CLUSTERING OF PROVINCE IN INDONESIA BASED ON AQUACULTURE PRODUCTIVITY USING AVERAGE LINKAGE METHOD

Fisheries are one of the agricultural sub-sectors that play an important role in contributing to income figures for the state and the region because most of Indonesia's territory is water so that the fisheries sector is a sub-sector that is feasible to be developed in this country, one of which is through aquaculture. One of the efforts that can increase and maintain productivity in the aquaculture sector is to classify provinces that produce aquaculture production into groups based on the similarity of characteristics possessed by each province in Indonesia. In this study, clustering was carried out using cluster analysis using the average linkage method and based on the analysis results obtained showed that cluster 1 consists of 25 provinces, cluster 2 consists of 5 provinces, cluster 3 consists of 2 provinces, cluster 4 consists of 1 province, and cluster 5 consists of 1 province with a standard deviation value within a cluster of 11,729 and a standard deviation between clusters of 118,745.

Occupational Disease as the Bane of Workers’ Lives: A Study of Its Incidence in Slovakia. Part 2

The main objective of this article is to monitor the development of the number of occupational diseases related to selected physical factors in the working environment (noise, vibration and dust). Each region of Slovakia has its own specific social and economic conditions. Due to the existence of a strong correlation between the several regional variables observed, principal component analysis (PCA) was used to determine the new variables. Cluster analysis was used to group regions with similar characteristics. A dendrogram was created using the average linkage method, which illustrated the similarity of the regions studied. The value of the cophenetic correlation coefficient (CC = 0.90) confirms the validity of the average linkage method. The result of the cluster analysis is the grouping of the eight regions into five homogenic groups (clusters). An analysis of the data shows that Slovakia’s regional differences significantly influence the incidence of occupational diseases in individual regions. It is shown that, in Slovakia, the development of the number of occupational diseases has seen a favourable trend in the long term.

Construction of the Core Collection of Catalpa fargesii f. duclouxii (Huangxinzimu) Based on Molecular Markers and Phenotypic Traits

To promote the conservation and utilization of Catalpa fargesii f. duclouxii (Huangxinzimu) germplasm resources, a total of 252 accessions were used to construct a preliminary core collection according to phenotypic traits and single nucleotide polymorphism (SNP) markers. In this study, 24 phenotypic traits, namely, 9 quantitative traits and 15 qualitative traits, were investigated. The core collection of C. fargesii f. duclouxii (Huangxinzimu) was constructed to remove redundant samples from the collected materials. First, the phenotypic core collection, with a sample proportion of 30, consisting of 24 clones, was constructed according to two genetic distances (Euclidean distance and Mahalanobis), four system clustering methods (the unweighted pair-group average method, Ward’s method, the complete linkage method, and the single linkage method), and three sampling methods (random sampling, deviation sampling, and preferred sampling). The best construction strategies were selected for further comparison. Three core collections (D2C3S3-30, D2C3S3-50, and D2C3S3-70) were constructed according to the optimal construction strategy at three sampling proportions. The core collection D2C3S3-30 with the best parameters was evaluated by using six parameters: the mean difference percentage (MD), variance difference percentage (VD), periodic rate of range (CR), changeable rate of the coefficient of variation (VR), minimum rate of change (CRMIN), and maximum rate of change (CRMAX). Three core collections (M-30, M-50, and M-70) were constructed by molecular markers, and the optimal core collection M-30 was selected by using five parameters, namely, Ho, He, PIC, MAF, and loci. The combination of D2C3S3-30 and M-30 was used to construct the final core collection DM-45, 45 samples representing the complete range of phenotypic and genetic variability. In this study, phenotypic traits combined with molecular markers were used to construct core collections to effectively capture the entire range of trait variation, effectively representing the original germplasm and providing a basis for the conservation and utilization of C. fargesii f. duclouxii (Huangxinzimu).

