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All Journal International Journal of Advances in Applied Sciences TEKNIK INFORMATIKA Jurnal Simetris Gaung Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal ULTIMA InfoSys Petir Majalah Ilmiah UNIKOM Jurnal Manajemen Informatika Jurnal Teknologi dan Informasi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Aptisi Transactions on Technopreneurship (ATT) JE (Journal of Empowerment) Jurnal Teknologi Informasi dan Pendidikan Jurnal Gema Ngabdi Abdi Laksana : Jurnal Pengabdian Kepada Masyarakat International Journal of Advances in Data and Information Systems International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) International Journal of Research and Applied Technology (INJURATECH) Jurnal Warta Desa (JWD)
R Fenny Syafariani
Universitas Komputer Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Local area network architecture design at Nurul Jalal Islamic Boarding School, North Jakarta Sitanggang, Andri Sahata; Syafariani, R. Fenny; Hasti, Novrini; Sari, Febilita Wulan; Pasya, Dhara
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp123-133

Abstract

A computer network is a telecommunications network that allows computers to communicate with each other by exchanging data. At Nurul Jalal Islamic Boarding School, they have taken advantage of advances in computer network technology, but have not been fully connected properly. Therefore, in this research, a local area network (LAN) architecture that is connected to speedy internet will be built and developed. The design of this network architecture includes designing a connection to the internet speedy network and designing a computer lab architecture that is connected to the network at the Nurul Jalal Islamic Boarding School. This study aims to design the existing technology with the system and add technologies and systems that do not yet exist so that they can be integrated into a computer network connected to the speedy internet network. It is hoped that this research will help teachers and students of Nurul Jalal Islamic Boarding School in exploring information so that it can help effective and efficient learning.
Leveraging A Hybrid Machine Learning Model for Enhanced Cyberbullying Detection Syafariani, Fenny; Lola, Muhamad Safiih; Mutalib, Sharifah Sakinah Syed Abd; Nasir, Wan Nuraini Fahana Wan; Hamid, Abdul Aziz K. Abdul; Zainuddin, Nurul Hila
Aptisi Transactions On Technopreneurship (ATT) Vol 7 No 2 (2025): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v7i2.536

Abstract

Cyberbullying is a form of bullying that occurs through digital technology on various social media platforms. This issue has become critical, particularly when it involves racial statements that can threaten community harmony. Many researchers worldwide are working on solutions for automatic hate speech and cyberaggression detection using different machine learning models. This study aims to introduce a novel hybrid method for detecting cyberbullying, utilizing a combination of Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA), collectively referred to as SVM-LDA. The methodology involves integrating SVM and LDA techniques. The models efficiency was assessed using various metrics, offering a comparative analysis of the hybrid model against individual machine learning models. The results show that the proposed hybrid model achieved 96.1% accuracy and outperformed single machine learning models on the Twitter dataset. The hybrid model also demonstrated robustness in handling imbalanced classes for cyberbullying detection. The proposed SVM-LDA hybrid approach shows significant potential in effectively detecting cyberbullying, even in cases of class imbalance. This model offers a more robust solution compared to traditional single machine learning models in detecting cyberaggression.
Co-Authors A. Nursikuwagus Agus Nursikuwagus Andri Sahata Sitanggang Asnandar Arianto Bakar, Maharani Abu Bondan Rachmat Santoso Dadan Akbar Suryadi Defranata Defranata Dian Pratama Dicky Ginanjar Euis Neni Hayati Evi Feryani Fachlevi, Mohamad Reza Fachlevi, Mohamad Reza Febilita Wulan Sari Gilang Nandapratama Hamid, Abdul Aziz K. Abdul Hayati, Euis Neni Irsalinda, Nursyiva Khaerul Saputra Leonardi Paris Hasugian Lusi Melian Lusi Melian Muhamad Safiih Lola Muhammad Daffa Shidiq Mutalib, Sharifah Sakinah Syed Abd Nasir, Wan Nuraini Fahana Wan Novrini Hasti Pandu Indrakusumah Pasya, Dhara Raeni Dwisanty Ronauli Nadeak Ronauli Nadeak Santoso, Bondan Rachmat Shidiq, Muhammad Daffa Sintya Sukarta Siti Helmyati Sussy Susanti Tatik Rohmawati Tono Hartono Triyanto, Aripin Wartika . Zainuddin, Nurul Hila