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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 Repositor 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)

Hardianto Wibowo

Universitas Muhammadiyah Malang

Author-ID : 556099

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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Articles

Title

Deteksi Gerak Otot Frontalis Berbasis Citra 3 Dimensi Menggunakan Gray Level Co-Occurrence Matrix (GLCM) Wibowo, Hardianto; Hery Purnomo, Mauridhi; Mulyanto Yuniarno, Eko
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 1, No 2, August-2016
Publisher : Universitas Muhammadiyah Malang

Ekspresi wajah atau mimik merupakan salah satu dari hasil gerak otot pada wajah. Dalam kamus besar bahasa Indonesia, ekspresi merupakan pengungkapan atau proses menyatakan, yaitu memperlihatkan atau menyatakan maksud, gagasan perasaan dan lain sebagainya. Ekspresi wajah atau mimik dipengaruhi oleh saraf tujuh atau nervuse facialis. Dalam penelitian yang dilakukan paul ekman didapat sebuah standarisasi ekspresi dalam format pergerakkan yang disebut dengan Facial Action Coding System (FACS). Dalam penelitiannya paul ekman menyatakan enam ekspresi dasar yaitu bahagia, sedih, terkejut, takut, marah dan jijik. Dalam anatomy otot, bahwa setiap otot yang bergerak pasti terjadi kontraksi, dan pada saat terjadi kontraksi, otot akan mengembang atau mengelembung. Otot dibagai menjadi tiga bagian yaitu origo dan insersio sebagai ujung otot dan belly sebagai titik tengah otot, jadi setiap terjadi gerakkan maka otot bagian beli akan mengembang atau menggelembung. Teknik pengambilan data yaitu dengan merekam data dalam bentuk 3D, setiap terjadi kontraksi maka otot bagian beli akan mengelembung dan data inilah yang akan diolah dan dibandingkan. Dari pengolahan data ini akan didapat kekuatan maksimum kontraksi yang akan dipakai sebagai acuan untuk besaran pergeseran otot khususnya pada otot frontalis. Dalam deteksi pergerakkan akan menggunakan metode gray level co-occurrence matrix (GLCM), dan akan didapatkan pula besaran pergeseran otot secara maksimal. Dari hasil pengujian didapatkan nilai pergeseran pergerakkan otot sebesar 1,367 4,460.

Gamification And GDLC (Game Development Life Cycle) Application For Designing The Sumbawa Folklore Game âThe Legend Of Tanjung Menangis (Crying Cape)â Husniah, Lailatul; Pratama, Bayu Fajar; Wibowo, Hardianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 4, November 2018
Publisher : Universitas Muhammadiyah Malang

Sumbawa is popularly known as one of the regions in Indonesia, having a well- known folklore among the Sumbawa people, entitled the legend of Tanjung Menangis (Crying Cape). However, Tanjung Menangis is commonly recognized for its beauty than the stories contained. Therefore, a research is carried out by developing a game that is employed as a tool to introduce the story of Tanjung Menangis Legend as effort to preserve the original story of the mainland Sumbawa. The media game is chosen due to its favoured technology by children and adolescent as the target users of this research. This study applies Game Development Life Cycle (GDLC) method in the development stage which consists of several stages includinng: pre-production, production, testing, and post-production by adding an element of gamification. The game is tested on students at Labangka Elementary School in Sumbawa district in an age range of 10-15 years. After playing the game, the majority of respondents states that students gain knowledge about the Legend of Tanjung Menangis as reported from the results of the t- test with a probability value of 7.369x10-41, which is far below the value of Î± = 0.05. This result means that there was an increase in user knowledge of application. The test results also showed that all respondents agreed that the game of The Legend of Tanjung Menangis was used as one of the media used to introduce the story of the original Sumbawa people. In addition, the testing results as conducted with playtesting and gameflow test achieved good grades, with a range of values 4.5-4.81 of the seven elements tested, including: Concentration, Challenge, Player Skills, Control, Clear Goals, Feedback, and Immersion.

Performance Comparisson Human Activity Recognition Using Simple Linear Method Kusuma, Wahyu Andhyka; Sari, Zamah; Minarno, Agus Eko; Wibowo, Hardianto; Akbi, Denar Regata; Jawas, Naser
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Human activity recognition (HAR) with daily activities have become leading problems in human physical analysis. HAR with wide application in several areas of human physical analysis were increased along with several machine learning methods. This topic such as fall detection, medical rehabilitation or other smart appliance in physical analysis application has increase degree of life. Smart wearable devices with inertial sensor accelerometer and gyroscope were popular sensor for physical analysis. The previous research used this sensor with a various position in the human body part. Activities can classify in three class, static activity (SA), transition activity (TA), and dynamic activity (DA). Activity from complexity in activities can be separated in low and high complexity based on daily activity. Daily activity pattern has the same shape and patterns with gathering sensor. Dataset used in this paper have acquired from 30 volunteers. Seven basic machine learning algorithm Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosted and K-Nearest Neighbor. Confusion activities were solved with a simple linear method. The purposed method Logistic Regression achieves 98% accuracy same as SVM with linear kernel, with same result hyperparameter tuning for both methods have the same accuracy. LR and SVC its better used in SA and DA without TA in each recognizing.

