ID3 Algorithm to Identify Customer Loyalty
Factor at Semarang Ceramics Company
Tesis
Oleh:
Isadora Nugroho
NIM: 972011006
Program Studi Magister Sistem Informasi
Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana
i
ID3 Algorithm to Identify Customer Loyalty
Factor at Semarang Ceramics Company
Tesis
Oleh:
Isadora Nugroho
NIM: 972011006
Program Studi Magister Sistem Informasi
Fakultas Teknologi Informasi
Universitas Kristen Satya Wacana
iii
Pernyataan
Tesis berikut ini :
Judul
: ID3 Algorithm to Identify Customer
Loyalty Factor at Semarang Ceramics
Company
Pembimbing
: 1. Prof. Ir. Danny Manongga, M.Sc., Ph.D
2. Dr. Ir. Wiranto H. Utomo, M.Kom.
adalah benar hasil karya saya :
Nama
:
Isadora Nugroho
NIM
:
972011006
Saya menyatakan tidak mengambil sebagian atau seluruhnya dari
hasil karya orang lain kecuali sebagaimana yang tertulis pada daftar
pustaka.
Pernyataan ini dibuat dengan sebenarnya sesuai dengan ketentuan
yang berlaku dalam penulisan karya ilmiah.
Salatiga, Juni 2013
(Isadora Nugroho)
iv
Prakata
Puji syukur ke hadirat Tuhan Yesus Kristus atas berkat,
rahmat, serta bimbingan-Nya sehingga penulis dapat menyelesaikan
Thesis yang berjudul “ID3 Algorithm to Identify Customer
Loyalty Factor at Semarang Ceramics Company”. Laporan thesis
ini disusun guna memenuhi persyaratan untuk memperoleh gelar
Master of Computer Science (M.Cs.) pada Program Studi Magister
Sistem Informasi Fakultas Teknologi Informasi Universitas Kristen
Satya Wacana Salatiga.
Dalam menyelesaikan thesis ini, penulis mendapat bantuan
dan dukungan dari berbagai pihak, baik secara langsung maupun
tidak langsung. Oleh karena itu pada kesempatan ini penulis ingin
mengucapkan terima kasih kepada:
1.
Tuhan Yesus Kristus yang telah memberi kesehatan kepada
penulis sehingga dapat dengan lancar mengerjakan thesis ini.
2.
Papi, Mami, Koko (sigit, eddy, santoso), Cece (olif, diana).
Terima kasih atas segala bantuan baik moril maupun materiil,
dorongan, dukungan, masukan, pengertian, kesabaran, kasih
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3.
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4.
Bapak Dr. Dharmaputra Palekahelu, M.Pd selaku Dekan
Fakultas Teknologi Informasi Universitas Kristen Satya
v
5.
Bapak Prof. Dr. Ir. Eko Sediyono, M.Kom selaku Kaprogdi
Magister Sistem Informasi Universitas Kristen Satya Wacana
Salatiga yang telah memberikan bantuan dan dorongan
semangat kepada penulis.
6.
Bapak Prof. Ir. Danny Manongga, M.Sc., Ph.D atas
kesediaannya menjadi dosen pembimbing pertama, yang telah
sabar dalam memberikan bimbingan dan pengarahan selama
penyusunan thesis ini.
7.
Bapak Dr. Ir. Wiranto Herry Utomo atas kesediaannya menjadi
dosen pembimbing kedua, yang telah sabar dalam memberikan
bimbingan, masukan dan pengarahan selama penyusunan
thesis ini.
8.
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9.
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10.
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persahabatan hingga akhir kuliah, semoga kalian semua tetap
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11.
Teman-teman ngajar, teman-teman kos, teman-teman dolan,
dan yang tidak dapat disebutkan satu persatu. Terima kasih
vi
12.
Teman-teman di UKSW dan semua pihak yang tidak dapat
penulis sebutkan satu persatu hingga selesainya thesis ini,
terimakasih all. SEMANGAT Semua.... Jiao You ya!!!...
13.
