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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Dinamisia: Jurnal Pengabdian Kepada Masyarakat Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Linguistik Komputasional Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) Jurnal Bumigora Information Technology (BITe) Jurnal Teknik Informatika (JUTIF) JINAV: Journal of Information and Visualization Jurnal Pengabdian Masyarakat Indonesia Journal La Multiapp eProceedings of Engineering Eduvest - Journal of Universal Studies Jurnal INFOTEL
Yuliant Sibaroni
Telkom University
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Neuroscience Public Health Social Sciences Other

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
Multi-aspect Sentiment Analysis of Tiktok Application Usage Using FasText Feature Expansion and CNN Method Rifki Alfian Abdi Malik; Yuliant Sibaroni
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2033

Abstract

Among the many social media platforms that have emerged, TikTok is a platform that has the most significant number of subscribers compared to other platforms. However, not all reviews given by TikTok users are good reviews and reviews are often found with slang and not all reviews have real meaning, therefore sentiment analysis is needed for these problems. These reviews will later be analyzed for sentiment according to predetermined aspects, namely feature aspects, business aspects, and content aspects based on reviews written on the Google Play Store, using data crawling techniques and will pass the preprocessing and weighting stages. The weighting method used is Term Frequency-Inverse Document Frequency (TF-IDF). Then, the sentiment analysis process will use the Convolutional Neural Network (CNN) method, and feature expansion will be carried out to determine what words are interrelated with certain words. The purpose of this research is to analyze sentiment using Convolutional Neural Network and fastText feature expansion. The highest accuracy result is 87.74%.
Performance Analysis of Air Pollution Classification Prediction Map with Decision Tree and ANN Rizky Fauzi Ramadhani; Sri Suryani Prasetiyowati; Yuliant Sibaroni
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2117

Abstract

Jakarta is a city in Indonesia that has a high population density that must pay attention to its health condition. Good air quality provides positive benefits to support public health so that they can be more productive at work and create fresh and healthy air. This study uses Machine Learning to classify air based on certain attributes. Then, the development of a prediction model based on time data is designed to produce a predictive map of air pollution in Jakarta area for the next 3 years. The methods applied are Decision Tree and Artificial Neural Networks. As a result, the Decision Tree and Artificial Neural Network models show very good accuracy for predictions from 2024 to 2026. The Decision Tree and Artificial Neural Network models get an accuracy of 98% and 94%. In 2025 the Decision Tree and Artificial Neural Network models get 99% and 93% accuracy. In 2026 the Decision Tree and Artificial Neural Network models get an accuracy of 94% and 93% which can be seen from the Decision Tree model which is superior to the Artificial Neural Network with a difference of 1 - 6%.
Radicalism Speech Detection in Indonesia on Twitter Using Backpropagation Neural Network Method Muhammad Rajih Abiyyu Musa; Yuliant Sibaroni
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2146

Abstract

In this modern era, many people use social media easily and freely. One of the social media used is Twitter. The reason people use Twitter is that they can express their opinion freely. However, this freedom does not always have a positive impact on other Twitter users. One of the negative impacts for users is that they can spread radical content. Therefore, this research aims to detect whether a tweet contains radical elements or not using the backpropagation neural network method. The process is carried out by taking data on Twitter, after which the preprocessing process is carried out. Then the data is processed using imbalanced handling, where the data is divided into oversampling and undersampling data. After the data is divided, the next process is to do stopword and then look for accuracy by comparing different epoch values, namely 100, 150, 200, and 250. The best epoch value obtained is 200, with a final accuracy result of 86%.
Identify User Behavior Based on The Type of Tweet on Twitter Platform Using Gaussian Mixture Model Clustering Ridha Novia; Sri Suryani Prasetyowati; Yuliant Sibaroni
Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i4.2208

Abstract

Social media has now become a place for social interaction to exchange information about business, politic, and many other. Twitter is one of the social media platforms that provides services for their users to share information and opinions on certain topics. The topic that will be discussed in this study is about politic by collecting tweet data about the student demonstration movement and SemuaBisaKena campaign. By using the word weighting method TF-IDF Vectorizer and Gaussian Mixture Model Clustering, it is possible to identify whether the user behavior is positive (support) or negative (blasphemy). To achieve the final result, there are several stages that must be passed. Such as data preprocessing, feature extraction using TF-IDF Vectorizer, Gaussian Mixture Model Clustering algorithm and data visualization. The results are there is 1 cluster identified as positive behavior and there are 2 clusters identified as negative behavior.
Clustering Content Types and User Motivation Using DBSCAN on Twitter Made Mita Wikantari; Yuliant Sibaroni; Aditya Firman Ihsan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3750

