Implementation of sugeno fuzzy method on bandwidth management at STMIK YMI Tegal
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Published:
Nov 8, 2023
Keywords:
Bandwidth Management, Fuzzy Sugeno, Matlab, Streaming Limit
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Computer Science
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Abstract
In the lecture process, the Internet becomes very important, and access settings or bandwidth management is needed so that Internet use can run smoothly. Many users can cause the burden of computer access to be high, so internet use will be unbalanced if bandwidth management is not carried out. Bandwidth management aims to allocate bandwidth in an internet network so that the distribution is equal and the comfort between users and one another is not disturbed. The method used is fuzzy Sugeno to implement Sugeno's fuzzy logic into bandwidth management and optimize internet usage. Fuzzy inputs used include download, streaming, and browsing variables. Using three fuzzy sets, namely low, standard, and solid. The output is Download Limit, Streaming Limit, and Browsing Limit. System testing will be conducted using MATLAB. After testing, results were obtained through bandwidth limits from downloading, streaming, and browsing. One of the study's results included a given system input download = 700, streaming = 668, and browsing = 611. Produce output is Download Limit = 700, Streaming Limit = 481, and Browsing Limit = 319
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Gunawan, G., Andriani, W. and Setiawan, D. (2023) “Implementation of sugeno fuzzy method on bandwidth management at STMIK YMI Tegal”, Jurnal Mantik, 7(3), pp. 1612-1622. doi: 10.35335/mantik.v7i3.4145.
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Sihotang, J., Hadi Nasyuha, A., StudiSistemInformasi, P., & Triguna Dharma, S. (2020). Sistem Pendukung Keputusan Menentukan Jumlah Permintaan Alat Musik Menggunakan Metode Fuzzy Mamdani Pada PT. Legato Internasional. Cyber Tech.
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Tundo, T., Akbar, R., & Sela, E. I. (2020). Analisis Perbandingan Fuzzy Tsukamoto dan Sugeno dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Base Rule Decision Tree. In Jurnal Teknologi Informasi dan Ilmu Komputer (Vol. 7, Issue 1, p. 171). https://doi.org/10.25126/jtiik.2020701751
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Wahab, R. A. (2019). Comparative Analysis of Broadband Internet Development for Digital Economy in China and Indonesia. Jurnal Penelitian Pos Dan Informatika, 9(1), 63. https://doi.org/10.17933/jppi.2019.090106
Walker-Andrews, A. S. (1997). Infants' perception of expressive behaviors: Differentiation of multimodal information. Psychological Bulletin, 121(3), 437–456. https://doi.org/10.1037/0033-2909.121.3.437
Wuragil, A. (2015). Alat Bantu Sistem Inferensi Fuzzy Dengan Menggunakan. 11(2), 163–168.
Yayla, M., Technologies, H., & Madi, M. (2020). A Comparative Study on Internet Performance Measurement Platforms. October.
Yulianto, T., Komariyah, S., & Ulfaniyah, N. (2017). Application of fuzzy inference system by Sugeno method on estimating of salt production. AIP Conference Proceedings, 1867. https://doi.org/10.1063/1.4994442
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Zhang, C., Patras, P., & Haddadi, H. (2019). Deep Learning in Mobile and Wireless Networking: A Survey. IEEE Communications Surveys and Tutorials, 21(3), 2224–2287. https://doi.org/10.1109/COMST.2019.2904897
Ayuningtias, L. P., Irfan, M., & Jumadi, J. (2017). Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, Dan Mamdani. Jurnal Teknik Informatika, 10(1), 9–16.
Bouraqia, K., Sabir, E., Sadik, M., & Ladid, L. (2020). Quality of Experience for Streaming Services: Measurements, Challenges and Insights. IEEE Access, 8, 13341–13361. https://doi.org/10.1109/ACCESS.2020.2965099
Cranford, S. W. (2020). Seven Seconds or Less: Buzzwordy Titles in the Era of MOFs and Tinder. Matter, 3(4), 965–967.
