconcentration and extension of the cities. Within this context, a regression model helped us to identify the geographic factors that correlate with these fundamental transformations in population geography, which were also indicative of new forms of social organization within the territory.

Tingkat Pemahaman Kompetensi Guru Pada Mahasiswa Pendidikan Geografi Sebagai Calon Guru Geografi

2020 ◽  
Vol 21 (1) ◽  
pp. 102-117
Author(s):  
Novia Zalmita ◽  
Muhajirah Muhajirah ◽  
Abdul Wahab Abdi
Keyword(s):  
Prospective Teachers ◽  
Prospective Teacher ◽  
Quantitative Description ◽  
Population Data ◽  
Geography Education ◽  
Teacher Competence ◽  
Education Department ◽  
Long Time

One that influences human resource indicators is education. The teacher is a profession as a job of academic specialization in a relatively long time in college. Understanding related to teacher competence is very important to have by a prospective teacher because it can affect the quality of performance as a professional teacher. The teacher's competence is known as pedagogic, professional, social and personality competencies. The issue in this study is how the competency of the teacher of the Department of Geography Education FKIP Unsyiah as a prospective teacher of geography? The purpose of this study was to determine the competence of teachers in the Department of Geography Education FKIP Unsyiah as prospective geography teachers. Quantitative description approach is used in this study to find answers to the issue. The population in this study were students of the Department of Geography Education FKIP Unsyiah class of 2015 and 2016 who had been declared to have passed the Micro Teaching and Magang Kependidikan 3 course totaling 50 people. Because the population is small and can be reached, the determination of the sample using total sampling techniques so that the sample in this study is the whole population. Data collection is done by distributing test questions to respondents. The data was analyzed using the descriptive statistics percentage formula. The results of the study indicate that the level of teacher competence of Geography Education Department students as prospective teachers is in the moderate category, namely as many as 22 respondents (44%). A total of 12 respondents (24%) were in the high category, 15 respondents (30%) were in the low category and 1 respondent (2%) were in the very low category.

Türkiye'de iller arası göçlerin nodexl ile sosyal ağ analizi

2017 ◽  
Vol 4 (1) ◽  
pp. 82-109 ◽  
Author(s):  
Mustafa Yakar ◽  
Fatma Sert Eteman
Keyword(s):  
Network Structure ◽  
Population Data ◽  
Single Mode ◽  
Turkish Population ◽  
Place Of Birth ◽  
Place Of Residence ◽  
Migration Flow ◽  
Population Structures ◽  
The Republic ◽  
Provincial Scale

Türkiye'de 20.yy'ın ortasından itibaren başlayan iç göçler zamanla kurulan göçmen ağları ile süreklilik kazanmış ve ülke içinde nüfusun kır-kent dağılımını değiştirecek boyutlara erişmiştir. Araştırma, göçün doğum yeri verisinden hareketle ikamet edilen yerdeki nüfus miktarına göre alınan ve verilen göç akışının büyüklüğünü iller ölçeğinde yönlü ağlar kullanılarak analiz edilmesini amaçlamaktadır. Araştırmada, TÜİK tarafından yayınlanmış olan 2015 yılına ait, iller ölçeğinde doğum yerine göre ikamet yeri verisi kullanılmıştır. Göçün kaynak ve hedef sahaları arasındaki akışını incelemek için NodeXL ile oluşturulan tek modlu, yönlü ve ağırlıklandırılmış göç ağının istatistiksel olarak tam ağ yapısına sahip olduğu görülmüştür. Ağ grafiklerinden ve istatistiklerinden göç hareketinin doğudan batıya doğru gerçekleştiği ve İstanbul’ un ülkenin tamamına hâkim bir görünüme sahip olduğu anlaşılmaktadır. Türkiye nüfusunun cumhuriyet tarihi içinde geçirdiği iç göç süreçleriyle birlikte ülke içinde kurulmuş ve oldukça karmaşık bir görünüme sahip ağ yapısının olduğu ileri sürülebilir. Kurulan ağlar göçlerin devamını sağladığı gibi, göçün yöneldiği merkezlerde daha heterojen nüfus yapılarının ortaya çıkmasına yol açmıştır.ABSTRACT IN ENGLISHSocial Network Analysis of Migration Inter Provinces In Turkey with Nodexl The internal migrations which started in Turkey in the middle of the 20th century have gained permanency with the migration networks that were established at the time and reached dimensions which have the potential to change the rural-urban distribution of the population within the country.  The study aims to analyze the magnitude of the incoming and outgoing migration flow at the provincial scale based on the population data for place of birth according to place of residence by using directional networks. Place of residence according to place of birth at the provincial scale data for 2015 published by TÜİK was used in the study. A single mode, directional and weighted migration network created with NodeXL to examine the migration flows between the source and target has a statistically complete network structure. The network graphs and statistics show that the migrations have taken place from east to west and Istanbul has a view as dominant of the country. It can be argued that internal network structure of Turkish population has  a very complex view because of internal migration in the history of the republic. The established networks have enabled the continuation of migration and have manifested as the emergence of more heterogeneous population structures in centers where migration had been directed.

