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Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Published by Universitas Muhammadiyah Malang
ISSN : 25032259     EISSN : 25032267     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve their knowledge in those particular areas and intended to spread the knowledge as the result of studies. KINETIK journal is a scientific research journal for Informatics and Electrical Engineering. It is open for anyone who desire to develop knowledge based on qualified research in any field. Submitted papers are evaluated by anonymous referees by double-blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully within 4 - 8 weeks. The research article submitted to this online journal will be peer-reviewed at least 2 (two) reviewers. The accepted research articles will be available online following the journal peer-reviewing process.
Arjuna Subject : -
Articles 9 Documents
 1 
Search results for , issue "Vol. 6, No. 2, May 2021" : 9 Documents clear
Developing an Instrument to Measure Information Assurance Implementation for eGovernment using Goal Question Metric Approach Utomo, Rio Guntur; Wills, Gary; Walters, Robert
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.v6i2.1200

Abstract

The eGovernment initiative is aimed to improve government services to the public by improving the quality and availability of services that can be accessed regardless of time and place. Consequently, the services must always be available at any time, and any threat to the information and systems should receive attention to ensure business continuity in the event of an incident. Therefore, in implementing eGovernment, information assurance (IA) must be considered. To determine the extent to which IA implementation status to protect eGovernment services in Indonesia, it is necessary to measure the implementation using an instrument. The measurement instrument was developed using the Goal Question Metric (GQM) approach. The developed instrument was then used in a case study to test its effectiveness in measuring the IA implementation. From the results of the case study, it can be concluded that the IA measurement instrument for eGovernment was proven to be effective within Indonesian context.
Moving Objects Semantic Segmentation using SegNet with VGG Encoder for Autonomous Driving Wahyudi Setiawan; Kori Cahyono
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.v6i2.1203

Abstract

Segmentation and recognition become the general steps to identify objects. This research discusses pixel-wise semantic segmentation based on moving objects. The data from the CamVid video which is a collection of autonomous driving images. The image data consist of 701 images accompanied by labels. The segmentation and recognition of 11 objects contained in the image (sky, building, pole, road, pavement, tree, sign-symbol, fence, car, pedestrian and bicyclist) is representing. This moving object segmentation is carried out using SegNet which is one of the Convolutional Neural Network (CNN) methods. Image segmentation on CNN generally consists of two parts: Encoder and Decoder. VGG16 and VGG19 pre-trained networks are used as encoders, while decoders are the upsampling of encoders. Network optimization uses stochastic gradient descent of Momentum (SGDM). The test produces the best recognition was road objects with an accuracy of 0.96013, IoU 0.93745, F1-Score 0.8535 using VGG19 encoder, while when using VGG16 encoder accuracy was 0.94162, IoU 0.92309, and F1-Score 0.8535.
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

Abstract

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.
Diagonal Based Feature Extraction and Backpropagation Neural Network in Handwritten Batak Toba Characters Recognition Zamzami, Elviawaty Muisa; Hayanti, Septi; Nababan, Erna Budhiarti
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.v6i2.1212

Abstract

Handwritten character recognition is considered a complex problem since one’s handwritten character has its characteristics.  Data used for this research was a photo of handwritten or scanned handwritten.  In this research, Backpropagation Neural Network (BPNN) was used to recognize handwritten Batak Toba character, wherein preprocessing stage feature extraction was done using Diagonal Based Feature Extraction (DBFE) to obtain feature value.  Furthermore, the feature value will be used as an input to BPNN. The total number of data used was190 data, where 114 data was used for the training process and another 76 data was used for testing. From the testing process carried out, the accuracy obtained was 87,19 %.
Convolutional Neural Network with Hyperparameter Tuning for Brain Tumor Classification Minarno, Agus Eko; Hazmi Cokro Mandiri, Mochammad; Munarko, Yuda; Hariyady, Hariyady
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.v6i2.1219

Abstract

Brain tumor has been acknowledged as the most dangerous disease through all its circles. Early identification of tumor disease is considered pivotal to identify the spread of brain tumors in administering the appropriate treatment. This study proposes a Convolutional Neural Network method to detect brain tumor on MRI images. The 3264 datasets were undertaken in this study with detailed images of Glioma tumor (926 images), Meningioma tumors (937 images), pituitary tumors (901 images), and other with no-tumors (500 images). The application of CNN method combined with Hyperparameter Tuning is proposed to achieve optimal results in classifying the brain tumor types. Hyperparameter Tuning acts as a navigator to achieve the best parameters in the proposed CNN model. In this study, the model testing was conducted with three different scenarios. The result of brain tumor classification depicts an accuracy of 96% in the third model testing scenario.
Network Forensics Against Ryuk Ransomware Using Trigger, Acquire, Analysis, Report, and Action (TAARA) Method Ridho Surya Kusuma; Rusydi Umar; Imam Riadi
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.v6i2.1225

