scholarly journals Cluster Analysis Using the Hierarki Method For Grouping Sub-Districts in The District Steps Based on Health Indicators

2020 ◽  
Vol 4 (1) ◽  
pp. 28
Author(s):  
Khairun Nisa ◽  
Rina Filia Sari ◽  
Hendra Cipta ◽  
Ismail Husein
Keyword(s):  
Cluster Analysis ◽  
Health Indicators ◽  
Daily Activities ◽  
Euclidian Distance ◽  
Grouping Method ◽  
Ward Method

<span lang="EN">Cluster analysis is a method used to group objects based on similarity of characteristics they have. Cluster analysis using the hierarchy method is a method with a grouping process that is used in stages. Health is a condition where a person is not sick, has no complaints, and can carry out daily activities. To find out information about the level of health in Langkat Regency, it is necessary to use the grouping method. The grouping was carried out in 23 districts in Langkat Regency. The purpose of this study is to classify sub-districts in Langkat Regency which have similar characteristics based on health indicators through the square euclidian distance is used to measure the similarity between object pairs and the ward method. From the results of cluster analysis using the ward method.</span>

scholarly journals Genetic divergence among Nellore breed herds raised in the South Region of Brazil

2013 ◽  
Vol 43 (5) ◽  
pp. 878-883
Author(s):  
Jader Silva Lopes ◽  
Paulo Roberto Nogara Rorato ◽  
Tomás Weber ◽  
Ronyere Olegário de Araújo ◽  
Dionéia Magda Everling ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Genetic Divergence ◽  
Rio Grande ◽  
Southern Region ◽  
Rio Grande Do Sul ◽  
The South ◽  
Santa Catarina ◽  
Weaning Weight ◽  
Breeding Values ◽  
Ward Method

The objective of this study was to evaluate the genetic divergence among Nellore breed animals raised in 45 farms in the Southern Region of Brazil. The characteristic studied was weaning weight adjusted to 205 days of life (P205), from 10,874 animals sired by 425 bulls and 7,629 cows, collected between 1976 and 2001, and distributed in the states of Rio Grande do Sul (1,499), Santa Catarina (2,332) and Paraná (7,043). The animals were distributed by cluster analysis in eight genetic divergent groups, enabling this technique to be applied to organize the matings in order to obtain heterotic effect. The herd/farm groups were formed through the hierarchical Ward method, using the direct (VGD) and maternal (VGM) breeding values predicted by the REML method. The VGD of the animal accounted for 90% of the differences among herds, and the remaining 10% was attributed to differences in the VGM. On average, the P205 for the animals from inter-group mating was 1.4kg higher than those from intra-group mating, representing 2.4% of heterosis.

scholarly journals Determinants of milk production in FADN dairy farms in the regions of the European Union with predominance of intensive production in 2011

Management ◽  
2016 ◽  
Vol 20 (2) ◽  
pp. 473-486
Author(s):  
Marta Guth
Keyword(s):  
European Union ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Milk Production ◽  
Dairy Farms ◽  
The European Union ◽  
Intensive Production ◽  
Ward Method

Summary The main aim of the considerations was to determine the factors determining the variability of milk production in selected macroregions of the European Union. The regions were selected on the basis of the analysis of the diversity of dairy farms FADN in the regions of the European Union, which was determined by the agglomeration cluster analysis using Ward method. In order to highlight the determinants of production there was factor analysis made. On the basis of the results of factor analysis there were factors that have a decisive impact on milk production in dairy farms from areas with a predominance of intensive production identified, and there was a possibility to find out which macro-regions of the European Union reached a relatively best and worst performance in terms of the distinguished factors.

The influence of various measures of health on different types of political participation

Politics ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 480-513 ◽  
Author(s):  
Daniel Stockemer ◽  
Carolin Rapp
Keyword(s):  
Political Participation ◽  
Negative Relationship ◽  
Health Indicators ◽  
European Social Survey ◽  
Daily Activities ◽  
Political Activity ◽  
Daily Lives ◽  
Political Behaviour ◽  
Reported Health ◽  
The Relationship

Recent research in political behaviour suggests that poor health can be an impediment for individuals to vote. At the same time, researchers argue that health may both hinder and reinforce other forms of political participation. With respect to these ambiguous expectations, our study asks: does the relationship between health and political involvement depend on how we measure health? We answer this question for two of the most widely used health indicators, self-reported health and being hampered by illness in daily activities. We use the European Social Survey (ESS) (N = 35,000) covering 20 European countries and find that the measurement of health indeed matters: our results illustrate that bad self-reported health is an impediment to voting, but not to other forms of political activity. When it comes to our second indicator, being hampered in daily activities, we also find a negative relationship with voting. Yet, our results also indicate that most individuals, who are hampered by illness in their daily lives, have a tendency to participate more regularly in most other forms of political activity, including boycotting, contacting a politician, or signing a petition. Robustness checks including waves 1–6 of the ESS support these findings.

