Journal of Telematics and Informatics
Vol 7, No 3: SEPTEMBER 2019

SIMBOX Identification Using K-Nearest Neighbor Based On Spectrum Analyzer

Agung Suryowibowo (Electrical Engineering Department, Universitas Islam Sultan Agung)
Imam Much Ibnu Subroto (Informatics Department, Universitas Islam Sultan Agung)
Eka Nuryanto Budi Susila (Electrical Engineering Department, Universitas Islam Sultan Agung)



Article Info

Publish Date
20 Feb 2020

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.

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Journal Info

Abbrev

JTI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Journal of Telematics and Informatics (e-ISSN: 2303-3703, p-ISSN: 2303-3711) is an interdisciplinary journal of original research and writing in the wide areas of telematics and informatics. The journal encompasses a variety of topics, including but not limited to: The technology of sending, ...