Semantikasi

Semantikasi is a term used to describe the process of adding semantic content to information to support interpretation by humans and machines. It encompasses the encoding of meaning in data, text, and systems, often through the alignment of signs with conceptual representations, such as concepts in an ontology or a controlled vocabulary. The term is a neologism formed in Indonesian from semantik (semantics) and the suffix -asi (indicating a process).

In practice, semantikasi appears in linguistics, information science, and computer science, especially in the development of knowledge graphs and the Semantic Web. It covers activities such as semantic tagging, annotation, and the construction of ontologies, taxonomies, and linked data schemas that enable interoperable data exchange and more robust search and reasoning.

Common methods include lexical and semantic annotation, corpus-based identification of meaning, ontology engineering, and the use of standardized vocabularies to describe entities and relationships. In natural language processing, semantikasi supports disambiguation, information retrieval, and question answering by providing structured meaning beyond surface text.

Applications span digital humanities, library science, e-commerce, healthcare, and governmental data portals. Example: annotating product records with a shared set of semantic tags improves cross‑vendor comparisons; in healthcare, aligning terms to standard terminologies supports clinical decision support.

Challenges include linguistic ambiguity, context dependence, multilinguality, and the ongoing need for maintained standards and governance. Despite these challenges, semantikasi aims to improve data interoperability, search relevance, and machine-assisted reasoning by making meanings explicit and machine-readable.