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Arief Huda
Telkom University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Implementasi Dan Analisis Pengukuran Cross Level Semantik Similarity Dengan Metode Alignment-based Disambiguation Dalam Pencarian Ayat Al Quran Mu`ti Putro; Moch. Bijaksana; Arief Huda
eProceedings of Engineering Vol 4, No 3 (2017): Desember, 2017
Publisher : eProceedings of Engineering

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Abstract

Al Qur’an merupakan kitab suci umat islam yang diturunkan kepada Nabi Muhammad SAW melalui malaikat Jibril sebagai pedoman hidup. Al Qur’an memiliki 30 juz, 114 surat, 6.243 ayat. Tentunya dengan banyaknya ayat AlQur’an membuat sulit dalam proses pencarian suatu ayat. Cross Level Semantic Similarity merupakan pengukuran kesamaan antara dua buah variabel yang memiliki ukuran yang berbeda seperti pengukuran kata dengan kalimat. Metode Alignment-Based Disambiguation merupakan metode yang ditujukan untuk mengukur nilai kesamaan(similarity) suatu pasangan data yang memiliki ukuran yang berbeda. Oleh karena itu, pada tugas akhir ini akan akan digunakan pengukuran nilai kesamaan dengan menggunakan metode Alignment-Based Disambiguation dengan bantuan WordNet yang dapat diterapkan dalam pencarian ayat Al Qur’an. Keywords: Al Qur’an, Cross Level Semantic Similarity, Alignment Based Disambiguation, Similarity, WordNet.
Indonesian Language Stemmer Algorithm Improvement By Rearrange Stemming Process Steps Sequence Hari Widayanto; Arief Huda
eProceedings of Engineering Vol 4, No 3 (2017): Desember, 2017
Publisher : eProceedings of Engineering

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Stemming is a processs to find root word from its compounded form by removing all affixes are attached on it. Stemmer was applied in various text mining application to improve application performance, such as in Information Retrieval stemmer could improve performance by providing variant morphological searched terms and reduce size of index [9]. In word based text compression, stemmer could simplify the dictionary as various word from could be represented by one word [6]. Besides reduce size of document index, stemmer could increase text retrieval accuracy [10]. In text classification stemmer reduce the number of features [18]. The first Indonesian stemmer was developed by Nazief-Adriani then Jelita Asian improved the algorithm called confix stripping (CS) stemmer. There were heaps of improvement was done by CS stemmer so it is highest accuracy stemmer algorithm. Experiment would be performed to compare the accuracy between Nazief – Adriani and CS stemmeralgorithm for stemm words were extracted from online news, Republika. Keywords : Stemming, Indonesian, Nazief-Adriani, CS stemmer
Co-Authors Hari Widayanto Moch. Bijaksana Mu`ti Putro