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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.
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Articles 10 Documents
 1 
Search results for , issue "Vol. 8, No. 2, May 2023" : 10 Documents clear
Assessing The Quality and Prioritize Improvements of E-government Using E-govqual and Importance Performance Analysis Prasetyo, Beny; Adnan, Fahrobby; Darmawan, Jihan Tsanisya
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.v8i2.1609

Abstract

The Gresik Regency Government in 2020 has made new innovations in the development of E-Government as a form of implementing Presidential Regulation Number 3 of 2003 Regarding National Policy and Strategy for E-Government Development. Through the launch of the Pelayanan Online Pendaftaran Administrasi Kependudukan Gresik (Poedak) managed by the Population and Civil Registration Service. Poedak service aims to make it easier for the people of Gresik Regency to take care of population files. This study uses the E-GovQual method to measure the extent to which the quality of Poedak services is based on what users perceive, and the IPA method maps attributes according to improvement priorities. This study showed that the average score on the performance level assessment on all E-GovQual variables had a score of 3.13. Then the average score on the importance assessment on all E-GovQual variables was 3.08. So that the value of the gap between performance and importance can be known by 0.05. The results of the conformity analysis between the performance level and the importance level have a conformity value of >100% which is 102%. Thus, the overall performance of the Poedak service is good and meets the expectations or interests of users. There are 4 attributes that are included in quadrant 1, namely the quadrant with the main priority scale, namely an adequate response format (FIAA2), providing timely service (RA2), loading speed time on the website (RA5), and ease of understanding information content (CAIA6).
Integration of Fuzzy C-Means and SAW Methods on Education Fee Assistance Recipients Fadlil, Abdul; Riadi, Imam; Mulyana, Yana
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.v8i2.1636

Abstract

Every year, UMTAS gets a quota for KIP tuition fee assistance provided by KEMDIKBUD. This program is intended for high school / vocational/equivalent graduates from poor and vulnerable families. The evaluation results of its implementation have problems, including the number of applicants exceeding the quota given by KEMDIKBUD and some applicants coming from well-off families. This research uses the fuzzy c-means method for data clustering and the SAW method for ranking. The results of data grouping using the fuzzy c-means method obtained the first cluster (C1) of 72 data and the second cluster (C2) of 119 data. Group C1 is closer to the provisions of aid recipients (eligible) compared to data group C2 (ineligible) because Data C1 consists of 100% DTKS recipients, 50% KIP and KKS card owners, 100% parental income <750,000, 40.28% parental dependents >=2 people and 29.17% applicants with achievements. 72 registrant data included in Data C1 are then ranked using the SAW technique to get weights, and 30 data with the highest weight will be used as a decision on recipients of KIP-Kuliah Education fee assistance according to the quota provided. The optimization of Fuzzy C-Means with SAW methods in selecting recipients of education fee assistance is objective and right on target.
Visual Analysis Based on CMY and RGB Image Cryptography Using Vigenere and Beaufort Cipher Atika Sari, Christy; Utomo, Danang Wahyu; Doheir, Mohamed A S
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.v8i2.1664

Abstract

The achievement of visual aspects and image security often cannot meet visibility standards, for example the acquisition of PSNR and UACI NPCR values. To increase security, this research has implemented a combination of the Vigenere cipher and Beaufort and the use of Fibonacci as a randomizer. The combination of the Vigenere Cipher and Beaufort Cipher substitution algorithms with the Fibonacci technique can be applied to encrypt color images in RGB and CMY, with a size of 256x256 pixels and in .bmp format. The Fibonacci cut-off value used in this study is 10000. The highest entropy value of the cipher image peppers.bmp is 7,991. The lowest PSNR cipher image value is accordion.bmp where for RGB it is 5,439 dB and for CMY it is 5,403 dB. accordion.bmp's highest UACI value is 44.018% for RGB and 44.312% for CMY. The NPCR value in the airplane.bmp image has the highest value in RGB of 99.792% and for CMY the highest value is in splash.bmp with a value of 99.798%. Evaluation of the decryption results shows that the decryption process can run perfectly as indicated by the values of MSE=0, PSNR=inf, UACI and NPCR=0%. Therefore, encrypt and decrypt was proven that the results obtained in the visual aspect are very good.
Comparison of CNN’s Architecture GoogleNet, AlexNet, VGG-16, Lenet -5, Resnet-50 in Arabic Handwriting Pattern Recognition Nugraha, Gibran Satya; Darmawan, Muhammad Ilham; Dwiyansaputra, Ramaditia
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.v8i2.1667

