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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) 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 JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Bumigora Information Technology (BITe) Jurnal Teknik Informatika (JUTIF) Charity : Jurnal Pengabdian Masyarakat Jurnal Pengabdian Masyarakat Indonesia eProceedings of Engineering Jurnal INFOTEL
Sri Suryani Prasetiyowati
Universitas Telkom
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Public Health Social Sciences

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
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%.
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.
Co-Authors Abduh Salam Adhe Akram Azhari Adhitya Aldira Hardy Aditya Andar Rahim Aditya Firman Ihsan Aditya Gumilar Aniq A. Rohmawati Aniq Atiqi Rohmawati Aqilla, Livia Naura arief rahman Arnasli Yahya Asramanggala, Muhammad Sulthon Aufa, Rizki Nabil Azmi Aulia Rahman Chamadani Faisal Amri Christina Natalia Claudia Mei Serin Sitio Damar, Muhammad Dede Tarwidi Derwin Prabangkara Ekaputra, Muhammad Novario Elqi Ashok Erna Sri Sugesti Fairuz, Mitha Putrianty Fatha, Rizkialdy Fathin, Muhammad Ammar Fatri Nurul Inayah Gede Astawa Pradika Gilang Brilians Firmanesha Gusti Aji, Raden Aria Gutama, Soni Andika Hawa, Iqlima Putri Haziq, Muhammad Raffif Hilda Fahlena I Putu Ananda Miarta Utama Ibnu Muzakky M. Noor Indra Kusuma Yoga Indri Octavellia Wulanissa Irfani Adri Maulana Jauzy, Muhammad Abdurrahman Al Juniardi Nur Fadila Lesmana, Aditya Mahadzir, Shuhaimi Maharani, Anak Agung Istri Arinta Mardha Al Nazhfi Ali Mitha Putrianty Fairuz Muh. Kiki Adi Panggayuh Muhammad Damar Muhammad Ghifari Adrian Muhammad Hadyan Baqi Muhammad Ikram Kaer Sinapoy Muhammad Novario Ekaputra Muldani, Muhamad Dika Nanda Ihwani Saputri Naufal Alvin Chandrasa Nenny Lisbeth Minarno Ni Made Dwipadini Puspitarini Nur Fadila, Juniardi Nuraena Ramdani Nurul Fajar Riani Pernanda Arya Bhagaskara S M Pilar Gautama, Hadid Purwanto, Brian Dimas Putra, Ihsanudin Pradana Putri, Pramaishella Ardiani Regita Rachmadania Irmanita Rafika Salis Rahmanda, Rayhan Fadhil Ridha Novia Ridho Isral Essa Rifaldy, Fadil Rizky Fauzi Ramadhani Rizky Yudha Pratama Rizky, Muhammad Zacky Faqia Salis, Rafika Salsabila, Syifa Sinaga, Astria M P Siti Uswah Hasanah Sri Harini Sri Harini Suhendar, Annisya Hayati Winico Fazry Wira Abner Sigalingging Yahya, Arnasli Yuliant Sibaroni Zaidan, Muhammad Naufal