Mauridhi Hery
Unknown Affiliation

Published : 2 Documents

Found 2 Documents

Lontar Komputer Vol. 1, No. 1 Desember 2010
Publisher : Lontar Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.575 KB)


The flow of water that flows in the river at an altitude of a certain level can be used to rotate turbinesthat can produce rotary energy. When this rotary we used to rotate a generator it will generateelectrical energy. Micro-hydro power plant generating electricity in a small capacity that could bebuilt in location depends on its environmental conditions and capable of generating electricity in alimited capacity. The problem arises is that the frequency resulting from micro-hydro plants can notbe stable at around 50 Hz, this will be very influential with the voltage drops due to the addition ofthe load. To stabilize the turbin at a certain round, so far only use the height of water level inside thetank as the input, so that the turbine is expected to generate a fixed rotation. This standard methodwill extremely unstable when there is an increase in load. To overcome this problem, the volume ofwater entering the turbine is adjusted by using the Application Control Neural Network (ANN) withfeedback from the output frequency of the generator. ANN will be able to produce output accordingto the learning process based on the weight of the input neurons of the frequency, rotation, and height level to be able to control the microcontroller to drive the water turbine governor, so that cankeep pace with the changing load on a stable frequency at 50 Hz and a voltage of 220 VA.
Text Mining for Fuzzy-based Emotion Expressions Sumpeno, Surya; Hariadi, Mochamad; Hery, Mauridhi
IPTEK The Journal for Technology and Science Vol 21, No 1 (2010)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v21i1.29


A model of emotion representation in the form of facial expressions using text mining technique, followed by fuzzy-based mechanisms using Fuzzy Inference System (FIS) is proposed. The model classifies the emotional content of sentences from text input and expresses corresponding emotions by a facial expression. Text input is classified using Na¨ıve Bayes text classifier, while facial expression of a virtual character are controlled by Mamdani fuzzy inference system utilizing results from text classifier. This model is able to show the facial expression with admixture blending emotions. As a demonstration, examples of facial expressions with corresponding text inputs as results from the implementation of our model are shown.