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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) POROS TEKNIK JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Jurnal Repositor Jurnal Perempuan & Anak Jurnal Impresi Indonesia

Chandranegara, Didih Rizki

Universitas Muhammadiyah Malang

Author-ID : 966221

Religion Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 30 Documents Claim Missing Document

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Articles

Title

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.

ClusterMix K-Prototypes Algorithm to Capture Variable Characteristics of Patient Mortality With Heart Failure Novidianto, Raditya; Wibowo, Hardianto; Chandranegara, Didih Rizki
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 2, May 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i2.1209

Cardiovascular Disease (CVD) is one of the leading causes of many death worldwide, leading to heart failure incidence. The World Health Organization (WHO) says the number of people dying from cardiovascular disease from heart failure each year has an average of 17,9 million deaths each year, about 31 percent of the total deaths globally. Identify the mortality factors of heart failure patients that need to be formed, which reduces death due to heart failure. One of them is by using variable mortality due to heart failure by applying the k-prototypes algorithm. The clustering result is formed 2 clusters that are considered optimal based on the highest silhouette coefficient value of 0,5777. The results of the study were carried out as segmentation of patients with variable mortality of heart failure patients, which showed that cluster 1 is a cluster of patients who have a low risk of the chance of mortality due to heart failure and cluster 2 is a cluster of patients with a high risk of mortality due to heart failure. The segmentation is based on the average value of each variable of heart failure mortality factor in each cluster compared to normal conditions in serum creatine variables, ejection fraction, age, serum sodium, blood pressure, anemia, creatinine phosphokinase, platelets, smoking, gender, and diabetes.

Keystroke Dynamic Authentication Using Combined MHR (Mean of Horner’s Rules) and Standard Deviation Didih Rizki Chandranegara; Fauzi Dwi Setiawan Sumadi
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 Horner’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 Fauzi Dwi Setiawan Sumadi; Didih Rizki Chandranegara
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 controller’s northbound layer for handling as well as cutting the Neighbor solicitation packet’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 experiment’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.

Implementation of Generative Adversarial Network (GAN) Method for Pneumonia Dataset Augmentation Chandranegara, Didih Rizki; Sari, Zamah; Dewantoro, Muhammad Bagas; Wibowo, Hardianto; Suharso, Wildan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 2, May 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i2.1675

As a communicable disease, the majority of pneumonia cases are brought on by bacteria or viruses, which cause the lungs' alveoli to swell with fluid or mucus. Pneumonia may arise from this and further making breathing challenging since the lungs' air sacs are unable to contain enough oxygen for the body. Pneumonia may generally be diagnosed clinically (by a physician based on physical symptoms) as well as through a photo chest radiograph, CT scan, and MRI. In this case, the lower cost of a chest radiograph examination making it as one of the most popular medical imaging tests. However, chest radiograph photo readings have a disadvantage, where it takes a long time for medical staff or physicians to identify the patient's illness since it is difficult to detect the condition. Therefore, an identification of chest radiograph imagery into various forms using machine learning becomes one way to address this issue. This research focuses on building a deep neural network model using techniques from the Generative Adversarial Network algorithm. GAN is a category of machine learning techniques using two models to be trained simultaneously, one is a generator model to generated fake data and the other is a discriminator model used to separate the raw data from the real data set images. The dataset used is Chest X-Ray images obtained from repo GitHub and repo Kaggle totaling 5,863 with normal data 1583 images and pneumonia data 4273 imagesThe results showed that the use of the Generative Adevrsarial Network method as augmentation data proved to be more effective in improving the generalization of neural networks, this can be seen from the results the result of the accuracy value obtained is 97%.

Co-Authors Agus Eko Minarno Agus Zainal Arifin Ahmad Hanif Nurfauzi Akbar, Muhammad Sulthoni Akbi, Denar Regata Aminudin, Aminudin Aprilya Dinathi, Devi Aulyah, Khairunnisa Azzahra, Kiara christian s.k.aditya Christian Sri Kusuma Aditya Christian Sri kusuma Aditya, Christian Sri kusuma christianskaditya Dewantoro, Muhammad Bagas Ekanita Rakhmah Eko Budi Cahyono Elan Cahya Niswary Elsandy Wirahadi Kusumah Fadhlan, Muhammad Ferdiansyah, Danny Gayatri, Agnes Ayu Maharani Dyah Hanif, Lathifah Hardianto Wibowo Heni Pujiastuti Ianatut Thoifah Imron, Moch L. Yasril Imam Lathifah Hanif Lathifah, Fildzah Moch Imron Moch. Rosid Noviansyah Ningsih Djamsi Novidianto, Raditya Nuryasin, Ilyas Raffi Ainul Afif Rahayu Nurul Khasanah Rakhmah, Ekanita Ramadanti, Elisa Rista Azizah Arilya Rizaldi, Muhammad Ikhwananda Rizky, Wahyu Saiful Amien Sari, Zamah Setiono, Fauzan Adrivano Setyarini, Dela Ananda Sofyan Arifianto Sumadi, Fauzi Dwi Setiawan Vallent Austin Theasar Kurniawan Wanvy Arifha Saputra Wicaksono, Galih Wasis Wildan Suharso Wildan Suharso Yuda Munarko Yufis Azhar Zamah Sari

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Journal : Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control