Kebakaran hutan di Indonesia setiap tahunnya masih sering terjadi. Dalam menanggulangi kebakaran sendiri, para peneliti belakangan ini semakin fokus untuk melakukan pengembangan sistem yang mampu prediksi hutan. Selain mengenai hutan, antisipasi dapat dilakukan membantu menangani pencegahan salah satunya adalah pengelompokkan terhadap wilayah memiliki potensi kebakaran. Pada penelitian Clusteri...

The article proposes an approach to the development of models for assessing resilience macroeconomic systems effects exogenous shocks with emphasis on study diagnostic classes. relevance chosen research topic is explained by fact that world economy takes place in context increasing globalization processes. In this economic environment, both positive and negative these processes are formed. Due ...

In many machine learning applications that deal with sequences, there is a need for learning algorithms that can effectively utilize the hierarchical grouping of words. We introduce Word Taxonomy guided Naive Bayes Learner for the Multinomial Event Model (WTNBL-MN) that exploits word taxonomy to generate compact classifiers, and Word Taxonomy Learner (WTL) for automated construction of word tax...

Nowadays the content based image retrieval (CBIR) is becoming a source of exact and fast retrieval. CBIR presents challenges in indexing, accessing of image data and how end systems are evaluated. Data clustering is an unsupervised method for extraction hidden pattern from huge data sets. Many clustering and segmentation algorithms both suffer from the limitation of the number of clusters speci...

This paper describes the participation of the Loz team in the Multilingual Web Person Name Disambiguation task of IberEval 2017. The solutions consist of diferent variants of the traditional hierarchical agglomerative clustering algorithm. Tha analysis of results gives information about the relative effectiveness of considering different feature projections (word presence, term frequency and if...

Relational data mining deals with datasets containing multiple types of objects and relationships that are presented in relational formats, e.g. relational databases that have multiple tables. This paper proposes a propositional hierarchical model-based method for clustering relational data. We first define an object-relational star schema to model composite objects, and present a method of fla...

Clustering is a process of discovering group of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem of clustering, but most of them are very sensitive to their input parameters. Minimum Spanning Tree clustering algorithm is capable of detecting clusters with irre...