Morphological diversity and relationship among cashew (Anacardium occidentale L) individuals in three districts of Southeast Sulawesi, Indonesia

Cashew (Anacardium occidentale L), a species belonging to the family Anacardiaceae, has been cultivated throughout most of Indonesia’s areas and has become a priority commodity in Southeast Sulawesi for years. However, the information about its variation on morphology and relationship among individuals are still limited. This study aimed to determine the morphological variations and relationships among cashew individuals in three districts (Konawe, South Konawe, and East Kolaka) of Southeast Sulawesi. As many as ninety individuals were analyzed on 15 morphological variables for the variations and 47 variables using the complete linkage method based on Gower distance for the clustering. The coefficients of variation were varied on all evaluated variables. The highest was the height of main branches (cm), ranging from 47.32 % to 73.72 %. Meanwhile, nut length had the lowest coefficient of variation (6.75%-7.99%). The individuals were divided into two main clusters with two sub-clusters for each cluster.

Comparison of Single Linkage, Complete Linkage, and Average Linkage Methods on Community Welfare Analysis in Cities and Regencies in East Java

Community welfare is one of the important points for a region and is also the essence of national development. The welfare of the people in Indonesia is fairly unequal, especially in East Java. To be able to map an area to the welfare of its people in East Java, one way that can be used is to use clustering. The hierarchical clustering method is one of the clustering methods for grouping data. In hierarchical clustering, single linkage, complete linkage, and average linkage methods are suitable methods for grouping data, which will compare the best method to use. The results of the calculation show that the average linkage method with three clusters is the best calculation with a silhouette index value of 0.6054, with the 1st cluster there are 23 regions, namely the city/district with the highest community welfare, the 2nd cluster there are 11 regions, namely cities/districts with moderate social welfare, and in the third cluster there are 4 regions, namely cities/districts with the lowest community welfare.

Linking a European cohort of children born with congenital anomalies to vital statistics and mortality records: A EUROlinkCAT study

EUROCAT is a European network of population-based congenital anomaly (CA) registries. Twenty-one registries agreed to participate in the EUROlinkCAT study to determine if reliable information on the survival of children born with a major CA between 1995 and 2014 can be obtained through linkage to national vital statistics or mortality records. Live birth children with a CA could be linked using personal identifiers to either their national vital statistics (including birth records, death records, hospital records) or to mortality records only, depending on the data available within each region. In total, 18 of 21 registries with data on 192,862 children born with congenital anomalies participated in the study. One registry was unable to get ethical approval to participate and linkage was not possible for two registries due to local reasons. Eleven registries linked to vital statistics and seven registries linked to mortality records only; one of the latter only had identification numbers for 78% of cases, hence it was excluded from further analysis. For registries linking to vital statistics: six linked over 95% of their cases for all years and five were unable to link at least 85% of all live born CA children in the earlier years of the study. No estimate of linkage success could be calculated for registries linking to mortality records. Irrespective of linkage method, deaths that occurred during the first week of life were over three times less likely to be linked compared to deaths occurring after the first week of life. Linkage to vital statistics can provide accurate estimates of survival of children with CAs in some European countries. Bias arises when linkage is not successful, as early neonatal deaths were less likely to be linked. Linkage to mortality records only cannot be recommended, as linkage quality, and hence bias, cannot be assessed.

A Cluster Analysis with Complete Linkage and Ward's Method for Health Service Data in Makassar City

Health care facilities are a place used to organize health efforts. Health service data in Makassar City has not shown which sub-districts have excellent service criteria, good enough, and not good. Therefore, it is necessary to group sub-districts with cluster analysis using hierarchy method. The hierarchy method used in this study is only 2, namely complete linkage and ward's method. Complete linkage method is the opposite of the approach to the minimum distance principle that is the furthest distance between objects while Ward's Method is a method that aims to minimize variance between objects in one cluster. There are four health services used, namely Hospitals, Health Centers, Home Care and Telemedicine with 15 sub-districts. This study also used a validity test namely Index Davies Bouldin (IDB) to determine the criteria of health services. The results of the analysis on complete linkage formed 3 clusters, namely cluster 1 with good health services, cluster 2 with excellent health services, and cluster 3 with poor health services. In addition, ward's Method also formed 3 clusters, namely cluster 1 with good health services, clusters 2 with poor service, and cluster 3 with excellent health services.

Optimisation of Distribution Routes: A Case Study

This article focuses on optimisation of the distribution routes for a company that produces carpets, floor coverings and tapestries. The optimisation process is based on operational research methods including, without limitations, Mayer’s method and the single linkage method. The obtained results are subsequently compared to the current situation and evaluated in terms of time and costs. The conclusion provides the optimised economic solution.