Institutional Repository | Satya Wacana Christian University: Using Data Mining to Analyze Usage Pattern of Mobile Providers (Case Study PT. XL Area Salatiga)
USING DATA MINING TO ANALYZE USAGE
PATTERN OF MOBILE PROVIDERS
(CASE STUDY PT. XL AREA SALATIGA)
TESIS
Oleh:
Andreas Artahsasta Taroreh
NIM: 972011015
Program Studi Magister Sistem Informasi
Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana
Salatiga
Maret 2015
iv
Kata Pengantar
Puji syukur saya panjatkan kepada Tuhan Yesus Kristus atas kasih
setia dan penyertaan- Nya saya dapat menyelesaikan Tesis yang berjudul
“Using Data Mining To Analyze Usage Pattern Of Mobile Providers (Case
Study PT. XL Area Salatiga)” dengan baik. Laporan Tesis ini disusun
sebagai salah satu persyaratan dalam memperoleh gelar Master of Computer
Science (M.Cs) pada Program Studi Magister Sistem Informasi, Fakultas
Teknologi Informasi Universitas Kristen Satya Wacana Salatiga.
Tesis ini dapat selesai berkat bantuan dari berbagai pihak yang telah
memberikan bimbingan, ide, dan berbagai dukungan lainnya kepada penulis.
Pada kesempatan ini saya ingin menyampaikan ucapan terima kasih kepada :
1.
Bapak Dr. Dharma Putra Palekahelu., M.Pd, selaku Dekan Fakultas
Teknologi Informasi, Universitas Kristen Satya Wacana Salatiga.
2.
Bapak Prof. Ir. Danny Manongga, M.Sc., Ph.D, selaku Ketua Program
Studi Magister Sistem Informasi, Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana Salatiga, dan selaku dosen
pembimbing atas kesabaran memberikan bimbingan dan motivasi
kepada penulis dalam menyelesaikan thesis ini.
3.
Ibu Ade Iriani, MM, selaku dosen pembimbing dua atas kesabaran
memberikan
bimbingan
dan
motivasi
kepada
penulis
dalam
menyelesaikan skripsi ini.
4.
Kedua Orang Tua, Ce Hesti dan Adik Priska yang menjadi sumber
inspirasi penulis, terima kasih atas cinta kasih kalian.
5.
Bapak Christian Rudianto, Ibu Tri, Ibu Frances Sinanu, Bapak Toar
Sumakul dan EASE Family, atas diskusi inspiratif yang mendorong
penulis untuk menjadi lebih baik di bidang akademik.
v
6.
Bapak Toni Anandya Wicaksono, atas bantuan dan dukungan dalam
pengumpulan data dalam penelitian ini.
7.
Globees 2013 dan 2014 atas kebersamaan, dukungan, dan kegilaan kita
di Hongkong dan Taiwan.
8.
Teman – teman seperjuangan MSI angkatan 9 atas kebersamaan selama
kuliah.
9.
Biro Promosi UKSW, Sales Promotion Team UKSW, International
Office UKSW, atas kebersamaan dan proses pengembangan diri yang
telah dilewati.
10. Rekan – rekan seatap, Pondok Happy : Tara, Ocka, Okta, Wulan, Tessa,
Manda, Josh, Egen, Dede, Adven (Begadang jangan begadang kalau
tiada artinya).
11. Dan semua pihak yang tidak dapat saya sebutkan satu persatu yang telah
membantu saya dalam penyusunan tesis ini.
Salatiga, 2 Maret 2015
Andreas Artahsasta Taroreh
vi
Daftar Isi
Halaman
Halaman Judul.....................................................................................i
Halaman Pengesahan..........................................................................ii
Halaman Pernyataan..........................................................................iii
Kata Pengantar...............................................................................................iv
Daftar Isi................................................................................. ..........vi
Daftar Gambar................................................................................vi i
Daftar Tabel.......................................................................vii i
Abstract.................................................. ...........................................1
Bab 1 Introduction..........................................................................................1
Bab 2 Literature Review
1.1 Related Works................................................................................2
1.2 Data Mining...................................................................................3
2.2.1 Pivot Table..................................................................................3
2.2.2 Arrangement of Consumer Data………….................................4
Bab 3 Methodology........................................................................................4
Bab 4 Analysis and Discussion......................................................................6
Bab 5 Conclusion ........................................................................................10
References......................................................................................................11
vii
Daftar Gambar
Halaman
Figure 1
Revenue....................................................................................6
Figure 2
The most frequently used services...........................................8
Figure 3
Calls through the same providers.............................................8
Figure 4
Calls to other providers by time division.................................9
Figure 5
Calls to another provider based on the community.................9
Figure 6
Other providers most frequently contacted.............................9
Figure 7
Time and number of text......................................................10
Figure 8
Social media usage by kodam and stikes...............................10
viii
Daftar Tabel
Halaman
Table 1
XL Social Community Members Benefit.........................4
Table 2
User‟s Profile...........................................................................5
Table 3
XL Social Community Members Revenue..............................5
Table 4
Cross Tabulation Result between Variable.............................6
Table 5
Revenue Percentage of Both Community................................7
ix
Journal of Theoretical and Applied Information Technology
10th April 2015. Vol. 74 No.1
© 2005 - 2014 JATIT & LLS. All rights reserved.
