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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science 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

Author-ID : 1478581

Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Environmental Science Public Health Social Sciences

Published : 34 Documents Claim Missing Document

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Keystroke Dynamic Authentication Using Combined MHR (Mean of HornerÃ¢Â€Â™s Rules) and Standard Deviation Chandranegara, Didih Rizki; Sumadi, Fauzi Dwi Setiawan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 1, February 2019
Publisher : Universitas Muhammadiyah Malang

Keystroke Dynamic Authentication used a behavior to authenticate the user and one of biometric authentication. The behavior used a typing speed a character on the keyboard and every user had a unique behavior in typing. To improve classification between user and attacker of Keystroke Dynamic Authentication in this research, we proposed a combination of MHR (Mean of HornerÃ¢Â€Â™s Rules) and standard deviation. The results of this research showed that our proposed method gave a high accuracy (93.872%) than the previous method (75.388% and 75.156%). This research gave an opportunity to implemented in real login system because our method gave the best results with False Acceptance Rate (FAR) is 0.113. The user can be used as a simple password and ignore a worrying about an account hacking in the system.

Controller Based Proxy for Handling NDP in OpenFlow Network Sumadi, Fauzi Dwi Setiawan; Chandranegara, Didih Rizki
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 1, February 2019
Publisher : Universitas Muhammadiyah Malang

A significant method should be deployed in OpenFlow environment for reducing the complexity during the implementation of IPv6 neighbor discovery protocol (NDP) in multicast manner. This paper was performed for deploying reactive-based application in controllerÃ¢Â€Â™s northbound layer for handling as well as cutting the Neighbor solicitation packetÃ¢Â€Â™s journey. The application had a capability for storing each of the incoming Neighbor Solicitation (NS) and Neighbor Advertisement (NA) packet information. Therefore, the controller could reply the NS packet directly by using OFPT_PACKET_OUT message that contained the NA packet extracted from the reactive application. The experimentÃ¢Â€Â™s result showed that the proposed approach could reduce the NS response time up to 71% than the normal result produced by the traditional/learning switch application.

Semi-reactive Switch Based Proxy ARP in SDN Setiawan Sumadi, Fauzi Dwi; Risqiwati, Diah; Syaifuddin, Syaifuddin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In order to achieve high scalability during the network discovery process in software-defined networking (SDN), an extensive method for generating switch-based proxy is essential. This paper investigated the semi reactive solution for guiding the controller to build an OFPT_FLOW_MOD message that allowed SDN switch to reply an Address Resolution Protocol (ARP) request directly by deploying the semi-reactive switch-based proxy ARP application in northbound application programming interface (API). We conduct the experiment by using Open Networking Operating System (ONOS) an open-source SDN controller simulated in Mininet environment. As can be seen from the evaluation result, the installed application can reduce the ARP reaction time up to 95% calculated from the sender host. The final result also indicates that our approach can decrease the controller's loads significantly.

Semi-supervised approach for detecting distributed denial of service in SD-honeypot network environment Fauzi Dwi Setiawan Sumadi; Christian Sri Kusuma Aditya; Ahmad Akbar Maulana; Syaifuddin Syaifuddin; Vera Suryani
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1094-1100

Distributed Denial of Service (DDoS) attacks is the most common type of cyber-attack. Therefore, an appropriate mechanism is needed to overcome those problems. This paper proposed an integration method between the honeypot sensor and software defined network (SDN) (SD-honeypot network). In terms of the attack detection process, the honeypot server utilized the Semi-supervised learning method in the attack classification process by combining the Pseudo-labelling model (support vector machine (SVM) algorithm) and the subsequent classification with the Adaptive Boosting method. The dataset used in this paper is monitoring data taken by the Suricata sensor. The research experiment was conducted by examining several variables, namely the accuracy, precision, and recall pointed at 99%, 66%, and 66%, respectively. The central processing unit (CPU) usage during classification was relatively small, which was around 14%. The average time of flow rule mitigation installation was 40s. In addition, the packet/prediction loss occurred during the attack, which caused several packets in the attack not to be classified was pointed at 43%.

