Searching Quran Chapters Verses Weight with TF and Pareto Principle to Support Memorizing (Case Study Juz 'Amma)

被引:0
|
作者
Darwiyanto, Eko [1 ]
Bijaksana, Moch Arif [1 ]
机构
[1] Telkom Univ, Sch Comp, Bandung, Indonesia
关键词
Quran; memorize; statistic; term frequency; weight verse; pareto; Juz Amma;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Quran is holy book for Moslems. Reading it, understanding its meaning, even memorizing it is very useful. But memorizing 6236 of its verses is not an easy task, even short juz 'amma chapters. Several memorizing methods have been known. In panipati, Turkey, Mauritanian, Singapore method, students memorize Quran page by page, from first juz or last juz. In Sudan, students memorize verses with writing its out. In mnemonic learning, verses are linked with the association. Photographic memory is used to recall an image of verses in any page. From computing theory, especially artificial intelligence, Breadth First Search algorithm can be hoped to support memorizing Quran. Memorize its chapter title, what the main topic, memorize verses that tell it, then expand to previously or next verses. Another method is using statistic, using Term Frequency (TF) to get list verses in each chapter of Juz 'Amma that its weight of term at least is eighty percent of chapter weight of term. With minimum verses, student has memorized most important verses in each chapter.
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页码:269 / 273
页数:5
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