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)