Murid-murid dan anak-anak mahasiswa, terimakasih atas
kekritisan
kalian
dalam
mengkuti
kelas
dan
telah
menghadirkan keceriaan dalam kelas. Sukses untuk kalian
semua yaaa...
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lucu-lucu ’n imut-imut yang membantu penulis dalam melepas
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Penulis menyadari bahwa Thesis ini masih jauh dari
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bermanfaat bagi semua pembaca. Terima kasih, Tuhan berkati.
Salatiga, Juni 2013
vii
Daftar Isi
Hal
Halaman Judul ... i
Halaman Pengesahan ...
ii
Halaman Pernyataan ...
iii
Prakata ...
iv
Daftar Isi ...
vii
Daftar Gambar ...
viii
Daftar Tabel ...
ix
Daftar Lampiran ...
x
Daftar Singkatan ...
xi
Abstract ...
1
Bab 1 Introduction ...
1
Bab 2 Literature Review ...
1
Bab 3
Customer Analysis ...
1
3.1 Customer Loyalty ...
1
3.2 Service Quality ...
2
3.3 Relationship between Customer Loyalty and Service
Quality ...
2
Bab 4
ID3 Algorithm ...
2
4.1 Entropy ...
3
4.2 Information Gain...
3
Bab 5
Data Preparation and Architecture Model ...
3
Bab 6
Discussion ...
3
6.1 Servqual Model Formulas ...
4
6.2 Correlation Test between Variable ...
4
6.3 ID3 Algorithm Integration (Entropy & Information Gain) 4
6.3.1 Reliability Dimension...
5
6.3.2 Ressponsiveness Dimension ...
5
6.3.3 Assurance Dimension ...
5
6.3.4 Emphaty Dimension ...
5
6.3.5 Tangibles Dimension ...
5
6.4 Decision Tree ...
5
6.5 Evaluation ...
5
Bab 7
Analysis ...
6
Bab 8
Conclusion...
7
References ... 7
viii
Daftar Gambar
Hal
Figure 1
Correlation between Service Quality and Customer
Loyalty ...
2
Figure 2
Architectural Model Flowchart ...
3
Figure 3
Servqual Method with ID3 ...
3
Figure 4
Correlation Test between Variable ...
4
Figure 5
Target Attribute ...
4
Figure 6
Servqual Attribute Dimension ...
5
Figure 7
Tangibles Attribute ...
5
ix
Daftar Tabel
x
Daftar Lampiran
Hal
Kuesioner Penelitian...
8
Dimensi Kehandalan (Reliability) ...
9
Dimensi Ketanggapan (Responsiveness)...
9
Dimensi Jaminan Mutu (Assurance) ...
10
Dimensi Empati (Emphaty) ...
10
xi
Daftar Singkatan
ID3
: Iterative Dichotomizer Tree
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
1
ID3 Algorithm to Identify Customer Loyalty Factor at
Semarang Ceramics Company
Isadora Nugroho
Master of Information Systems,
Faculty of Information
Technology, Satya Wacana
Christian University, Indonesia
isadoranugroho@gmail.com
Danny Manongga
Information System Department
Faculty of Information
Technology, Satya Wacana
Christian University, Indonesia
dmanongga@gmail.com
Wiranto H. Utomo
Information System Department
Faculty of Information
Technology, Satya Wacana
Christian University, Indonesia
wiranto.utomo@staff.uksw.edu
ABSTRACT
The aim of this research is to identify the customer loyalty at a Semarang ceramics company. The research process uses ID 3 algorithm and 5 SERVQUAL attributes, reliability, assurance, tangible, empathy, and responsiveness. Questioner data is the main data, which is analyzed by WEKA 3.7.7 software. The result of this research is Responsiveness attribute and its indicator quick service to the customer is the main factor which is influence the customer loyalty.
Keywords
Decision Tree, Algorithm ID3, Service Quality, Customer Loyalty
1.
INTRODUCTION
Recently, ceramics import from other country enters Indonesia and they give the best offer to the customer. Mirrored to this situation, local company should prepare and plan some strategic in providing the best service to the customer. With good strategic, local company can compete to foreign ceramics company especially to reach the customer loyalty. This research observes the problem in Semarang Ceramics Company, Indonesia. There are some factors to reach customer loyalty, first, creating a good relationship to the customer, give the best service and maintain the customer satisfaction. To implement these three factors is not as easy as turning a hand. Company should exert every effort to reach the customer satisfaction and profit company so the company can survive in the middle of competition.
