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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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Game Development "Kill Corona Virus" for Education About Vaccination Using Finite State Machine and Collision Detection Andi; Juan Charles; Octara Pribadi; Carles Juliandy; Robet
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1470

Abstract

COVID-19 is a disease caused by the coronavirus and causes the main symptoms in the form of respiratory problems. One way to overcome the COVID-19 pandemic is through the vaccination process. However, in practice, the public is still not educated about the importance of vaccination in preventing coronavirus infection, so it is necessary to develop a game that provides education to the public to vaccinate. This study chose games as educational media because there are many game enthusiasts and the delivery of education through games is more memorable than on other platforms. This study uses the Game Development Life Cycle (GDLC) method in the game development stage. In addition, to create intelligent coronavirus enemy NPC characters in this study, Finite State Machine (FSM) and Collision Detection methods will be implemented to detect the accuracy of players' shots. The results were obtained in the form of a game "Kill Corona Virus" which is used as a medium of education for the public about the importance of vaccination. Based on the results of the tests carried out, it was found that the implementation of the Collision Detection method in the game in detecting collisions was appropriate and quite accurate and the Finite State Machine method succeeded in creating coronavirus enemy NPCs with appropriate states. In addition, based on the results of processing respondents' answers, it is known that the ”Kill Corona Virus” game that was built can convey vaccination education messages well and make people interested in vaccinating.
KNN Algorithm for Identification of Tomato Disease Based on Image Segmentation Using Enhanced K-Means Clustering Nasution, Amir Saleh; Alvin, Alvin; Siregar, Ana Tince; Sinaga, Monica Sari
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1486

Abstract

Image segmentation is an important process in identifying tomato diseases. The technique that is often used in this segmentation is k-means clustering. One of the main problems in this technique is the case of local minima, where the cluster that is formed is not suitable due to the incorrect selection of the initial centroid. In image data, this case will have an impact on poor segmentation results because it can erase parts that are actually important to be lost or there is still background in the recognition process, which has an impact on decreasing accuracy results. In this research, a method for image segmentation will be proposed using the k-means clustering algorithm, which has been added with the cosine similarity method as the proposed contribution. The use of the cosine method will determine the initial centroid by calculating the level of similarity of each image feature based on color and dividing them into several categories (low, medium, and high values). Based on the results obtained, the proposed algorithm is able to segment and distinguish between leaf and background images with good results, with the kNN reaching a value of 94.90% for accuracy, 99.50% for sensitivity, and 93.75% for specificity. The results obtained using the kNN method with k-means segmentation obtained a value of 92.46% for accuracy, 96.30% for sensitivity, and 91.50% for specificity. The results obtained using the kNN method without segmentation obtained a value of 90.22% for accuracy, 93.30% for sensitivity, and 89.45% for specificity.
Javanese Character Recognition Based on K-Nearest Neighbor and Linear Binary Pattern Features Susanto, Ajib; Mulyono, Ibnu Utomo Wahyu; Sari, Christy Atika; Rachmawanto, Eko Hari; Ali, Rabei Raad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1491

Abstract

Javanese script (Hanacaraka) is one of the cultures owned by Indonesia. Javanese script is found in temples, inscriptions, cultural and prehistoric sites, ancient Javanese manuscripts, Gulden series banknotes, street signage, and palace documents. Javanese script has a form with an article, and the use of reading above the script is a factor that affects the character detection process. Punctuation marks, clothing, Swara script, vowels, and consonants are parts of the script that are often found in Javanetest scripts. Preserving Javanese script in the digital era, of course, must use technology that can support the digitization of Javanese script through the script detection process. The concept of script image is the image of Javanese script in ancient manuscripts. The process of character detection using certain techniques can be carried out to extract characters so that they can be read. Detection of Javanese characters can be found by finding a testing image. Here, we had been used 10 words images consisting of 3 to 5 syllables with the vowel aiu. Dataset process by Linear Binary Pattern (LBP) feature extraction, which is used to characterize images and describe image textures locally. LBP has been used in r=4 and preprocessing is also done by thresholding with d=0.3. This process can be done using the K-Nearest Neighbor algorithm. In 10 datasets of Javanese script words, an average accuracy value of 90.5% was obtained. The accuracy value of 100% is the highest and 50% is the lowest.
Optimization Improvement Using Pi Controller to Reach CCCV Method in Lead Acid Battery Load Irianto; Rachma Prilian Eviningsih; Farid Dwi Murdianto; Amir Muhyidin
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1496

