ANALISA SENTIMEN MENGENAI AKSI CEPAT TANGGAP (ACT) PADA TWITTER MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE

TAUFIK, AHMAD (2024) ANALISA SENTIMEN MENGENAI AKSI CEPAT TANGGAP (ACT) PADA TWITTER MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Aksi Cepat Tanggap (ACT) is a mass organization that is independent, universal and free to cooperate with various parties to defend the interests and rights of the community with an orientation towards the development of a strong civil society. Fast Response Action consists of individual volunteers who have the commitment and contribution in creating positif changes to their environment, both micro and macro environment on the basis of the principle of volunteerism as a form of social responsibility as individuals, as citizens of society, as citizens of the state, and as citizens of the world. This research will use the Naïve Bayes algorithm and the Support Vector Machine, where this algorithm is the Naïve Bayes Classifier (NBC) which is a classification method that is rooted in Bayes' theorem. The method used is the Naïve Bayes classification algorithm and Support Vector Machine assisted by RapidMiner and Python tools. The experimental results show that the Support Vector Machine algorithm gives the highest accuracy, namely 89% for automatic labeling and 77% for manual labeling. Keywords: ACT, Fast Response Action, Naïve Bayes, Support Vector Machine, Sentiment, Algorithm Aksi Cepat Tanggap (ACT) adalah sebuah organisasi masa independen, universal dan bebas melakukan kerjasama dengan berbagai pihak untuk membela kepentingan dan hak-hak masyarakat dengan berorientasi pada pembangunan masyarakat sipil yang kuat. Aksi cepat tanggap beranggotakan individu-individu relawan yang memiliki komitmen dan kontribusi dalam menciptakan perubahan positif pada lingkunganya baik lingkungan mikro maupun makro atas dasar prinsip kesukarelaan sebagai wujud tanggung jawab sosial sebagai individu, sebagai warga masyarakat, sebagai warga negara, dan sebagai warga dunia. Pada penelitian ini akan menggunakan algoritma Naïve Bayes dan Support Vector Machine, yang dimana algoritma ini adalah Naïve Bayes Classifier (NBC) merupakan sebuah metode klasifikasi yang berakar pada teorema Bayes. Metode yang digunakan adalah algoritma klasifikasi Naïve Bayes dan Support Vector Machine dengan dibantu oleh tools RapidMiner dan Python. Hasil eksperimen menunjukkan bahwa algoritma Support Vector Machine memberikan nilai akurasi paling tinggi yaitu 89% untuk labeling otomatis dan 77% untuk labeling manual. Kata kunci: ACT, Aksi Cepat Tanggap, Naïve Bayes, Support Vector Machine, Sentimen, Algoritma

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 24 027
NIM/NIDN Creators:	41518010063
Uncontrolled Keywords:	ACT, Aksi Cepat Tanggap, Naïve Bayes, Support Vector Machine, Sentimen, Algoritma
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.6 Interfacing and Communications/Tampilan Antar Muka (Interface) dan Jaringan Komunikasi Komputer > 004.66 Data Transmission Modes and Data Switching Methods/Metode Transmisi Data 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.7 Multimedia Systems/Sistem-sistem Multimedia > 006.75 Social Multimedia/Multimedia Social 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.7 Multimedia Systems/Sistem-sistem Multimedia > 006.75 Social Multimedia/Multimedia Social > 006.754 Online Social Network/Situs Jejaring Sosial, Sosial Media 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 512 Algebra/Aljabar > 512.5 Linear, Multilinear, Multidimensional Algebra/Aljabar Linear, Multilinear, Aljabar Multidimensional > 512.52 Vector Spaces/Ruang Vektor
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	07 Feb 2024 03:10
Last Modified:	07 Feb 2024 03:10
URI:	http://repository.mercubuana.ac.id/id/eprint/85919

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