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All Journal Jurnal Sosial Ekonomi Pertanian JUSIFO : Jurnal Sistem Informasi Annual Research Seminar CCIT (Creative Communication and Innovative Technology) Journal Sriwijaya Journal of Informatics and Applications Jurnal Generic
Yunita Yunita
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Journal : Annual Research Seminar

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Peringkasan Teks Berita Berbahasa Indonesia Menggunakan Metode Latent Semantic Analysis (LSA) dan Teknik Steinberger&Jezek Jerry Satiamy Saputra; Muhammad Fachrurrozi; Yunita Yunita
Annual Research Seminar (ARS) Vol 3, No 1 (2017): ARS 2017
Publisher : Annual Research Seminar (ARS)

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Abstract

Dokumen berita merupakan dokumen yang memuat berbagai macam informasi. Semakin banyak informasi yang terdapat pada suatu dokumen membuat dokumen tersebut semakin panjang. Membaca keseluruhan dokumen tersebut memakan banyak waktu. Ringkasan dokumen diperlukan untuk memudahkan memahami informasi yang berukuran besar dengan cepat. Peringkasan dokumen secara otomatis merupakan solusi untuk membantu mendapatkan intisari dari dokumen. Pada penelitian ini dilakukan penerapan metode Latent Semantic Analysis dan teknik Steinberger&Jezek yang digunakan untuk peringkasan teks otomatis. Jumlah data uji yang digunakan sebanyak 10 teks berita yang diambil dari data uji penelitian sebelumnya. Hasil penelitian yang telah dilakukan menghasilkan rata-rata recall 0.7027, precision 0.6973, dan f-measure 0.6974.
Indonesian-English Machine Translation Using Rule-Based Method Novi Yusliani; Yunita Yunita; Wenty Octaviani
Annual Research Seminar (ARS) Vol 1, No 1 (2015)
Publisher : Annual Research Seminar (ARS)

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Abstract

Rule-Based Machine Translation (RBMT) used a set of linguistic information to translate source language to target language. POS tagger and Shift-Reduce-Parsing (SRP) could be used to get the linguistic information. POS tagger was used to get word class of each word in sentence and SRP was used to get the function of each word in sentence. SRP was also used to get the structure of sentence. In this research, POS tagger and SRP were used to get the linguistic information of source sentence. Translation process was done by using billingual dictionary. Last, a set of rules was used to generate the target sentence. The accuracy of Indonesian-English machine translation was 100% for the S-P-Adv pattern, but for the S-P pattern and S-P-O pattern is 93,33%.
Co-Authors Allsela Meiriza, Allsela Angga Adiningrat Mulyanata Desty Rodiah Dicky Ahmad Rizaldi Evita Hardanita Fadhlan Jiwa Hanuraga Jerry Satiamy Saputra Kanda Januar Miraswan Kartika Rahmayani Luh Sri Mulia Eni M. Fachrurrozi . Muhammad Arbi Muhammad Rizkiansyah Novi Yusliani Oktadini, Nabila Rizky Osvari Arsalan Risky Tama Putri Rizki Kurniati Rusdi Efendi Wenty Octaviani