Abstract

Solar energy can produce electrical energy with the help of photovoltaics so as to produce sufficient or even excessive supply to the electrical load. Therefore, it is necessary to store electrical energy (battery) from the excess unused energy. However, in the process of charging the battery, it takes a long time to fully charge the battery capacity and damage often occurs due to excessive voltage used. This can reduce battery life. The characteristics of the battery need to be considered so that the charging process can be carried out in accordance with the required provisions. The existence of the CCCV method can speed up the battery charging process with a constant current of 20% of the nominal current of the lead acid battery. To avoid overvoltage, the constant voltage method can anticipate the occurrence of damage. Utilization CUK Converter as charging can reduce output voltage ripple. The PI control on the CUK Converter produces a constant voltage of 13.8 Volts and a constant current of 1.44 Ampere. The average error generated by this system is 0.14%.
Adoption of Mobile Learning at Universities Using the Extended Technology Acceptance Model Misbahul Aziz; Edwin Pramana; Hartarto Junaedi
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1522

Abstract

This study aims to contribute to the proof of factors likely to determine the success of M-learning adoption based on previous research.  This is done because there are many different theoretical models proposed.  However, there is not yet a model that can be generally accepted as an established theoretical model for the adoption of M-learning in universities.  This research is expected to make a significant contribution to the development of a better theoretical understanding of the determinants that influence the adoption of M-learning using the Technology Acceptance Model (TAM).  To collect the data, researchers distributed questionnaires to respondents using google forms.  Forms are distributed via WhatsApp and Telegram.  The data used was 515 M-learning users.  Theoretical model research was carried out with Structural Equation Model (SEM) analysis, then SPSS and Amos as support for analysis.  There are six factors that determine the results of acceptance of M-leaning adoption in this study, namely Social Influence, Perceived Enjoyment, Facilitating Condition, Self-Efficacy, Perceived Usefulness, and Perceived Ease of Use.  The five factors that show positive and significant relationships are Social Influence, Perceived Enjoyment, Self-Efficacy, Perceived Usefulness, and Perceived Ease of Use.  Perceived Usefulness has the first strongest positive and significant value, and then Social Influence has the second strongest value.  Each factor has a medium influence value on Behavioral Intention.  That factor is the most influential in the application of M-learning in universities.
Robot Ankle Foot Orthosis with Auto Flexion Mode for Foot Drop Training on Post-Stroke Patient in Indonesia Dimas Adiputra; Ubaidillah; Ully Asfari; Hari Sulistiyo Budi Waspada; Reza Humaidi; Bagas Wahyu Prakoso; Andi Nur Halisyah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1533

Abstract

Robot Ankle Foot Orthosis (AFO) has been proven to assist the gait impairment, such as the foot drop. However, development challenge is still remains, such as the trade-off between complexity, functionality and cost. High functionality resulted in high cost, bulky, and complex device. But affordability and simplicity may decrease functionality. Therefore, this research proposed a robot AFO, which has the necessary function of auto dorsi-plantarflexion so it can keep the affordability and simplicity. The robot AFO consists of structure, electronics part and algorithm. The structure is custom made according to the user’s anatomy. A brushless DC (BLDC) motor, Force-Sensing Resistor (FSR) and microcontroller builds the electronic parts. The BLDC motor actuates the flexion, while the FSR detects the gait phase to determine the action. Both are integrated by the microcontroller with the P control algorithm that commands the BLDC motor to generate necessary torque so it rotates in a constant speed. A functionality test has been carried out on the robot AFO, where the robot AFO perform a dorsi-plantarflexion continuously in three conditions, such as no load, 1 Kg load, and foot load. The robot AFO successfully performed a constant velocity rotation in both directions, in all conditions. In the case of 1 Kg load, the maximum angular speed is 0.7 rad/s dorsiflexion and -1.8 rad/s plantarflexion. The torque keeps increasing and decreasing from -0.3 Nm to 4 Nm to keep the angular velocity. The result shows that the robot AFO can perform the necessary function to assist the foot drop training. Functionality test on the gait detection has also been done where it shows that the robot AFO can detect the four gait phases accurately. The robot AFO has been tested and future study should test the robot on a real post-stroke patient to see the effect of the gait control in reality.
Electronic Medical Record Data Analysis and Prediction of Stroke Disease Using Explainable Artificial Intelligence (XAI) Yuri Pamungkas; Adhi Dharma Wibawa; Meiliana Dwi Cahya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1535

