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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 536 Documents
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Application of Early Diagnosis of Diabetes Mellitus (DM) Equipped with Calorie Needs for DM Sufferers using the Fuzzy Mamdani Method Wardana, Humaidillah Kurniadi; Ummah, Imamatul; Fitriyah, Lina Arifah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1088

Abstract

Diabetes Mellitus (DM) is one of the deadliest degenerative diseases in the world. The prevalence of DM in Indonesia from year to year shows asignificant increase. The high number of these causes the need for appropriate action and anticipation for health workers, DM families and DM people themselves. In this study, a system application model was created by using informatics techniques in health for early diagnosis of DM and what calorie needs needed for DM sufferers. This system was created using a GUI application and the Mamdani fuzzy method. The purpose of creating this system is to help in making an initial decision for DM diagnosis. The results obtained, first a DM diagnosis system with 6 input variables, 3 output variables, and 155 rules with MAPE achieved 29.48%. The second is the calorie requirements system with 2 input variables, 2 output variables namely BMI with MAPE 10.57% BMR with MAPE 9.7% and 9 rules with the results achieved by 99%.
Hopscotch Game to Support Stimulus in Children’s Gross Motor Skill using IoT Jati, Riyan Kuncoro; Suwastika, Novian Anggis; Yasirandi, Rahmat
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1090

Abstract

Every movement that has connection to stability and coordination between each body part were accounted as the gross motor skill system. If gross motor skill development were interrupted especially for 3-5 years old, their activities would be negatively affected. Foot-based games such as jumping and stepping can be used to train a child's motor balance. One example of a famous traditional game is hopscotch. Hopscotch is a game that demand high flexibility of foot movement a coordination skills thus proved scientifically can train children gross motor skill system. Various types of hopscotch games have the potential to improve children's dynamic balance. But in traditional hopscotch games it is difficult to see how the mechanism of improving children's dynamic balance is established. The development of a child's dynamic balance cannot be constantly tracked by teachers or parents. Therefore, we design and create hopscotch with an automated system that can overcome these limitations with digital records, data stored safely, system requirements easily duplicated, and more accurate. In the Hopscotch game, there are features, namely levels 1–3, and memory test, where the memory test serves to train children's memory. The hopscotch game using Footstep based capacitive sensor and LED feedback, the improved gameplay used for training and measuring child’s gross motor skill system by their time completion and true/false footstep ratio. As the result the IoT based Hopscotch game with randomized lane are successfully mimic hopscotch gameplay with its added gameplay feature, the player subject performance has increased adaptability performance through each level the capacitive sensor-based footprint system has shown 100% accuracy, the system fully response to the footstep with average 456 milliseconds reading time per step, the system interface can fully control the gameplay level and can show players performance.
As-RaD System as a Design Model of the Network Automation Configuration System Based on the REST-API and Django Framework Adian Fatchur Rochim; Abda Rafi; Adnan Fauzi; Kurniawan Teguh Martono
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1093

Abstract

The use of information technology these days are very high. From business through education activities tend to use this technology most of the time. Information technology uses computer networks for integration and management data. To avoid business problems, the number of network devices installed requires a manageable network configuration for easier maintenance. Traditionally, each of network devices has to be manually configured by network administrators. This process takes time and inefficient. Network automation methods exist to overcome the repetitive process. Design model uses a web-based application for maintenance and automates networking tasks. In this research, the network automation system implemented and built a controller application that used REST API (Representational State Transfer Application Programming Interface) architecture and built by Django framework with Python programming language. The design modeled namely As-RaD System. The network devices used in this research are Cisco CSR1000V because it supports REST API communication to manage its network configuration and could be placed on the server either. The As-RaD System provides 75% faster performance than Paramiko and 92% than NAPALM.
Front and Back Matter Volume 5 Issue 2 Waskito, Adhitya Dio
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 2, May 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i2.1108

Abstract

Front and Back Matter Volume 5 Issue 3 Waskito, Adhitya Dio
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i3.1109

Abstract

Towards an Effective Tuberculosis Surveillance in Indonesia through Google Trends Fudholi, Dhomas Hatta; Fikri, Khairul
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1114

Abstract

Background. The search digital footprint, such as in Google Trend (GT), forms a large dataset that is suitable to be used as surveillance data and supports early warning systems. These advantages become great opportunities for disease surveillance agencies in Indonesia to get rapid early disease monitoring. Objective. Due to limited research in this area and the increasing level of internet penetration in Indonesia, a further study is needed in disease monitoring by utilizing Google Trends. In this research, we explore, analyze and create a set of the best search terms to be used in utilizing GT for disease surveillance in Indonesia, especially Tuberculosis. Method. We use correlation as the technique to define the relatedness between the real case data and GT results. We collect data from the Ministry of Health of Indonesia. From the data, we design a set of new search terms to take GT trend data. The collected data is analyzed using the Pearson correlation. Result. The analysis shows that the studied search terms give strong positive relationships between GT trend data and Tuberculosis cases number in Indonesia. From the correlation analysis, we get a set of proposed effective search terms with the highest score equals to 0.907. Conclusion. Finally, it is possible to monitor and make quick surveillance in tuberculosis in Indonesia through Google Trend and we have created a novel set of search terms that can be used as the basis in monitoring other diseases in Indonesia
Mental Disorder Detection via Social Media Mining using Deep Learning Binti Kholifah; Iwan Syarif; Tessy Badriyah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1120

