iii

KLASIFIKASI PADA TWEET BERBAHASA INDONESIA

MENGGUNAKAN METODE GRAVITASI DATA

TUGAS AKHIR

Disusun Oleh :

Mufida Lutfiah Ulfa

201010370311410

JURUSAN TEKNIK INFOMRATIKA

FAKULTAS TEKNIK

UNIVERSITAS MUHAMMADIYAH MALANG

2015

KLASIFIKASI EMOSI PADA TWEET BERBAHASA

INDONESIA

MENGGUNAKAN METODE GRAVITASI DATA

TUGAS AKHIR

Diajukan Untuk Memenuhi

Persyaratan Guna Meraih Gelar Sarjana Strata 1

Teknik Informatika Universitas Muhammadiyah Malang

Disusun Oleh :

MUFIDA LUTFIAH ULFA

NIM : 201010370311410

JURUSAN TEKNIK INFORMATIKA

FAKULTAS TEKNIK

UNIVERSITAS MUHAMMADIYAH MALANG

2015

iv

KATA PENGANTAR

Assalamu’alaikum Wr. Wb.

Dengan memanjatkan puji syukur kehadirat Allah SWT atas limpahan

rahmat dan hidayah-Nya sehingga penulis dapat menyelesaikan tugas akhir yang

berjudul:

KLASIFIKASI EMOSI PADA TWEET BERBAHASA INDONESIA

MENGGUNAKAN METODE GRAVITASI DATA

Dalam penulisan ini disajikan tahap-tahap pengklasifikasian emosi

menggunakan metode Gravitasi Data, mulai dari proses text mining, weighting,

weighted distance, dan Data Gravitation.

Penulis menyadari masih terdapat banyak kekurangan dan keterbatasan

dalam penulisan tugas akhir ini. Untuk itu, penulis sangat mengharapkan saran yang

membangun agar tulisan ini dapat berguna untuk perkembangan ilmu pengetahuan

kedepan.

Malang, Januari 2015

Penulis

Mufida Lutfiah Ulfa

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DAFTAR ISI

ABSTRAK ............................................................................................................................. i

ABSTRACT .......................................................................................................................... ii

LEMBAR PENGESAHAN ..................................................................................................... iii

KATA PENGANTAR............................................................................................................. iv

DAFTAR ISI.......................................................................................................................... v

DAFTAR GAMBAR ............................................................................................................. vii

DAFTAR TABEL ................................................................................................................ viii

BAB I PENDAHULUAN ........................................................................................................ 1

Latar Belakang .................................................................................................... 1

Rumusan Masalah .............................................................................................. 2

Tujuan ................................................................................................................ 3

Batasan Masalah ................................................................................................ 3

Metodologi ......................................................................................................... 3

Sistematika Penulisan ......................................................................................... 5

BAB II LANDASAN TEORI .................................................................................................... 6

Twitter ................................................................................................................ 6

Data Mining ........................................................................................................ 7

Manfaat Data Mining ................................................................................. 8

Teknik Data Mining ..................................................................................... 9

Text Mining ...................................................................................................... 10

Data Gravitation Based Classification ............................................................... 11

Hukum Gravitasi Data ............................................................................... 12

BAB III ANALISA DAN PERANCANGAN SISTEM ................................................................. 13

Analisa Sistem .................................................................................................. 13

Kebutuhan Sistem ............................................................................................ 14

Kebutuhan Fungsional .............................................................................. 14

Kebutuhan Nonfungsional ........................................................................ 14

Desain Sistem ................................................................................................... 15

Preprocessing ........................................................................................... 15

Pembobotan ............................................................................................. 17

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Gravitasi Data ........................................................................................... 17

Contoh kasus ............................................................................................ 19

Desain Antarmuka .................................................................................... 29

BAB IV IMPLEMENTASI DAN PENGUJIAN SISTEM............................................................. 33

Implementasi ................................................................................................... 33

Class-class yang digunakan ....................................................................... 33

Pengujian Sistem .............................................................................................. 39

Pengujian Kebutuhan Fungsional ............................................................. 40

Pengujian Non-Fungsional ........................................................................ 40

Pengujian Klasifikasi Data ......................................................................... 40

Hasil Pengujian ......................................................................................... 41

BAB V KESIMPULAN DAN SARAN ..................................................................................... 47

Kesimpulan ....................................................................................................... 47

Saran ................................................................................................................ 47

DAFTAR PUSTAKA ............................................................................................................ 48

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DAFTAR GAMBAR

Gambar 1.1 Perancangan Sistem ....................................................................................... 4

Gambar 2.1 Bidang Ilmu Data Mining(Luthfi 2009) ............................................................ 8

Gambar 2.2 Clustering(Pramudiono 2003)......................................................................... 9

Gambar 2.3 proses text mining(Abdurrahman 2014) ...................................................... 11

Gambar 3.1 Diagram Alur Sistem ..................................................................................... 15

Gambar 3.2 Diagram alur preprocessing .......................................................................... 16

Gambar 3.3 Diagram alur pembobotan TF-IDF ................................................................ 17

Gambar 3.4 Diagram Alur Gravitasi Data ......................................................................... 18

Gambar 3.5 Data contoh kasus ........................................................................................ 19

Gambar 3.6 Hasil Case Folding ......................................................................................... 20

