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Manajemen Alokasi Bandwidth Layanan Internet Menggunakan Fractional Knapsack Problem

Bandwidth Allocation Management of Internet Services Using Fractional Knapsack Problem

Department of Computer Science, Institut Pertanian Bogor, Indonesia

Received: 14 Jan 2019; Revised: 26 Apr 2019; Accepted: 29 Apr 2019; Available online: 16 Jul 2019; Published: 30 Apr 2019.
Open Access Copyright (c) 2019 Jurnal Teknologi dan Sistem Komputer
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
The technical problems faced in e-government implemented by the Ministry of Religion of Indonesia since 2015 are minimal bandwidth requirements to provide information services and behavior of users who access entertainment sites. When peak hours occur, the congested network often occurs which becomes a significant bottleneck. This study aims to implement bandwidth management using the fractional knapsack problem method by limiting access to entertainment services. The QoS parameters used in this management are throughput, delay, and jitter. The method was tested using a paired t-test using throughput, jitter, and delay test parameters by comparing test parameters before and after bandwidth management applied. The significance value produced is between 75-85%. The method used can control the amount of traffic for each service, but on the other, hand the delay and jitter are still high. It is necessary to add additional free space to each service that can be used when needed to reduce the delay and jitter.
Keywords: bandwidth allocation; fractional knapsack problem;e-government services management
Funding: Institut Pertanian Bogor;Kementerian Agama Republik Indonesia

Article Metrics:

  1. Sekretaris Jenderal Kementerian Agama, “Surat Edaran Nomor SJ/B.VIII/2/HM.00/1558/2017 tentang Kebijakan Penggunaan Jaringan Internet dan Internet di Lingkungan Kementerian Agama,” Kementerian Agama Republik Indonesia, 2017
  2. M. A. Shargabi, A. Shaikh, and A. S. Ismail, “Enhancing the Quality of Service for Real Time Traffic over Optical Burst Switching (OBS) Networks with Ensuring the Fairness for Other Traffics,” PloS One, vol. 11, no. 9, pp. 1-29, 2016
  3. V. K. Singh, “Qos-based Techniques: Investigation and Optimization,” International Journal of Engineering Science (IJEST), vol. 6, no. 5, pp. 5242-5246, 2016
  4. N. Ferdosian, M. Othman, K. Y. Lun, and B. M. Ali, “Optimal Solution to the Fractional Knapsack Problem for LTE Overload-State Scheduling,” in 2016 IEEE 3rd International Symposium on Telecommunication Technologies (ISTT), Kuala Lumpur, Malaysia, Nov. 2016. 2016, pp. 97-102
  5. X. W. Zhang and H. H. Dong, “A Bandwidth Allocation Strategy for Train-to-Ground Communication System of Urban Mass Transit,” Applied Mechanics and Materials, vol. 742, pp. 669-673, 2015
  6. S. Martello and P. Toth, “Algorithms for Knapsack Problem,” North-Holland Mathematics Studies, vol 132, pp. 213-257, 1987
  7. B. Korte and J. Vygen, Combinatorial Optimization. Heidelberg: Springer-Verlag. 2018
  8. S. Supono, Modul MTCNA (Mikrotik Certified Network Associate). Jakarta: Inixindo, 2011
  9. W. Navidi, Statistics for Engineers & Scientists 4th Edition. New York: McGraw-Hill, 2014
  10. P. Saxela and S. K. Sharma, “Analysis of Network Traffic by using Sniffing Tool: Wireshark,” International Journal of Advance Research, Ideas and Innovations In Technology (IJARIIT), vol. 3, no. 6, pp. 804-808, 2017

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