Cronje, J. C. (2020). Designing Questions for Research Design and Design Research in e?Learning. Electronic Journal of E-Learning, 18(1), pp13-24.
Doni, F. R. (2019). IMPLEMENTASI MANAJEMEN BANDWIDTH PADA JARINGAN KOMPUTER DENGAN ROUTER MIKROTIK. Jurnal Sains Dan Manajemen, 7, 52–57.
Fryer, L. K., & Dinsmore, D. L. (2020). The Promise and Pitfalls of Self-report: Development, research design and analysis issues, and multiple methods. Frontline Learning Research, 8(3), 1–9.
Grieshaber, S. (2020). Equity and research design. In Doing early childhood research (pp. 177–191). Routledge.
Hekmat, R., & Van Mieghem, P. (2005). Interference power sum with log-normal components in ad-hoc and sensor networks. Proceedings - WiOpt 2005: Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, 2005, 174–182. https://doi.org/10.1109/WIOPT.2005.23
Hidayanto, F., & Zidni Ilmi, M. (2015). Pentingnya Internet Sehat. Jurnal Inovasi Dan Kewirausahaan, 4(1), 21–24.
Khademi, F., Akbari, M., Jamal, S. M., & Nikoo, M. (2017). Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete. Frontiers of Structural and Civil Engineering, 11(1), 90–99. https://doi.org/10.1007/s11709-016-0363-9
Komariyah, S., Yunus, R. M., & Rodiansyah, S. F. (2016). Logika Fuzzy Dalam Sistem Pengambilan Keputusan Penerimaan Beasiswa. Proceeding Stima 2.0, 62.
LENDARIS, G. G. (1994). A review of: "FUZZY THINKING:" The New Science of Fuzzy Logic, by Bart Kosko, Hyperion, 1993. International Journal of General Systems, 22(3), 330–332. https://doi.org/10.1080/03081079408928570
Mukaromah, M. (2019). Penerapan Metode Fuzzy Sugeno Untuk Menentukan Jalur Terbaik Menuju Lokasi Wisata Di Surabaya. Jurnal Matematika Sains Dan Teknologi, 20(2), 95–101. https://doi.org/10.33830/jmst.v20i2.187.2019
Nunes, B. A. A., Mendonca, M., Nguyen, X. N., Obraczka, K., & Turletti, T. (2014). A survey of software-defined networking: Past, present, and future of programmable networks. IEEE Communications Surveys and Tutorials, 16(3), 1617–1634. https://doi.org/10.1109/SURV.2014.012214.00180
Nur Azizah, E., Cholissodin, I., & Firdaus Mahmudy, W. (2015). Optimasi Fungsi Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Penentuan Harga Jual Rumah. Journal of Enviromental Engineering and Sustainable Technology, 2(2), 79–82. https://doi.org/10.21776/ub.jeest.2015.002.02.3
Nurdini, S., Nurcahyo, G. widi, & Santony, J. (2021). Analisis Perkiraan Jumlah Produksi Tahu Menggunakan Metode Fuzzy Sugeno. Jurnal Sistim Informasi Dan Teknologi, 3(3), 18–23. https://doi.org/10.35134/jsisfotek.v1i3.4
Prihantoro, C., Hidayah, A. K., & Fernandez, S. (2021). Analisis Manajemen Bandwidth Menggunakan Metode Queue Tree pada Jaringan Internet Universitas Muhammadiyah Bengkulu. Just TI (Jurnal Sains Terapan Teknologi Informasi), 13(2), 81. https://doi.org/10.46964/justti.v13i2.750
Purwodwiyogo, Y., & Subardono, A. (2018). Kontrol Bandwidth Dinamis Berbasis Algoritma Logika Fuzzy pada Jaringan Wireless Ad-Hoc. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 2(3), 728–735. https://doi.org/10.29207/resti.v2i3.577
Ray, P. P. (2018). A survey on Internet of Things architectures. Journal of King Saud University - Computer and Information Sciences, 30(3), 291–319. https://doi.org/10.1016/j.jksuci.2016.10.003
Rozie, F., Syarif, I., Al Rasyid, M. U. H., & Satriyanto, E. (2021). Sistem Akuaponik untuk Peternakan Lele dan Tanaman Kangkung Hidroponik Berbasis IoT dan Sistem Inferensi Fuzzy. Jurnal Teknologi Informasi Dan Ilmu Komputer, 8(1), 157. https://doi.org/10.25126/jtiik.0814025
Saputri, A. D., Ramadhani, R. D., & Adhitama, R. (2019). Logika Fuzzy Sugeno Untuk Pengambilan Keputusan Dalam Penjadwalan Dan Pengingat Service Sepeda Motor. Journal of Informatics, Information System, Software Engineering and Applications (INISTA), 2(1), 49–55. https://doi.org/10.20895/inista.v2i1.95
Saragih, M., & Novimariono, N. (2020). An Experimental Study of The Effectiveness PEOW MODEL Through Applying Quartet Card in Teaching English Writing. Indonesian Journal of Education, Social Sciences and Research (IJESSR), 1(1), 32–40.