SD-Honeypot Integration for Mitigating DDoS Attack Using Machine Learning Approaches Fauzi Dwi Setiawan Sumadi; Alrizal Rakhmat Widagdo; Abyan Faishal Reza; - Syaifuddin
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.853

Distributed Denial of Services (DDoS) is still considered the main availability problem in computer networks. Developing a programmable Intrusion Prevention System (IPS) application in a Software Defined Network (SDN) may solve the specified problem. However, the deployment of centralized logic control can create a single point of failure on the network. This paper proposed the integration of Honeypot Sensor (Suricata) on the SDN environment, namely the SD-Honeypot network, to resolve the DDoS attack using a machine learning approach. The application employed several algorithms (Support Vector Machine (SVM), Multilayer Perceptron (MLP), Gaussian Naive Bayes (GNB), K-Nearest Neighbors (KNN), Classification and Regression Trees (CART), and Random Forest (RF)) and comparatively analyzed. The dataset used during the emulation utilized the extracted Internet Control Message Protocol (ICMP) flood data from the Suricata sensor. In order to measure the effectiveness of detection and mitigation modules, several variables were examined, namely, accuracy, precision, recall, and the promptness of the flow mitigation installation process. The Honeypot server transmitted the flow rule modification message for blocking the attack using the Representational State Transfer Application Programming Interface (REST API). The experiment results showed the effectiveness of CART algorithm for detecting and resolving the intrusion. Despite the accuracy score pointed at 69-70%, the algorithm could promptly deploy the mitigation flow within 31-49ms compared to the SVM, which produced 93-94% accuracy, but the flow installation required 112-305ms. The developed CART module can be considered a solution to prevent the attack effectively based on the analyzed variable.

Enabling seamless communication over several IoT messaging protocols in OpenFlow network Fauzi Dwi Setiawan Sumadi; Agus Eko Minarno; Lailis Syafa’ah; Muhammad Irfan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20412

The most prominent protocols for data transfer in internet of things (IoT) are message queuing telemetry transport (MQTT) and constrained application protocol (CoAP). The existing clients from both sides are unable to communicate directly because of the packet’s header structure difference in application and transport layer. In response, this paper aims to develop a bidirectional conversion server used to translate the specified messaging protocol interchangeably in the OpenFlow network and transmit the converted packet from both sides. The conversion server integrated the MQTT subscriber and CoAP POST object for converting the MQTT message into CoAP data. Similarly, the CoAP-MQTT translation was processed by CoAP GET and MQTT publisher object. The research was evaluated by analysing the round trip time (RTT) value, conversion delay, and power consumption. The RTT value for MQTT-CoAP required 0.5 s while the CoAP-MQTT was accumulated in 0.1 s for single-packet transmission. In addition, the SDN controller and the conversion server only consumed less than 1% central processing unit (CPU) usage during the experiment. The result indicated that the proposed conversion server could handle the translation even though there was an overwhelming request from the clients.

Classification of batik patterns using K-Nearest neighbor and support vector machine Agus Eko Minarno; Fauzi Dwi Setiawan Sumadi; Hardianto Wibowo; Yuda Munarko
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

This study is proposed to compare which are the better method to classify Batik image between K-Nearest neighbor and support vector machine using minimum features of GLCM. The proposed steps are started by converting image to grayscale and extracting colour feature using four features of GLCM. The features include energy, entropy, contras, correlation and 0o, 45o, 90o, and 135o. The classifier features consist of 16 features in total. In the experimental result, there exist comparison of previous works regarding the classification KNN and SVM using multi texton histogram (MTH). The experiments are carried out in the form of calculation of accuracy with data sharing and cross-validation scenario. From the test results, the average accuracy for KNN is 78.3% and 92.3% for SVM in the cross-validation scenario. The scenario for the highest accuracy of data sharing is at 70% for KNN and at 100% for SVM. Thus, it is apparent that the application of the GLCM and SVM method for extracting and classifying batik motifs has been effective and better than previous work.