Company should prepare and plan the best strategy to face the competition and to reach the potential customer. There are 5 dimension which influence the customer loyalty, reliability, assurance, tangible, empathy, and responsiveness. In measuring customer satisfaction and customer loyalty, analyzed and data observed should be held to find the factors of the problem through quisioner method. Some journals use ID3 Algorithm as decision tree in every problem. ID3 concept implementation could help the company to identify potential customer. From the tools, the company can understand the customer behavior as a recommendation to marketing implementation strategy which can reach the best benefit to Semarang Ceramics Company.
2.
LITERATURE REVIEW
There are some previous researches related to the theory. The first title is ID3 Classifier for Pupils’ Status Prediction [8]. The research explained that decision tree is used as a basic to predict required student status to further studies. Data mining is the source data of this research. The result of this research is the student classification which has high academic output.
Second research evaluated the patient disease diagnose,
Performance Evaluation of Decision Tree Classifiers on Medical Datasets [1]. This research is a broad material, so the researcher decide to use decision tree to diagnose disease such as Brest cancer diagnose with ultrasonic picture, ovaries cancer and heart beat diagnose. The research compares analysis accuracy and time complexity by using ID3, C4.5 and CART. These tools is able to read and translate to medical diagnose. The result of this research is decision tree works well in the medical classification data.
The last research is Case Study on High Dimensional Data Analysis Using Decision Tree Model [12]. This research is to predict the disease possibility in a region. This research, which identificate the parameter significant in prediction process, uses Decision tree. There are 3 models which is created trough ID3 Algorithm, unsupervised model to identification low level family characteristics and supervised model to high level family. Grouping model is enabling to understand the disease history group and decision tree is used to solve problem. The result is risk factor like climate, rainfall, deadly disease spread, water, temperature and environment is the highest factor which influences the low level family life and hereditary health history is for high level one.
In calculating and creating decision tree, this research uses ID3 Algorithm. Customer questionnaire result, with 5 dimensions in SERVQUAL, is the research data. In calculation process, the system is automatically calculating in ID3 Algorithm. The result of this research is loyalty customer format, loyal and non-loyal customer to the company.
3.
CUSTOMER ANALYSIS
This research focuses on customer analysis especially customer behavior. The aim is to identify the loyalty customer factors and its relation to customer service quality of the company. These factors are divided to some variable and attribute which is the most influence to the company. From the variable data, it can conclude basic factor of customer loyalty to the company.
3.1 Customer Loyalty
Customer loyalty is repurchasing of a product or a service because of the interest of the product or the service. Customer loyalty is a continue manifest of customer satisfaction in using a product or service. There are some loyal customers like below [6]:
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
2 b. Purchase out of common product/service. Loyal customer doesn’t only purchase a product, but also purchase another product or service in the same company.
c. Give a recommendation to others. Loyal customer will recommend to others about their positive experience in purchasing a product or a service in a company. They persuade other not to purchase in the other company.
d. Show uninterested to try another product. They trust the product or a service, that they use is the best product and different to other.
3.2 Service Quality
A group of attribute is needed to analyze service quality. Attribute is behavior or specific characteristics which represent and point of the service [4]. Service dimension is the main thought in deciding the characteristics of the service. There are 5 dimensions to analyze the service:
1. Tangible
Attribute and dimension, which include physical facilities, to fulfill the customer satisfaction, like: building, equipment. 2. Reliability
Attribute and dimension, which include capability in servicing to the customer like promised.
3. Responsiveness
Willingness to help customer and responsive to what customer need. Capability to give proper information and always give the best service as soon as possible.
4. Assurance
Make a safety feeling and comfortable to the customer. These conditions influence to the customer because of its credibility, politeness, hospitality and employee knowledge in servicing customer.
5. Emphaty
Give more attention to the customer. Simplicity of making a relation, good communication, personal attention and understand the customer needs.
