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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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A Study on Visual Understanding Image Captioning using Different Word Embeddings and CNN-Based Feature Extractions Dhomas Hatta Fudholi; Annisa Zahra; Royan Abida N. Nayoan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 1, February 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i1.1394

Abstract

Image captioning is a task that can provide a description of an image in natural language. Image captioning can be used for a variety of applications, such as image indexing and virtual assistants. In this research, we compared the performance of three different word embeddings, namely, GloVe, Word2Vec, FastText and six CNN-based feature extraction architectures such as, Inception V3, InceptionResNet V2, ResNet152 V2, EfficientNet B3 V1, EfficientNet B7 V1, and NASNetLarge which then will be combined with LSTM as the decoder to perform image captioning. We used ten different household objects (bed, cell phone, chair, couch, oven, potted plant, refrigerator, sink, table, and tv) that were obtained from MSCOCO dataset to develop the model. Then, we created five new captions in Bahasa Indonesia for the selected images. The captions might contain details about the name, the location, the color, the size, and the characteristics of an object and its surrounding area. In our 18 experimental models, we used different combination of the word embedding and CNN-based feature extraction architecture, along with LSTM to train the model. As the result, models that used the combination of Word2Vec + NASNetLarge performed better in generating Indonesian captions than the other models based on BLEU-4 metric.
Accessibility Analysis of Websites of Provincial Governments in Indonesia Vinna Rahmayanti Setyaning Nastiti; Amelia Deastu; Gita Indah Marthasari
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 1, February 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i1.1406

Abstract

Web accessibility means that people with disabilities can use, navigate, and interact with the website. The World Wide Web Consortium (W3C) has provided important guidelines on web accessibility known as the Web Content Accessible Guidelines (WCAG). The Indonesian government encourages the use of new media, namely website, via Presidential Instruction number 3 of 2003 concerning the National Policy and Strategy for e-government development, which mandates every government agency to build a website. In the previous study, the tools used had limitations and were unable to complete the websites evaluation. Therefore, in this study, WCAG 2.0 standard was applied to analyze the websites of provincial governments in Indonesia. Two accessibility evaluation tools were employed, namely TAW and aXe. In addition, for data analysis and interpretation, descriptive statistics and normality tests were applied. The results showed that the most common violation was found in perceivable principle. It was expected that the findings of this study could provide insight and recommendation for web developers working on provincial government website in Indonesia.
Performance Evaluation of 198 Village Governments using Fuzzy TOPSIS and Intuitionistic Fuzzy TOPSIS Wridhasari Hayuningtyas; Mauridhi Hery Purnomo; Adhi Dharma Wibawa
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1393

Abstract

Currently, volatility, uncertainty, complexity, and ambiguity (VUCA) have become unavoidable problems. In addition, knowledge or information that is not managed properly can result in inappropriate decision-making processes within an organization. Business Intelligence conception is then becoming an essential view for converting unstructured data and information into a more actionable strategic plan that allows organizations to make competitive decisions. Village Government (VG) is the smallest organization in the Indonesian government system because VG implemented regulation and development programs in all areas of a national government. VG executes a series of tasks every year starting from planning, budgeting, administrating, executing, and reporting. However, the important role of VG in the development of a country brings also some drawbacks such as corruption and other domino effects. Several factors have been identified that cause those problems such as lack of capabilities in managing village organization and human resources quality. Monitoring and evaluation regarding those VG performances normally have been done each year. However, measurable evaluation standard for VG performance until recently has not been determined nationally. This study is intended to make a comprehensive standard of village government performance assessment through a Good Governance Framework approach. This study involved 198 villages from Madiun Regency as a case study. Seventy-four measured parameters were proposed to evaluate VG performance mapping. Fuzzy TOPSIS is implemented to rank those 198 villages into 4 groups of VG performance levels. The fuzzy TOPSIS classification result has been validated by using manual scoring and the accuracy reached 86,4%.
Low-Rate Attack Detection on SD-IoT Using SVM Combined with Feature Importance Logistic Regression Coefficient Mirza Maulana Azmi; Fauzi Dwi Setiawan Sumadi
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1405

