Article Per Year (5 Year)
p-Index From 2020 - 2025
8.154
P-Index
This Author published in this journals
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
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 : 71 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search
Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

 1 
Comparison of Methods for Batik Classification Using Multi Texton Histogram Agus Eko Minarno; Ayu Septya Maulani; Arrie Kurniawardhani; Fitri Bimantoro; Nanik Suciati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.7376

Abstract

Batik is a symbol reflecting Indonesian culture which has been acknowledged by UNESCO since 2009. Batik has various motifs or patterns. Because most regions in Indonesia have their own characteristic of batik motifs, people find difficulties to recognize the variety of Batik. This study attempts to develop a system that can help people to classify Batik motifs using Multi Texton Histogram (MTH) for feature extraction. Meanwhile, k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM) algorithm were employed for classification. The performance of those classifications is then compared to seek the best classification method for Batik classification. The performance is tested 300 images divided into 50 classes. The results show the optimum accuracy achieved using k-NN with k=5 and MTH with 6 textons is 82%; however, SVM and MTH with 6 textons denote 76%. According to the result, MTH as feature extraction, k-NN or SVM as a classifier can be applied on Batik image classification.
Enabling seamless communication over several IoT messaging protocols in OpenFlow network Fauzi Dwi Setiawan Sumadi; Agus Eko Minarno; Lailis Syafa’ah; Muhammad Irfan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20412

Abstract

The most prominent protocols for data transfer in internet of things (IoT) are message queuing telemetry transport (MQTT) and constrained application protocol (CoAP). The existing clients from both sides are unable to communicate directly because of the packet’s header structure difference in application and transport layer. In response, this paper aims to develop a bidirectional conversion server used to translate the specified messaging protocol interchangeably in the OpenFlow network and transmit the converted packet from both sides. The conversion server integrated the MQTT subscriber and CoAP POST object for converting the MQTT message into CoAP data. Similarly, the CoAP-MQTT translation was processed by CoAP GET and MQTT publisher object. The research was evaluated by analysing the round trip time (RTT) value, conversion delay, and power consumption. The RTT value for MQTT-CoAP required 0.5 s while the CoAP-MQTT was accumulated in 0.1 s for single-packet transmission. In addition, the SDN controller and the conversion server only consumed less than 1% central processing unit (CPU) usage during the experiment. The result indicated that the proposed conversion server could handle the translation even though there was an overwhelming request from the clients.
Image Retrieval Based on Multi Structure Co-occurrence Descriptor Agus Eko Minarno; Arrie Kurniawardhani; Fitri Bimantoro
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3292

Abstract

This study present a new technique for Batik cloth image retrieval using Micro-Structure Co-occurence Descriptor (MSCD). MSCD is a developed method based on Enhanced Micro Structure Descriptor (EMSD). Previously, EMSD has been improved by adding edge orientation feature. In previous study, EMSD cannot achieve an optimal precision. Therefore, MSCD is proposed to overcome the EMSD drawback using global feature approach, namely Gray Level Co-occurrence Matrix (GLCM). There are 300 batik cloth images which contain 50 classes used for dataset. The performance result show that MSCD can retrieve Batik cloth images more effective than EMSD.
Combined scaled manhattan distance and mean of horner’s rules for keystroke dynamic authentication Didih Rizki Chandranegara; Hardianto Wibowo; Agus Eko Minarno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14815

Abstract

Account security was determined by how well the security techniques applied by the system were used. There had been many security methods that guaranteed the security of their accounts, one of which was Keystroke Dynamic Authentication. Keystroke Dynamic Authentication was an authentication technique that utilized the typing habits of a person as a security measurement tool for the user account. From several research, the average use in the Keystroke Dynamic Authentication classification is not suitable, because a user's typing speed will change over time, maybe faster or slower depending on certain conditions. So, in this research, we proposed a combination of the Scaled Manhattan Distance method and the Mean of Horner's Rules as a classification method between the user and attacker against the Keystroke Dynamic Authentication. The reason for using Mean of Horner’s Rules can adapt to changes in values over time and based on the results can improve the accuracy of the previous method.
Human activity recognition for static and dynamic activity using convolutional neural network Agus Eko Minarno; Wahyu Andhyka Kusuma; Yoga Anggi Kurniawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 6: December 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i6.20994

Abstract

Evaluated activity as a detail of the human physical movement has become a leading subject for researchers. Activity recognition application is utilized in several areas, such as living, health, game, medical, rehabilitation, and other smart home system applications. An accelerometer was popular sensors to recognize the activity, as well as a gyroscope, which can be embedded in a smartphone. Signal was generated from the accelerometer as a time-series data is an actual approach like a human actifvity pattern. Motion data have acquired in 30 volunteers. Dynamic actives (walking, walking upstairs, walking downstairs) as DA and static actives (laying, standing, sitting) as SA were collected from volunteers. SA and DA it's a challenging problem with the different signal patterns, SA signals coincide between activities but with a clear threshold, otherwise the DA signal is clearly distributed but with an adjacent upper threshold. The proposed network structure achieves a significant performance with the best overall accuracy of 97%. The result indicated the ability of the model for human activity recognition purposes.
Batik Image Retrieval Based on Color Difference Histogram and Gray Level Co-Occurrence Matrix Agus Eko Minarno; Nanik Suciati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 3: September 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i3.80

Abstract

Study in batik images retrieval is still challenging until today. One of the methods for this problem is using Color Difference Histogram (CDH) which is based on the difference of color features and edge orientation features. However, CDH is only utilizing local features instead of global features; consequently it cannot represent images globally. We suggest that by adding global features for batik images retrieval, the precision will increase. Therefore, in this study, we combine the use of modified CDH to define local features and the use of Gray Level Co-occurrence Matrix (GLCM) to define global features. The modified CDH is performed by changing the size of image quantization, so it can reduce the number of features. Features that detected by GLCM are energy, entropy, contrast and correlation. In this study, we use 300 batik images which are consisted of 50 classes and 6 images in each class. The experiment result shows that the proposed method is able to raise 96.5% of precision rate which is 3.5% higher than the use of CDH only. The proposed method is extracting a smaller number of features; however it performs better for batik images retrieval. This indicates that the use of GLCM is effective combined with CDH.
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 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 Deris Stiawan Dwi Rahayu Dyah Ayu Irianti Eko Budi Cahyono Elfrida Ratnawati Fadhlan, Muhammad 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 Hazmi Cokro Mandiri, Mochammad Ibrahim, Zaidah Ilham Setiyo Kantomo Iqbal Fairus Zamani Irfan, Muhammad irma fitriani Izzah, Tsabita Nurul Lailis Syafa'ah Lailis Syafa’ah Laofin Aripa Linggar Bagas Saputro Lusianti, Aaliyah Mandiri, Mochammad Hazmi Cokro Moch Ilham Ramadhani Moch. Chamdani Mustaqim Mochammad Hazmi Cokro Mandiri Muhammad Afif Muhammad Azhar Ridani Muhammad Hussein Muhammad Nafi Maula Hakim Muhammad Nasrul Tsalatsa Putra Muhammad Nuchfi Fadlurrahman Muhammad Yusril Hasanuddin 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 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 Zaidah Ibrahim Zamah Sari Zamani, Iqbal Fairus