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All Journal Proceedings of KNASTIK CommIT (Communication & Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JURNAL MEDIA INFORMATIKA BUDIDARMA JUTEI (Jurnal Terapan Teknologi Informasi) Jurnal ULTIMATICS Share : Journal of Service Learning Jurnal Informatika Jurnal Linguistik Komputasional International Journal of Industrial Research and Applied Engineering Patria : Jurnal Pengabdian Kepada Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Gloria Virginia
Universitas Kristen Duta Wacana
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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Semantic Web Seni Pertunjukan Indonesia Gloria Virginia; Budi Susanto; Umi Proboyekti; Silvanus Satno Nugraha
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4327

Abstract

Documentation of performance arts is an effort of cultural heritage to maintain the dignity and nobility of a nation.   Semantic web is a promising alternative that support the objective.   From the user side, the website will be more informative, while from the technical side, the website has ontology (a well-defined formal knowledge which is highly potential to be related to other websites). This research is an effort to developed a performance arts ontology using Methontology method.   To enrich the ontology, two ontologies were merged .   Linked-data principal was implemented by the use of dbpedia.   The ontology was evaluated based on 4 parameters (consistency, completeness, verification, and validation) and proved to be effective while implemented in a website.
PENERAPAN SENTIMENT ANALYSIS PADA HASIL EVALUASI DOSEN DENGAN METODE SUPPORT VECTOR MACHINE Valonia Inge Santoso; Gloria Virginia; Yuan Lukito
Jurnal Transformatika Vol. 14 No. 2 (2017): January 2017
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v14i2.439

Abstract

The quality of lectures can be determined by some feedbacks from students. From the feedbacks, we can give appreciations for those lectures who get good feedback from students, and evaluations for those who get bad feedback. The problem is classifying large size of feedbacks manually isn t effective and took a lot of time. Therefore, we need a system that can classify feedbacks automatically. These feedbacks will be classified into positive, negative, and neutral, usually called as sentiment analysis. Sentiment analysis implementation can be done by several methods, one of them that has a good accuracy is Support Vector Machine (SVM). SVM performance in this research is measured with the level of accuracy. The number of accuracy indicate the success level of system. The conclusion of this research is factors that affects the accuracy. The factors are the range of each classes and number of unique words in the training document.
Co-Authors Aditya Ratnasari Agata Filiana Agata Filiana Agustinus Rendi Walewowan Andhika Galuh P Andhika Galuh Prabawati Antarani, Mariaty Octavia Antonius Rachmat Chrismanto Bastian Surya Hartono Bill Edward Butar-Butar Budi Susanto Budi Susanto Budi Susanto Butar-Butar, Bill Edward Daisy Ika Christiana Daniel Daniel Debora Syebat Nazir Deni Ariyanto Abadi Desyandri Desyandri Ernawati, Lussy Hung Son Nguyen Ivana Eka Santhi Helvin Joko Purwadi Joko Purwadi Laurentius Kuncoro Probo Saputra Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo Lim, Joseph F Lucia D. Krisnawati Lucia Dwi Krisnawati Lukas Kurniawan Michael Abadi Santoso Nazir, Debora Syebat Neshia Aditya Santoso Ni Luh Muryanti Prabawati, Andhika Galuh Restyandito Rini, Maria Nila Anggia Silvanus Satno Nugraha Sunjaya, Susiana Talenggoran, Rivai Tandirilambun, Tandirilambun Thalia Maria Camilo Theresa Mariana Kurniasih Umi Proboyekti Valonia Inge Santoso Willy Sudiarto Raharjo Yanuar Budi Prasetyo Yuan Lukito