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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Resona : Jurnal Ilmiah Pengabdian Masyarakat Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Jurnal Repositor
Sumadi, Fauzi Dwi Setiawan
Universitas Muhammadiyah Malang
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Environmental Science Public Health Social Sciences

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Low Rate DDOS Attack Detection Using KNN On SD-IOT Achmad Irfani Nur Iman; Fauzi Dwi Setiawan Sumadi; Zamah Sari
Jurnal Repositor Vol 5 No 1 (2023): Februari 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v5i1.1520

Abstract

Internet of Things (IoT) devices are highly developed and can be found in everyday life such as watches, smart lights and so on. For now, there are 24 billion IoT devices connected to the internet and the number will continue to grow. The number of IoT devices connected to the internet means there are many security holes that can be exploited by irresponsible people to carry out attacks that have a wide impact on the network. One of the attacks that can be done is Low Rate Attack. To solve these problems, many researchers have created a new paradigm in networking, which is to take advantage of the advantages of Software Defined Network (SDN) to be applied to IoT networks. This study proposes a classification method for detecting low rate attacks using machine learning using the K-Nearest Neighbors (KNN) algorithm. This study also proposes a new feature scheme for the dataset by utilizing the port statistics feature in the SDN environment. The results showed that the KNN classification model applied got good results, namely 92% when evaluating the model applied to the SD-IoT environment. On the other hand, the lowest packet loss is 1.6% and the highest packet loss is 99%, this can be greatly influenced by the hardware resources used because the detection system requires high hardware resources.
Rancang Bangun Document Management System (DMS) Kwartir Cabang Gerakan Pramuka Kota Malang Moch Rizky Wibowo; Ilyas Nuryasin; Fauzi Dwi Setiawan Sumadi
Jurnal Repositor Vol 5 No 2 (2023): Mei 2023 (In Press)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v5i2.1462

Abstract

Penelitian ini berawal dari kendala yang terjadi dalam pendataan yang sering terbengkalai dalam waktu yang lama. Jika data gudep tersebut tidak segera diperbaiki dua sampai tiga tahun mendatang dan hal ini terus berlanjut maka akan menyebabkan data gudep tersebut hilang dan akan menimbulkan permasalahan baru. Oleh karena itu, untuk mengatasi masalah kearsipan tersebutLDocument Management System (DMS) adalah solusi alternatif untuk mengubah bentuk dokumen-dokumen dalam fisik kertas dengan harapan meminimalisir penggunaan kertas atau menjadi bentuk digital sehingga prosesddistribusi dari dokumen yang ada di Kwarcab Kota Malang menjadi lebih cepat dan mudah untuk diterapkan. Hasil penelitian menunjukkan bahwa DMS sangat efisien untuk diterapkan dalam kelola data gudep di tingkat Gerakan Pramuka Kwartir Cabang Kota Malang Sehingga diharapkan fitur ini memberi kemudahan dalam monitoring arsip dari data gudep serta dapat memberikan solusi tentang sebuah kearsipan yang baik. Sehingga dengan sistem ini akan membantu dalam kelola arsip yang mudah diakses dan dimonitoring dari setiap data yang masuk.
Low-rate distributed denial of service attacks detection in software defined network-enabled internet of things using machine learning combined with feature importance Muhammad Abizar; Muhammad Ferry Septian Ihzanor Syahputra; Ahmad Rizky Habibullah; Christian Sri Kusuma Aditya; Fauzi Dwi Setiawan Sumadi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1974-1984

Abstract

One of the main challenges in developing the internet of things (IoT) is the existence of availability problems originated from the low-rate distributed denial of service attacks (LRDDoS). The complexity of IoT makes the LRDDoS hard to detect because the attack flow is performed similarly to the regular traffic. Integration of software defined IoT (SDN-Enabled IoT) is considered an alternative solution for overcoming the specified problem through a single detection point using machine learning approaches. The controller has a resource limitation for implementing the classification process. Therefore, this paper extends the usage of Feature Importance to reduce the data complexity during the model generation process and choose an appropriate feature for generating an efficient classification model. The research results show that the Gaussian Naïve Bayes (GNB) produced the most effective outcome. GNB performed better than the other algorithms because the feature reduction only selected the independent feature, which had no relation to the other features.
Combination of Term Weighting with Class Distribution and Centroid-based Approach for Document Classification Sri Kusuma Aditya, Christian; Sumadi, Fauzi Dwi Setiawan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 4, November 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i4`.1793

Abstract

A text retrieval system requires a method that is able to return a number of documents with high relevance upon user requests. One of the important stages in the text representation process is the weighting process. The use of Term Frequency (TF) considers the number of word occurrences in each document, while Inverse Document Frequency (IDF) considers the wide distribution of words throughout the document collection. However, the TF-IDF weighting cannot represent the distribution of words to documents with many classes or categories. The more unequal the distribution of words in each category, the more important the word features should be. This study developed a new term weighting method where weighting is carried out based on the frequency of occurrence of terms in each class which is integrated with the distribution of centroid-based terms which can minimize intra-cluster similarity and maximize inter-cluster variance. The ICF.TDCB term weighting method has been able to provide the best results in its application to SVM modeling with a dataset of 931 online news documents. The results show that SVM modeling had accuracy of 0.723, outperforming the use of other term weightings such as TF.IDF, ICF & TDCB.
Co-Authors - Syaifuddin Abyan Faishal Reza Achmad Irfani Nur Iman Agung Wahyu Purnadi Agus Eko Minarno Agus Eko Minarno Ahmad Akbar Maulana Ahmad Fahri Jamaluddin Ahmad Rizky Habibullah Akbi, Denar Regata Alrizal Rakhmat Widagdo Amrul Faruq Basuki, Setio Chandranegara, Didih Rizki Christian Sri Kusuma Aditya Diah Risqiwati Edi H. Kalabo Flora Salfa Salsabila Hanung Adi Nugroho Hardianto Wibowo Haris Zulfikar Islam Hariyady Ilham Setiyo Kantomo Irfan, Muhammad Irmawati Feren Kilwalaga Jurdan Wahyu Adi Saputra Lailis Syafa’ah Lucky Nurfiqin Mahar Faiqurahman Mauridhi Hery Purnomo Mirza Maulana Azmi Moch Rizky Wibowo Muhamad Fathul Azis Muhammad Abizar Muhammad Ferry Septian Ihzanor Syahputra Muhammad Nur Ichsan Muhammad Zain Iqbal Muzakki Muhammad Zidan Najmuddin Tsaqib Nur Armita Nuryasin, Ilyas Oxicusa Gugi Housman Said imam Baihaqqi Sri Kusuma Aditya, Christian Syafaah, Lailis Syaifuddin Syaifuddin Syaifuddin Syaifuddin Syaifuddin, Syaifuddin Vera Suryani Wahyuli Dwiki Nanda Yoga Pamungkas Yuda Munarko Yusril Izza Rizqony Zaidah Ibrahim Zamah Sari