ISSN: 1992-8645
www.jatit.org
E-ISSN: 1817-3195
USING DATA MINING TO ANALYZE USAGE PATTERN
OF MOBILE PROVIDERS
(CASE STUDY PT. XL AREA SALATIGA)
1
ANDREAS ARTAHSASTA TAROREH, 2DANNY MANONGGA, 3ADE IRIANI
1, 2, 3,
Information System Departement, SATYA WACANA CHRISTIAN UNIVERSITY
E-mail: 1andreas_artahsasta@yahoo.com, 2 dmanongga@gmail.com , 3ade.iriani@staff.uksw.edu
ABSTRACT
Data mining is one of the disciplines in computer science that explores the useful
information about individual trends and segments. The numbers of mobile operators in
Indonesia and high consumer displacement cause the competition among the operators
to provide service and rate that attract users. PT. XL Axiata (XL) as the second biggest
cellular providers in Indonesia gives special rate to the members of target community.
The purpose of this study was to analyze the usage patterns of service build from XL
community members who belong to groups of workers and students by conducting data
mining using a pivot table on the users‟ profile and consumer service usage data for
three consecutive months. The data was processed and analyzed to determine the
marketing strategy in accordance with constumer needs in order to improve loyalty. The
results of processing data showed that the variable of occupation and sex have effect on
the usage patterns of service which emerged. Moreover, the internet service was a
service that provides intake for most major mobile operators. By analyzing the usage
patterns of community members, it can assist the service providers in determining the
marketing strategy according to user needs.
Keywords: Data Minning, Pivot Table, Usage Pattern
PATTERN OF MOBILE PROVIDERS
(CASE STUDY PT. XL AREA SALATIGA)
TESIS
Oleh:
Andreas Artahsasta Taroreh
NIM: 972011015
Program Studi Magister Sistem Informasi
Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana
Salatiga
Maret 2015
iv
Kata Pengantar
Puji syukur saya panjatkan kepada Tuhan Yesus Kristus atas kasih
setia dan penyertaan- Nya saya dapat menyelesaikan Tesis yang berjudul
“Using Data Mining To Analyze Usage Pattern Of Mobile Providers (Case
Study PT. XL Area Salatiga)” dengan baik. Laporan Tesis ini disusun
sebagai salah satu persyaratan dalam memperoleh gelar Master of Computer
Science (M.Cs) pada Program Studi Magister Sistem Informasi, Fakultas
Teknologi Informasi Universitas Kristen Satya Wacana Salatiga.
Tesis ini dapat selesai berkat bantuan dari berbagai pihak yang telah
memberikan bimbingan, ide, dan berbagai dukungan lainnya kepada penulis.
Pada kesempatan ini saya ingin menyampaikan ucapan terima kasih kepada :
1.
Bapak Dr. Dharma Putra Palekahelu., M.Pd, selaku Dekan Fakultas
Teknologi Informasi, Universitas Kristen Satya Wacana Salatiga.
2.
Bapak Prof. Ir. Danny Manongga, M.Sc., Ph.D, selaku Ketua Program
Studi Magister Sistem Informasi, Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana Salatiga, dan selaku dosen
pembimbing atas kesabaran memberikan bimbingan dan motivasi
kepada penulis dalam menyelesaikan thesis ini.
3.
Ibu Ade Iriani, MM, selaku dosen pembimbing dua atas kesabaran
memberikan
bimbingan
dan
motivasi
kepada
penulis
dalam
menyelesaikan skripsi ini.
4.
Kedua Orang Tua, Ce Hesti dan Adik Priska yang menjadi sumber
inspirasi penulis, terima kasih atas cinta kasih kalian.
5.