PENENTUAN DAERAH PRIORITAS PELAYANAN AKTA KELAHIRAN DENGAN METODE K-NN DAN K-MEANS

2020 ◽  
Vol 17 (1) ◽  
pp. 319-328
Author(s):  
Ade Muchlis Maulana Anwar ◽  
Prihastuti Harsani ◽  
Aries Maesya
Keyword(s):  
Nearest Neighbor ◽  
Information Gain ◽  
Birth Certificate ◽  
Population Data ◽  
Community Services ◽  
Birth Certificates ◽  
Similar Data ◽  
K Nearest Neighbor ◽  
Civil Registration ◽  
The Family

Population Data is individual data or aggregate data that is structured as a result of Population Registration and Civil Registration activities. Birth Certificate is a Civil Registration Deed as a result of recording the birth event of a baby whose birth is reported to be registered on the Family Card and given a Population Identification Number (NIK) as a basis for obtaining other community services. From the total number of integrated birth certificate reporting for the 2018 Population Administration Information System (SIAK) totaling 570,637 there were 503,946 reported late and only 66,691 were reported publicly. Clustering is a method used to classify data that is similar to others in one group or similar data to other groups. K-Nearest Neighbor is a method for classifying objects based on learning data that is the closest distance to the test data. k-means is a method used to divide a number of objects into groups based on existing categories by looking at the midpoint. In data mining preprocesses, data is cleaned by filling in the blank data with the most dominating data, and selecting attributes using the information gain method. Based on the k-nearest neighbor method to predict delays in reporting and the k-means method to classify priority areas of service with 10,000 birth certificate data on birth certificates in 2019 that have good enough performance to produce predictions with an accuracy of 74.00% and with K = 2 on k-means produces a index davies bouldin of 1,179.

Faktor yang Berhubungan dengan Penggunaan Partograf dalam Persalinan oleh Bidan Praktik Mandiri

2020 ◽  
Vol 2 (2) ◽  
pp. 72-80
Author(s):  
Niluh Nita Silfia
Keyword(s):  
Total Population ◽  
Sampling Technique ◽  
Population Data ◽  
Statistical Test ◽  
Influential Factor ◽  
Test Results ◽  
Cross Sectional ◽  
Factors Associated ◽  
Survey Results ◽  
Research Criteria

Partographs are guidelines for childbirth observations that will facilitate labor assistants in first identifying emergency cases and complications for mothers and fetuses. Preliminary survey at the Sigi Community Health Sub-Center (Pustu) of the 8 Pustu midwives found two midwives (25%) to complete a complete partograph, six midwives (75%) incomplete. The purpose of this study was to determine the determinant factors associated with the use of partographs in labor. The design of this study used observational analytic methods with a cross-sectional approach. 24 BPM survey results were obtained with 30 samples of midwives who met the research criteria and data completeness. The sampling technique was by the total population. Data analysis used logistic regression. The multivariate analysis results showed that APN training was the most influential factor in the use of partographs in labor by midwives. Statistical test results obtained a POR value of 37.7 (95% CI 12.1 - 60.2). This study suggests that midwives must have APN certificates to be valid in providing services.

Fire Risk Analysis Using Geospatial Approach and Mitigation Measures for South-West Delhi

2018 ◽  
Vol 6 (8) ◽  
pp. 131
Author(s):  
S. K. Tomar ◽  
A. Kaur ◽  
H. K. Dangi ◽  
T. Ghawana ◽  
K. Sarma
Keyword(s):  
Risk Analysis ◽  
Fire Risk ◽  
Population Data ◽  
Fire Service ◽  
Capital City ◽  
Mitigation Measures ◽  
Fire Risk Analysis ◽  
South West ◽  
Geospatial Tools ◽  
Fire Stations

One of the major challenge from unplanned growth in the cities is the fire incidents posing a serious threat to life and property. Delhi, the capital city of India, has seen unplanned growth of colonies resulting in a serious concern for the relevant agencies. This paper investigates the relation between potential causes of fire incidents during 2013-2016 in South-West Delhi Division of Delhi Fire Services as part of risk analysis using the data about fire stations & their jurisdictions, incidents of fire, water reservoirs available, landuse and population data along with the divisional & sub-divisional boundaries of South-West Delhi division under Delhi Fire Service. Statistical and Geospatial tools have been used together to perform the risk analysis. The analysis reveals that difference in actual occupancy and defined landuse as a part of unplanned growth of settlements is found to be the main reason behind the major fire incidents. The suggested mitigation measures focus on legal, policy, physical & technological aspects and highlight the need to bring the systemic changes with changing scenario of demographics and infrastructure to accommodate more aspects of ground reality.

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