scholarly journals Multivariable Panel Data Cluster Analysis using Ward Method Gross Enrollment Ratio (GER) Data in West Java in the Year 2015-2018

2020 ◽  
Vol 3 ◽  
pp. 291-296
Author(s):  
Reka Ramadhan ◽  
Asep Solih Awalluddin ◽  
Rini Cahyandari
Keyword(s):  
High School ◽  
Cluster Analysis ◽  
High Schools ◽  
Panel Data ◽  
Senior High School ◽  
West Java ◽  
Enrollment Rate ◽  
Minimum Number ◽  
Measure Of Similarity ◽  
Ward Method

The aim of this study is to determine cluster analysis for panel data with multivariable data structures. Choosing a Ward method Choosing a method in a cluster analysis hierarchical technique. Ward method is a method based on Sum Square Error (SSE) with a measure of homogeneity between two objects based on the minimum number of error squares. The measure of similarity used is the Euclidean distance squared. The Ward method is used to add variation between objects in one cluster and maximize variation with objects in another cluster. The steps of the analysis are described in the discussion of this study. The method of implementation uses education gross enrollment rate (GER) data in West Java Province in 2015-2018. The results of the study indicate that the grouping of education GER data in West Java in 2015-2018 using the Ward method produces four clusters. The first cluster consists of five regions, GER for Elementary school, junior and senior high school in the cluster are below the average APK in West Java. The second cluster consists of two regions, in contrast to the first cluster GER for elementary schools in this cluster according to the average GER in West Java but for junior and senior high school GER below the average GER in West Java. The third cluster consists of seven regions, the GER for elementary, junior and senior high schools in this cluster is above the average GER in West Java while the fourth cluster consists of five regions, the GER for elementary and junior high schools in this area is above the average GER in West Java.

scholarly journals A Grouping Method of Distribution Substations Using Cluster Analysis

2005 ◽  
Vol 125 (3) ◽  
pp. 278-285
Author(s):  
Toshiya Ohtaka ◽  
Shinichi Iwamoto
Keyword(s):  
Cluster Analysis ◽  
Grouping Method

scholarly journals Pengklasteran Kabupaten/Kota di Jawa Tengah berdasarkan Tenaga Kesehatan dengan Menggunakan Metode Ward dan K-Means

2018 ◽  
Vol 7 (2) ◽  
pp. 103-109
Author(s):  
Sri Puji Lestari ◽  
Epha Diana Supandi ◽  
Pipit Pratiwi Rahayu
Keyword(s):  
Cluster Analysis ◽  
Standard Deviation ◽  
Nursing Staff ◽  
Health Workers ◽  
Medical Personnel ◽  
Central Java ◽  
Deviation Ratio ◽  
Standard Deviation Ratio ◽  
Ward Method ◽  
Central Java Province

Analisis klaster merupakan suatu metode yang digunakan untuk mengelompokkan objek (kasus) ke dalam klaster (kelompok) yang relatif sama.  Tujuan penelitian ini untuk mengklasterkan Kabupaten/Kota di Provinsi Jawa Tengah berdasarkan tenaga kesehatan tahun 2015 seperti tenaga medis, tenaga keperawatan, tenaga kebidanan, tenaga kefarmasian dan tenaga kesehatan lainnya dengan menggunakan metode Ward dan K-Means. Hasil penelitian menunjukkan ada tiga klaster terbentuk dimana metode Ward menghasilkan nilai rasio simpangan baku sebesar 0,3019% lebih besar jika dibandingkan dengan nilai rasio simpangan baku pada metode K-Means yaitu 0,2974%. Pada kasus ini, metode K-Means merupakan metode yang lebih baik dibandingkan metode Ward. [Cluster analysis is a method used to group objects (cases) into clusters (groups) that are relatively the same. The purpose of this study is to classify districts/cities in Central Java Province based on health worker in 2015 such as medical personnel, nursing staff, midwifery staff, pharmacy personnel and health workers using the Ward and K-Means methods. The results show that there are three clusters formed where the Ward method produce a standard deviation ratio of 0.3019% greater than the standard deviation ratio in the K-Means method, which is 0.2974%. In this case, the K-Means method is a better method than the Ward method.]

scholarly journals Evaluation of saturated and aromatic hydrocarbons oil-oil maturity correlation parameters (SE Pannonian Basin, Serbia)

2007 ◽  
Vol 72 (12) ◽  
pp. 1237-1254 ◽  
Author(s):  
Ksenija Stojanovic ◽  
Branimir Jovancicevic ◽  
Dragomir Vitorovic ◽  
Yulia Golovko ◽  
Galina Pevneva ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Pannonian Basin ◽  
Oil Field ◽  
Crude Oils ◽  
Methyl Group ◽  
Cluster Analyses ◽  
Saturated And Aromatic Hydrocarbons ◽  
Correlation Parameters ◽  
Ward Method ◽  
Maturity Parameters

