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All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Penelitian Komunikasi dan Opini Publik Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal TAM (Technology Acceptance Model) INOVTEK Polbeng - Seri Informatika Communications in Science and Technology SENTIA 2015 Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Buletin Ilmiah Sarjana Teknik Elektro INSERT: Information System and Emerging Technology Journal Journal of Electrical, Electronic, Information, and Communication Technology (JEEICT) Jurnal Pengabdian Polinema Kepada Masyarakat Jurnal Abdi Masyarakat Indonesia Jurnal Fortech Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Informatika Polinema (JIP) Jurnal TAM (Technology Acceptance Model) Jurnal FORTECH
Faisal Rahutomo
Universitas Sebelas Maret
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Public Health Other

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Journal : Jurnal TAM (Technology Acceptance Model)

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IMPLEMENTASI SUPPORT VECTOR MACHINE PADA ANALISA SENTIMEN TWITTER BERDASARKAN WAKTU Faisal Rahutomo; Imam Fahrur Rozi; Haris Setiyono
Jurnal TAM (Technology Acceptance Model) Vol 10, No 2 (2019): Jurnal TAM (Technology Acceptance Model)
Publisher : LPPM STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.767 KB)

Abstract

Sentiment analysis is one branch of science from data mining that aims to analyze, understand, process, and extract textual data in the form of opinions on entities such as products, services, organizations, individuals, and certain topics. In determining positive, negative or neutral categories, a public response on twitter can be done manually by reading each tweet. This certainly requires a lot of time and takes a lot of energy. In this study using the Support Vector Machine classification algorithm to classify tweet data into positive, negative or neutral sentiments. Analysis is carried out based on a certain time span, because each time can have a different topic of discussion and from the results of these data can be seen the development of sentiment trends and can be seen how the public response to a particular topic. The tweet data is obtained by crawling periodically with the target keywords of the names of candidates and vice president in the 2019 election. The dataset used in this study uses 600 tweets. In testing the classification using k-fold cross validation by dividing into 10 data parts, average value of 66% accuracy, 67% precision and 66% recall.
Co-Authors Abdul Latif Priyadi Agustaf Fanisnaini Narolis Ahmad Hafidh Ayatullah Aisy Muhammad R Ali, Muhammad Haidar Aljalal, Majid Annisa Taufika Firdausi Annisa Taufika Firdausi Ariadi Retno Tri Hayati Ririd Ariyo, Bashiru Olalekan Astiningrum, Mungki Aulia, Indinabilah Bambang Harjito, Bambang Carfin Febriawan Pratama Putra Christine Dewi Christine Kartika Dewi Daffa , Aminuddin Dhebys Suryani Hormansyah, Dhebys Suryani Dhiana Novita Sari Diana Mayangsari Ramadhani Diana Mayangsari Ramadhani Dimas Rossiawan Hendra Putra Dwi Puspitasari Dyah Ayu Irawati Dyah Ayu Irawati, Dyah Ayu Ekojono Febri Liantoni Fidyawan, Miftahul Agtamas Gunawan Budi Prasetyo Hafidh Ayatullah, Ahmad Haris Setiyono Henda, Reihan Ibrahim, Sutrisno Ikawati, Deasy Sandhya Elya Imam Fahrur Rozi Imam Nawawi Imam Nawawi, Imam Indinabilah Aulia Inggrid Yanuar Risca Pratiwi Inggrid Yanuar Risca Pratiwi Irvan Wahyu Nurdian Joko Haryono Josaphat Tetuko Sri Sumantyo Kharismadita, Paratisa Kurniawan, Muhammad Fachrul Latif Priyadi, Abdul M Bisri Musthofa Meiyanto Eko Sulistyo Meiyanto Eko Sulistyo Meiyanto Eko Sulistyo Mekonnen, Atinkut Molla Miftahul Agtamas Fidyawan Moechammad Sarosa Muhammad Arief Rahman Muhammad Arief Rahman Muhammad Bisri Musthafa Muhammad Elfa Rodhian Putra Muhammad Fachrul Kurniawan Muhammad Hamka Ibrahim Muhammad Hamka Ibrahim Muhammad R, Aisy Muhammad Rifky Prayanta Musthafa, Muhammad Bisri Ngat mari Ngatmari Ngatmari Ngatmari, Ngatmari Nugraha, Bagus Putra Nur Rochmanshah Nurdian, Irvan Wahyu Pangestu Nur Mirzha Paratisa Kharismadita Pramana Yoga Saputra Pramudita, Muhammad Aisamuddin Eka Putra Prima Arhandi, Putra Prima Putra, Carfin Febriawan Pratama Rahmad, Cahya Rahman, Muhammad Arief Ridwan Rismanto Riyanarto Sarno Rochmanshah, Nur Rohman, Obby Auliyaur Rosa Andrie Asmara Sari, Dhiana Novita Septarina, Amalia Agung Subuh Pramono Sulistyoningrum, Trie Endah Sutrisno Sutrisno Sutrisno Sutrisno Sutrisno Sutrisno Sutrisno, Sutrisno Ulla Delfana Rosiani Yoppy Yunhasnawa Yushintia Pramitarini Yushintia Pramitarini Zanuar Hanif Rachmat Adi