Finding a data clustering in a data set is a challenging task since algorithms usually depend on the adopted inter-cluster distance as well as the employed definition of cluster diameter. The work described in this paper approaches a well-known agglomerative clustering algorithm named AGNES (Agglomerative Nesting), in regards to its performance on three case studies namely, datasets formed by c...

Electroencephalogram (EEG) is one of the useful biological signals to distinguish different brain diseases and mental states. In recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from EEG signals. In this research, we introduce an emot...

Clustering web users based on their access patterns is a quite significant task in Web Usage Mining. Further to clustering it is important to evaluate the resulted clusters in order to choose the best clustering for a particular framework. This paper examines the usage of Kullback-Leibler divergence, an information theoretic distance, in conjuction with the k-means clustering algorithm. It comp...

Studying the communities of microbial species is highly important since many natural and artificial processes are mediated by groups of microbes rather than by single entities. One way of studying them is the search of common metabolic characteristics among microbial species, which is not only a potential measure for the differentiation and classification of closely-related organisms but also t...

One of data mining model that is often used the clustering model. The to create a grouping datasheet. Data can be distinguish in Many best groupings done with evaluation process. In method, process use various methods. research will cluster results survey on reviews tourist destinations consisting 10 categories. method namely Knowledge Discovery Database (KDD). Stages KDD include selection, cle...

Résumé. L’algorithme des K-moyennes prédictives est un des algorithmes de clustering prédictif visant à décrire et à prédire d’une manière simultanée. Contrairement à la classification supervisée et au clustering traditionnel, la performance de ce type d’algorithme est étroitement liée à sa capacité à réaliser un bon compromis entre la description et la prédiction. Or, à notre connaissance, il ...

Indonesia sebagai negara maritim meghasilkan banyak komoditas ekspor dari bidang kelautan yang salah satunya adalah udang, dibandingkan dengan lain di kawasan ASEAN. Komoditas udang merupakan satu unggulan paling diminati karena memiliki kandungan gizi tinggi, nilai ekonomi tinggi dan mempunyai peluang pasar baik dalam maupun luar negeri. Terdapat berbagai jenis dihasilkan perairan Indonesia. U...

In marriage, the thing that is most avoided a divorce. Divorce termination of husband and wife relationship which carried out legally at time trial. From year to year, there an increase in number divorces Indonesia, including Kuningan Regency. This study analyzes divorce cases villages Regency, analysis by using data mining clustering methods K-Means algorithm. The method grouping based on same...