Article Per Year (5 Year)
p-Index From 2020 - 2025
5.071
P-Index
This Author published in this journals
All Journal Teknika SITEKIN: Jurnal Sains, Teknologi dan Industri JTT (Jurnal Teknologi Terpadu) Jurnal CoreIT Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi Krea-TIF: Jurnal Teknik Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Jurnal Sosial Humaniora Sigli INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Computer Science and Information Technology (CoSciTech) SINTA Journal (Science, Technology, and Agricultural) Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) J-Intech (Journal of Information and Technology) Jurnal Indonesia Raya Jurnal Dehasen Mengabdi SATIN - Sains dan Teknologi Informasi Journal Of Artificial Intelligence And Software Engineering Jurnal Malikussaleh Mengabdi Jurnal Indonesia : Manajemen Informatika dan Komunikasi Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Muhammad Fikry
Universitas Islam Negeri Sultan Syarif Kasim Riau
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 44 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

 1 
Analisis Sentimen Terhadap Sebuah Figur Publik di Twitter Menggunakan Metode K-Nearest Neighbor Yenggi Putra Dinata; Yusra; Fikry, Muhammad; Yanto, Febi; Cynthia, Eka Pandu
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1904

Abstract

The development of online media, particularly through social media platforms like Twitter, has created a vast stage for various activities, including political campaigns and public opinion on public figures. When information technology advances rapidly, public opinion can be conveyed without time constraints through social media. Twitter, with its character limitations and the use of hashtags by users, is considered easier to gather information about existing opinions and sentiments. Currently, social media is widely used for communication and making friends, but also for other activities. Advertising products, buying and selling anything, including advertising political parties and campaigning for members of Congress or presidential candidates. This research focuses on sentiment analysis towards Puan Maharani, the Speaker of the Indonesian House of Representatives (DPR RI), using data from the social media platform Twitter. Twitter, as a platform that allows users to express opinions in a concise format, is used as the main source of information in this research. The K-Nearest Neighbor algorithm for sentiment analysis technique is utilized to classify individual tweets into positive or negative categories regarding views on Puan Maharani. The methods used in this research include data crawling, labeling, and data preprocessing, which involve case folding, cleaning, tokenizing, negation handling, normalization, stopword removal, and stemming. For the classification process, the K-Nearest Neighbor method, feature weighting (TF-IDF), and feature selection (thresholding) are employed, with a threshold value of 0.001. The data used comprises 9,000 tweets in the Indonesian language. The results of the testing conducted in the K-Nearest Neighbor method, using confusion matrices, with 6 different values of K (3, 5, 7, 9, 11, 13), with comparison mechanisms of 90:10, 80:20, and 70:30 achieved the highest accuracy of 90.00% with K = 11 from the comparison using the 90:10 ratio
Peningkatan Performa Klasifikasi Sentimen Tweet Kaesang Menggunakan Naïve Bayes dengan PSO pada Dataset Kecil Muhammad Ravil; Agustian, Surya; Fikry, Muhammad; Insani, Fitri
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1939

Abstract

After the news of Kaesang's appointment as the Chairman of the Indonesian Solidarity Party (PSI), various speculations emerged on social media, particularly on Twitter (X). This study aims to classify sentiments regarding Kaesang's appointment as PSI Chairman using the Naïve Bayes algorithm optimized with Particle Swarm Optimization (PSO). The data used in this study consists tweets about Kaesang and tweets related to COVID-19. The text preprocessing process includes cleaning, case folding, tokenizing, stemming, and stopword removal. TF-IDF is used to represent words in vector form. In the initial experiment, Naïve Bayes performed classification using Kaesang data combined with COVID-19 data, with 300 data points for each label. Particle Swarm Optimization was used to improve the performance of the Naïve Bayes algorithm. The experiment results showed that the model tested with test data achieved the highest f1-score of 50%.
Co-Authors -, Yusra Agustian, Surya Ahadi, Ridho Alwis Nazir Ananda, Silvia Andini, Nanda Angela, Angela Anggraeni, Ni Ketut Pertiwi Annisa Annisa Ayu Fransiska Bahari, Bayu Dwi Prasetya Damayanti, Elok Dermawan, Jozu Detha Yurisna Dimas Pratama, Dimas Eka Pandu Cynthia Eka Pandu Cynthia, Eka Pandu Eko Sumartono, Eko Elin Haerani Elin Haerani Elin Haerani Elvia Budianita Fadhilah Syafria Febi Yanto, Febi Fitri Insani Fitri Insani Hasugian, Leonardo Hutagalung, Yorio Arwandi Wisdom Ibnu Surya Ida Wahyuni Inggih Permana Iwan Iskandar kurnia, fitra Lestari Handayani Lola Oktavia Lutfi, Raihansyah Mardiansyah, M Rizki Mei Lestari, Mei Muchlis Abdul Muthalib Muhammad Abdillah Muhammad Iqbal Maulana Muhammad Irsyad Muhammad Ravil Nanda Sepriadi Nazir, Alwis Nazruddin Safaat H Ndruru, Arlan Joliansa Nuari Ananda Nurdin Nurdin nuryana nuryana, nuryana Oktavia, Lola Pizaini Pizaini Pizaini Pizaini Pizaini, Pizaini Prananda, Alga Putra, Wahyu Eka Putri Mardatillah Rahma Yunita, Rahma Rahmat Rizki Hidayat Ramadanu Putra Razi, Ar Reski Mai Candra Rinaldi Syarfianto Ritonga, Sinta Wahyuni Sagala, Ruflica Sapriadi, Muhammad Saputra, Ikhsan Dwi Sari, Cut Jora Sayed Omas Tutus Arifta Sayed Siti Ramadhani Sofiah Surya Agustian Surya Agustian Suwanto Sanjaya Tarigan, Anggun Kinanti Taufik Hidayat Taufiq Taufiq Tiara Dwi Arista Wirdiani, Putri Syakira Yani, Susmi Syahfrida Yenggi Putra Dinata Yolanda, Khovifah Yossie Yumiati Yuda Zafitra Fadhlan Yulinazira, Ulfa Yusra Yusra Yusra . YUSRA YUSRA Yusra, Yusra Yusriyana, Yusriyana Zukhruf, Muhammad Firmansyah