Abstract

We are currently in an era full of information and communication technology. One of the communication media used is Twitter. Twitter is a microblogging service that is used by its users to express their thoughts on a topic called a tweet. Tweets that are posted can be either positive tweets or negative tweets. One of the topics that is currently being discussed by Twitter users is Anies Baswedan as a 2024 Indonesian Presidential Candidate. Many people have tweeted this but it is not known how many users support or reject Anies Baswedan to run as a 2024 Indonesian presidential candidate. To assist the analysis, use the method clustering namely algorithm (Density-Based Spatial Clustering of Application with Noise). DBSCAN has the advantage of being able to detect data that is not included in a cluster and will be considered noise. This can improve the accuracy of the grouping because the data in the cluster will be cleaner. The TF-IDF Vectorizer is used to make it easier for programs to manage data because it can turn sentences into vectors that can be processed by the algorithm. To determine the evaluation of the program, the silhouette score method will be used. The results of calculating the silhouette score show a value of 0.29 with the formation of 3 clusters. Then an analysis is carried out based on the top words from each cluster and it can be identified that cluster 0 has a positive category supporting Anies Baswedan to run for the 2024 Presidential Candidate and cluster 1 has a negative category that does not support Anies Baswedan not advancing for the 2024 Presidential Candidate.
Clustering Content Types and User Roles Based on Tweet Text Using K-Medoids Partitioning Based Raisa Benaya; Yuliant Sibaroni; Aditya Firman Ihsan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3751

