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All Journal International Journal of Electrical and Computer Engineering Jurnal Dedikasi Jurnal Gamma TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Inovasi Teknologi Pendidikan International Journal of Advances in Intelligent Informatics POSITIF CESS (Journal of Computer Engineering, System and Science) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal JOIV : International Journal on Informatics Visualization Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control KOMPUTIKA - Jurnal Sistem Komputer Jurnal Repositor Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Makara Journal of Technology

Agus Eko Minarno

Universitas Muhammadiyah Malang

Author-ID : 320354

Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health

Published : 74 Documents Claim Missing Document

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Articles

Title

Vehicle Classification using Haar Cascade Classifier Method in Traffic Surveillance System Ramadhani, Moch Ilham; Minarno, Agus Eko; Cahyono, Eko Budi
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 1, February-2018
Publisher : Universitas Muhammadiyah Malang

Object detection based on digital image processing on vehicles is very important for establishing monitoring system or as alternative method to collect statistic data to make efficient traffic engineering decision. A vehicle counter program based on traffic video feed for specific type of vehicle using Haar Cascade Classifier was made as the output of this research. Firstly, Haar-like feature was used to present visual shape of vehicle, and AdaBoost machine learning algorithm was also employed to make a strong classifier by combining specific classifier into a cascade filter to quickly remove background regions of an image. At the testing section, the output was tested over 8 realistic video data and achieved high accuracy. The result was set 1 as the biggest value for recall and precision, 0.986 as the average value for recall and 0.978 as the average value for precision.

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.

Internet of Things Platform for Manage Multiple Message Queuing Telemetry Transport Broker Server Wardana, Aulia Arif; Rakhmatsyah, Andrian; Minarno, Agus Eko; Anbiya, Dhika Rizki
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 4, No 3, August 2019
Publisher : Universitas Muhammadiyah Malang

This study proposed the Internet of Things (IoT) monitoring platform model to manage multiple Message Queuing Telemetry Transport (MQTT) broker server. The Broker is a part of the MQTT protocol system to deliver the message from publisher to subscriber. The single MQTT protocol that setup in a server just have one broker system. However, many users used more than one broker to develop their system. One of the problems with the user that use more than one MQTT broker to develop their system is no recording system that helps users to record configurations from multi brokers and connected devices. This can cause to slow the deployment process of the device because the configuration of the device and broker not properly managed. The platform built is expected to solve the problem. This proposed platform can manage multiple MQTT broker server and device configuration from different product or vendor. The platform also can manage the topic that connects to a registered broker on the platform. The other advantages of this platform are open source and can modify to a specific business process. After usability testing and response time testing, the proposed platform can manage multiple MQTT broker server, functional to use, and an average of response time from the platform page is not more than 10 seconds.

Image Retrieval Based on Texton Frequency-Inverse Image Frequency Azhar, Yufis; Minarno, Agus Eko; Munarko, Yuda; Ibrahim, Zaidah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 2, May 2020
Publisher : Universitas Muhammadiyah Malang

In image retrieval, the user hopes to find the desired image by entering another image as a query. In this paper, the approach used to find similarities between images is feature weighting, where between one feature with another feature has a different weight. Likewise, the same features in different images may have different weights. This approach is similar to the term weighting model that usually implemented in document retrieval, where the system will search for keywords from each document and then give different weights to each keyword. In this research, the method of weighting the TF-IIF (Texton Frequency-Inverse Image Frequency) method proposed, this method will extract critical features in an image based on the frequency of the appearance of texton in an image, and the appearance of the texton in another image. That is, the more often a texton appears in an image, and the less texton appears in another image, the higher the weight. The results obtained indicate that the proposed method can increase the value of precision by 7% compared to the previous method.

Visualization of Granblue Fantasy Game Traffic Pattern Using Deep Packet Inspection Method Stiawan, Deris; Prabowo, Christian; Heryanto, Ahmad; Afifah, Nurul; Minarno, Agus Eko; Budiarto, Rahmat
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 3, August 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v5i3.1073

Granblue Fantasy is one of Role Playing Games (RPG). It’s a video role-playing game developed by Cygames. This research to observes the Granblue Fantasy Game. The purpose is to analyze the traffic data of the Granblue Fantasy to find the pattern using Deep Packet Inspection (DPI), Capturing the Data Traffic, Feature Extraction Process and Visualize the Pattern. The Pattern are Gacha, Solo Raid, Casino and Multiraid. This research demonstrate that Multiraid battle has more data than other pattern with TTL 237.

Convolutional Neural Network with Hyperparameter Tuning for Brain Tumor Classification Minarno, Agus Eko; Hazmi Cokro Mandiri, Mochammad; Munarko, Yuda; Hariyady, Hariyady
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.v6i2.1219

Brain tumor has been acknowledged as the most dangerous disease through all its circles. Early identification of tumor disease is considered pivotal to identify the spread of brain tumors in administering the appropriate treatment. This study proposes a Convolutional Neural Network method to detect brain tumor on MRI images. The 3264 datasets were undertaken in this study with detailed images of Glioma tumor (926 images), Meningioma tumors (937 images), pituitary tumors (901 images), and other with no-tumors (500 images). The application of CNN method combined with Hyperparameter Tuning is proposed to achieve optimal results in classifying the brain tumor types. Hyperparameter Tuning acts as a navigator to achieve the best parameters in the proposed CNN model. In this study, the model testing was conducted with three different scenarios. The result of brain tumor classification depicts an accuracy of 96% in the third model testing scenario.

