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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Computing, Engineering, and Design Journal of Applied Data Sciences Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Community Services: Sustainability and Empowerment CSRID
Teddy Mantoro
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Arts Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : JOIN (Jurnal Online Informatika)

 1 
Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods Jelita Asian; Moneyta Dholah Rosita; Teddy Mantoro
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.900

Abstract

Sexual harassment is defined as giving sexual attention both verbally, either in speech or writing, and physically to victims who are predominantly women, On July 13, 2022, there was a tweet featuring a video of sexual harassment that made it trend in various countries. The video irritated Twitter users and made various comments resulting in various sentiments that can be analyzed using sentiment analysis. The purpose of this study is to see what the public thinks about the sexual harassment case of Brazilian anesthesiologist. Besides the sentiment analysis, another aim of this study is to see how objective are those sentiments based on their polarity. This study uses a comparison of two methods in sentiment analysis, namely Multi-Layer Perceptron Classifier and Random Forest, and labeling automatically using TextBlob.  This results in 94.44% accuracy, 94.44% precision, 92% recall and 93% f1_score. For MLP Classifier and accuracy 96.42%, precision 94.44%, recall 96.66% and f1_score 95.56% for Random Forest. Sentiment polarity score from the TextBlob is -0.5 and subjectivity is 0.4 which indicates that most statements are negative and subjective score is 0.4, which means those sentiments are subjective in nature.
Social Network Analysis: Identification of Communication and Information Dissemination (Case Study of Holywings) Umar Aditiawarman; Mega Lumbia; Teddy Mantoro; Adamu Abubakar Ibrahim
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.911

Abstract

Social media especially Twitter has been used by corporation or organization as an effective tool to interact and communicate with the consumers. Holywings is one of the popular restaurants in Indonesia that use social media as a tool to promote and disseminate information regarding their products and services. However, one of their promotional items has gone viral and invited public protests which turned into a trending topic on Twitter for a couple of weeks. Holywings allegedly improperly promoted their products by using the most honorable names, “Muhammad” and “Maria”. Social network analysis of Twitter data is conducted to identify and examine information circulating among the users, which leads to wider public attention and law enforcement. In this study, we focused on the conversation about Holywings on Twitter from 24 June to 31 July 2022. The analysis was carried out using Python to retrieve data and Gephi software to visualize the interactions and the intensity of the network group in viewing the spread of information. The findings reveal the centrality account that caused the news to go viral are the CNN Indonesia (@CNNIndonesia) news media account and Haris Pertama (@knpiharis), with a centrality of 0.161 and 0.282, respectively. There are also 121 groups involved in the conversation with modularity of 0.821.
Sentiment Analysis for the Brazilian Anesthesiologist Using Multi-Layer Perceptron Classifier and Random Forest Methods Asian, Jelita; Dholah Rosita, Moneyta; Mantoro, Teddy
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.900

Abstract

Sexual harassment is defined as giving sexual attention both verbally, either in speech or writing, and physically to victims who are predominantly women, On July 13, 2022, there was a tweet featuring a video of sexual harassment that made it trend in various countries. The video irritated Twitter users and made various comments resulting in various sentiments that can be analyzed using sentiment analysis. The purpose of this study is to see what the public thinks about the sexual harassment case of Brazilian anesthesiologist. Besides the sentiment analysis, another aim of this study is to see how objective are those sentiments based on their polarity. This study uses a comparison of two methods in sentiment analysis, namely Multi-Layer Perceptron Classifier and Random Forest, and labeling automatically using TextBlob.  This results in 94.44% accuracy, 94.44% precision, 92% recall and 93% f1_score. For MLP Classifier and accuracy 96.42%, precision 94.44%, recall 96.66% and f1_score 95.56% for Random Forest. Sentiment polarity score from the TextBlob is -0.5 and subjectivity is 0.4 which indicates that most statements are negative and subjective score is 0.4, which means those sentiments are subjective in nature.
Social Network Analysis: Identification of Communication and Information Dissemination (Case Study of Holywings) Aditiawarman, Umar; Lumbia, Mega; Mantoro, Teddy; Ibrahim, Adamu Abubakar
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.911

Abstract

Social media especially Twitter has been used by corporation or organization as an effective tool to interact and communicate with the consumers. Holywings is one of the popular restaurants in Indonesia that use social media as a tool to promote and disseminate information regarding their products and services. However, one of their promotional items has gone viral and invited public protests which turned into a trending topic on Twitter for a couple of weeks. Holywings allegedly improperly promoted their products by using the most honorable names, “Muhammad” and “Maria”. Social network analysis of Twitter data is conducted to identify and examine information circulating among the users, which leads to wider public attention and law enforcement. In this study, we focused on the conversation about Holywings on Twitter from 24 June to 31 July 2022. The analysis was carried out using Python to retrieve data and Gephi software to visualize the interactions and the intensity of the network group in viewing the spread of information. The findings reveal the centrality account that caused the news to go viral are the CNN Indonesia (@CNNIndonesia) news media account and Haris Pertama (@knpiharis), with a centrality of 0.161 and 0.282, respectively. There are also 121 groups involved in the conversation with modularity of 0.821.
Co-Authors Abdul Rahman Wijaya Putra Abdullah Alkalbani Achmad Benny Mutiara Achmad Farid Wadjdi Adamu Abubakar Ibrahim Adi Putra Andriyandi Agung Nugroho Akeem Olowolayemo Alam, Sirojul Alfian Dody Andri Zakariya Andri Zakariya Anggy Pradiftha Anggy Pradiftha Junfithrana Aris Gunaryati Aris Gunaryati, Aris Arisantoso Arisantoso Ben Rahman Benrahman Dholah Rosita, Moneyta Dian Sa’adillah Maylawati Dian Sa’adillah Maylawati Dimas Erlangga Edi Irawan Effendi, Nicholas Lasca Ernastuti Ernastuti Hamdan Sugilar Haris Al Qodri Maarif Haris Al Qodri Maarif I Made Alan Priyatna Ibrahim, Adamu Abubakar Jelita Asean Jelita Asian Lumbia, Mega Lutfil Khakim Media A. Ayu Media Anugerah Ayu, Media Anugerah Mega Lumbia Mohammad Iwan Wahyuddin Moneyta Dholah Rosita Muchlis Nurseno Muhamad Rausyan Fikri Muhammad Agni Catur Bhakti Muhammad Ali Ramdhani Muhammad Anton Permana Nugroho, Agung Prihandoko Prihandoko Putra, Abdul Rahman Wijaya Raffliansyah, Alfarizky Esah Rahman, Ben Rimbawa, H.A Danang Saputro, Joko W. Septi Andryana Septya Egho Pratama Sony Surya Wijaya Tarigan, William Hazkel Umar Aditiawarman Wahyuddin, Mohammad Iwan Wahyudin Darmalaksana Wandy Wandy