3.3 Relation between Service Quality and
Customer Loyalty
Service quality and customer loyalty has a tight correlation. If the company can fill customer’s expectation, need and wish, the value of the service quality is good. They will be a loyal customer if their need, wish and expectation about the product are filled. For sure, they will come back and repurchase a product or service in the same company and don’t have any interest to purchase another product from competitor. Having loyal customer is the end of the business. To reach the aim, the company should improve their service quality with focus on 5 dimensions, tangible, reliability, responsiveness, assurance, and empathy. Through the efforts, the company can fill customer need, hope and expectation. It can attract loyal customer to come to purchase in the company, like shown in Figure 1.
Figure 1: Correlation between Service quality and Customer loyalty
4.
ID3 ALGORITHM
One of i nduction decisi on tree algori thms is ID3 (Iter at ive Dichotomies 3). ID3 built by J. Ross Quinlan [ 1] . ID3 Algor ithm could be implemented t o Recur sive function (functi on w hich can call it). ID3 is basic deci sion tr ee lear ning algorithm. Algori thm sear ches gr eedil y i n all decision tree possibil ities.
ID3 character isti cs in buldi ng decision tree ar e fr om root to leaf (top-dow n) and traini ng data recur si vely. It i s parted to a small categor ies in bui lt the tr ee (divide and conquer ). The fir st attr ibute should be plant on the r oot, and then it i s evaluated by statistics i nfor mation gain measurement. Data gr oup consist of decisi on variable and outcome var iable. Bot h var iables shoul d have categorical value. ID3 need t he value as a label and symbol which doesn’t have relati on one another . Below is the ID3 Algor ithm:
1. Tree is started as a single root, which represent all data.
2. After node root, the data will measured by information gain to select which attribute can be divided attribute.
3. A branch of the tree is made from the divided attribute and the data will distribute to other branch.
4. Algorithm will use the same process (recursive) to make secession tree. When the attribute is the dividing node or branch, the attribute will be kept out from information gain value.
5. Recursive dividing process will stop if one of the conditions is not fulfilled:
All data from branch include in the same class. All attribute is already used, but the rest is in the
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
There is no data on the new branch. In this case, we should take from the previous node and the data is taken which represent the most class to be class label.
4.1 Entropy
A classified object on the tree should be tested entropy value. Entropy is a measurement of the information theory to get the characteristics of impurity and homogeneity from the group data. From entropy value, we can count the information gain value (IG) from each attribute [8].
Entropy(S) = -pa log2 pa - pb log2 S : Sample Room (data) to train.
Pa : Positive Solution amount (supported) of the sample data in some criteria.
Pb : Negative Solution (unsupported) of the sample data in some criteria.
From the entropy formula show that Entropy (S) is a needed bit to be extracted in a class (a or b) from the random data in an S sample room. It can conclude that the smaller entropy value, the better extraction in a class. The code, which gives optimal information, is –log2p bits. It is to inform probability p. Bit amount to extract S in to a class is -pa log2 pa - pb log2.
4.2 Information Gain
After getting entropy value in a group data, we can measure the attribute affectivity to classify the data. It is information gain. Information gain of an attribute is like bellow [8]:
A : attribute
v : a possibility value for an attribute
Values(A) : a possibility assemblage for an attribute |Sv| : Sample amount for v value
|S| : Total sample data
Entropy(Sv) : entropy for sample v value
5.
DATA PREPARATION AND
ARCHITECTURE MODEL
The method of collecting data is questionnaire method. The questionnaires spread out to the customer, which is direct purchase and online purchase in a Semarang ceramics company. There are 128 data collected and will be analyzed. The analysis is to solve the problem which shows up in the company, especially Service quality dimension. Flowchart model as shown in Figure 2.
Start
Identification Servqual 5 variables
Check Completeness Attributes Count Value Entropy Count Value Gain Gain the Highest Value
Check the rest of Attributes
Result
End
NO YES
Figure 2: Architectural Model Flowchart
6.
