Penerapan Analisis Cluster Ensemble Dengan Metode Rock Untuk Mengelompokkan Provinsi Di Indonesia Berdasarkan Indikator Kesejahteraan Rakyat

Belinda, Nadira Sri; Hg, Izzati Rahmi; Yozza, Hazmira

doi:10.25077/jmu.8.2.108-119.2019

Cited by 1 publication

(2 citation statements)

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“…Many clustering algorithms are intended to process numerical data, one of it is the Hierarchical Clustering algorithm that groups objects by creating a hierarchy where objects that have a large similarity will be placed in an adjacent hierarchy while objects that have large dissimilarities in the far apart hierarchy. However, problems arise when the algorithm is applied to data that has attribute values that are boolean or categorical [16]. The ROCK (Robust Clustering Using Links) clustering method uses a measure of similarity called "links" in forming clusters, unlike traditional clustering techniques such as Hierarchical Clustering techniques that use distance values [6].…”

Section: Rock (Robust Clustering Using Links)mentioning

confidence: 99%

“…Often, the results of the clustering process group object that do not have the same items and have a small similarity value. To handle the problem of categorical data, in this article the ROCK clustering method will be used to cluster the data by grouping the data that has the most links or the same number of items with its neighbors, with the parameter number of clusters (k) and threshold value [16].…”

Section: Rock (Robust Clustering Using Links)mentioning

confidence: 99%

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Building Synsets for Indonesian WordNet using ROCK (Robust Clustering Using Links) Algorithm

2020

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On the development of Indonesian WordNet, the synonym set is an important part that represents the similarity of meaning between words. Synonym sets are built using the Indonesian Thesaurus as the lexical database. After going through the extraction process from the Indonesian Thesaurus, we will get a synonym set that has a similarity or word sense between words. In general, the difference between WordNet and the dictionary is their main focus, in which the dictionary usually focuses on just one word, while in WordNet the focus is on the meaning of words and connectedness with other words. Explained in previous research, the constructions of synonym sets were done using several approaches, which is clustering to produce synonym sets and WSD (Word Sense Disambiguation). In this article, the approach used to produce synonym sets is the ROCK (Robust Clustering Using Links) algorithm, which uses similarity and link values. The resulting synonym sets will then be used for lexical database development. Therefore, the main focus of this article is to produce synonym sets through the clustering process and calculate their accuracy, using the F-Measure method involving the gold standard for performance calculation and evaluation.

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Section: Rock (Robust Clustering Using Links)mentioning

confidence: 99%

Section: Rock (Robust Clustering Using Links)mentioning

confidence: 99%