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All Journal JURNAL BISNIS STRATEGI TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Inovasi Teknologi Pendidikan Jurnal Edukasi dan Penelitian Informatika (JEPIN) POROS TEKNIK Journal of Animation & Games Studies Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SINTECH (Science and Information Technology) Journal Jurnal ULTIMATICS CYBERNETICS Jurnal Keperawatan dan Fisioterapi (JKF) Jurnal Perempuan & Anak Joutica : Journal of Informatic Unisla JURNAL INOVASI DAN PENGABDIAN MASYARAKAT INDONESIA Makara Journal of Technology JGGAG (Journal of Games, Game Art, and Gamification) Jurnal Repositor
Hardianto Wibowo
Universitas Muhammadiyah Malang
Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Designing a QR Code Attendance System Using BYOD (Bring Your Own Device) Djamarullah, Ahmad Raihan; Nuryasin, Ilyas; Wibowo, Hardianto
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3522

Abstract

Attendance is an activity of collecting attendance data from each individual who attends events, work, and learning. The current application of attendance in certain companies, schools, or universities is still done manually using paper so it is considered less efficient and effective. Digitizing attendance activities can provide many benefits, such as making managing large amounts of attendance data easier. This is usually used in companies or schools. To reduce additional costs, this can be done by using a personal device as a medium for taking attendance, this can be called BYOD or Bring Your Own Device. The attendance that will be designed will use the user's smartphone or mobile device as a medium for taking attendance by scanning the QR code. The results of tests carried out using black box testing on mobile and web applications, shows that all the features contained in both applications are running according to their function. The use of QR Codes and also the implementation of BYOD can make it easier for users to take attendance. Apart from this, it is also easier for admins to manage user attendance data.
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%.
Classification of Skin Cancer Images Using Convolutional Neural Network with ResNet50 Pre-trained Model Minarno, Agus Eko; Lusianti, Aaliyah; Azhar, Yufis; Wibowo, Hardianto
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2156

Abstract

The skin, an astonishingly expansive organ within the human body, plays a pivotal role in safeguarding us against the environment's harsh elements. It acts as a formidable barrier, shielding our delicate internal systems from the scorching heat of the sun and the harmful effects of relentless exposure to light. Nevertheless, it is not impervious to damage, especially when subjected to excessive sunlight and the potentially hazardous ultraviolet (UV) radiation that accompanies it. Prolonged UV exposure can wreak havoc on our skin cells, potentially setting the stage for the development of skin cancer. This condition demands prompt and accurate diagnosis for effective treatment. To address the pressing need for swift and precise skin cancer diagnosis, cutting-edge technology has come to the fore in the form of deep learning systems. These sophisticated systems have been meticulously designed and trained to classify skin lesions autonomously with remarkable accuracy. The Convolutional Neural Network (CNN) architecture is a formidable choice for handling image classification tasks among the array of deep learning techniques. In a recent breakthrough study, a CNN-based model was meticulously constructed to explicitly classify skin lesions, leveraging the power of a pre-trained ResNet50 architectural model to augment its capabilities. This groundbreaking ResNet50 architecture was meticulously trained to classify seven distinct skin lesions, surpassing the performance of its predecessor, MobileNet. The results achieved in this endeavor are nothing short of impressive. The overall accuracy of the ResNet50 model stands at a commendable 87.42% when tasked with classifying the seven diverse classes within the dataset. Delving further into its proficiency, we find that the Top2 and Top3 accuracy rates soar to an astounding 95.52% and 97.86%, respectively, illustrating the model's exceptional precision and reliability.
UMM metaverse batik as a learning media to introduce nitik batik motifs in the Sonobudoyo Museum Minarno, Agus Eko; Faiz, Ahmad; Wibowo, Hardianto; Akbi, Denar Regata; Munarko, Yuda
Jurnal Inovasi Teknologi Pendidikan Vol. 12 No. 1 (2025): March
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jitp.v12i1.81821