Abstract

This study aims to reconstruct an attack event and analyze the source of viral infection based on network traffic logs so that the information obtained can be used for a new reference in the security system. Recent attacks on computer network systems cannot be easily detected, as cybercrime has used a variant of the Ryuk Ransomware virus to penetrate security systems, encrypt drives, and computer network resources. This virus is very destructive and has an effective design with a file size of about 200,487 Bytes so it does not look suspicious. The research steps are done through Trigger, Acquire, Analysis, Report, and Action (TAARA). The forensic tools used to obtain log data are Wireshark, NetworkMiner, and TCPDUMP. Based on the results of forensic data obtained include a timestamp, source of the attack, IP address, MAC address, hash signature sha256, internet protocol, and the process of infection. Based on the data obtained in this study has been by the expected objectives.
Comparison Analysis of Multipath Routing Implementation in Software Defined Network Syaifuddin Syaifuddin; Muhamad Fathul Azis; Fauzi Dwi Setiawan Sumadi
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.v6i2.1228

Abstract

Multipath routing is a path search method used as a data transmission process utilizing more than one available path on a network. The multipath routing concept is directed to substitute the single path routing concept for reducing network traffic congestion by distributing data transmission through several available paths. It can be implemented in the Software Defined Network (SDN) environment that separates the control plane and the data plane, which provides flexibility by deploying application-based solutions to resolve the problem. This paper is directed to implement the modified Deep First Search (DFS) multipath routing algorithm and compare the proposed method with Dijkstra and normal DFS multipath algorithm. The contribution was designed by combining the node, edge, path, and bucket weight using port statistics available in OpenFlow standard and manual calculation. The results of the system’s emulation showed that the overall algorithm could determine more than one path for the data transmission process. The average execution time on all algorithms produced 0.0903 ms for the modified DFS multipath algorithm, 0.0858 ms for DFS multipath algorithm, and 0.901 ms Dijkstra multipath algorithm, respectively. The QoS parameter testing results illustrated that the proposed method was better than another multipath routing algorithm in terms of throughput and jitter. However, based on packet loss percentage, the modified method was placed after normal DFS but still generated better results than Dijkstra. Overall, the implement multipath routing concept in SDN with all algorithms could be deployed to provide more than one data transmission path.
An Evaluation of Complementary Filter Method in Increasing the Performance of Motion Tracking Gloves for Virtual Reality Games Fairus Zuhair Azizy Atoir; Aji Gautama Putrada; Rizka Reza Pahlevi
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.v6i2.1234

Abstract

In the use of Virtual Reality-based video games, users need additional devices to interact, one of which is a Motion Tracking Glove. The Motion Tracking Glove is one of the enhancements that users can use to interact with objects in VR video games. To get the angle value, an accelerometer sensor is used in the MPU6050 module. However, the problem that arises is the accuracy of the sensor because VR demands a low error rate. The purpose of this study is to improve the accuracy of the angular value of the accelerometer sensor value with a complementary filter. Complementary filters can increase the accuracy of the accelerometer sensor by combining its value with the gyroscope sensor value. The Motion Tracking Glove is built using the Arduino Nano and the MPU6050 module to capture angles that move according to hand movements, to connect and exchange data to the main VR device, the Motion Tracking Glove using the Bluetooth module. The results are RMSE 0.6 and MAPE 2.5% with a static Motion Tracking Glove position without movement. In sending Motion Tracking Glove data using the Bluetooth module, the resulting delay time when sending ranges from 0.1 second to 0.4 seconds by trying to move the Motion Tracking Glove from 0 degrees to 90 degrees and back to 0 degrees.
On the Experiment of Path Planning Using Multi-way Points with A* Algorithm for Autonomous Surface Vehicle Bayu Erfianto; Adysti Adrianne; Ramzy Rashaun Arif
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.v6i2.1244

Abstract

Commonly, surveillance activities on lake waters is mostly carried out by using a surface vehicle as special-designed vehicle, especially to conduct water quality measurements, underwater surveys, and bathymetry mapping. However, conventional survey and monitoring still involves humans on the site. If a survey is conducted during strong wind conditions, it could jeopardize surveyor’s safety. Therefore, a vehicle must have several criteria, e.g., it must be pretty spacious and comfortable to carry surveyors, free from engine vibrations, stabilized and easy to maneuver, and the surveyor's safety can be guaranteed. This paper discusses preliminary research aiming to develop an Autonomous Raft Vehicle (ARV), a type of autonomous unmanned surface vehicle. The ARV is equipped with autonomous control based on multi-way-points with an A* algorithm. Thus, a user only requires giving a command once initially during path planning. A* algorithm over multi-way-point could improve ARV navigation when there are obstacles along the predetermined trajectory. Hence the predetermined trajectory will be maintained throughout the mission. It is a significant contribution to this paper.

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