ANALISIS HUBUNGAN KAUSALITAS PADA TRAFIK INTERNET SPASIAL BERDASARKAN KINERJA JARINGANNYA

This paper presents the analysis of causal relationships in the internet traffic measured at four different traffic locations (spatial measurements) on Universitas Surabaya campus. Analysis of causality relationships is based on self-similarity traffic characteristics which is expressed by the Hurst parameter (H). The greater of H parameter value worse the network performance. The methods used in causality analysi is Granger Causality, the method is tested whether the Internet traffic in one location do not affect each other or against other Internet traffic location. The causality pattern is analyzed based on the H parameter. The result show Internet traffic with a small value of the H parameter in one location will affect traffic to the other locations but not vice versa. Meanwhile, between locations that have a large H parameter values are not mutually exclusive

Perbandingan Kinerja Jaringan Internet Kampus Berdasarkan Karakteristik Trafik Self-Similarity

Internet traffic measurements performed at four locations on the campus of the University of Surabaya the Faculty of Engineering, Faculty of Business and Economics, Library and campus Ubaya Ngagel. Daily Internet traffic measurement period was conducted between the hours of 03:00 am until 23:59 pm with an average sample every 5 minutes. Internet network performance in this study were analyzed based on the characteristics of traffic self-similarity. Characteristics of Self-Similarity is expressed in the Hurst parameter (H) with a value of H (½, 1), where getting close to H = 1 then the worse the performance of its network. While the value of H parameter can be obtained using FARIMA (p, d, q) model whose relationship can be expressed H = d + ½, d is the order of FARIMA model. From the calculation and analysis of daily Internet traffic obtained that contained the smallest value of H parameter on the location of the Library. It can be concluded that the best network performance between the three other locations on campus are at the Library

Pembuatan Aplikasi Informasi Lalu Lintas Berbasis Android Dengan Visualisasi Map

Tugas Akhir ini adalah membuat sebuah aplikasi informasi lalu lintas pada smartphone Android. Penyajian informasi lalu lintas pada smartphone Android ini adalah dengan menampilkan icon informasi banjir, kecelakaan lalu lintas, dan macet pada peta digital Google Maps. Aplikasi bernama BAJUL ini menekankan pada komunikasi client-server antara smartphone dan komputer server. Aplikasi client melakukan query jenis informasi ke server dengan protokol HTTP. Kemudian web service pada komputer server memproses query tersebut untuk melakukan manipulasi data dari database, lalu memberikan data balasan ke aplikasi client. Balasan berupa string XML tersebut lalu diterima oleh smartphone untuk dilakukan parsing sehingga masing-masing informasi akan ditampilkan sebagai icon pada overlay peta digital Google Maps. Selain koneksi client-server aplikasi Location Based Service ini juga mengakses lokasi pengguna dengan Integrated GPS atau Assisted GPS pada smartphone untuk menambahkan informasi baru. Sistem client-server yang didesain memiliki respon cepat sehingga menjamin pengguna dapat menerima informasi lalu lintas terkini