Article Per Year (5 Year)
p-Index From 2021 - 2026
0.817
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TELKOMNIKA (Telecommunication Computing Electronics and Control) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah Kursor Journal of ICT Research and Applications International Journal of Advances in Intelligent Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JUMANJI (Jurnal Masyarakat Informatika Unjani) Jurnal Manajemen Informatika
Masayu Leylia Khodra
Institut Teknologi Bandung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Jurnal Ilmiah Kursor

 1 
TRANSFORMING RHETORICAL DOCUMENT PROFILE INTO TAILORED SUMMARY OF SCIENTIFIC PAPER Masayu Leylia Khodra; Mohammad Dimas; Dwi Hendratmo Widyantoro; E. Aminudin Aziz; Bambang Riyanto Trilaksono
Jurnal Ilmiah Kursor Vol 6 No 3 (2012)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Since abstract of scientific paper is author biased, readers’ required information may not be included in the abstract. Tailored summary may help them to get a summary based on their information needs. This research is the first one that implements tailored summary system for scientific paper. Tailored summary applies information extraction that transforms a scientific paper into Rhetorical Document Profile, a structured representation of paper content based on rhetorical scheme of fifteen slots. This research adapted building plan that used rhetorical scheme of seven slots. We also implement tailored summary system. After generating initial summary, surface repair is conducted to improve summary readability. Each sentence in initial summary is combined with template phrase based on syntax-tree combination method. There are five groups of template phrases provided in surface repair. We construct evaluation standards by asking five human raters. The best method for sentence selection subsystem that uses Maximal Marginal Importance-Multi Sentence is employing TF.IDF weighting system with precision/recall of 0.61. The surface repair subsystem has acceptance of 0.91.
RESTRICTED CONTENT CLASSIFICATION BASED ON VIDEA METADATA AND COMMENTS (CASE STUDY : YOUTUBE.COM) Stefanus Thobi Sinaga; Masayu Leylia Khodra
Jurnal Ilmiah Kursor Vol 7 No 4 (2014)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

RESTRICTED CONTENT CLASSIFICATION BASED ON VIDEA METADATA AND COMMENTS (CASE STUDY : YOUTUBE.COM) aStefanus Thobi Sinaga, aMasayu Leylia Khodra a,bSekolah Teknik Elektro dan Informatika, Institut Teknologi Bandung, Jl. Ganesha 10 Bandung E-Mail: s.thobi.sinaga@gmail.com Abstrak Klasifikasi konten terbatas merupakan kegiatan memisahkan konten video yang layak untuk seluruh pengguna dari konten yang tidak layak untuk pengguna di bawah umur (<18 tahun). Pada situs Youtube, proses klasifikasi konten terbatas dilakukan secara manual oleh karyawan berdasarkan laporan yang dikirimkan oleh komunitas pengguna. Pada penelitian ini dirancang sebuah sistem klasifikasi konten terbatas secara otomatis yang dapat melakukan klasifikasi terhadap video Youtube berdasarkan teks metadata (judul, deskripsi) dan komentar dari video tersebut. Sistem tersebut memanfaatkan model klasifikasi hasil eksperimen terhadap dataset video Youtube yang telah dikumpulkan. Judul dan deskripsi video dipilih sebagai atribut klasifikasi karena mengandung informasi utama yang ditulis oleh penggunggah terkait video yang diunggah. Sedangkan komentar dipilih sebagai atribut klasifikasi karena dapat dijadikan sumber informasi ketika informasi yang disediakan oleh pengunggah tidak dapat mereprentasikan video yang digunakan. Melalui eksperimen, didapatkan model klasifikasi dengan F-Measure sebesar 83,45%. Model dibangun dengan menggunakan pendekatan leksikal terhadap dataset judul dan deskripsi video (tanpa komentar), Support Vector Machines sebagai algoritma klasifikasi, serta metode binary sebagai metode pembobotan fitur. Dengan menggunakan model tersebut, telah dikembangkan sistem klasifikasi konten terbatas berdasarkan teks metadata dan komentar video. Kata kunci: Klasifikasi, Konten Terbatas, Support Vector Machines. Abstract Restricted content classification is an activity of labeling video content into two category, which are restricted content that is appropriate for all audiences and non-restricted content that are not appropriate for minor audiences (age < 18). On Youtube, restricted content classification is being processed manually by the expert staffs based on user reports. This research aims to build automatic restricted content classification system which is able to classify Youtube video based on its metadata (title, description) and video comments. This system would use the best model achieved from the experiment on Youtube video dataset. Video title and description are chosen as the classification attribute since they contain the main information about the video provided by the uploader. Meanwhile, video comments are chosen as the other classification attribute under the assumption that they would provide the information necessary when video title and description are not able to give any information related to the video. Our experiment shows that the best classification model with F-Measure of 83.45% is achieved by using lexical feature on dataset built from video title and description (without comments). We employed Support Vector Machines as the classification algorithm and binary as the feature weighting method. In this paper, a restricted content classification system based on metadata and video comments has been built. Keywords:Classification,Restricted Content, Support Vector Machines.
Co-Authors Agus Nursikuwagus Ary Setijadi Prihatmanto Bambang Riyanto Trilaksono Benhard Sitohang Carmadi Machbub Dwi Hendratmo Widyantoro Dwi Hendratmo Widyantoro Dwi Hendratmo Widyantoro Dwi Hendratmo Widyantoro E. Aminudin Aziz E. Aminudin Aziz Ema Rachmawati Ghoziyah Haitan Rachman Gusti Ayu Putri Saptawati Iping Supriana Iping Supriana Suwardi Ivana Clairine Irsan Jan Wira Gotama Putra Jan Wira Gotama Putra Mohammad Dimas Muhammad Haris Maulana Nadya Aditama Nasy`an Taufiq Al Ghifari Reinhart, Richard Ridwan Ilyas Rinaldi Munir Ruskanda, Fariska Zakhralativa Stefanus Stanley Yoga Setiawan Stefanus Thobi Sinaga Supriana, Iping Wahyudi Wahyudi