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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Computer Engineering and Applications Journal Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Annual Research Seminar Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics 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 Sriwijaya Journal of Informatics and Applications Jurnal Generic
Deris Stiawan
Universitas Sriwijaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Hubungan Prilaku Remaja Berinternet di Inderalaya Reza Firsandaya Malik; Deris Stiawan; Erwin Erwin; Rossi Passarella; sutarno sutarno; Sarmayanta Sembiring; Ahmad Heryanto
Annual Research Seminar (ARS) Vol 1, No 1 (2015)
Publisher : Annual Research Seminar (ARS)

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Abstract

Indralaya known as the City of Students and Education, also has more than 30 boarding school, and 60 senior high school / vocational school spread over Ogan Ilir. Implementation of community service performed in Inderalaya to determine the relationship of the behavior of teenagers surfs the internet and provide knowledge about healthy and safe while surfing an internet. The method of data collection using questionnaires. Number of questionnaires distributed as many as 27 participants from SMAN 1 Inderalaya Utara and Pondok Pesantren Al Ittifaqiyah based on age from 15 to 17 years. Results showed teenagers have the tendency to access the internet every day with a duration of 1-2 hours and mostly done in the bedroom. Applications often they use is social networking. The teens also have the courage to meet with people who are known via online with a percentage of 29.6%.
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

Abstract

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.
The Implementation of Deep Neural Networks Algorithm for Malware Classification Nurul Afifah; Deris Stiawan
Computer Engineering and Applications Journal Vol 8 No 3 (2019)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.253 KB) | DOI: 10.18495/comengapp.v8i3.294

Abstract

Malware is very dangerous while attacked a device system. The device that can be attacked by malware is a Mobile Phone such an Android. Antivirus in the Android device is able to detect malware that has existed but antivirus has not been able to detect new malware that attacks an Android device. In this issue, malware detection techniques are needed that can grouping the files between malware or non-malware (benign) to improve the security system of Android devices. Deep Learning is the proposed method for solving problems in malware detection techniques. Deep Learning algorithm such as Deep Neural Network has succeeded in resolving the malware problem by producing an accuracy rate of 99.42%, precision level 99% and recall 99.4%.
IoT Smart Device for e-Learning Content Sharing on Hybrid Cloud Environment Yazid Idris, Mohd.; Stiawan, Deris; Habibullah, Nik Mohd; Fikri, Abdul Hadi; Abd Rahim, Mohd Rozaini; Dasuki, Massolehin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (697.409 KB) | DOI: 10.11591/eecsi.v4.978

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.552 KB) | DOI: 10.11591/eecsi.v3.1163

Abstract

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.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.552 KB) | DOI: 10.11591/eecsi.v3.1163

Abstract

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.
The Architecture of Indonesian Publication Index: A Major Indonesian Academic Database Imam Much Ibnu Subroto; Tole Sutikno; Deris Stiawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 1: March 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i1.15

Abstract

Journal articles are required all researchers as references to improve the quality of research so that the results are better than existing studies. The presence of many journal indexers that collect articles from many publishers and repositories are very helpful to lecturers and researchers to locate articles in their specific areas of interest. The main issues in the indexing include: (i) the selection and collection process articles data, (ii) the management of indexing based on source and relevance of science (iii) the accuracy and speed of the search process, and (iv) the relationship between the articles each other called citation. The desirable by readers from the indexer is to get relevant and good-quality articles easily and accurately. While the interest of the journal managers is to supply their article which reader preferred then hope many cited to their journals. This is where the position of an indexer to bridge publisher and reader. This paper presents the architecture of Indonesian Publications Index (IPI) as the bridge. This architecture is designed with three layers. The layers are the data collection layer, storage layer, and service layer. The functionality of the first layer is IPI collaboration with publishers, the second layer is the index management system, the third layer is a service to the readers. Service layer built on a variety of applications such as web based applications, mobile applications and e-library.
An Introduction to Journal Phishings and Their Detection Approach Mehdi Dadkhah; Tole Sutikno; Mohammad Davarpanah Jazi; Deris Stiawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.1436

Abstract

Nowadays, the most important risk and challenge in online system are online scam and phishing attacks. Phishing attacks have been always used to steal important information of users. In this kind of scam, attacker direct victim to fake pages using social engineering techniques, then, starts stealing users` important information such as passwords. In order to confronting these attacks, numerous techniques have been invented which have the ability to confront different kinds of these attacks. Our goal in this paper is to introducing new kind of phishing attacks which are not identifiable by techniques and methods which have been invented to confronting phishing attacks. Unlike other kinds of phishing attacks which target all kinds of users, researchers are the victims of these kinds of journal phishing attacks. Finally, we`ll introduce an approach based on classification algorithms to identify these kind of journal phishing attacks and then we`ll check our suggested approach in error rate.
Visualisasi Serangan Brute Force Menggunakan Metode K-Means dan Naive Bayes Sari Sandra; Deris Stiawan; Ahmad Heryanto
Annual Research Seminar (ARS) Vol 2, No 1 (2016)
Publisher : Annual Research Seminar (ARS)

