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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) ComEngApp : Computer Engineering and Applications Journal Jurnal Pendidikan Karakter TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Bulletin of Electrical Engineering and Informatics Annual Research Seminar Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Information Systems and Informatics Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Sriwijaya Journal of Informatics and Applications Jurnal Generic Journal of Applied Data Sciences Journal of Innovation and Research in Primary Education Jurnal Indonesia Sosial Teknologi Jurnal Pendidikan Indonesia (Japendi)

Deris Stiawan

Universitas Sriwijaya

Author-ID : 386367

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

Published : 72 Documents Claim Missing Document

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Articles

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IoT Smart Device for e-Learning Content Sharing on Hybrid Cloud Environment Mohd. Yazid Idris; Deris Stiawan; Nik Mohd Habibullah; Abdul Hadi Fikri; Mohd Rozaini Abd Rahim; Massolehin Dasuki
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Centralized e-Learning technology has dominated the learning ecosystem that brings a lot of potential usage on media rich learning materials. However, the centralized architecture has their own constraint to support large number of users for accessing large size of learning contents. On the other hand, Content Delivery Network (CDN) solution which relies on distributed architecture provides an alternative solution to eliminate bottleneck access. Although CDN is an effective solution, the implementation of technology is expensive and has less impact for student who lives in limited or non-existence internet access in geographical area. In this paper, we introduce an IoT smart device to provide e-Learning access for content sharing on hybrid cloud environment with distributed peer-to- peer communication solution for data synchronization and updates. The IoT smart device acts as an intermediate device between user and cloud services, and provides content sharing solution without fully depending on the cloud server.

IAES International Conference on Electrical Engineering, Computer Science and Informatics Munawar A Riyadi; Sri Arttini Dwi Prasetyowati; Tole Sutikno; Deris Stiawan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

The 3rd International Conference of Electrical Engineering, Computer Science and Informatics (EECSI) 2016 was held in Semarang, Indonesia from 23th to 25thNovember, 2016. The conference was organized by Universitas Islam Sultan Agung as the host in collaboration with Universitas Diponegoro, Universitas Ahmad Dahlan and Universitas Sriwijaya, and with full technical support from IAES Indonesia Section. Authors and participants from 10 countries made the conference truly international in scope. Participants have delivered their talks of valuable research outputs that vary from many fields of electrical engineering (power electronics, telecommunication, electronics engineering, control system and signal processing) to the field of computer science and informatics. These wide range of topics have colorized this conference.This volume of IOP Conference Series: Materials Science and Engineering contains selected articles from those presented in the conference. After presentation, the revised papers were peer reviewed by fellow reviewers to ensure the quality of published materials. Finally, Editors decided to select and publish as many as 49 papers. It is hoped that the presented papers can offer more insight towards broad audience.On behalf of Editors, we appreciate enormous work of all staffs and reviewers in the preparation of this volume. We would like to express our sincere thanks to all authors and presenters for their valuable contributions. We hope to see you again in the next event of EECSI 2017 which will be held in Yogyakarta, Indonesia, next year.

Information Framework of Pervasive Real Time Monitoring System: Case of Peat Land Forest Fires and Air Quality in South Sumatera, Indonesia Siti Nurmaini; Reza Firsandaya Malik; Deris Stiawan; Firdaus Firdaus; Saparudin Saparudin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

The information framework aims to holistically address the problems and issues posed by unwanted peat and land fires within the context of the natural environment and socio-economic systems. Informed decisions on planning and allocation of resources can only be made by understanding the landscape. Therefore, information on fire history and air quality impacts must be collected for future analysis. This paper proposes strategic framework based on technology approach with data fusion strategy to produce the data analysis about peat land fires and air quality management in in South Sumatera. The research framework should use the knowledge, experience and data from the previous fire seasons to review, improve and refine the strategies and monitor their effectiveness for the next fire season. Communicating effectively with communities and the public and private sectors in remote and rural landscapes is important, by using smartphones and mobile applications. Tools such as one-stop information based on web applications, to obtain information such as early warning to send and receive fire alerts, could be developed and promoted so that all stakeholders can share important information with each other.