ClusterMix K-Prototypes Algorithm to Capture Variable Characteristics of Patient Mortality With Heart Failure Novidianto, Raditya; Wibowo, Hardianto; Chandranegara, Didih Rizki
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 2, May 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i2.1209

Cardiovascular Disease (CVD) is one of the leading causes of many death worldwide, leading to heart failure incidence. The World Health Organization (WHO) says the number of people dying from cardiovascular disease from heart failure each year has an average of 17,9 million deaths each year, about 31 percent of the total deaths globally. Identify the mortality factors of heart failure patients that need to be formed, which reduces death due to heart failure. One of them is by using variable mortality due to heart failure by applying the k-prototypes algorithm. The clustering result is formed 2 clusters that are considered optimal based on the highest silhouette coefficient value of 0,5777. The results of the study were carried out as segmentation of patients with variable mortality of heart failure patients, which showed that cluster 1 is a cluster of patients who have a low risk of the chance of mortality due to heart failure and cluster 2 is a cluster of patients with a high risk of mortality due to heart failure. The segmentation is based on the average value of each variable of heart failure mortality factor in each cluster compared to normal conditions in serum creatine variables, ejection fraction, age, serum sodium, blood pressure, anemia, creatinine phosphokinase, platelets, smoking, gender, and diabetes.

Deteksi Gerak Otot Frontalis Berbasis Citra 3 Dimensi Menggunakan Gray Level Co-Occurrence Matrix (GLCM) Hardianto Wibowo; Mauridhi Hery Purnomo; Eko Mulyanto Yuniarno
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 1, No 2, August-2016
Publisher : Universitas Muhammadiyah Malang

Ekspresi wajah atau mimik merupakan salah satu dari hasil gerak otot pada wajah. Dalam kamus besar bahasa Indonesia, ekspresi merupakan pengungkapan atau proses menyatakan, yaitu memperlihatkan atau menyatakan maksud, gagasan perasaan dan lain sebagainya. Ekspresi wajah atau mimik dipengaruhi oleh saraf tujuh atau nervuse facialis. Facial Action Coding System (FACS) standardiasi ekspresi dalam format pergerakan enam ekspresi dasar, yaitu bahagia, sedih, terkejut, takut, marah dan jijik. Dalam otot, bahwa setiap otot yang bergerak pasti terjadi kontraksi, dan pada saat terjadi kontraksi, otot akan mengembang atau menggelembung. Otot dibagai menjadi tiga bagian, yaitu origo dan insersio sebagai ujung otot dan belly sebagai titik tengah otot, jadi setiap terjadi gerakkan maka otot bagian belly akan mengembang atau menggelembung. Teknik pengambilan data yaitu dengan merekam data dalam bentuk 3D, setiap terjadi kontraksi maka otot bagian belly akan menggelembung dan data inilah yang akan diolah dan dibandingkan. Dari pengolahan data ini akan didapat kekuatan maksimum kontraksi yang akan dipakai sebagai acuan untuk besaran pergeseran otot khususnya pada otot frontalis. Dalam deteksi pergerakan akan menggunakan metode Gray Level Co-occurrence Matrix (GLCM), dan akan didapatkan pula besaran pergeseran otot secara maksimal. Dari hasil pengujian didapatkan nilai pergeseran pergerakan otot sebesar 2.928.

Gamification And GDLC (Game Development Life Cycle) Application For Designing The Sumbawa Folklore Game ”The Legend Of Tanjung Menangis (Crying Cape)” Lailatul Husniah; Bayu Fajar Pratama; Hardianto Wibowo
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 4, November 2018
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v3i4.721

Sumbawa is popularly known as one of the regions in Indonesia, having a well- known folklore among the Sumbawa people, entitled the legend of Tanjung Menangis (Crying Cape). However, Tanjung Menangis is commonly recognized for its beauty than the stories contained. Therefore, a research is carried out by developing a game that is employed as a tool to introduce the story of Tanjung Menangis Legend as effort to preserve the original story of the mainland Sumbawa. The media game is chosen due to its favoured technology by children and adolescent as the target users of this research. This study applies Game Development Life Cycle (GDLC) method in the development stage which consists of several stages includinng: pre-production, production, testing, and post-production by adding an element of gamification. The game is tested on students at Labangka Elementary School in Sumbawa district in an age range of 10-15 years. After playing the game, the majority of respondents states that students gain knowledge about the Legend of Tanjung Menangis as reported from the results of the t- test with a probability value of 7.369x10-41, which is far below the value of α = 0.05. This result means that there was an increase in user knowledge of application. The test results also showed that all respondents agreed that the game of The Legend of Tanjung Menangis was used as one of the media used to introduce the story of the original Sumbawa people. In addition, the testing results as conducted with playtesting and gameflow test achieved good grades, with a range of values 4.5-4.81 of the seven elements tested, including: Concentration, Challenge, Player Skills, Control, Clear Goals, Feedback, and Immersion.

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

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%.

Co-Authors Abims Fardiansa Achmadi, Taufan Reza Agus Eko Minarno Ahmad Faiz, Ahmad Akbi, Denar Regata Ali Akbar Montazeri Andriyani, Vivi Aris Widayati 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 Didih Rizki Chandranegara 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 Ibnu Jahsy Karyati, Rina L. Yasril Imam Lailatul Huasniah Lailatul Husniah 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 Sofyan Arifianto Sumadi, Fauzi Dwi Setiawan Syaifuddin Syaifuddin Taufan Reza Achmadi Tino Firmansyah Ubay, Sabrina Nurul Vivi Andriyani Vizza Dwi Vitanti Wahyu Andhyka Kusuma Wicaksono, Galih Wasis Wildan Suharso Wildan Suharso Wildan Suharso Yuda Munarko Yufis Azhar Zamah Sari Zidni Lubis

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