Diabetes prediction based on discrete and continuous mean amplitude of glycemic excursions using machine learning Lailis Syafaah; Setio Basuki; Fauzi Dwi Setiawan Sumadi; Amrul Faruq; Mauridhi Hery Purnomo
Bulletin of Electrical Engineering and Informatics Vol 9, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i6.2387

Chronic hyperglycemia and acute glucose fluctuations are the two main factors that trigger complications in diabetes mellitus (DM). Continuous and sustainable observation of these factors is significant to be done to reduce the potential of cardiovascular problems in the future by minimizing the occurrence of glycemic variability (GV). At present, observations on GV are based on the mean amplitude of glycemic excursion (MAGE), which is measured based on continuous blood glucose data from patients using particular devices. This study aims to calculate the value of MAGE based on discrete blood glucose observations from 43 volunteer patients to predict the diabetes status of patients. Experiments were carried out by calculating MAGE values from original discrete data and continuous data obtained using Spline Interpolation. This study utilizes the machine learning algorithm, especially k-Nearest Neighbor with dynamic time wrapping (DTW) to measure the distance between time series data. From the classification test, discrete data and continuous data from the interpolation results show precisely the same accuracy value that is equal to 92.85%. Furthermore, there are variations in the MAGE value for each patient where the diabetes class has the most significant difference, followed by the pre-diabetes class, and the typical class.

Pengembangan Sistem Monitoring Budidaya Jamur Tiram Untuk Optimalisasi Hasil Panen Kelompok Tani Wanita Tani Desa Beji Kota Batu Diah Risqiwati; Fauzi Dwi Setiawan Sumadi; Oxicusa Gugi Housman; Muhammad Zidan; Najmuddin Tsaqib
RESONA : Jurnal Ilmiah Pengabdian Masyarakat Vol 4, No 2 (2020)
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah (LPPI) Universitas Muhammadiyah Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35906/resona.v4i2.382

Teknik pembudidayaan jamur tiram pada kelompok tani wanita Desa Beji Kota Batu Jawa Timur, masih menggunakan metode tradisional. Ekosistem penanaman berdasarkan kondisi lingkungan yang memadai untuk proses tersebut. Hal ini menyebabkan optimasi hasil panen yang kurang menentu tiap harinya. Adanya perkembangan teknologi khususnya dalam bidang Internet of Things (IoT) dapat dijadikan sebagai alternatif solusi dengan proses pengambilan data kondisi lingkungan secara real-time dan akurat yang digunakan sebagai bahan kajian dalam proses penyiraman. Penulis mengusulkan untuk membangun sebuah sistem monitoring dan penyiraman dengan model prototyping. Sistem yang dibangun berfungsi sebagai filter keadaan dalam kumbung jamur dengan variabel input berupa suhu dan kelembapan digunakan sebagai nilai ambang batas minimal untuk proses penyemprotan secara otomatis. Dari hasil pengabdian yang dilakukan, petani jamur dapat dengan mudah melakukan pengecekan kondisi kumbung tanpa harus mendatangi kumbung secara langsung. Selain itu, sistem juga berhasil mengontrol kondisi kumbung dengan penyemprotan secara otomatis, berkala bila kelembaban dan suhu pada kondisi tidak ideal sehingga dapat memberikan hasil positif pada peningkatan hasil panen.Kata Kunci: Jamur Tiram, Monitoring, Suhu, Kelembaban, Real Time Abstract. The technique of cultivating oyster mushrooms in a female farmer group in Beji Village, Batu City, East Java, still uses traditional methods. A planting ecosystem based on adequate environmental conditions for the process. This causes the optimization of crop yields that are uncertain every day. The existence of technological developments, especially in the field of the Internet of Things (IoT), can be used as an alternative solution with the process of real-time and accurate environmental condition data collection which is used as study material in the watering process. The author proposes to build a monitoring and watering system with a prototyping model. The system built functions as a filter for conditions in the mushroom kumbung with input variables in the form of temperature and humidity which are used as minimum threshold values for the automatic spraying process. From the results of the dedication, mushroom farmers can easily check the conditions of the kumbung without having to come directly to the kumbung. Besides, the system also managed to control the kumbung condition by spraying it automatically, periodically when the humidity and temperature were not ideal so that it could give positive results in increasing crop yields.Keywords: Oyster Mushroom, Monitoring, Temperature, Humidity, Real Time

Semi-reactive Switch Based Proxy ARP in SDN Fauzi Dwi Setiawan Sumadi; Diah Risqiwati; Syaifuddin Syaifuddin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

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 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 Ilyas Nuryasin 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 Oxicusa Gugi Housman Said imam Baihaqqi Setio Basuki Syafaah, Lailis Syaifuddin Syaifuddin Syaifuddin Syaifuddin Syaifuddin, Syaifuddin Vera Suryani Wahyuli Dwiki Nanda Yoga Pamungkas Yuda Munarko Yusril Izza Rizqony Zaidah Ibrahim Zamah Sari

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