ANALISIS PENGGUNA DATA INTERNET JAKWIFI RW 07 KELURAHAN LAGOA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

HARDIAN, RISKY (2023) ANALISIS PENGGUNA DATA INTERNET JAKWIFI RW 07 KELURAHAN LAGOA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Bekasi.

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Abstract

Perkembangan internet telah berkembang pesat dan menjadi gaya hidup. pemakaian internet merupakan kebutuhan yang sangat penting untuk mendukung kinerja dan aktivitas di rumah. Pada tanggal 28 Agustus 2020 pemerintah Provinsi DKI Jakarta resmi meluncurkan Jakwifi secara virtual, sebagai wifi publik yang tersedia diseluruh RW di DKI Jakarta. Peneliti melakukan observasi dengan mengambil data dari wifi hospot di RW 07 Kelurahan Lagoa yaitu RT 03 dan RT 06. Metode yang digunakan untuk klasifikasi menggunakan algoritma Support Vector Machine (SVM). Tujuan dari penelitian ini adalah untuk mengetahui destination, protocol, dan lebar bandwitch yang banyak diakses di waktu weekday atau weekend dan mengetahui penerapan metode klasifikasi menggunakan Support Vector Machine (SVM) pada pengguna data. Data trafik internet diambil menggunakan software Wireshark, sedangkan pengolahan data melalui WEKA. Hasil klasifikasi mendapatkan hasil akurasi yang berbeda-beda. Klasifikasi destination pada weekday di RT 03 mendapatkan nilai accuracy 72.4248 sedangkan protocol mendapatkan nilai accuracy sebesar 79.4612%. Klasifikasi destination pada weekend di RT 03 mendapatkan nilai accuracy 60.165% sedangkan protocol mendapat nilai accuracy sebesar 78.3248%. Klasifikasi destination pada weekday di RT 06 mendapatkan nilai accuracy sebesar 95.3252% sedangkan protocol nilai accuracy sebesar 95.8708%. Klasifikasi destination pada weekend di RT 06 mendapatkan nilai accuracy 64.8659% sedangkan protocol mendapat nilai accuracy sebesar 83.3643%. Kata Kunci: Traffik Jaringan, Support Vector Machine Internet development has grown rapidly and become a lifestyle. internet usage is a very important need to support performance and activities at home. On August 28, 2020 the DKI Jakarta Provincial Government officially launched Jakwifi virtually, as public wifi available in all RWs in DKI Jakarta. Researchers made observations by taking data from wifi hospots in RW 07 Lagoa Village, namely RT 03 and RT 06. The method used for classification uses the Support Vector Machine (SVM) algorithm. The purpose of this research is to find out the destination, protocol, and bandwidth that are widely accessed on weekdays or weekends and to find out the application of the classification method using Support Vector Machine (SVM) to user data. Internet traffic data is taken using Wireshark software, while data processing through WEKA. Classification results get different accuracy results. The destination classification on weekdays in RT 03 gets an accuracy value of 72.4248 while the protocol gets an accuracy value of 79.4612%. Classification of destinations on weekends in RT 03 gets an accuracy value of 60.165% while the protocol gets an accuracy value of 78.3248%. Classification of destinations on weekdays in RT 06 gets an accuracy value of 95.3252% while the protocol accuracy value is 95.8708%. Classification of destinations on weekends in RT 06 gets an accuracy value of 64.8659% while the protocol gets an accuracy value of 83.3643%. Keywords: Network Traffic, Support Vector Machine

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO 23 047
NIM/NIDN Creators:	41519210051
Uncontrolled Keywords:	Traffik Jaringan, Support Vector Machine
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	siti maisyaroh
Date Deposited:	29 Sep 2023 04:33
Last Modified:	29 Sep 2023 04:33
URI:	http://repository.mercubuana.ac.id/id/eprint/81640

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