Twenty three crude oils from the Serbian part of the Pannonian Basin (14 from the Vojvodina Province and 9 from the Drmno Depression) were investigated, aimed at an evaluation of oil-oil maturity correlation parameters based on the distribution and abundance of saturated biomarkers and alkylarene constituents. Factor and cluster analyses were used for this purpose. Factor analyses using varimax rotation were first run separately, i.e., of maturity parameters based on the abundance of (a) n-alkanes and isoprenoids, (b) steranes and triterpanes, (c) alkylnaphthalenes, and (d) alkylphenanthrenes. These analyses yielded 9 important "maturity factors". Eight of them, showing higher than 30 % of variance, were further involved in another factor analysis, as well as in cluster analysis using the Ward method. In this way, all maturity parameters based on saturated biomarkers and alkylarenes were evaluated and ranged, considering the fact that the observed factors represented their linear combinations. The results showed that in the correlation of crude oils from the Serbian part of the Pannonian Basin, the most important were maturity parameters based on isomerization reactions involving one methyl group in thermodynamically less stable ?-methylnaphthalenes, ethylnaphthalenes, dimethylnaphthalenes and methylphenanthrenes, and their change into more stable isomers with the methyl group in the ?-position in the aromatic ring. Processes constituting high loadings factor 2 and factor 3 parameters were also defined. Hierarchy between the "factors" and parameters were controlled, and approved, by cluster analysis using the Ward method. Finally, the investigated crude oils were correlated by factor and cluster analyses, using all the important "maturity factors". Differences in maturity were observed between the Vojvodina and Drmno Depression crude oils, as well as between oils originating from South Banat, North Banat and the Velebit oil field (Vojvodina locality).

scholarly journals ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018)

2019 ◽  
Vol 8 (4) ◽  
pp. 486-495
Author(s):  
Sisca Indah Pratiwi ◽  
Tatik Widiharih ◽  
Arief Rachman Hakim
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Traffic Accidents ◽  
Optimal Number ◽  
Cophenetic Correlation ◽  
Central Java ◽  
Average Linkage ◽  
Linkage Method ◽  
Ward Method ◽  
Squared Euclidean Distance

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient

Classification of Iraqi governorates by using cluster analysis for 2016: تصنيف المحافظات العراقية صحياً باستخدام التحليل العنقودي لعام 2016

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Wafaa Abdul Samed Ashoor
Keyword(s):  
Cluster Analysis ◽  
Human Life ◽  
Health Indicators ◽  
Direct Link ◽  
Analysis Method ◽  
The Third ◽  
Central Statistical ◽  
Cluster Analysis Method ◽  
The Difference

The development of human societies is measured by the level of success achieved in health because of its direct link to human life. If any society can improve the health of its citizen, it will achieve similar success in other areas of life. If it fails in this aspect, it will fail in other aspects. So this important subject had to be discussed. This study aimed to know the difference between the Iraqi governorates in terms of the level of health indicators provided to the citizen, in addition to determining any of the indicators that contributed significantly to this difference and disparity between the provinces. Data were obtained from the Annual Statistical Abstract of 2017 issued by the Central Statistical Organization. The study included (13) governorates, except for the northern governorates, Mosul and Anbar because data is not available for these governorates and (25) variables representing health indicators. The cluster analysis method was used in the hierarchical and non-hierarchical way. The researcher concluded Baghdad is the best in providing health services to citizens, where the distance between them and other the governorates ranged from (3.875) to (4.841). and Najaf and Qadissiyah are close in providing these services to the citizen, Where the distance between them (0.411). And that the governorates clustered in three clusters, the first included (Kerkok, Diyala, Babylonl, Karbala, Wasit, Saladyn, Najaf, Qadisya, Muthanna, Thi Qar, Mysan) of and the second included Basra only and the third included Baghdad only.

scholarly journals Consumer Segment Based on Food Quality Dimension

2021 ◽  
Vol 56 (2) ◽  
pp. 512-523
Author(s):  
Hanifa Hasna Perdana ◽  
Fernianda Rahayu Hermiatin ◽  
Tomy Perdana ◽  
Agriani Hermita Sadeli ◽  
Velanda Ahtayary Putri
Keyword(s):  
Cluster Analysis ◽  
Supply Chain ◽  
Food Quality ◽  
Research Result ◽  
New Product ◽  
Point Of View ◽  
Fresh Food ◽  
Consumer Segment ◽  
Insight Into ◽  
Ward Method

The consumer has a different point of view when they decide to buy food. It depends on their desire for food quality. The actors in the supply chain may adjust their business to provide the quality that meets consumer demand. This study determines consumer segments based on quality, namely search, experience, and credence characteristics. Homogenous groups identify using k-means cluster analysis. Ward method used to decide the most exact number of clusters. The analysis based on consumer perceives on fresh food quality conducts on 238 respondents. The cluster analysis shows that there are four different groups. The first group consists of consumers who have a serious concern about new product quality. Also, there is a group which only emphasizes experience characteristics. In contrast, the second and fourth groups do not pay attention to quality. The research result represents a new insight into consumer segmentation through a study focus on quality characteristics. The result is to understand and improve marketing and supply chain development.

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