Gambar 3.7 Hasil tokenizing............................................................................................. 21

Gambar 3.8 Hasil TF(term frequency)............................................................................... 22

Gambar 3.9 Ruang Vektor ................................................................................................ 24

Gambar 3.10 Hasil TF-IDF ................................................................................................. 27

Gambar 3.11 Rancangan antarmuka Home ..................................................................... 30

Gambar 3.12 Rancangan antarmuka Preprocessing ......................................................... 30

Gambar 3.13 Rancangan antarmuka Tweets.................................................................... 31

Gambar 3.14 Rancangan antarmuka TF-IDF ..................................................................... 31

Gambar 3.15 Rancangan antarmuka Klasifikasi ............................................................... 32

Gambar 4.1 class Koneksi ................................................................................................. 33

Gambar 4.2 Source code class koneksi ............................................................................ 34

Gambar 4.3 Source code method token() ........................................................................ 35

Gambar 4.4 Source code method cekterm() .................................................................... 35

Gambar 4.5 Source code method x() ................................................................................ 36

Gambar 4.6 Source code method tf() ............................................................................... 36

Gambar 4.7 Source code method idf() .............................................................................. 37

Gambar 4.8 Source code method tfidf() .......................................................................... 37

Gambar 4.9 Source code method ri() ............................................................................... 38

Gambar 4.10 Source code method dgc() .......................................................................... 38

Gambar 4.11 Source code method precision() ................................................................. 38

Gambar 4.12 Source code recall ...................................................................................... 39

Gambar 4.13 Source code method F-Measure ................................................................ 39

Gambar 4.14 Pembagian Data set .................................................................................... 42

Gambar 4.15 Grafik hasil pengujian precision .................................................................. 43

Gambar 4.16 Grafik hasil pengujian recall ....................................................................... 44

Gambar 4.17 Grafik hasil pengujian F-Measure ............................................................... 44

Gambar 4.18 Grafik Hasil Pengujian Akurasi .................................................................... 45

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DAFTAR TABEL Tabel 3.1 Kebutuhan Fungsional ...................................................................................... 14

Tabel 3.2 Kebutuhan Nonfungsional ................................................................................ 14

Tabel 3.3 File index .......................................................................................................... 23

Tabel 3.4 IDF(inverse document frequency) ..................................................................... 25

Tabel 4.1 Pengujian Kebutuhan Fungsional ..................................................................... 40

Tabel 4.2 Pengujian Kebutuhan Non-Fungsional.............................................................. 40

Tabel 4.3 Confusion Matrix .............................................................................................. 41

Tabel 4.4 Hasil pengujiann precision, recall, dan F-measure sistem ................................. 42

48

DAFTAR PUSTAKA

Abdurrahman. 2014. KLASTERISASI BUKU BERBAHASA INDONESIA DENGAN MENGIMPLEMENTASIKAN METODE TEXT MINING DAN ALGORITMA ARTIFICIAL BEE COLONY K-MEANS.

Cano, Alberto, Amelia Zafra, Sebastián Ventura, and Senior Member. 2012. “For Standard and Imbalanced Data.” 1–16.

Hidayat, Muhamad Arief. “Klasifikasi Berbasis Gravitasi Data Dan Probabilitas Posterior.” 1–6.

Honeycutt, Courtenay, and Susan C Herring. 2009. “Beyond Microblogging : Conversation and Collaboration via Twitter.” 1–10.

Krisandi, Nobertus, Bayu Prihandono, and Naive Bayes. 2013. “ALGORITMA K - NEAREST NEIGHBOR DALAM KLASIFIKASI DATA HASIL PRODUKSI KELAPA SAWIT PADA PT . MINAMAS.” 02(1): 33–38.

Kwak, Haewoon, Changhyun Lee, Hosung Park, and Sue Moon. 2010. “What Is Twitter , a Social Network or a News Media ? Categories and Subject Descriptors.” 591–600.

Luthfi, Emha Taufiq dan Kusrini. 2009. “Algoritma Data Mining.” In ed. Theresia Ari Prabawati. Yogyakarta: C.V Andi Offset.

Mustafidah, Hidayatul, Moch Kautsar Sophan, and Yeni Kustiyah Ningsih. 2013. “RANCANG BANGUN E-DOCUMENT DI KANTOR PELAYANAN NAÏVE BAYES CLASSIFIER.” 1: 1–9.

Peng, Lizhi, and Yuehui Chen. 2005. “A Novel Classification Method Based on Data Gravitation.” 667–72.

Peng, Lizhi, Bo Yang, Yuehui Chen, and Ajith Abraham. 2009. “Data Gravitation Based Classification.” Information Sciences 179(6): 809–19. http://linkinghub.elsevier.com/retrieve/pii/S0020025508004623 (March 28, 2014).

Pramudiono, Iko. 2003. “Pengantar Data Mining : Menambang Permata Pengetahuan Di Gunung Data.” 1–4.

Purnama, Ketut Eddy. 2012. “Classification of Emotions in Indonesian TextsUsing K-NN Method.” International Journal of Information and Electronics Engineering 2(6). http://www.ijiee.org/show-34-190-1.html (April 23, 2014).

Widodo, Prabowo Pudjo. 2013. Penerapan Data Mining Dengan Matlab. Bandung:

Rekayasa Sains.