Abstract

In this modern era, the spread of information occurs rapidly through social media. One of the channels for disseminating information is through the Twitter platform. Many Twitter users respond to existing content with positive, negative and neutral responses. One of the hot content to respond to is political content. This content is currently being discussed considering the approaching election of the 2024 Presidential Candidate of the Republic of Indonesia. One of the candidate pairs discussed was Anies Baswedan. With so many responses from Twitter users, it will be difficult to track whether users support Anies Baswedan to run as a presidential candidate due to the large number of responses. This study aims to determine the response of twitter users to the advancement of Anies Baswedan as a presidential candidate. The method used in this study is the K-Medoids Partitioning-Based algorithm based on twitter user text. This algorithm was chosen because it is easy to implement considering the basis of K-Medoids development is the K-Means algorithm but the K-Medoids algorithm can overcome the shortcomings of the K-Means algorithm which is sensitive to outliners. The evaluation will be done using Silhouette Score which produces a value of 0.35 with the number of clusters is 2. Then an analysis of each cluster is carried out by looking at the words in the cluster. As a result, from the two clusters formed, both clusters contain positive content and show that Twitter users support Anies Baswedan to run as a 2024 presidential candidate.
Co-Authors Abduh Salam Adhe Akram Azhari Aditya Andar Rahim Aditya Firman Ihsan Aditya Gumilar Aditya Iftikar Riaddy Adiwijaya Agi Maulana Al Ghazali, Nabiel Muhammad Alfauzan, Muhammad Fikri Alya, Hasna Rafida Andrew Wilson Angger Saputra, Revelin Annisa Aditsania Apriani, Iklima Aqilla, Livia Naura Ardana, Aulia Riefqi Arista, Dufha Arminta, Adisaputra Nur Arya Pratama Anugerah Asramanggala, Muhammad Sulthon Atikah, Balqis Sayyidahtul Attala Rafid Abelard Aufa, Rizki Nabil Aulia Rayhan Syaifullah Aurora Az Zahra, Elita Azmi Aulia Rahman Bunga Sari Chamadani Faisal Amri Chindy Amalia Claudia Mei Serin Sitio Damar, Muhammad Damarsari Cahyo Wilogo Delvanita Sri Wahyuni Derwin Prabangkara Desianto Abdillah Devi Ayu Peramesti Dhina Nur Fitriana Dhina Nur Fitriana Diyas Puspandari Ekaputra, Muhammad Novario Ellisa Ratna Dewi Ellisa Ratna Dewi Elqi Ashok Erwin Budi Setiawan Fadhilah Nadia Puteri Fadli Fauzi Zain Fairuz, Mitha Putrianty Faiza Aulia Rahma Putra Farizi, Azziz Fachry Al Fatha, Rizkialdy Fathin, Muhammad Ammar Fatihah Rahmadayana Fatri Nurul Inayah Fauzaan Rakan Tama Feby Ali Dzuhri Fery Ardiansyah Effendi Ferzi Samal Yerzi Fhira Nhita Fitriansyah, Alam Rizki Fitriyani Fitriyani F. Fitriyani Fitriyani Fitriyani Fitriyani Gilang Brilians Firmanesha Gusti Aji, Raden Aria Gutama, Soni Andika Hanif, Ibrahim Hanurogo, Tetuko Muhammad Hanvito Michael Lee Hawa, Iqlima Putri Haziq, Muhammad Raffif I Gusti Ayu Putu Sintha Deviya Yuliani I Putu Ananda Miarta Utama Ibnu Muzakky M. Noor Indra Kusuma Yoga Indwiarti irbah salsabila Irfani Adri Maulana Irma Palupi Islamanda, Muhammad Dinan Izzan Faikar Ramadhy Izzatul Ummah Janu Akrama Wardhana Jauzy, Muhammad Abdurrahman Al Kemas Muslim Lhaksmana Kinan Salaatsa, Titan Ku Muhammad Naim Ku Khalif Lanny Septiani Laura Imanuela Mustamu Lesmana, Aditya Lintang Aryasatya Lisbeth Evalina Siahaan Made Mita Wikantari Mahadzir, Shuhaimi Maharani, Anak Agung Istri Arinta Mahmud Imrona Maulida , Anandita Prakarsa Mitha Putrianty Fairuz Muhamad Agung Nulhakim Muhammad Arif Kurniawan Muhammad Damar Muhammad Ghifari Adrian Muhammad Hadyan Baqi Muhammad Ikram Kaer Sinapoy Muhammad Kiko Aulia Reiki Muhammad Novario Ekaputra Muhammad Rajih Abiyyu Musa Muhammad Reza Adi Nugraha Muldani, Muhamad Dika Nanda Ihwani Saputri Naufal Alvin Chandrasa Ni Made Dwipadini Puspitarini Niken Dwi Wahyu Cahyani Novitasari, Ariqoh Nuraena Ramdani Okky Brillian Hibrianto Okky Brillian Hibrianto Pernanda Arya Bhagaskara S M Pilar Gautama, Hadid Prasetiyowati, Sri Prasetyo, Sri Suryani Prasetyowati, Sri Sulyani Prawiro Weninggalih Priyan Fadhil Supriyadi Purwanto, Brian Dimas Puspandari, Dyas Putra, Daffa Fadhilah Putra, Ihsanudin Pradana Putra, Maswan Pratama Putri, Dinda Rahma Putri, Pramaishella Ardiani Regita Rachmadania Irmanita Rafik Khairul Amin Rafika Salis Rahmanda, Rayhan Fadhil Raisa Benaya Revi Chandra Riana Rian Febrian Umbara Rian Putra Mantovani Ridha Novia Ridho Isral Essa Ridho, Fahrul Raykhan Rifaldy, Fadil Rifki Alfian Abdi Malik Riski Hamonangan Simanjuntak Rizki Annas Sholehat Rizky Fauzi Ramadhani Rizky Yudha Pratama Rizky, Muhammad Zacky Faqia Salis, Rafika Salsabila, Syifa Saniyah Nabila Fikriyah Saragih, Pujiaty Rezeki Satyananda, Karuna Dewa Septian Nugraha Kudrat Septian Nugraha Kudrat Serly Setyani Shyahrin, Mega Vebika Sinaga, Astria M P Siti Inayah Putri Siti Uswah Hasanah Sri Suryani Prasetiyowati Sri Suryani Prasetyowati Sri Suryani Sri Suryani Sri Utami Sujadi, Cika Carissa Suryani Prasetyowati, Sri Syarif, Rizky Ahsan Umulhoir, Nida Varissa Azis, Diva Azty Viny Gilang Ramadhan Vitria Anggraeni WAHYUDI, DIKI Widya Pratiwi Ali Winico Fazry Wira Abner Sigalingging Zaenudin, Muhammad Faisal Zaidan, Muhammad Naufal Zain, Fadli Fauzi ZK Abdurahman Baizal