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Abstract

Penelitian ini menyajikan visualisasi dalam bidang two dimensional (2D) untuk mengkategorikan paket ISCX dan DARPA dataset. Paket data akan dibedakan dalam dua kategori yaitu paket data attack dan paket data normal berdasarkan pattern serangan brute force. Serangan brute force melakukan penyerangan pada beberapa layanan protokol seperti secure shell (SSH) dan telecommunication network (Telnet). Pada ISCX dataset serangan brute force terjadi pada layanan SSH , sedangkan DARPA dataset terjadi pada layanan TELNET.Metode K-Means dan metode Naïve Bayes diimplementasikan pada penelitian ini untuk mendapatkan hasil pengkategorian yang efektif Hasil akhir dari penelitian menunjukkan metode yang digunakan mendapatkan hasil yang baik dalam hal accuracy dengan mengurangi false alarm yang terjadi.
Review of the machine learning methods in the classification of phishing attack John Arthur Jupin; Tole Sutikno; Mohd Arfian Ismail; Mohd Saberi Mohamad; Shahreen Kasim; Deris Stiawan
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (723.905 KB) | DOI: 10.11591/eei.v8i4.1344

Abstract

The development of computer networks today has increased rapidly. This can be seen based on the trend of computer users around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether for work purposes or access to social media accounts. However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. This problem will allow hackers to hack and commit network attacks. This is very dangerous, especially for Internet users because hackers can steal confidential information such as bank login account or social media login account. The attacks that can be made include phishing attacks. The goal of this study is to review the types of phishing attacks and current methods used in preventing them. Based on the literature, the machine learning method is widely used to prevent phishing attacks. There are several algorithms that can be used in the machine learning method to prevent these attacks. This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail.
Co-Authors Abd Rahim, Mohd Rozaini Abdul Hadi Fikri Abdul Hanan Abdullah Abdul Harris Adi Sutrisman Aditya Putra Perdana Prasetyo Aditya Putra Perdana Prasetyo Adji Pratomo Agung Juli Anda Agus Eko Minarno Ahmad Fali Oklilas Ahmad Firdaus Ahmad Heryanto Ahmad Heryanto Ahmad Heryanto Ahmad Heryanto, Ahmad Ahmad Zarkasi Albertus Edward Mintaria Ali Bardadi Bedine Kerim Bedine Kerim Bhakti Yudho Suprapto Bhakti Yudho Suprapto Darmawijoyo, Darmawijoyo Dasuki, Massolehin Desak Putu Dewi Kasih Dewi Bunga Dian Palupi Rini Eko Arip Winanto Endang Lestari Ruskan Ermatita Ermatita Erwin, Erwin Fachrudin Abdau Ferdiansyah Ferdiansyah Fikri, Abdul Hadi Firdaus Firdaus Firdaus, Firdaus Firsandaya Malik, Reza Habibullah, Nik Mohd Harris, Abdul Huda Ubaya Huda Ubaya I Gede Yusa Idris, Mohd. Yazid Idris, Mohd. Yazid Imam Much Ibnu Subroto John Arthur Jupin Kurniabudi, Kurniabudi Lelyzar Siregar Lina Handayani M. Miftakul Amin M. Ridwan Zalbina Majzoob K. Omer Massolehin Dasuki Mehdi Dadkhah Mintaria, Albertus Edward Mohamed S. Adrees Mohammad Davarpanah Jazi Mohammad Sulkhan Nurfatih 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 Muhammad Afif Muhammad Fermi Pasha Munawar A Riyadi Munawar Agus Riyadi Ni Ketut Supasti Dharmawan Nik Mohd Habibullah Nur Sholihah Zaini Osama E. Sheta Osvari Arsalan Prabowo, Christian Purnama, Benni Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Rahmat Budiarto Raja Zahilah Md Radzi Reza Firsandaya Malik Riyadi, Munawar A Rizki Kurniati Rossi Passarella Samsuryadi Samsuryadi Saparudin Saparudin Saparudin, Saparudin Sari Sandra Sarmayanta Sembiring Sasut A Valianta Sasut Analar Valianta Shahreen Kasim Sharipuddin Sharipuddin Sharipuddin Sharipuddin Sharipuddin Sharipuddin Sharipuddin Sharipuddin Sharipuddin, Sharipuddin Siti Hajar Othman Siti Nurmaini Sri Arttini Dwi Prasetyawati Sri Desy Siswanti Susanto Susanto Susanto Susanto Susanto, Susanto Sutarno Sutarno Syamsul Arifin, M. Agus tasmi salim Tasmi Salim Tole Sutikno Wan Isni Sofiah Wan Din Yaya Sudarya Triana Yazid Idris, Mohd. Yesi Novaria Kunang Yoga Yuniadi Yundari, Yundari