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Journal : Knowledge Engineering and Data Science

Opinion Analysis for Emotional Classification on Emoji Tweets using the Naïve Bayes Algorithm Siti Sendari; Ilham Ari Elbaith Zaeni; Dian Candra Lestari; Hanny Prasetya Hariyadi
Knowledge Engineering and Data Science Vol 3, No 1 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i12020p50-59

Abstract

Opinion Analysis is a research study needed to social media, since the content could become a trending topic and has a significant impact on social life. One of the social media that have a big contribution to cyberspace and information development is Twitter. In the Twitter application, users can insert images that represent emotions, facial expressions, or icons. Emoji is a graphic symbol in the form of an image to express a thing, with the Emoji, a text can be read and understood according to its meaning because the image represents it. Of the several things that have been mentioned then, the researchers conducted research on the classification of tweet content based on the use of Emojis. This study aims to determine the emotional uses of Twitter in one period. Every tweet on the Twitter timeline, which contains both text and Emojis, will be classified according to several categories. The algorithm used was Naïve Bayes. It calculated the probability of Emoji tweet to obtain the text classification with Emojis. The results of the classification of emotions are grouped with three categories, namely "angry," "joy," and "sad," it showed that the category "joy" had become the emotional trend of Twitter users where Emojis (x1f60a) dominate the most. Meanwhile, the accuracy of the algorithm used to reach 90% with a 70:30 holdout technique.
Generating Javanese Stopwords List using K-means Clustering Algorithm Aji Prasetya Wibawa; Hidayah Kariima Fithri; Ilham Ari Elbaith Zaeni; Andrew Nafalski
Knowledge Engineering and Data Science Vol 3, No 2 (2020)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v3i22020p106-111

Abstract

Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created by a Javanese linguist. The accuracy of the proposed method is 78.28% (K=7). The result shows that the generation of Javanese stopword lists using a clustering method is reliable.
Co-Authors A.N. Afandi Adam Rachmawan Adib Nur Sasongko Aditama Yudha Atmanegara Adjie Rosyidin Afifah Salim Afnan Habibi, M. Agung Bella Putra Utama Aji Prasetya Wibawa Aji Wibawa Akhmad Afrizal Rizqi Amalia Sufa Andrew Nafalski Andrew Nafalski Andy Hermawan Anggraeni Budiarti Anik N. Handayani Anik Nur Handayani Arengga Wibowo, Danang Arifin, Samsul Aripriharta - Arya Kusuma Wardhana Arya Tandy Hermawan Atmaja, Nimas Hadi Dessy Rif’a Anzani Dian Candra Lestari Dony Setiawan Dwiyanto, Felix Andika Dyah Lestari Eko Pambagyo Setyobudi Fanani, Erianto Faozan Fauzi, Rochmad Felix Andika Dwiyanto Felix Andika Dwiyanto Ferdiansyah, Dodik Septian Ferdinand, Miftakhul Anggita Bima Fitriana Kurniawati Gunawan Gunawan Gunawan Gwinny Tirza Rarastri Hanny Prasetya Hariyadi Hari Putranto Harits Ar Rosyid Hartono, Nickolas Hendrawan, William Hartanto Hidayah Kariima Fithri Hsien-I Lin I Made Wirawan Irvan, Mhd Ismail, Amelia Ritahani Ivatus Sunaifah Kartika Kirana Kevin Raihan Khafit Zaman Kotaro Hirasawa Liliek Rahayu M. Adib Nursasongko Maftuh Ahnan Mahisha Laila Moh. Iqbal Ardiansyah Mohamad Iqbal Mokh Sholihul Hadi Muhammad Arrazy Muhammad Firmansyah muhammad hafiizh, muhammad Muhammad Iqbal Akbar Muhammad Khusairi Osman Muhammad Rifai Muhammad Syauqi Muhammad Usman Mursyit, Mohammad Nafalski, Andrew Ningtyas, Yana Nusantar, Alrizal Akbar Nusantar Akbar Piska Dwi Nurfadila Prana Ihsanuddin, Adika Puji Santoso Pundhi Yuliawati Rasidy, Ahmad Himawari Retno Indah Rokhmawati Ridwan Shalahuddin Rina Dewi Indahsari Riris Andriani Rizal Kholif Nurrohman Ronny Afrian Samsul Arifin Setumin, Samsul Shandy Darmawan Simbolon, Triyanti Siti Sendari Sugiono, Bhima Satria Rizki Sujito Sujito Suyono Suyono Syaad Patmanthara Syafaat, Mokhammad Tri Atmadji Sutikno Utama, Agung Bella Putra Yandhika Surya Akbar Gumilang Yogi Dwi Mahandi Yosi Kristian Zafifatuz Zuhriyah