DISCUSSION
The analysis method to implement ID3 Algorithm based on the scope of company service quality especially in Semarang Ceramics Company to the customer. Qualitative approach is used to make quantitative approach. Case study of this research is the service quality implementation can be seen in Figure 3.
Servqual Model Formulas
Test the Correlation Between Variable
Integration Algorithm ID 3
(Entropy & Information Gain )
Decision Tree
Evaluation
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
4
6.1 Servqual Model Formulas
Model Servqual variable is like below:
1. Tangibles (X1) surface of service quality like physical facilities, equipment, personnel and communication.
2. Reliability (X2) Capability to show the best service like promises punctual and trustable. Service should be punctual and in time without any fault.
3. Responsiveness (X3) willingness to help the customer and give a proper service. Long service cause negative response about the company service.
4. Assurance (X4) knowledge, politeness and capability to say trust and assure to the customer and give safety feeling or guarantee to the service.
5. Empathy (X5) give attention and understanding to customer personally as shown in Table 1.
Table 1. Variable in Servqual Model Variable Operational Indicators
Tangibles (X1) Real aspect of the physical appearance.
-Product -Modern
equipment -Facilities -Employee Neat Reliability (X2) Capability to serve
on time, punctual and trustable without any mistake
-Consistent -On time -Serve like
promised -Care -Sincerity Responsiveness
(X3)
Willingness to help customer and give a proper service.
-Clear Information -Service Speed -Service
accuracy - Willingness to
help - Readiness to
respond Assurance (X4) Knowledge,
politeness and employee capability to say trust and say trust to the customer. Give safety feeling or guarantee. - Trust - Safe - Comfortable - Polite - Guarantee
Emphaty (X5) Give a personal attention to the customer. - Personal Attention - Proper operational time - Specifically need understanding - Work time
suitability
In the research, service quality variable will represented trough alternative respond like: Good, Bad, Quick, Slow, Convince, Satisfaction, Comfortable and Less.
6.2 Correlation Test between Variable
If attribute and variable are correlated, the relation can be shown in Figure 4.Figure 4: Correlation Test between Variable
6.3 ID3 Algorithm Integration (Entropy &
Information Gain)
Target Attribute is customer loyalty which has loyal and disloyal value, while dimension is Reliability, Responsiveness, Assurance, Empathy, and Tangibles. There are 128 services from customer types, and the loyalty can be shown in Figure 5.
Figure 5: Target Attribute
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
5
Figure 6: Servqual Attribute Dimension
6.3.1
Reliability Dimension
There are 64 well worth variable from loyal type. 33 well worth variables for disloyal type, 18 variables with a bad value for loyal type and 13 variables with a bad value for disloyal type.
6.3.2
Responsiveness Dimension
There are 50 quick value variables from loyal type, 13 quick variable from disloyal type, 15 slow value variable from loyal type and 50 slow value variables from disloyal.
6.3.3
Assurance Dimension
There are 29 low value variables from loyal type, 12 low variables from disloyal, 32 convince value variable from loyal type and 55 convince value variable from disloyal.
6.3.4
Emphaty Dimension
There are 61 satisfy value variables from loyal type, 25 satisfy value variables from disloyal, 12 less satisfy value variable from loyal type and 30 less satisfy value variable from disloyal.
6.3.5
Tangibles Dimension
There are 21 less comfortable value variables from loyal type, 22 less comfortable value variables from disloyal, 29 comfortable value variable from loyal type and 30 comfortable value variable from disloyal.
6.4 Decision Tree
Figure 6: Tangibles Attribute
Figure 6 is a tracking decision tree problem trough ID3 Algorithm. It shows that Responsiveness is a root of the tree. The tree has some leaf, Reliability, Empathy, Assurance. Empathy, Reliability, Tangibles, Assurance. Empathy, Reliability, Assurance. Empathy, Assurance, Tangibles, Reliability.
6.5 Evaluation
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
6
Figure 7: Loyal Customer Factor
7.
ANALYSIS
From the research of service quality uses Servqual method in ID3 Algorithm; show that loyal customer can be shown in the Table 2.
