sistem notifikasi kemacetan lalu lintas berbasis media sosial

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
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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
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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
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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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