Abstract

The evolution of computer network technology is now experiencing substantial changes, particularly with the introduction of a new paradigm, Software Defined Networking (SDN). The SDN architecture has been applied in a variety of networks, including the Internet of Things (IoT), which is known as SD-IoT. IoT is made up of billions of networking devices that are interconnected and linked to the Internet. Since the SD-IoT was considered as a complex entity, several types of attack on vulnerabilities vary greatly and can be exploited by careless individuals. Low-Rate Distributed Denial of Service (LRDDoS) is one of the availability-based attack that may affect the SD-IoT integration paradigm. Therefore, it is necessary to have an Intrusion Detection System (IDS) to overcome the security hole caused by LRDDoS. The main objective of this research was the establishment of an IDS application for resolving LRDDoS attack using the SVM algorithm combined with the Feature Importance method, namely the Logistic Regression Coefficient. The implemented approach was developed to reduce the complexity or resource’s consumption during the classification process as well as increasing the accuracy. It could be concluded that the Linear kernel SVM algorithm acquired the highest results on the test schemes at 100% accuracy, but the training time required for this model was longer, about 23.6 seconds compared to the Radial Basis Function model which only takes about 1.5 seconds.
Hybrid Frequency and Period Based for Angular Speed Measurement of DC Motor Using Kalman Filter Novendra Setyawan; Basri Noor Cahyadi; Ermanu Azizul Hakim; Mas Nurul Achmadiah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1420

Abstract

The Incremental Rotary Encoder have been widely used to measure the angular speed of electrical drive such as Permanent Magnet Direct Current Motor (PMDCM). Nevertheless, speed measurement of PMDCM from the encoder signals can be subject to errors in some special condition such as in low resolution encoder. There are two main methods to measure the angular speed of PMDCM through encoder signal such as frequency-based and period-based wich has its own properties. Hence in this reseach aimed to improve the angular speed measurement with hybridization of frequency and period-based measurement. The Hybrid method is defined as paralleling the period and frequency then estimated the angular speed using sensor fusion with Kalman Filter. The experiment is doing by comparing of all method to get the best way in measuring. From the experimental showed that the Kalman filter parameter was fine tuned that resulting the sensor fusion or the mixed measurement between the frequency-based and the period based measure the angular speed accurately.
XGB-Hybrid Fingerprint Classification Model for Virtual Screening of Meningitis Drug Compounds Candidate Mohammad Hamim Zajuli Al Faroby; Helisyah Nur Fadhilah; Siti Amiroch; Rahmat Sigit Hidayat
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1424

Abstract

Meningitis is an infection of the lining of the brain caused by diffuse inflammation, and this condition is caused by viruses or bacteria that cause Meningitis. Prevention for this disease is still in the form of strengthening antibodies with vaccines. There is no significant compound to relieve or treat Meningitis patients. In previous studies, they got seven proteins vital to Meningitis. We continued to investigate the compounds associated with the seven proteins. We chose the in-silico process by utilizing data in an open database. We use several databases for the data collection process. After that, the compound data were extracted for bonding features and chemical elements using molecular fingerprints. We use two fingerprint methods, where both we combine with three types of combinations. The combined results produce three types of datasets with different matrix sizes. We establish the Extreme Gradient Boosting (XGB) method to form the classification model for the three datasets, select the best classification model, and compare it with other classification algorithms. The XGB model has better quality than the classification model of other algorithms. We used this model to predict and quantify compounds that strongly bind to seven vital meningitis proteins. The compound with the highest predictive score (we found more than 0.99) became a drug candidate to inhibit or neutralize Meningitis.
QSAR Study on Aromatic Disulfide Compounds as SARS-CoV Mpro Inhibitor Using Genetic Algorithm-Support Vector Machine Rizki Amanullah Hakim; Annisa Aditsania; Isman Kurniawan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1428

Abstract

COVID-19 is a type of pneumonia caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus causes severe acute respiratory syndrome and 2 million active cases of COVID-19 have been found worldwide. A new strain of the SARS-CoV-2 virus emerged that proved to be more virulent than its predecessor. Regarding the design of a new inhibitor for this strain, SARS-CoV Main Protease (Mpro) was used as the target inhibitor. In the in silico development, the Quantitative Structure-Activity Relationship (QSAR) method is commonly used to predict the biological activity of unknown compounds to improve the process of drug design of a disease, including COVID-19. In this study, we aim to develop a QSAR model to predict the activity of aromatic disulfide compounds as SARS-CoV Mpro inhibitors using Genetic Algorithm (GA) – Support Vector Machine (SVM). GA was used for feature selection, while SVM was used for model prediction. The used dataset is set of features of aromatic disulfide compounds, along with information on the toxicity activity. We found that the best SVM model was obtained through the implementation of the polynomial kernel with the value of R2­­train and R2test­ scores are 0.952 and 0.676, respectively.
Sentiment Analysis of Community Response Indonesia Against Covid-19 on Twitter Based on Negation Handling Viry Puspaning Ramadhan; Purwanto Purwanto; Farrikh Alzami
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1429

