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KEMIRIPAN SEMANTIK DOKUMEN TUGAS AKHIR TERHADAP ONTOLOGI BIDANG ILMU INFORMATIKA MENGGUNAKAN METODE WU PALMER
The increasing number of multidisciplinary undergraduate theses in Informatics field presents challenges in categorizing these documents accurately. This study develops a system to measure the semantic similarity of final project documents to the ontology of Informatics using the Wu Palmer method as a solution to this problem. This method utilizes ontology tree structures and taxonomic depth to measure semantic similarity between concepts. The system employs BidangIlmuInformatika.owl as a knowledge base to represent hierarchical structures and relationships between concepts in Informatics. The classification process involves computing the similarity between document text and ontology concepts. Testing was conducted on 200 undergraduate thesis abstracts, categorized into four fields: Data Science and Pattern Recognition, Distributed Systems, Natural Language Processing, and Graphics and Visualization. The evaluation results show that the system correctly classified 105 out of 200 documents, achieving an accuracy of 53%. However, the broad scope of concepts in the Data Science and Pattern Recognition (DSPR) domain led to higher similarity values in this field, affecting the overall classification performance.
Inventory Code | Barcode | Call Number | Location | Status |
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2507001876 | T169917 | T1699172025 | Central Library (Reference) | Available but not for loan - Not for Loan |
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