Bapak Christian Rudianto, Ibu Tri, Ibu Frances Sinanu, Bapak Toar
Sumakul dan EASE Family, atas diskusi inspiratif yang mendorong
penulis untuk menjadi lebih baik di bidang akademik.
v
6.
Bapak Toni Anandya Wicaksono, atas bantuan dan dukungan dalam
pengumpulan data dalam penelitian ini.
7.
Globees 2013 dan 2014 atas kebersamaan, dukungan, dan kegilaan kita
di Hongkong dan Taiwan.
8.
Teman – teman seperjuangan MSI angkatan 9 atas kebersamaan selama
kuliah.
9.
Biro Promosi UKSW, Sales Promotion Team UKSW, International
Office UKSW, atas kebersamaan dan proses pengembangan diri yang
telah dilewati.
10. Rekan – rekan seatap, Pondok Happy : Tara, Ocka, Okta, Wulan, Tessa,
Manda, Josh, Egen, Dede, Adven (Begadang jangan begadang kalau
tiada artinya).
11. Dan semua pihak yang tidak dapat saya sebutkan satu persatu yang telah
membantu saya dalam penyusunan tesis ini.
Salatiga, 2 Maret 2015
Andreas Artahsasta Taroreh
vi
Daftar Isi
Halaman
Halaman Judul.....................................................................................i
Halaman Pengesahan..........................................................................ii
Halaman Pernyataan..........................................................................iii
Kata Pengantar...............................................................................................iv
Daftar Isi................................................................................. ..........vi
Daftar Gambar................................................................................vi i
Daftar Tabel.......................................................................vii i
Abstract.................................................. ...........................................1
Bab 1 Introduction..........................................................................................1
Bab 2 Literature Review
1.1 Related Works................................................................................2
1.2 Data Mining...................................................................................3
2.2.1 Pivot Table..................................................................................3
2.2.2 Arrangement of Consumer Data………….................................4
Bab 3 Methodology........................................................................................4
Bab 4 Analysis and Discussion......................................................................6
Bab 5 Conclusion ........................................................................................10
References......................................................................................................11
vii
Daftar Gambar
Halaman
Figure 1
Revenue....................................................................................6
Figure 2
The most frequently used services...........................................8
Figure 3
Calls through the same providers.............................................8
Figure 4
Calls to other providers by time division.................................9
Figure 5
Calls to another provider based on the community.................9
Figure 6
Other providers most frequently contacted.............................9
Figure 7
Time and number of text......................................................10
Figure 8
Social media usage by kodam and stikes...............................10
viii
Daftar Tabel
Halaman
Table 1
XL Social Community Members Benefit.........................4
Table 2
User‟s Profile...........................................................................5
Table 3
XL Social Community Members Revenue..............................5
Table 4
Cross Tabulation Result between Variable.............................6
Table 5
Revenue Percentage of Both Community................................7
ix
Journal of Theoretical and Applied Information Technology
10th April 2015. Vol. 74 No.1
© 2005 - 2014 JATIT & LLS. All rights reserved.
ISSN: 1992-8645
www.jatit.org
E-ISSN: 1817-3195
USING DATA MINING TO ANALYZE USAGE PATTERN
OF MOBILE PROVIDERS
(CASE STUDY PT. XL AREA SALATIGA)
1
ANDREAS ARTAHSASTA TAROREH, 2DANNY MANONGGA, 3ADE IRIANI
1, 2, 3,
Information System Departement, SATYA WACANA CHRISTIAN UNIVERSITY
E-mail: 1andreas_artahsasta@yahoo.com, 2 dmanongga@gmail.com , 3ade.iriani@staff.uksw.edu
ABSTRACT
Data mining is one of the disciplines in computer science that explores the useful
information about individual trends and segments. The numbers of mobile operators in
Indonesia and high consumer displacement cause the competition among the operators
to provide service and rate that attract users. PT. XL Axiata (XL) as the second biggest
cellular providers in Indonesia gives special rate to the members of target community.
The purpose of this study was to analyze the usage patterns of service build from XL
community members who belong to groups of workers and students by conducting data
mining using a pivot table on the users‟ profile and consumer service usage data for
three consecutive months. The data was processed and analyzed to determine the
marketing strategy in accordance with constumer needs in order to improve loyalty. The
results of processing data showed that the variable of occupation and sex have effect on
the usage patterns of service which emerged. Moreover, the internet service was a
service that provides intake for most major mobile operators. By analyzing the usage
patterns of community members, it can assist the service providers in determining the
marketing strategy according to user needs.
Keywords: Data Minning, Pivot Table, Usage Pattern