Table 2. ID3 Algorithm result table
Reliability Responsiveness Assurance Emphaty Tangibles
Good Quick Convince Satisfy Comfortable
Good Quick Convince Satisfy Less Comfortable
Good Quick Convince Less Satisfy Comfortable
Good Quick Convince Kurang Less Comfortable
Good Quick Less Convince Satisfy Comfortable
Good Quick Less Convince Satisfy Less Comfortable
Good Quick Less Convince Kurang Comfortable
Good Quick Less Convince Kurang Less Comfortable
Good Slow Convince Satisfy Comfortable
Good Slow Convince Satisfy Less Comfortable
Good Slow Convince Kurang Comfortable
Good Slow Less Convince Satisfy Comfortable
Bad Quick Convince Satisfy Comfortable
Bad Quick Convince Satisfy Less Comfortable
Bad Quick Convince Kurang Comfortable
Bad Quick Convince Kurang Less Comfortable
Bad Quick Less Convince Satisfy Comfortable
Bad Quick Less Convince Satisfy Less Comfortable
Bad Slow Convince Satisfy Comfortable
Bad Slow Convince Satisfy Less Comfortable
From the all the variable Reliability, Responsiveness, Assurance, Empathy, and Tangibles can be conclude that:
If they have quick responses and good reliability, the other variable will not be influenced. But if they has bad reliability, the other factor that should be focus is Empathy, should satisfy the customer. If the empathy is not satisfying enough, Assurance factor will play the main role and should convince the customer.
If the response is slow, the other factor which should be focus on is empathy and Assurance or empathy and Tangibles. Empathy should satisfy the customer. Assurance should assure the customer and tangibles should make the customer feel comfortable in purchasing or transacting. While Reliability doesn’t have a big influence if the responsiveness to the customer is slow.
Ressponsiveness Quick
Reliability=good
Reliability=bad, Emphaty=satisfy
Reliability=bad, Emphaty=less satisfy, Assurance= convince Slow
Emphaty=satisfy, Reliability=good, Tangibles=less comfortable, Assurance= convince Emphaty=satisfy, Reliability=good, Tangibles=comfortable
Emphaty=satisfy, Reliability=bad, Assurance=convince
International Journal of Computer Applications (0975 – 8887) Volume 69– No.11, Mey 2013
7
8.
CONCLUSION
Decision tree in ID3 Algorithm and WEKA 3.7.7 can solve some problems in understanding the customer loyalty factor. Both are easy to understand especially to analyze the loyalty factor. The main factor of this analysis is responsiveness. It is related to the employee capability to help the customer and give a quick response to the customer. Responsiveness is a dynamic dimension. It is influence the employee behavior, like Clear Information, Service Speed, Service accuracy, Willingness to help, and Readiness to respond.
9.
REFERENCES
[1]
D. Lavanya, and K. U. Rani, "Performance Evaluation of Decision Tree Classifiers on Medical Datasets", (IJCA) International Journal of Computer Applications, Vol. 26 No. 4, July 2011.[2]
D. L. Gupta, A. K. Malviya, and S. Singh, "Performance Analysis of Classification Tree Learning Algorithms", (IJCA) International Journal of Computer Applications, Vol. 55 No. 6, October 2012.[3]
D. S. Kumar, N. Ananthi, and M. Devi, "An Approach to Automation Selection of Decision Tree based on Training Data Set", (IJCA) International Journal of Computer Applications, Vol. 64 No. 21, February 2013.[4]
Firdian Endy, Surachman, and Santoso Budi, 2012, Servqual Application Method and Six Sigma to Analise PT. PLN (Persero) Service Quality Network Service Unit (UPJ) Dinoyo Malang, Science and Engineering, Vol.13 No.3 September 2012, ISSN: 1412-7237.[5]
H. Monem, A. R. C. Hussin, and R. Sharifian, "Comprehensive Prioritized Perspectives of CRM System for Implementation in the Developing Countries Hospitals", (IJCA) International Journal of Computer Applications, Vol. 50 No. 20, July 2012.[6]
H. S. Soliman, "Customer Relationship Management and Its Relationship to the Marketing Performance", International Journal of Business and Social Science, Vol. 2 No. 10, June 2011.[7]
J. Munusamy, S. Chelliah, and H. W. Mun, "Service Quality Delivery and Its Impact on Customer Satisfaction in the Banking Sector in Malaysia", International Journal of Innovation Management and Technology, Vol. 1, No. 4, October 2010, ISSN: 2010-0248.[8]
K. Nandhini, and S. Saranya, "ID3 Classifier for Pupils' Status Prediction", (IJCA) International Journal of Computer Applications, Vol. 57, November 2011.[9]
Nino, 2012, Service Quality Infulence Analysis and Relationship Quality to Customer Loyalty on AHASS Tamtama Motor in Kediri Region, REVITALISATION Management Journal, Vol.1, No.2, September 2012.[10]
N. Malpathak, S. Shinde, and R.George, "Cloud Based CRM Application", (IJCA) International Journal of Computer Applications, April 2012, ISSN: 0975-8887.[11]
R. A. Soeini, B. Jafari, and M. Abdollahzadeh, "CRM Performance Measurement Process", (IJES) International Journal of Emerging Sciences, March 2012, ISSN: 2222-4254.8