Abstract

The use of the internet globally, especially on the use of social media, includes Indonesia as one of the most active users in the world. The amount of information that can be obtained can be used to be processed into useful information, for example, information about the public sentiment on a particular topic. Tracking and analyzing tweets can be a method to find out people's thoughts, behavior, and reactions regarding the impact of Covid-19. The key to sentiment analysis is the determination of polarity, which determines whether the sentiment is positive or negative. The word negation in a sentence can change the polarity of the sentence so that if it is not handled properly it will affect the performance of the sentiment classification. In this study, the implementation of negation handling on sentiment analysis of Indonesian people's opinions regarding COVID-19 on Twitter has proven to be good enough to improve the performance of the classifier. Accuracy results obtained are 59.6% compared to adding negation handling accuracy obtained is 59.1%. Although the percentage result is not high, documents that include negative sentences have more meaning than negative sentences. However, for the evaluation using the MCC evaluation matrix, the results were quite good for the testing data. For the results of the proposed method whether it is suitable for data that has two classes or three classes when viewed from the results of the evaluation matrix, the proposed method is more suitable for binary data or data that has only two classes.
Color Based Feature Extraction and Backpropagation Neural Network in Tamarind Turmeric Herb Recognition Mila Fauziyah; Supriatna Adhisuwignjo; Bagus Fajar Afandi Afandi; Lathifatun Nazhiroh
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1432

Abstract

The aim of this paper is finding the optimum image pattern of the tamarind turmeric herb. So far, in the process of producing tamarind turmeric herb, it is not constant in terms of taste and color, which is influenced by maturity and the amount of turmeric. Image pattern recognition will use Backpropagation algorithm applied to typical Content-based image retrieval systems. The main purpose is to apprehend various parts of tamarind turmeric herb in the retrieving processing. The camera is applied to classify the tamarind turmeric herb product, process into 5x5 pixels, and take an average of the RGB value so the stable RGB values will be obtained in each category and used as input for Backpropagation algorithm. The most suitable and the fastest process from the Backpropagation algorithm will be searched and applied in a real-time machine. In this paper will be using two methods, first, train the algorithm using ten data by change neuron, layer, momentum, and learning rate, and the last is testing with ten data. The results obtained from the training and testing algorithm that the two hidden layers can recognize 100% inputs, with three input layers used for R, G, and B value, ten neurons in the first hidden layers and the second hidden layers, one output layer with a parameter used is Learning rate 0.5 and Momentum 0.6. The best image pattern standard for tamarind turmeric herb is dark yellow with RGB values of 255, 102, 32 up to 255, 128, 48.
A Wearable Device for Enhancing Basketball Shooting Correctness with MPU6050 Sensors and Support Vector Machine Classification Baginda Achmad Fadillah; Aji Gautama Putrada; Maman Abdurohman
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 2, May 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i2.1435

Abstract

One of the impacts of Covid-19 is the delay of basketball sports competitions, which influences the athlete’s fitness and the athlete’s ability to play, especially for shooting techniques. Existing research in wearable devices for basketball shooting correctness classification exists. However, there is still an opportunity to increase the classification performance. This research proposes designing and building a smartwatch prototype to classify the basketball shooting technique as correct or incorrect with enhanced sensors and classification methods. The system is based on an Internet of things architecture and uses an MPU6050 sensor to take gyroscope data in the form of X, Y, and Z movements and accelerometer data to accelerate hand movements. Then the data is sent to the Internet using NodeMCU microcontrollers. Feature extraction generates 18 new features from 3 axes on each sensor data before classification. Then, the correct or incorrect classification of the shooting technique uses the Support-Vector-Machine (SVM) method. The research compares two SVM kernels, linear and 3rd-degree polynomial kernels. The results of using the max, average, and variance features in the SVM classification with the polynomial kernel produce the highest accuracy of 94.4% compared to the linear kernel. The contribution of this paper is an IoT-based basketball shooting correctness classification system with superior accuracy compared to existing research.

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