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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

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.
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.
Frontalis Muscle Strength Calculation Based On 3D Image Using Gray Level Co-occurrence Matrix (GLCM) and Confidence Interval Hardianto Wibowo; Eko Mulyanto Yuniarno; Aris Widayati; Mauridhi Hery Purnomo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 1: February 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i1.6490

Abstract

One of the effects of the disorders of nervus VII (n. Facialis) is the damage of facial muscle. The research is needed in order to detect or as the therapies aids on the damage of the VII nerve by measuring the strength of maximum contraction, to help a therapy or detect the damage which caused by the decreasing of the VII nerve function. These measurement is taken from the difference on myofibrin when the contractions, because when the contraction happen, the myofibrin will distend and the difference can be detected as the strength of contraction. From the result of the comparison, EMG with the test result is the shift muscle movement amount of 1.367 up to 4.460. The mean value of rest muscle is in the range of 0.635 with interval at+0.463, on the move muscles the mean value of the muscle moving is in the range of 3,563 with interval at+1,069. This test is linear with the data EMG.