Abstract

The deficiency of oxygen in the brain will cause the cells to die, and the body parts controlled by the brain cells will become dysfunctional. Damage or rupture of blood vessels in the brain is better known as a stroke. Many factors affect stroke. These factors certainly need to be observed and alerted to prevent the high number of stroke sufferers. Therefore, this study aims to analyze the variables that influence stroke in medical records using statistical analysis (correlation) and stroke prediction using the XAI algorithm. Factors analyzed included gender, age, hypertension, heart disease, marital status, residence type, occupation, glucose level, BMI, and smoking. Based on the study results, we found that women have a higher risk of stroke than men, and even people who do not have hypertension and heart disease (hypertension and heart disease are not detected early) still have a high risk of stroke. Married people also have a higher risk of stroke than unmarried people. In addition, bad habits such as smoking, working with very intense thoughts and activities, and the type of living environment that is not conducive can also trigger a stroke. Increasing age, BMI, and glucose levels certainly affect a person's stroke risk. We have also succeeded in predicting stroke using the EMR data with high accuracy, sensitivity, and precision. Based on the performance matrix, PNN has the highest accuracy, sensitivity, and F-measure levels of 95%, 100%, and 97% compared to other algorithms, such as RF, NB, SVM, and KNN.
PID Controllers Performance On Dual Axis Tracking With Tetrahedron Based Sensor Melinda; Andri Novandri; Yuwaldi Away
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1549

Abstract

This study compares control systems applied to a dual-axis tetrahedron-based sensor tracker. A tetrahedron-based sensor is a tracking sensor that can detect the coordinates of a light source. This study aims to determine a control system that can control sensors with high accuracy and precision and has a fast-tracking ability. Tests are carried out periodically by providing light at certain coordinates. After carrying out the testing and analysis process, it is concluded that the P controller is a better control system than the other controllers. This controller can control sensors with high accuracy and precision compared to PI, PD, and PID control systems. The P controller can also control the sensor to move towards the light coordinates with a travel time of 1.6 seconds on the X-axis and 3.1 seconds on the Y-axis, with a MAE value of 1.1 on the X-axis and 0.3 on the Y-axis. While the RSME value obtained is 1.33 on the X-axis and 0.55 on the Y-axis.
Performance Evaluation of LoRa in Farm Irrigation System with Internet of Things Kurniawan Dwi Irianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1551

Abstract

Long Range (LoRa) Communication is one of the emerging Internet of Things (IoT) technologies and has been widely discussed by researchers. LoRa is also part of the Low Power Wide Area Networks (LPWAN) technology where this technology focuses on communication systems on energy efficiency, wide coverage, low data rates, and long battery life. LoRa uses industrial, scientific, and medical (ISM) radio frequencies. These frequencies can be used for free without paying for a license. Theoretically and under ideal conditions, the LoRa range can reach < 3 km in urban areas and > 3 km in rural areas. However, only a few studies discuss the evaluation and analysis of LoRa performance, which is implemented in the real world with particular case studies. This article aims to evaluate and analyze the performance of LoRa, which is applied to a case study of an IoT-based agricultural irrigation system. Several parameters will be assessed and analyzed, including distance, received signal strength indication (RSSI), spreading factor, coding rate, power transmission, and packet delivery ratio (PDR). Experimental and measurement results show that LoRa can transmit data packets up to a distance of 2.5 km but with a very low PDR rate of around 5-7%. The results also show that LoRa can work optimally if the distance is > 1 km with a PDR rate of about 70-100%.
Image Captioning using Hybrid of VGG16 and Bidirectional LSTM Model Yufis Azhar; M. Randy Anugerah; Muhammad Al Reza Fahlopy; Alfin Yusriansyah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1568

Abstract

Image captioning is one of the biggest challenges in the fields of computer vision and natural language processing. Many other studies have raised the topic of image captioning. However, the evaluation results from other studies are still low. Thus, this study focuses on improving the evaluation results from previous studies. In this study, we used the Flickr8k dataset and the VGG16 Convolutional Neural Networks (CNN) model as an encoder to generate feature extraction from images. Recurrent Neural Network (RNN) uses the Bidirectional Long-Short Term Memory (BiLSTM) method as a decoder. The results of the image feature extraction process in the form of feature vectors are then forwarded to Bidirectional LSTM to produce descriptions that match the input image or visual content. The captions provide information on the object’s name, location, color, size, features of an object, and surroundings. A greedy Search algorithm with Argmax function and Beam-Search algorithm are used to calculate Bilingual Evaluation Understudy (BLEU) scores. The results of the evaluation of the best BLEU scores obtained from this study are the VGG16 model with Bidirectional LSTM using Beam Search with parameter K = 3 and the BLEU-1 score is 0.60593, so this score is superior to previous studies.

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