IoT Botnet Malware Classification Using Weka Tool and Scikit-learn Machine Learning Susanto Susanto; Deris Stiawan; M. Agus Syamsul Arifin; Mohd. Yazid Idris; Rahmat Budiarto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2080

Botnet is one of the threats to internet network security-Botmaster in carrying out attacks on the network by relying on communication on network traffic. Internet of Things (IoT) network infrastructure consists of devices that are inexpensive, low-power, always-on, always connected to the network, and are inconspicuous and have ubiquity and inconspicuousness characteristics so that these characteristics make IoT devices an attractive target for botnet malware attacks. In identifying whether packet traffic is a malware attack or not, one can use machine learning classification methods. By using Weka and Scikit-learn analysis tools machine learning, this paper implements four machine learning algorithms, i.e.: AdaBoost, Decision Tree, Random Forest, and Naïve Bayes. Then experiments are conducted to measure the performance of the four algorithms in terms of accuracy, execution time, and false positive rate (FPR). Experiment results show that the Weka tool provides more accurate and efficient classification methods. However, in false positive rate, the use of Scikit-learn provides better results.

Features Extraction on IoT Intrusion Detection System Using Principal Components Analysis (PCA) Sharipuddin Sharipuddin; Benni Purnama; Kurniabudi Kurniabudi; Eko Arip Winanto; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Rahmat Budiarto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2098

There are several ways to increase detection accuracy result on the intrusion detection systems (IDS), one way is feature extraction. The existing original features are filtered and then converted into features with lower dimension. This paper uses the Principal Components Analysis (PCA) for features extraction on intrusion detection system with the aim to improve the accuracy and precision of the detection. The impact of features extraction to attack detection was examined. Experiments on a network traffic dataset created from an Internet of Thing (IoT) testbed network topology were conducted and the results show that the accuracy of the detection reaches 100 percent.

Improving the Anomaly Detection by Combining PSO Search Methods and J48 Algorithm Kurniabudi Kurniabudi; Abdul Harris; Albertus Edward Mintaria; Darmawijoyo Hanapi; Deris Stiawan; Mohd. Yazid Idris; Rahmat Budiarto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2099

The feature selection techniques are used to find the most important and relevant features in a dataset. Therefore, in this study feature selection technique was used to improve the performance of Anomaly Detection. Many feature selection techniques have been developed and implemented on the NSL-KDD dataset. However, with the rapid growth of traffic on a network where more applications, devices, and protocols participate, the traffic data is complex and heterogeneous contribute to security issues. This makes the NSL-KDD dataset no longer reliable for it. The detection model must also be able to recognize the type of novel attack on complex network datasets. So, a robust analysis technique for a more complex and larger dataset is required, to overcome the increase of security issues in a big data network. This study proposes particle swarm optimization (PSO) Search methods as a feature selection method. As contribute to feature analysis knowledge, In the experiment a combination of particle swarm optimization (PSO) Search methods with other search methods are examined. To overcome the limitation NSL-KDD dataset, in the experiments the CICIDS2017 dataset used. To validate the selected features from the proposed technique J48 classification algorithm used in this study. The detection performance of the combination PSO Search method with J48 examined and compare with other feature selection and previous study. The proposed technique successfully finds the important features of the dataset, which improve detection performance with 99.89% accuracy. Compared with the previous study the proposed technique has better accuracy, TPR, and FPR.

