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All Journal Majalah Ilmiah Teknologi Elektro Jurnal Sistem dan Informatika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Informatics for Educators and Professional : Journal of Informatics Jurnal Teknologi Informasi dan Komputer Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas WIDYABHAKTI Jurnal Ilmiah Populer Mattawang: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
I Komang Dharmendra
Institut Teknologi Dan Bisnis STIKOM Bali
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Journal : Majalah Ilmiah Teknologi Elektro

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Analisa Sentiment Untuk Opini Alumni Perguruan Tinggi komang dharmendra; Komang Oka Saputra; I Nyoman Pramaita
Jurnal Teknologi Elektro Vol 18 No 2 (2019): (Mei-Agustus) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (483.896 KB) | DOI: 10.24843/MITE.2019.v18i02.P11

Abstract

Opinion is one of the most important parts in decision making, in processing opinions require a thorough analysis process. Especially text-based opinion, where opinion in the form of opinions do not have a definite value limit for the input. Sentiment Analysis as a branch of knowledge from Text mining can be applied in the opinion analysis process in the form of text. Where opinions will be classified into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. This study grouped opinions from university graduated students using the SVM and NBC algorithms which in this study were divided into 3 main components, namely the input component, opinion grouping system, and output components.Opinion to be processed is data in the form of a * .csv format opinion file, which then conducts a grouping of opinions. Then the system produces output in the form of 3 types of opinions, namely, positive opinions, neutral opinions and negative opinions. In general, the accuracy results show the differences in the accuracy of each sentiment. From the test results generally shows the accuracy with the highest accuracy value in the NBC algorithm reaching 94.45 while the highest accuracy rate in the SVM algorithm reaches 75.76%.
Co-Authors Dedy Panji Agustino EDWAR Edwar Edwar I Gede Bintang Arya Budaya I Gede Harsemadi I Gede Harsemadi I Gusti Agung Ngurah Rai Semadi I Gusti Agung Ngurah Rai Semadi I Gusti Ayu Desi Saryanti I Gusti Ngurah Ady Kusuma I Made Agus Wirahadi Putra I Made Ari Santosa I Made Pasek Pradnyana Wijaya I Made Pradipta I Made Suandana Astika Pande I Putu Ramayasa, I Putu Ida Ayu Mirah Cahya Dewi Ida Bagus Suradarma Komang Oka Saputra Luh Putu Ayu Desiani, Luh Putu Ayu Muhamad Samsudin Muhamad Samsudin Ni Luh Ari Yusasrini Ni Nyoman Utami Januhari, Ni Nyoman Ni Wayan Setiasih Nyoman Pramaita Ricky Aurelius Nutanto Diaz, Ricky Aurelius Tubagus Mahendra Kusuma Tubagus Mahendra Kusuma