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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 : Jurnal Teknik Informatika UNIKA Santo Thomas

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Implementasi keamanan informasi file dokumen shipping menggunakan algoritma AES Shipping I Komang Dharmendra; Ni Nym Utami Januhari; I Putu Ramayasa; I Made Agus Wirahadi Putra
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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Abstract

Opinion is an important part of decision making, so it takes the ability to get information from opinions. Sentiment Analysis is a branch of science from Text mining that can be used for opinion analysis in the form of text to classify opinions into 3 types of opinions, namely positive opinions, neutral opinions and negative opinions. Support Vector Machine (SVM) is one method that is widely applied for text mining because it is able to show good performance (Styawati and Mustofa, 2019). SVM works with a learning system that uses a hypothetical space in the form of linear functions in a high-dimensional feature space. Maximum Entropy is a probabilistic classification algorithm that belongs to the class of exponential models, which is based on the principle of Maximum Entropy. Maximum Entropy can be used to solve text classification problems such as Language detection, topic classification, and sentiment analysis. Sentiment analysis was tested using the Support Vector Machine (SVM) and Maximum Entropy methods to test the accuracy of each method in analyzing the sentiments of college alumni opinions. from the test results show Maximum Entropy has a better level of accuracy with the results of 95.45%
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