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s/d 100 juta
f. > 100 juta
2. Sudah berapa lama anda menjadi Customer PT SCI ?
a. < 1 tahun
b. 1 tahun s/d 2 tahun
c. 2,1 tahun s/d 3 tahun
d. > 4 tahun
3. Apakah anda membeli produk keramik di Perusahaan lain selain
di PT SCI?
a. Ya
b. Tidak
4. Apa alasan anda memilih Perusahaan lain selain PT SCI ?
a. Keamanan
b. Fasilitas
c. Pelayanan (Service)
d. Lainnya, sebutkan ______________________________________
Data ini akan ditangani dengan penuh kerahasiaan
Berdasarkan pengalaman Bapak/Ibu sebagai sebagai customer
dari PT SCI, kami memohon kesediaan anda untuk memikirkan
tentang kualitas pelayanan perusahaan perbankan yang ideal
menurut anda. Mohon tunjukkan pendapat anda dengan memberi
tanda centang (
√) pada jawaban yang Bapak/Ibu anggap paling mewakili keadaan
Bapak/Ibu.
DIMENSI KEHANDALAN (RELIABILITY)
Kemampuan karyawan untuk memberikan pelayanan yang
dijanjikan dengan baik dan tepat.
No.
Pernyataan
Baik
Buruk
1.
Bagaimana pelayanan perusahaan, ketika anda
memiliki
masalah
dan
apakah
pihak
perusahaan
cepat
serta tanggap
dalam
menyelesaikannya
2.
Apakah pelayanan pihak perusahaan baik
pertama kalinya
10
perusahaan di mata customer
Sehingga secara umum anda menyimpulkan bahwa
kemampuan
karyawan
untuk
memberikan
pelayanan yang dijanjikan dengan baik dan tepat
adalah…
DIMENSI KETANGGAPAN (RESPONSIVENESS)
Ketersediaan Perusahaan untuk membantu customernya dan
memberikan pelayanan yang cepat
No.
Pernyataan
Cepat
Lambat
1.
Bagaimana
karyawan
perusahaan
memberikan pelayanan yang tepat di saat
customer membutuhkannya
2.
Bagaimana reaksi karyawan perusahaan
dalam memberikan pelayanan secara tepat
kepada customer
3.
Bagaimana
perilaku
karyawan
dalam
menunjukkan reaksi tidak pernah terlalu
sibuk dan selalu memiliki waktu terhadap
customer
Sehingga secara umum anda menyimpulkan bahwa
ketersediaan
Perusahaan
untuk
membantu
customernya dan memberikan pelayanan yang
cepat adalah…
DIMENSI JAMINAN MUTU (ASSURANCE)
Pengetahuan dan keramahan dari karyawan perusahaan dan
kemampuan untuk memberikan rasa aman dan percaya terhadap
customer.
No.
Pernyataan
Meyakinkan
Kurang
1.
Bagaimana tanggapan karyawan saat
menjawab
pertanyaan-pertanyaan
yang anda ajukan, apakah memiliki
pengetahuan yang cukup.