Abstract

The exposure of Yogyakarta's Nitik Batik motifs is one of the important efforts to maintain and introduce Indonesia's cultural heritage to the younger generation. In this context, metaverse-based learning media is used as an innovative solution. This research discusses the implementation of metaverse-based learning media with an Extended Reality (XR) approach to introduce the Yogyakarta Nitik Batik motif. This research uses the Game Development Life Cycle (GDLC) development method to design a VR-based Batik museum virtual space, with black box testing and refinement testing to assess functionality and fun aspects. Involving 33 participants from visitors to the Sono Budoyo Batik exhibition in Yogyakarta, this study analyzed the data descriptive quantitative to develop recommendations for improving user experience and introducing Yogyakarta Nitik Batik culture through the metaverse. The test results showed that the virtual space of the Batik Museum passed the functional test without failure and had a feasibility rate of 86.1% in the category of "Excellent." These findings indicate that VR technology effectively introduces and preserves Batik culture, especially as an educational material in virtual media. This metaverse based learning media is anticipated to be an innovative step in introducing Yogyakarta's dotted Batik while offering a valuable immersive experience for users. Future research can be done by adding gamification to increase visitor involvement and optimizing multimedia aspects that have not been the main focus.
Implementation of Enhanced Re-Engineering on Trivia Game to Improve Immersion Adryan Nur, Fathur; Nuryasin, Ilyas; Wibowo, Hardianto
Journal of Games, Game Art, and Gamification Vol. 9 No. 2 (2024)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/jggag.v9i2.11332

Abstract

Trivia games are one type of educational game that is in great demand and can be used as a medium of entertainment as well as a learning medium. In order to make a game in the same segment more unique and immersion, software re-engineering techniques are used in the trivia game. In re-engineering the trivia game, three methods are used: Enhanced Re-Engineering as a software re-engineering method; Game Development Life Cycle (GDLC) in the development of the Hidden Object Trivia game; and MEEGA+ as a testing method for the trivia game and the Hidden Object Trivia game to determine the increase in immersion value of the two games. The results of re-engineering the Tech Geek Quiz game led to the successful integration of trivia and hidden object genres, resulting in the creation of the Guess The Tech Tool game. The test results using MEEGA+ with 30 respondents showed an increase in immersion values of 50.26% from 1.89 to 2.84 in the usability factor and 30.29% from 2.08 to 2.71 in the player experience factor. The results were taken from all dimensions of the questions that had been asked.
Comparing the Immersive Levels of Trivia Hidden Object Game Paper-based and Game Applications Jahsy, Ibnu; Ilyas Nuryasin; Hardianto Wibowo
Journal of Games, Game Art, and Gamification Vol. 10 No. 1 (2025)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/jggag.v9i2.11415

Abstract

The widespread development of the digital gaming industry in Indonesia began in 2000. The growth in interest in gaming has led to various objectives and encouraged research into several aspects and concepts of digital games. The aim of this research is to examine how significant the immersive differences are between paper-based game versions and applications/games among participants over 40 years old. The total average immersion obtained from the paper version is 4.43, while the application/game version is 5.85. For the average immersion per scale, the results of testing per scale show that the lowest average for the paper version is found in the Presence scale with 4.15, and the highest in Usability with 4.81. In the application/game version, the lowest average is found in the Focus Of Attention scale with a total of 5.55. The Usability scale scored 6.11, which is the highest result in the application/game version. The Interest scale is a category that has a significant difference between the paper and application/game versions with a margin of 1.6.
Analysis of the Combination of Naïve Bayes and MHR (Mean of Horner’s Rule) for Classification of Keystroke Dynamic Authentication Sari, Zamah; Chandranegara, Didih Rizki; Khasanah, Rahayu Nurul; Wibowo, Hardianto; Suharso, Wildan
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.839

Abstract

Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a nonattacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.
The Relationship Between Sitting Duration And Flexibility Hamstring Muscle In Employees At RSUD Ngimbang Wibowo, Hardianto; Rahmanto, Safun; Lubis, Zidni
JURNAL KEPERAWATAN DAN FISIOTERAPI (JKF) Vol. 6 No. 1 (2023): Jurnal Keperawatan dan Fisioterapi (JKF)
Publisher : Fakultas Keperawatan dan Fisioterapi Institut Kesehatan Medistra Lubuk Pakam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35451/jkf.v6i1.1712

