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All Journal Perfecting a Video Game with Game Metrics Proceeding of the Electrical Engineering Computer Science and Informatics
Fachrunnisa Firdausi
Universitas Muhammadiyah Malang
Computer Science & IT Electrical & Electronics Engineering

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Facial expression recognition of 3D image using facial action coding system (FACS) Hardianto Wibowo; Fachrunnisa Firdausi; Wildan Suharso; Wahyu Andhyka Kusuma; Dani Harmanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.9304

Abstract

Facial expression or mimic is one of the results of muscle motion on the face. In a large Indonesian dictionary, the expression is a disclosure or process of declaring, i.e. showing or expressing intentions, ideas of feelings and so on. Facial expression is affected by the cranial nerve VII or Nervus Facialis. In research conducted Paul Ekman got a standardization of expression in the format of a movement called the Facial Action Coding System (FACS). In his research, Paul Ekman said six basic expressions of happiness, sadness, shock, fear, anger, and disgust. In muscle anatomy, that every moving muscle must be contraction, and in the event of contraction, the muscle will expand or swell. Muscles are divided into three parts of origo and insersio as the tip of muscle and belli as the midpoint of the muscle, so any movement occurs then the muscle part belli will expand or swell. Data retrieval technique that is by recording data in 3D, any contraction occurs then the belli part of the muscle will swell and this data will be processed and compared. From this data processing will be obtained the maximum strength of contraction that will be used as a reference for the magnitude of expression made by the model. In the detection of expression is ecluidience distance by comparing the initial data with movement data. The result of this research is a detection of expression and the amount of expression that occurs. A conclusion of this research, we can reconstruction of facial expression detection using FACS, for the example the happiness expression using AU 6 and AU 12 and in this research AU 6 and AU 12 in area 1 and area 4, and in this area it so higher than the other.
Correlation Between Bruto Domestic Products (Gdp) With Duty Schools Hardianto Wibowo; Daroe Iswatiningsih; Wildan Suharso; Fachrunnisa Firdausi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.421 KB) | DOI: 10.11591/eecsi.v5.1718

Abstract

This study aims to analyze the linkage of dropout rates with Gross Domestic Product (GDP). The data source of this research is the Central Bureau of Statistics (BPS), with data acquisition of GDP and drop out rate of elementary, junior and senior high school year 2008 until 2011. Data obtained through quantitative approach with secondary data source. The connectedness value between school dropout and GDP at primary level was 0.7294 in 2008, 0.7225 in the year of 2009, 0.4393 in 2010 and 0.3878 in 2011. While the relationship between the number of dropouts and GDP of junior high school level is 0.6095 in 2008, 0.6238 in 2009, 0.3605 in 2010 and 0.2467 in 2011. while the relationship between the drop out rate and GDP of the SMA level was 0.6061 in 2008, 0.5965 at in 2009, 0.5321 in 2010 and 0.2606 in 2011.
Co-Authors Dani Harmanto Daroe Iswatiningsih Hardianto Wibowo Wahyu Andhyka Kusuma Wildan Suharso