Vehicle Classification using Haar Cascade Classifier Method in Traffic Surveillance System Moch Ilham Ramadhani; Agus Eko Minarno; Eko Budi Cahyono
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 3, No 1, February-2018
Publisher : Universitas Muhammadiyah Malang

The Implementation of Pretrained VGG16 Model for Rice Leaf Disease Classification using Image Segmentation Suseno, Jody Ririt Krido; Azhar, Yufis; Minarno, Agus Eko
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 1, February 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i1.1592

Rice is an agricultural sector that produces rice which is one of the staple foods for the majority of the population in Indonesia. In the cultivation of rice plants there are also factors that affect rice production and are not realized by farmers causing that they are late in handling and diagnosing symptoms and making rice production decline. Therefore, it is necessary to have an early diagnosis of rice plants to identify them correctly, quickly and accurately. Machine learning is one of the classification techniques to detect various plant diseases such as rice plants. There are several studies on machine learning using the Convolutional Neural Network with the VGG16 model to classify rice leaf diseases and using Image Segmentation techniques on rice leaf datasets for make the image becomes a form that is not too complicated to analyze. The data used in this research is Rice Leaf Disease which consists of 3 classes including Bacterial leaf blight, Brown spot, and Leaf smut. Then segmentation is carried out using two techniques, namely threshold and k means. Then data augmentation for make dataset used has a large and varied number and training using VGG16 model with hyperparameter tuning and obtained 91.66% accuracy results for scenarios with the k-means dataset.

Co-Authors Abu Abbas Mansyur Achmad Fauzi Saksenata Ahmad Annas Al Hakim Ahmad Faiz, Ahmad Ahmad Heryanto, Ahmad Akbi, Denar Regata Alfarizy, Muhammad Rifal Alfian Yuniarto Anbiya, Dhika Rizki Andhika Pranadipa Andrian Rakhmatsyah Aria Maulana Eka Mahendra Arif Bagus Nugroho Aripa, Laofin Arrie Kurniawardhani arrie kurniawardhany, arrie AULIA ARIF WARDANA Ayu Septya Maulani Bagaskara, Andhika Dwija Basuki, Setio Bayu Yudha Purnomo Bella Dwi Mardiana Chandranegara, Didih Rizki Cokro Mandiri, Mochammad Hazmi Deris Stiawan Dwi Rahayu Dyah Ayu Irianti Eko Budi Cahyono Fachry Abda El Rahman Feny Aries Tanti Firdhansyah Abubekar Fitri Bimantoro Galang Aji Mahesa Gita Indah Marthasari Hanung Adi Nugroho Haqim, Gilang Nuril Hardianto Wibowo Hariyady Hariyady Harmanto, Dani Hasanuddin, Muhammad Yusril Hazmi Cokro Mandiri, Mochammad Ibrahim, Zaidah Indah Soesanti Iqbal Fairus Zamani Irfan, Muhammad irma fitriani Izzah, Tsabita Nurul Lailis Syafa'ah Lailis Syafa’ah Linggar Bagas Saputro Lusianti, Aaliyah Mandiri, Mochammad Hazmi Cokro Moch Ilham Ramadhani Moch. Chamdani Mustaqim Muhammad Afif Muhammad Azhar Ridani Muhammad Hussein Muhammad Nafi Maula Hakim Muhammad Nasrul Tsalatsa Putra Muhammad Nuchfi Fadlurrahman Nanik Suciati Naser Jawas, Naser Nia Dwi Nurul Safitri Noor Aini Mohd Roslan Norizan Mat Diah Prabowo, Christian Ramadhani, Moch Ilham Rangga Kurnia Putra Wiratama Ratna Sari Riksa Adenia Rizalwan Ardi Ramandita Rizka Nurlizah Sabrila, Trifebi Shina Sari, Veronica Retno Sari, Zamah Sasongko Yoni Bagas Setiyo Kantomo, Ilham Sumadi, Fauzi Dwi Setiawan Suryani Rachmawati Suseno, Jody Ririt Krido Toton Dwi Antoko Trifebi Shina Sabrila Tsabitah Ayu Ulfah Nur Oktaviana Veronica Retno Sari Vizza Dwi Wahyu Andhyka Kusuma Wahyu Budi Utomo Wicaksono, Galih Wasis Wicaksono, Galih Wasis Widya Rizka Ulul Fadilah Wildan Suharso Yesicha Amilia Putri Yoga Anggi Kurniawan Yuda Munarko Yudhono Witanto Yufis Azhar Yundari, Yundari Zaidah Ibrahim Zaidah Ibrahim Zamah Sari Zamani, Iqbal Fairus

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