September, W. (2007). St at e, In St at e, In. 1–10.
Shu, K., Mahudeswaran, D., Wang, S., Lee, D., & Liu, H. (2020). Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media. Big Data, 8(3), 171–188.
Sihotang, J., Hadi Nasyuha, A., StudiSistemInformasi, P., & Triguna Dharma, S. (2020). Sistem Pendukung Keputusan Menentukan Jumlah Permintaan Alat Musik Menggunakan Metode Fuzzy Mamdani Pada PT. Legato Internasional. Cyber Tech.
Singh, K., & Singh Tomar, D. D. (2019). Architecture, enabling technologies, security and privacy, and applications of Internet of things: A survey. Proceedings of the International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2018, 642–646. https://doi.org/10.1109/I-SMAC.2018.8653708
Stewart, E. (2021). Detecting Fake News: Two Problems for Content Moderation. Philosophy & Technology, 1–18.
Tundo, T., Akbar, R., & Sela, E. I. (2020). Analisis Perbandingan Fuzzy Tsukamoto dan Sugeno dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Base Rule Decision Tree. In Jurnal Teknologi Informasi dan Ilmu Komputer (Vol. 7, Issue 1, p. 171). https://doi.org/10.25126/jtiik.2020701751
van der Giesen, C., Cucurachi, S., Guinée, J., Kramer, G. J., & Tukker, A. (2020). A critical view on the current application of LCA for new technologies and recommendations for improved practice. Journal of Cleaner Production, 259, 120904.
Wahab, R. A. (2019). Comparative Analysis of Broadband Internet Development for Digital Economy in China and Indonesia. Jurnal Penelitian Pos Dan Informatika, 9(1), 63. https://doi.org/10.17933/jppi.2019.090106
Walker-Andrews, A. S. (1997). Infants' perception of expressive behaviors: Differentiation of multimodal information. Psychological Bulletin, 121(3), 437–456. https://doi.org/10.1037/0033-2909.121.3.437
Wuragil, A. (2015). Alat Bantu Sistem Inferensi Fuzzy Dengan Menggunakan. 11(2), 163–168.
Yayla, M., Technologies, H., & Madi, M. (2020). A Comparative Study on Internet Performance Measurement Platforms. October.
Yulianto, T., Komariyah, S., & Ulfaniyah, N. (2017). Application of fuzzy inference system by Sugeno method on estimating of salt production. AIP Conference Proceedings, 1867. https://doi.org/10.1063/1.4994442
Yupapin, P. P., Mitatha, S., Ali, J., & Teeka, C. (2012). Nanocommunication networks. Nanocommunication Networks, 1–193. https://doi.org/10.1007/978-3-319-78262-1_300430
Zhang, C., Patras, P., & Haddadi, H. (2019). Deep Learning in Mobile and Wireless Networking: A Survey. IEEE Communications Surveys and Tutorials, 21(3), 2224–2287. https://doi.org/10.1109/COMST.2019.2904897
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