2.
Bagaimana
sikap
karyawan
11
3.
Bagaimana kekonsistenan karyawan
dalam bersikap ramah terhadap anda
Sehingga secara umum anda menyimpulkan
bahwa pengetahuan dan keramahan dari
karyawan perusahaan dan kemampuan untuk
memberikan rasa aman dan percaya terhadap
customer adalah…
DIMENSI EMPATI (EMPATHY)
Kepedulian perusahaan dalam memberikan perhatian secara khusus
kepada customernya.
No.
Pernyataan
Memuaskan
Kurang
1.
Bagaimana pelayanan perusahaan
dalam memberikan perhatian khusus
secara individu
2.
Bagaimana operasi layanan dalam
memberikan waktu yang sesuai
kepada customernya
3.
Bagaimana
pola
karyawan
perusahaan
dalam
memahami
kebutuhan khusus masing-masing
customer
Sehingga secara umum anda menyimpulkan
bahwa
kepedulian
perusahaan
dalam
memberikan perhatian secara khusus kepada
customernya
adalah…
DIMENSI FISIK (TANGIBLE)
Penampilan dari fasilitas fisik (gedung, kursi, dll), perlengkapan,
karyawan, dan alat- alat komunikasi.
No.
Pernyataan
Nyaman
Kurang
12
3.
Apakah karyawan berpenampilan rapi
dan meja kerja tertata rapi dan nyaman.
Sehingga secara umum anda menyimpulkan
bahwa penampilan dari fasilitas fisik (gedung,
kursi, dll), perlengkapan, karyawan, dan alat-
alat komunikasi.
13
Isadora Nugroho <isadoranugroho@gmail.com>
IJCA May 2013 Edition: Letter of Acceptance
1 pesan
Editor IJCA <editor@ijcaonline.org>
4 Mei 2013 19.08
Kepada: isadoranugroho@gmail.com, dmanongga@gmail.com,
wiranto.utomo@staff.uksw.edu
Dear Isadora Nugroho, Danny Manongga and Wiranto H. Utomo,
We are delighted to inform that your research paper has been
“Accepted for Publication” in International Journal of Computer
Applications (IJCA) May 2013 Edition.
Paper Title:
ID3 Algorithm to Identify Customer Loyalty Factor at
Semarang Ceramics Company
Paper Reference ID: pxc3887900
The important deadlines regarding publication are as follows:
Camera ready paper submission : May 15, 2013
Copyright transfer : May 15, 2013 (
IJCA Copyright Form
)
Publication fees transfer : May 15, 2013
The research article will be published in IJCA Digital Library on May
17, 2013.
All the selected papers will be published in IJCA Digital Library with
initial indexing with Google Scholar, CiteSeer, UlrichsWeb and
ScientificCommons Index, University of St. Gallen, Switzerland. The
articles are also indexed with SAO/NASA ADS Physics Abstract
Service supported by Harvard University and NASA, Informatics and
ProQuest CSA Technology Research Database. International Journal
of Computer Applications is a voting member of CrossRef, USA and
each of its research articles is allotted a unique DOI reference.
Article Processing Fees
Processing charge for each general paper : USD 62.50 (INR
2900)
The Charges includes publication, indexing, maintenance of link
resolvers and journal infrastructures. Find attached IJCA Payment
Instructions for the payment transfer guidelines and the mode of
payment according to your domicile country. The invoice/ receipt will
be delivered to you on subject to realization of the payment.
You are requested to re-submit your paper as Camera Ready Copy
14
prescribed IJCA Paper Template on or before May 15, 2013. Also
find attached the copy of the Review Report upon your research
article along with the IJCA template.
IMPORTANT: Conformance to IJCA template is mandatory for
inclusion and citation with Google Scholar, CiteSeer, UlrichsWeb,
NASA ADS and ProQuest CSA Technology Research Database.
Thank you for your association with IJCA.
Best regards,
Editorial Support Team,
International Journal of
Computer Applications,
Foundation of Computer Science,
New York, USA.
www.ijcaonline.org
[ Call for Paper (Open):
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]
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