Abstract

The Arabic script is written from right to left and consists of 28 characters, with no capital or lowercase letters. The Arabic script has several orthographic and morphological properties that make handwriting recognition of the Arabic script challenging. In addition, one of the biggest challenges in recognizing Arabic script patterns is the different handwriting styles and characters of each person's writing. The authors propose a study to compare the accuracy of handwriting pattern recognition in Arabic script which has been done previously by comparing five CNN architectures, namely GoogleNet, AlexNet, VGG-16, LeNet-5, and ResNet-50. Considering that previous research has not obtained excellent accuracy. The number of datasets used is 8400 image data and the most optimal comparison of testing and training data is 80:20. Based on the research that has been done, there are several things that the author can conclude. The model is made using 64 filters for each convolution layer because the optimal size is used for 5 architectures, kernel size is 3x3, neurons is 128, dropout weight is 50% to reduce overfitting, learning rate is 0.001, image size is 64x64, the normalization method with the ReLU activation function, and 1-dimensional input image (grayscale), and with a comparison of testing and training data of 80:20. The VGG-16 architectural model is the architecture that gets the highest score, namely 83.99%. This can have good potential to be developed as a medium for learning Arabic script.
Stand-Alone Hybrid PV System by Using The Bypass Converter Topology to Optimize the Reliable of Device Prasojo, Fadillah; Mardiayah, Nur Alif; Hidayat, Khusnul
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.v8i2.1669

Abstract

One of the applications of DC-DC converters in photovoltaic-battery hybrid systems is a two-way converter used for battery charging. The power supplied to the two-way converter experiences twice the power lost during the battery charging process. Therefore, it is necessary to arrange a phovoltaic-battery hybrid system topology so that only one stage of power conversion occurs when charging the battery so that the power loss is smaller. The proposed topology of this system uses three DC-DC converters connected to a battery and a DC bus. The one-way converter used in this system allows cross-connection between other DC-DC converters. Two one-way converters connect the phovoltaics to the DC bus and the photovoltaics to the battery, and the other one-way converter connects the battery to the DC bus. The purpose of using a one-way converter for charging the battery is called a bypass converter so that charging the battery does not go through two power conversions which cause twice the lost power. To make the proposed system more reliable, an inverter is added to the self-contained photovoltaic-battery hybrid system. Therefore, a control system is needed to maintain the DC bus voltage as input to the inverter using a double-loop control system. The two-loop Proportional-Integral control system is used for the DC electricity section while the Proportional-Resonant control system is used as an inverter control to maintain the balance of AC power. The results of system testing using Simulink/Matlab simulations show that the proposed topology uses a one-way converter capable of carrying out the battery charging process and can control the flow of power while maintaining DC and AC voltages.
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

Abstract

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%.
Public Opinion Analysis of Presidential Candidate Using Naïve Bayes Method Firdaus, Asno Azzawagama; Yudhana, Anton; Riadi, Imam
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.v8i2.1686

Abstract

Elections for president and vice president will take place in 2024. Heading into the election, promoted candidates were vying for public sympathy. People often discussed as presidential candidates are Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto. Therefore, we need a way to predict potential candidates and voter demographics from public opinion on Twitter using sentiment analysis. One of his methods commonly used to classify sentiment analysis is Naive Bayes. This study used the naive Bayes classifier and the TF-IDF extraction function to add weights to the text. Use the scikit-learn Python library to help determine the polarity of negative and positive sentiment classes in your dataset. The datasets used were Twitter datasets acquired from October to December 2022, for a total of 15,000 datasets. The best test scenario obtained by splitting the test and training data is 70% test data and 30% training data, with the highest accuracy generated from the 95% Ganjar dataset. Using the Anies, Ganjar, and Prabowo test data, the positive mood scores for each candidate were 833, 77, and 524, respectively, while the negative mood scores were 637, 1423, and 976, respectively. The test was performed using a confusion matrix and k-fold cross-validation, and the best results were obtained on the Ganjar data set. That is a confusion matrix of 94.93% and a k-fold cross-validation of 94.46%. The lowest f1-score for the positive class is 67% for the Anies dataset and 27% for the negative class for the Ganjar dataset.
Forecasting Model for Lighting Electricity Load with a Limited Dataset using XGBoost Abdurohman, Maman; Putrada, Aji Gautama
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.v8i2.1687