Abstract

Some employees at Ngimbang Hospital work activities are carried out in a sitting position for a long duration and almost done every day, especially for office administration employees. This will pose a risk of musculoskeletal disorders, especially hamstring muscle flexibility. A decrease in muscle flexibility will affect body fitness which can affect the work productivity of these employees. This study aims to determine the relationship between sitting duration and hamstring muscle flexibility. This study used a Cross Sectional Study research design involving 32 employee samples. Sitting duration is the independent variable while the dependent variable is hamstring muscle flexibility. The results of the normality test using the Shapiro-wilk test showed that the sitting duration variable was worth 0.000 and the hamstring muscle flexibility variable was worth 0.799, meaning that there was one variable that was not normally distributed, while the correlation test using Spearman obtained a value of 0.000 (<0.05). It is concluded that there is a relationship between sitting duration and hamstring muscle flexibility in employees at Ngimbang Hospital. The longer the duration of sitting, the more hamstring muscle flexibility decreases.
Designing a QR Code Attendance System Using BYOD (Bring Your Own Device) Djamarullah, Ahmad Raihan; Nuryasin, Ilyas; Wibowo, Hardianto
ULTIMATICS Vol 16 No 1 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i1.3522

Abstract

Attendance is an activity of collecting attendance data from each individual who attends events, work, and learning. The current application of attendance in certain companies, schools, or universities is still done manually using paper so it is considered less efficient and effective. Digitizing attendance activities can provide many benefits, such as making managing large amounts of attendance data easier. This is usually used in companies or schools. To reduce additional costs, this can be done by using a personal device as a medium for taking attendance, this can be called BYOD or Bring Your Own Device. The attendance that will be designed will use the user's smartphone or mobile device as a medium for taking attendance by scanning the QR code. The results of tests carried out using black box testing on mobile and web applications, shows that all the features contained in both applications are running according to their function. The use of QR Codes and also the implementation of BYOD can make it easier for users to take attendance. Apart from this, it is also easier for admins to manage user attendance data.
User Classification Based On Mouse Dynamic Authentication Using K-Nearest Neighbor Chandranegara, Didih Rizki; Ashari, Anzilludin; Sari, Zamah; Wibowo, Hardianto; Suharso, Wildan
Makara Journal of Technology Vol. 27, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Mouse dynamics authentication is a method for identifying a person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such mouse movements can be used as the basis for security. The development of technology is followed by the urge to keep private data safe from hackers. Therefore, increasing the accuracy of user classification and reducing the false acceptance rate (FAR) are necessary to improve data security. In this study, we propose to combine the K-nearest neighbor method and simple random sampling and obtain a sample from a dataset to improve the classification of users and attackers. The results show that our proposed method has high accuracy for implement to practical system and reports the best results than previous research with a FAR of 0.037. Therefore, this method can be implemented in a real login system. The high false rejection rate of our proposed method will not be a problem because the most important thing in the login system is denying the attacker system access.
Co-Authors Abims Fardiansa Achmadi, Taufan Reza Adryan Nur, Fathur Agus Eko Minarno Ahmad Faiz Ahmad Faiz, Ahmad Akbi, Denar Regata Ali Akbar Montazeri Ali Akbar Montazeri Andriyani, Vivi Aris Widayati Ashari, Anzilludin Bayu Fajar Pratama BAYU PRASTOWO Chandra Sebastian Chandranegara, Didih Rizki Christian Sri Kusuma Aditya Dani Harmanto Dani Harmanto Daroe Iswatiningsih Dewantoro, Muhammad Bagas Diah Ayu Fitriani Djamarullah, Ahmad Raihan Eko Budi Cahyono Eko Mulyanto Yuniarno Fachrunnisa Firdausi Firdausi, Fachrunnisa Firmansyah, Tino Fitriani, Diah Ayu Hapzi Ali Harmanto, Dani Hazmi Rizky Heni Pujiastuti Jahsy, Ibnu Karyati, Rina Khasanah, Rahayu Nurul L. Yasril Imam Lailatul Huasniah Lailatul Husniah Lailatul Husniah Lubis, Zidni Lusianti, Aaliyah Matahari Bhakti Nendya, Matahari Bhakti Mauridhi Hery Purnomo Mochammad Yusuf Fachroni Moh Ridwan Multohadi Hamzaturrazak Naser Jawas, Naser Norhabibah, Siti Novidianto, Raditya Nuryasin, Ilyas Raditya Novidianto Raffi Ainul Afif Rahayu Nurul Khasanah Rina Karyati Sabrina Nurul Ubay Safun Rahmanto Sari, Zamah Siti Norhabibah Sofyan Arifianto Sumadi, Fauzi Dwi Setiawan Syaifuddin Syaifuddin Taufan Reza Achmadi Tino Firmansyah Ubay, Sabrina Nurul Vitanti, Vizza Dwi Vivi Andriyani Wahyu Andhyka Kusuma Wicaksono, Galih Wasis Wildan Suharso Wildan Suharso Yuda Munarko Yufis Azhar Zamah Sari