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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Nur Annisa Tresnasari
Department of Electrical Engineering & Information Technology, UGM, Yogyakarta
Computer Science & IT Control & Systems Engineering

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Social-Child-Case Document Clustering based on Topic Modeling using Latent Dirichlet Allocation Nur Annisa Tresnasari; Teguh Bharata Adji; Adhistya Erna Permanasari
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 2 (2020): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.54507

Abstract

Children are the future of the nation. All treatment and learning they get would affect their future. Nowadays, there are various kinds of social problems related to children.  To ensure the right solution to their problem, social workers usually refer to the social-child-case (SCC) documents to find similar cases in the past and adapting the solution of the cases. Nevertheless, to read a bunch of documents to find similar cases is a tedious task and needs much time. Hence, this work aims to categorize those documents into several groups according to the case type. We use topic modeling with Latent Dirichlet Allocation (LDA) approach to extract topics from the documents and classify them based on their similarities. The Coherence Score and Perplexity graph are used in determining the best model. The result obtains a model with 5 topics that match the targeted case types. The result supports the process of reusing knowledge about SCC handling that ease the finding of documents with similar cases
Co-Authors Adhistya Erna Permanasari Teguh Bharata Adji