Abstract

Energy forecasting is an important application of machine learning in renewable energy because it is used for operational, management, and planning purposes. However, using the electricity load dataset during COVID-19 is a research challenge in the forecasting model due to the limited dataset and non-stationarity. This paper proposes an extreme gradient boosting (XGBoost) forecasting model for a limited dataset. Forecasting models require large amounts of data to create high-accuracy models. We conduct research using the PT Biofarma office electricity usage dataset for eight months during the COVID-19 period. Because office activities were limited during the pandemic, the datasets obtained were few. Several methods are used for modeling limited datasets, namely XGBoost, multi-layer perceptron (MLP), autoregressive integrated moving average (ARIMA), and long short-term memory (LSTM). We have conducted several experiments using a limited dataset with these four methods. The test results with the t-test show that the electricity load data for work-from-office (WFO) and work-from-home (WFH) periods have a significant average difference. Then the test results with the augmented Dickey–Fuller (ADF) test show that our data is non-stationary. Compared to the benchmark method, the XGBoost method shows the best forecasting performance with mean absolute percentage error (MAPE), root mean squared error (RMSE), mean absolute error (MAE), and R2 of 0.48, 5.00, 3.09, and 0.61 respectively.
Leveraging Text-Mining Techniques On Electronic Medical Records to Analyze National Drug-insured Medication Use Wibawa, Adhi Dharma; Ramadhani, Prio Adi; Buntoro, Ghulam Asrofi; Hariadi, Ridho Rahman; Siswanto, Putri Alief; Sabilla, Shoffi Izza
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.v8i2.1695

Abstract

Processing electronic medical record (EMR) data has become a common practice among scientists for extracting valuable insights and studying diseases. Given the large volumes of text data in EMRs, efficient computerized text-mining techniques are necessary. As academics, we recognize that drug-used analysis from EMR data in Indonesia is currently limited. This study focuses on obtaining meaningful insights from EMR data to make positive recommendations for hospitals. The proposed method uses pattern-based Regular Expressions (regex) to extract drug names and a Levenshtein distance algorithm to check their compatibility. We developed the pattern based on analyzing Indonesia EMR data. The extracted drug names were compared to a list of selected drugs (National Drug-Insured/Fornas) that are required and must be provided at healthcare facilities in Indonesia. The Levenshtein distance threshold was set to two to decide whether the extracted drug names belonged to nationally drug-insured or not. Only about 11.09 – 16.11% of medications given by doctors are listed in the Fornas drug list. Between 2019 and 2021, there was an inaccuracy in the writing of prescriptions for Fornas drugs, with as many as 57.53% to 63.21% of drug names being written incorrectly. The results of this study indicate that the Levenshtein distance algorithm has promising potential for implementation in the Ministry of Health of Indonesia, with a precision rate of 97.07%.
Evolutionary Algorithm in Game – A Systematic Review Armanto, Hendrawan; Rosyid, Harits Ar; Muladi; Gunawan
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.v8i2.1714

Abstract

Research in the game field is increasingly numerous and challenging. The high interest in research on games is influenced by public awareness of the importance of games in developing ways of thinking, although it is undeniable that many people only pursue pleasure in playing games. In the past, not much games research has influenced into topics such as artificial intelligence, education, or other computer topics. But now games are having a tremendous impact on these topics. In fact, not infrequently games are used in various areas of life. Right now, artificial intelligence is an integral part of the game. If before, it was only used for creating an enemy. Right now artificial intelligence can affect various things, starting from assets, game difficulty levels, non-player characters (NPC), and even bots (AI agents) to run player characters. The complexity of artificial intelligence which is getting higher and higher requires a good optimization algorithm. The evolutionary algorithm is one of the optimization algorithms, even though it cannot find the best one, with the high speed it can find a good solution. Through this paper review, good conclusions are drawn regarding the use of evolutionary algorithms, representations made, fitness functions used, ways to prove a success, to what topics should be studied further.

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