Semantic Model Evaluation Dataset For Indonesian In Al-Qur'an Vocabulary: Similarity and Relatedness - Falia Amalia; Moch Arif Bijaksana (Jurnal Teknologi Informasi dan Terapan, 2020)
Abstract — The Qur'an is one of the research in linguistic branches that have not been studied by many experts in their field so it has not gotten a popular place. Whereas in the Qur'an, very many words can be used to be researched especially in terms of Natural Language Processing such as text classification, document clustering, text summarization, etc. One of them is like the semantic similarity and the Distribution Semantic Model. The purpose of this writing is to try to create an evaluation dataset in the model of semantic distribution in Bahasa Indonesia with two classes of words that are noun and verb, looking for equal value and linkage of 500 word-pairs provided. Hopefully by looking at this, the semantic sciences that exist for the study of the Qur'an are growing, especially in the translation of the Quran in the Indonesia Language. This research was created at the same time to create datasets such as previously conducted research, in order to hope that future research with the focus of other discussions can use this dataset to help with the research. The study uses 6236 number of verses and from the number of such verses, the system gets 2193 for nouns and 1733 for verbs. The amount is processed using the Sim-rail vector method, a questionnaire against 15 respondents and gold standard, to get the performance value measured using Spearman Rank and get a correlation result of 0.909. Keywords — Natural Language Processing; Distribution Semantic Model; Sim-Rel Vector; Spearman Rank