Co-Authors Abd Rahim, Mohd Rozaini Abdiansah, Abdiansah Abdul Hadi Fikri Abdul Hanan Abdullah Abdul Harris Adi Hermansyah, Adi Adi Sutrisman Aditya Putra Perdana Prasetyo Aditya Putra Perdana Prasetyo Adji Pratomo Agung Juli Anda Agus Eko Minarno Ahmad Fali Oklilas Ahmad Firdaus Ahmad Ghiffari Ahmad Heryanto Ahmad Heryanto Ahmad Heryanto Ahmad Heryanto, Ahmad Ahmad Zarkasi Ahmad Zarkasi Albertus Edward Mintaria Ali Bardadi Ali Firdaus Alshaflut, Ahmed Anto Saputra, Iwan Pahendra Bedine Kerim Bedine Kerim Bhakti Yudho Suprapto Bhakti Yudho Suprapto Bhakti Yudho Suprapto Bin Idris, Mohd Yazid Cahyani, Nyimas Sabilina Darmawijoyo, Darmawijoyo Dasuki, Massolehin Desak Putu Dewi Kasih Dewi Bunga Dian Palupi Rini Dwi Budi Santoso Edi Surya Negara Eko Arip Winanto Endang Lestari Ruskan Ermatita - Erwin, Erwin Fachrudin Abdau Fakhrurroja, Hanif Ferdiansyah Ferdiansyah Fikri, Abdul Hadi Firdaus Firdaus Firdaus, Firdaus Firnando, Rici Firsandaya Malik, Reza Gonewaje gonewaje Habibullah, Nik Mohd Hadipurnawan Satria Harris, Abdul Hermanto, Dedy Heru Saputra Huda Ubaya Huda Ubaya Huda Ubaya I Gede Yusa Idris, Mohd. Yazid Idris, Mohd. Yazid Imam Much Ibnu Subroto Iswari, Rosada Dwi John Arthur Jupin Juli Rejito Kemahyanto Exaudi Kurniabudi, Kurniabudi Latius Hermawan Lelyzar Siregar Lina Handayani M. Miftakul Amin M. Ridwan Zalbina Majzoob K. Omer Makmum Raharjo Mardhiyah, Sayang Ajeng Marisya Pratiwi Marita, Raini Massolehin Dasuki Mehdi Dadkhah Meilinda Meilinda Meilinda, Meilinda Mintaria, Albertus Edward Mohamed S. Adrees Mohamed Shenify Mohammad Davarpanah Jazi Mohammed Y. Alzahrani Mohd Arfian Ismail Mohd Azam Osman Mohd Faizal Ab Razak Mohd Rozaini Abd Rahim Mohd Saberi Mohamad Mohd Yazid bin Idris Mohd Yazid Bin Idris Mohd Yazid Idris Mohd Yazid Idris Mohd. Yazid Idris Mohd. Yazid Idris Mohd. Yazid Idris Muhammad Afif Muhammad Fahmi MUHAMMAD FAHMI Muhammad Fermi Pasha Muhammad Qurhanul Rizqie Muhammad Sulkhan Nurfatih Munawar A Riyadi Munawar Agus Riyadi Naufal Semendawai, Jaka Negara, Edi Surya Ni Ketut Supasti Dharmawan Nik Mohd Habibullah Nur Sholihah Zaini Nuzulastri, Sari Osama E. Sheta Osman, Mohd Azam Osvari Arsalan Pahendra, Iwan Permana, Dendi Renaldo Pertiwi, Hanna Prabowo, Christian Purnama, Benni Putra Perdana Prasetyo, Aditya Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Raja Zahilah Md Radzi Ramayanti, Indri Ramayanti, Indri Reza Firsandaya Malik Reza Maulana Riyadi, Munawar A Rizki Kurniati Rizma Adlia Syakurah Rizqie, Muhammad Qurhanul Rossi Passarella Samsuryadi Samsuryadi Saparudin Saparudin Saparudin, Saparudin Saputra, Muhammad Ajran Sari Sandra Sarmayanta Sembiring Sarmayanta Sembiring Sasut A Valianta Sasut Analar Valianta Semendawai, Jaka Naufal Shahreen Kasim Sharipuddin, Sharipuddin Sidabutar, Alex Onesimus Siti Hajar Othman Siti Nurmaini Sri Arttini Dwi Prasetyawati Sri Desy Siswanti Susanto Susanto Susanto Susanto Susanto, Susanto Sutarno Sutarno Syakurah, Rizma Adlia Syamsul Arifin, M. Agus tasmi salim Tasmi Salim Tole Sutikno Wan Isni Sofiah Wan Din Yaya Sudarya Triana Yazid Idris, Mohd. Yazid Idris, Mohd. Yesi Novaria Kunang Yoga Yuniadi Yudho Suprapto, Bhakti Yundari, Yundari Zulhipni Reno Saputra Els

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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics