SISTEM NOTIFIKASI KEMACETAN LALU LINTAS BERBASIS MEDIA SOSIAL DENGAN METODE NLP TUGAS AKHIR
Sebagai Persyaratan Guna Meraih Gelar Sarjana Strata 1 Teknik Informatika Universitas Muhammadiyah Malang
Oleh : Hendra Triwijaya 09560303
JURUSAN TEKNIK INFORMATIKA FAKULTAS TEKNIK UNIVERSITAS MUHAMMADIYAH MALANG 2014 i
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ABSTRAK Kemacetan lalu lintas merupakan hal yang tidak asing lagi di Indonesia, khususnya di kota-kota besar. Kemacetan ini merupakan suatu permasalahan yang berdampak negatif terhadap penduduk pada setiap kota besar. Permasalahan kemacetan lalu lintas ini,sampai sekarang belum dapat teratasi. Di karenakan pertumbuhan penduduk yang sangat pesat dan meningkatnya konsumen untuk memiliki kendaraan pribadi, serta kurangnya informasi mengenai kemacetan lalu lintas Dengan berkembangnya teknologi saat ini, jejaring sosial adalah situs di internet yang sudah setingkat dengan sumber berita arus utama, informasi yang kita sampaikan di situs jejaring sosial sangat cepat menyebar. Dengan cara mengirimkan tweet untuk menyebarkan informasi kemacetan, pemanfaatan Twitter sebagai sumber informasi khususnya memberitahu kemcetan lalu lintas di kota Malang. Twitter merupakan microblog yang berkembang pesat. Dari berbagai posting-an terdapat beberapa topik dari informasi yang dapat bermanfaat untuk dikembangkan, diantaranya adalah informasi tentang lalu lintas. Pengambilan data atau tweet menggunakan twitter API. Metode Natural Language Processing (NLP) Pada prinsipnya bahasa alami adalah penguraian kalimat atau sering disebut dengan parser.Parser berfungsi untuk membaca kalimat, kata demi kata dan menentukan jenis kata apa saja yang boleh mengikuti kata tersebut. Dengan penerapan teknologi ini sebagai media untuk mempermudah mendapat informasi secara tepat dan akurat dimana titik – titik area terjadi kemacetan yang memiliki tujuan mempersingkat mencapai tujuan. Salah satunya sistem yang akan dikembangkan berupa aplikasi Web, yang melalui proses masukan pesan teks berupa tweet, dengan menggunakan kata kunci yang melalui tokenisasi, dihubungkan dengan google maps sehingga dapat mengetahui lokasi kemacetan yang ditampilkan dalam bentuk peta beserta informasinya.
Keywords : kemacetan, Twitter API, tokenisasi, aplikasi web, Google Maps
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ABSTRACT Traffic congestion is not familiar in Indonesia, especially in large cities. This congestion is a problem that negatively impact residents in every major city. This traffic congestion problem, until now, has yet to be resolved. In karenakan rapid population growth and rising consumer to have private vehicles, as well as the lack of information regarding traffic jams. With the development of current technologies, social networking site on the internet that is already on par with mainstream news sources, the information we provide on social networking websites very quickly spread. By sending tweets to spread information bottlenecks, utilization of Twitter as a source of information especially to tell kemcetan of traffic in the city of Malang. Twitter is a micro blogging is growing rapidly. Posting-an there are a number of different topics, from information that may be beneficial to developed, including information about the traffic. Data retrieval or tweet using twitter API. Method of Natural Language Processing (NLP) in principle natural language sentences or decomposition is often called by the parser.The parser function to read a sentence, Word for Word and determine the type of any word that can follow those words. With the application of this technology as a medium to facilitate informed appropriately and accurately where point – a point that congestion has occurred areas goal shorten reach. One system that will be developed in the form of a Web application, which through the process input message text in the form of Tweets, with the use of keywords thru tokenisasi, linked to google maps so that they can know the location of bottlenecks that are displayed in the form of a map with the information. Keywords : congestion, TwitterAPI, web applications, Google Maps
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LEMBAR PERSEMBAHAN
Puji syukur kepada Allah SWT atas rahmat dan karunia-Nya sehingga penulis dapat menyelesaikan Tugas Akhir ini. Penulis menyampaikan ucapan terima kasih yang sebesar-besarnya kepada :
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KATA PENGANTAR
Dengan memanjatkan puji syukur kehadirat Allah subhanahu wa ta’ala atas limpahan rahmat dan hidayah-Nya sehingga penulis dapat menyelesaikan tugas akhir yang berjudul : “SISTEM NOTIFIKASI KEMACETAN LALU LINTAS BERBASIS MEDIA SOSIAL DENGAN METODE NLP “
Di dalam tulisan ini disajikan pokok-pokok pembahasan yang meliputi pendahuluan, landasan teori, perancangan sistem, implementasi dan pengujian sistem. Peneliti menyadari sepenuhnya bahwa dalam penulisan tugas akhir ini masih banyak kekurangan dan keterbatasan. Oleh karena itu peneliti mengharapkan saran yang membangun agar tulisan ini bermanfaat bagi perkembangan ilmu pengetahuan ke depan. Malang, 20 Januari 2015 Penulis
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DAFTAR ISI COVER ................................................................................................................... i LEMBAR PERSETUJUAN ................................................................................... ii LEMBAR PENGESAHAN .................................................................................. iii LEMBAR PERNYATAAN ................................................................................... iv ABSTRAK ...............................................................................................................v ABSTRACT ........................................................................................................... vi LEMBAR PERSEMBAHAN .............................................................................. vii KATA PENGANTAR ......................................................................................... viii DAFTAR ISI .......................................................................................................... ix DAFTAR GAMBAR ...............................................................................................x 1. PENDAHULUAN ...............................................................................................1 1.1 Latar Belakang ..........................................................................................1 1.2 Rumusan Masalah ....................................................................................2 1.3 Batasan Masalah .......................................................................................3 1.4 Tujuan Penelitian ......................................................................................3 1.5 Metodologi ................................................................................................3 1.6 Sistematika Penulisan ...............................................................................5 2. LANDASAN TEORI ..........................................................................................6 2.1 Media Sosial .............................................................................................6 2.1.1 Twitter ...............................................................................................8 2.2 Google Maps ...........................................................................................12 2.3 Metode Natural Language Processing ....................................................15 2.3.1 Part-of-Speech (POS) Tagging .......................................................17 2.4 Text Mining ............................................................................................19 2.4.1 Proses Text Mining .........................................................................21 3. ANALISIS DAN PERANCANGAN SISTEM ................................................25 3.1 Analisis Sistem .......................................................................................25 3.1.1 Analisis Tweet Mengenai Kemacetan Lalu lintas ..........................25 3.1.2 Analisis Proses Sistem ....................................................................27 3.1.3 Use Case Diagram...........................................................................28 3.2 Perancangan Sistem ................................................................................29 ix
3.2.1 Activity Diagram ............................................................................29 3.2.2 Sequence Diagram ..........................................................................32 3.2.3 Rancangan Umum Sistem ...............................................................35 3.2.4 Perancangan Data............................................................................36 3.2.5 Perancangan Alur Kerja ..................................................................37 3.3 Desain Interface ......................................................................................38 4. IMPLEMENTASI DAN PENGUJIAN .............................................................42 4.1 Implementasi...........................................................................................42 4.1.1 Implementasi User Interface ...........................................................42 4.1.2 Implementasi Method......................................................................46 4.1.3 Proses Text Mining .........................................................................49 4.1.4 Proses Metode Natural Language Processing .................................52 4.2 Pengujian Sistem ....................................................................................53 4.2.1 Hasil Pengujian Aplikasi.................................................................53 4.2.2 Pengujian Data ................................................................................54 4.2.2 Skenario Pengujian .........................................................................54 5. KESIMPULAN DAN SARAN .........................................................................59 5.1 Kesimpulan .............................................................................................59 5.2 Saran .......................................................................................................59 DAFTAR PUSTAKA ............................................................................................60 BIOGRAFI PENULIS ...........................................................................................61
DAFTAR GAMBAR Gambar 2.1: Proses streaming API ...........................................................................10 Gambar 2.2: Proses realtime data Tweet ...................................................................11 Gambar 2.3: Arsitektur Sistem NLP ......................................................................17 Gambar 2.4: Tahapan Text Mining ........................................................................21 Gambar 2.5: Proses teks mining.............................................................................21 Gambar 2.6: Hasil Tokenisasi ................................................................................22 Gambar 2.7: Proses Tokenisasi ..............................................................................22 Gambar 2.8: Hasil Filtering....................................................................................22 Gambar 2.9: Hasil Stemming .................................................................................23 Gambar 2.10: Hasil Tagging ..................................................................................23 x
Gambar 2.11: Proses analyzing ..............................................................................24 Gambar 3.1: Flow Chart Alur Sistem dan proses pos tagging ..............................27 Gambar 3.2: Use case Diagram .............................................................................28 Gambar 3.3: Activity Diagram Input Lokasi ..........................................................30 Gambar 3.4: Activity Diagram View Lalu Lintas ..................................................31 Gambar 3.5: Activity Diagram Help ......................................................................32 Gambar 3.6: Sequence Diagram Input Loasi .........................................................33 Gambar 3.7: Sequence Diagram View Lalu Lintas ...............................................34 Gambar 3.8: Sequence Diagram Help ...................................................................34 Gambar 3.9: Rancangan Arsitektur Sistem ............................................................35 Gambar 3.10: Model data sistem ...........................................................................36 Gambar 3.11: Halaman Utama...............................................................................38 Gambar 3.12: Halaman Searching .........................................................................40 Gambar 3.13: view lalu lintas ................................................................................40 Gambar 3.14: Help .................................................................................................41 Gambar 4.1: Halaman Utama .................................................................................43 Gambar 4.2: Input Lokasi/Searching Lokasi .........................................................44 Gambar 4.3: Notifikasi Data ..................................................................................44 Gambar 4.4: Notifikasi hasil pencarian ..................................................................44 Gambar 4.5: hasil pencarian dan informasi............................................................45 Gambar 4.6: View Lalu lintas ................................................................................45 Gambar 4.7: Help ...................................................................................................46 Gambar 4.8: Data tweet puspita .............................................................................55 Gambar 4.9: kumpulan kata benda dan kata sifat ..................................................56
DAFTAR TABEL Tabel 2.1: Pilihan parameter penggunaan Twitter Streaming API .........................12 Tabel 4.1: Rencana pengujian ................................................................................53 Tabel 4.2: Pengujian Halaman utama ....................................................................54 Tabel 4.3: pengujian notifikasi ...............................................................................54 Tabel 4.4: pengujian ...............................................................................................57
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