Abstract

Due to the imperceptible nature of mental disorders, diagnosing a patient with a mental disorder is a challenging task. Therefore, detection in people with mental disorders can be done by looking at the symptoms they experience. One symptom in patients with mental disorders is solitude. Patients with mental disorders feel indifferent to their environment and mainly focus on their own thoughts and emotions. Therefore, the patient looks for a place that can accommodate his feelings. Twitter is one of the most widely used media in measuring one's personality through everyday statements. The symptoms as suggested by psychologists can be explored more broadly using Natural Languages Processing. The process involves taking a lexicon containing keywords that could indicate symptoms of depression. This study uses five criteria as a measure of mental health in a statement: sentiment, basic emotions, the use of personal pronouns, absolutist words, and negative words. The results show that the use of sentiments, emotions, and negative words in a statement is very influential in determining the level of depression. A depressed person more often uses negative words that indicate his self-despair, prolonged sadness, even suicidal thoughts (e.g. "sadly”, “scared”, “die”, “suicide”). In the classification process, LSTM Deep Learning generates an accuracy of 70.89%; precision of 50.24%; recall 70.89%.
Attention-based CNN-BiLSTM for Dialect Identification on Javanese Text Hidayatullah, Ahmad Fathan; Cahyaningtyas, Siwi; Pamungkas, Rheza Daffa
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1121

Abstract

This study proposes a hybrid deep learning models called attention-based CNN-BiLSTM (ACBiL) for dialect identification on Javanese text. Our ACBiL model comprises of input layer, convolution layer, max pooling layer, batch normalization layer, bidirectional LSTM layer, attention layer, fully connected layer and softmax layer. In the attention layer, we applied a hierarchical attention networks using word and sentence level attention to observe the level of importance from the content. As comparison, we also experimented with other several classical machine learning and deep learning approaches. Among the classical machine learning, the Linear Regression with unigram achieved the best performance with average accuracy of 0.9647. In addition, our observation with the deep learning models outperformed the traditional machine learning models significantly. Our experiments showed that the ACBiL architecture achieved the best performance among the other deep learning methods with the accuracy of 0.9944.
ANP and ELECTRE Methods for Determine New Student Admissions Kustiyahningsih, Yeni; Sophan, Mochammad Kautsar; Ikhsan, Achmad Faris
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 4, November 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i4.1124

Abstract

Higher Education is a level of education after High School which selects new students based on achievement, report cards, and tests. Admission selection was based on report cards. Number of indicators and who register make it difficult for determine which students are accepted in education. Multi criteria Group Decision Making (MCGDM) is decision-making method to determine best alternative from a number of alternatives based on certain criteria. In this study, MCGDM used is Analytic Network Process (ANP) and Elimination and Choice Expression Reality (ELECTRE). ANP model is a development of AHP and requires linkages between criteria using a network. ELECTRE is method based concept of ranking through pairwise comparisons between alternatives on the appropriate criteria. Contribution is integration ANP and ELECTRE methods based on group, by determining decisions based on consistency ratio. The results of testing level consistency ratio, group-based ANP-ELECTRE can be applied to assessment selection at Electrical Engineering with highest accuracy of 86.36%.
A Non-Blind Robust and Impercept Watermarking Using Discrete Cosine Transform and Discrete Wavelet Transform Eko Hari Rachmawanto; Heru Agus Santoso
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 1, February 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i1.1132

Abstract

Non-blind watermarking is a form of watermarking with a watermark image validation process that requires a host image. The use of the transform domain is more robust and imperceptible. The transform domain method is resistant to various forms of digital image attacks. In this study, Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) were selected as watermark insertion algorithms. DCT is faster and more resistant to attacks, especially in image compression attacks, but has lower imperceptibility than DWT. DWT is also known to be resistant to noise attacks, filtering, blurring, cropping, and has high imperceptibility depending on the sub-band selection but is not resistant to image compression attacks. Based on each algorithm's advantages and disadvantages, there is an opportunity to combine it to analyze and compare the insertion results with DCT and DWT itself. To test the results of imperceptibility, we used the Peak Signal to Noise Ratio (PSNR), while to test the robustness, we used Cross-Correlation (CC) and Bit Error Ratio (BER). Without attacks, the PSNR on the proposed method can reach 71 dB. The CC value without attack can reach a perfect value of 1 and BER = 0. The highest attack test result is CC = 1 on the filtering attack. From the various tests we have conducted, it has been proven that the DCT-DWT is more imperceptive and robust than previous studies

Page 31 of 54 | Total Record : 536

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