Agfianto Eko Putra on May 8th, 2021

WORKSHOP - Riset dan Implementasi di Bidang Speech, Signal dan Music Processing - Sabtu, 8 Mei 2021

Continue reading about Implementasi Sinyal dan Speech Processing

Agfianto Eko Putra on April 25th, 2021

Sosialisasi Pembentukan Pengurus dan Anggota Asosiasi Kecerdasan Buatan DAY 2 - Minggu, 25 april 2021.
Pada kesempatan ini saya coba menjelaskan dengan singkat konten stranas Kecerdasan Artifisial di Indonesia, khususnya terkait dengan arah aktivitas atau penelitian Kecerdasan Artifisial di Indonesia. Silahkan untuk lebih jelasnya menyaksikan tayangan berikut…

Continue reading about Arah Aktivitas/Penelitian Kecerdasan Artifisial Indonesia

Rekaman live Sabtu, 4 Juli 2020
Pada Roundtable ini akan membahas mengenai Digital Signal Processing dan Deep Learning dengan narasumber:

Dr. Agfianto Eko Putra (Dosen DIKE, Fak. MIPA, Universitas Gadjah Mada, Ketua Aptikom Daerah Istimewa Yogyakarta) — Pembahasan: digital signal processing untuk kasus speech signal dan seismic dengan MATLAB;
M. Octaviano Pratama, M.Kom (Chief Scientist BISA AI) — [...]

Continue reading about Digital Signal Processing and Deep Learning - Bisa.AI dan APTIKOM DIY

Rangkuti, A.H., Harjoko, A., and Putra, A.E.
This research evolves feature extraction algorithms in overcoming difficulties in classifying batik images that encounter changes in scale and rotation. the algorithm is multiscale and multilevel extended center symmetric local binary pattern (M2ECS-LBP). In utilizing this algorithm using several types of windows to obtain optimal feature extraction results, ranging [...]

Continue reading about Improvement of accuracy in batik image classification due to scale and rotation changes using M2ECS-LBP algorithm

Random Forest (RF) is known as one of the best classifiers in many fields. They are parallelizable, fast to train and to predict, robust to outlier, handle unbalanced data, have low bias, and moderate variance. Apart from these advantages, there are still opportunities to increase RF efficiency. The absence of recommendations regarding the number of [...]

Continue reading about Depth Limitation and Splitting Criteria Optimization on Random Forest for Efficient Human Activity Classification

Heriyanto, Hartati and Putra, 2018
The recitation of the Qur’an has its own uniqueness, among others having a special rule in reading and pronunciation, which is called tajwid science. At the time of the Qur’an is recited, there are often mistakes due to the limitations of knowledge of Tajwid. Therefore, the availability of tools to facilitate [...]

Continue reading about Evaluation of Suitability of Voice Reading of Al-Qur’an Verses Based on Tajwid Using Mel Frequency Cepstral Coefficients (MFCC) and Normalization of Dominant Weight (NDW)

by Agfianto Eko PUTRA, Wiwit SURYANTO, Agung Nugraha SULISTYANA
Seismic data analysis of the 2006 Merapi volcano eruption has been carried out using the Continuous Wavelet Transform (CWT) and the Wavelet-based Decomposition and Correlation (WAVEDECOR) combined with the Fast Fourier Transform (FFT). The CWT is used to show the frequency pattern of the event while the WAVEDECOR [...]

Continue reading about Analysis of 2006 Merapi Eruption Data Based on Continous Wavelet Transform, Wavelet Decomposition and Correlation

Achmad Solichin, Agus Harjoko, and Agfianto Eko Putra
This study proposed a model for determining the movement direction of the object based on the optical flow features. To increase the speed of computational time, optical flow features derived into a Histograms of Oriented Optical Flow (HOOF). We extracted them locally on the grid with a certain [...]

Continue reading about Movement Direction Estimation on Video using Optical Flow Analysis on Multiple Frames

Agfianto Eko Putra, Catur Atmaji, and Fajrul Ghaleb
In the area of affective computing technology, the classification of emotions can be used for a variety of things such as health, entertainment, education, etc. This study determined the classification of emotions based on EEG (Electroencephalography) signals, which is emotions are classified according to the 2-dimensional graphics modeling [...]

Continue reading about EEG-Based Emotion Classification Using Wavelet Decomposition and K-Nearest Neighbor

Catur Atmaji, Agfianto Eko Putra, and Irvan Albab Tontowi
Many research on how the human brain works have been done in the last century. The use of electroencephalogram signal generated from quantifying the brainwave has been developed in many areas including the development of brain-computer interface (BCI) concept. One type of BCI that interesting for the [...]

Continue reading about Three-Class Classification of EEG Signals Using Support Vector Machine Methods