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Journal : Journal of Telematics and Informatics

Determination of Exposure Factors and Interlock System Base On Fuzzy Logic In X-Ray Conventional Generator Sugeng Santoso; Muhammad Haddin; Eka Nuryanto Budi Susila
Journal of Telematics and Informatics Vol 6, No 3: September 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.002 KB) | DOI: 10.12928/jti.v6i3.

Abstract

One of the utilization of x-Ray on medical area is radiogram. Result of the radiogram can determine patient diagnosis of disease. More clearly the result of imaging, can bring pecise and accurate diagnosis. To solve that problem, we need to calculate distance between X-Ray tube and object, type of film, screen kaset, and also situation or condition of body weight either mature, child or infant to determine exposure factors. Exposure factors is kilovolt, miliampere and time. That exposure factors means electrical load toward X-Ray tube to produce radiant intensity. Interlock system is used to prevent useless generation of X-Ray and doesn’t produce diagnostic value. In this research using fuzzy logic to determine exposure factors on thorax examination which is implemented in software by  using pre-defined reference data. By input distance, body weight, body height in software will be obtained appropriate exposure factors setting for radiografer. By determining the focus distance of the appropriate (valid) film, then the fuzzy logic system can build an interlock system that will prevent the useless x-rays. The results showed that data taken from a radiographer in a local hospital in Semarang compared with the output of exposure factor software was appropriate and when interlock system is activated the fuzzy control system can prevent the generation of x-rays
SIMBOX Identification Using K-Nearest Neighbor Based On Spectrum Analyzer Agung Suryowibowo; Imam Much Ibnu Subroto; Eka Nuryanto Budi Susila
Journal of Telematics and Informatics Vol 7, No 3: SEPTEMBER 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i3.

Abstract

Telecommunication Service Provider should deal with illegal players (grey operators) who do not have permission to conduct international voice service. These illegal players perform their activities by passing international incoming traffic using Simbox devices. To identify visual simbox usage is very difficult and less reliable, therefore by using spectrum analyzer and K-Nearest Neighbor (K-NN) method is one way to identify simbox usage. The attributes used in the identification process are Location / Document, Strong Frequency Signal, and by applying K-NN algorithm based on proximity of training data with data testing. The determination of this attribute is based on GSM DCS 1800 MHz uplink frequency measurement in Cilacap and Banyumas area. The identification process was conducted on six frequencies points on 18 data with the largest signal strength as training data. Moreover, the signal strength data testing  by using 32 data gives result 81.25% accuracy. The results of K-NN algorithm calculations can be implemented to identify the use of simbox, hence it can be used as a reference for mobile operators to identify simbox usage in other areas.Telecommunication Service Provider should deal with illegal players (grey operators) who do not have permission to conduct international voice service. These illegal players perform their activities by passing international incoming traffic using Simbox devices. To identify visual simbox usage is very difficult and less reliable, therefore by using spectrum analyzer and K-Nearest Neighbor (K-NN) method is one way to identify simbox usage. The attributes used in the identification process are Location / Document, Strong Frequency Signal, and by applying K-NN algorithm based on proximity of training data with data testing. The determination of this attribute is based on GSM DCS 1800 MHz uplink frequency measurement in Cilacap and Banyumas area. The identification process was conducted on six frequencies points on 18 data with the largest signal strength as training data. Moreover, the signal strength data testing  by using 32 data gives result 81.25% accuracy. The results of K-NN algorithm calculations can be implemented to identify the use of simbox, hence it can be used as a reference for mobile operators to identify simbox usage in other areas.