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Sasmoko, Sasmoko

Lembar Peer Review "Corruption Cases Mapping Based on Indonesia's Corruption Perception Index"

Triady, Mochamad Sandy

Kurniasari, Ratih

Utami, Ami Fitri

Sofyan, Muhammad Idham

(Check) Investigation of
Leverage Effect in Indonesian
Stock Market
by Rini Wongso
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English

Similarity - Investigation of Leverage Effect in Indonesian Stock Market

Hamali, Sambudi

Nur Suci, Rumondang Puji

Hanisman, Hanisman

Arga, Filia

(Check) Using analytic hierarchy
process
by Rini Wongso
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Sulistyo Heripracoyo, Fenny Meilia, Candra
Ronny, Umar Eko Prasetyo. "Model of
measuring the influence of Knowledge
Management system to IT complaints, case
study in telecomunication company", 2016
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Yunus, Ulani

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Heripracoyo, Sulistyo

978-1-5090-3352-2/16/$31.00 ©2016 IEEE 16-18 November 2016, Aston Tropicana Hotel, Bandung, Indonesia 
2016 International Conference on Information Management and Technology (ICIMTech) 
Page 102 
Model of Measuring the Influence of Knowledge 
Management System to IT Complaints, Case Study in 
Telecomunication Company 
 
Sulistyo Heripracoyo, Fenny Meilia, Candra Ronny,  Umar Eko Prasetyo 
Information Systems Department 
Bina Nusantara University 
Jakarta, Indonesia 
hpracoyo@binus.edu, {fenny.meilia, chandraronisinaga, umareko27}@gmail.com 
Abstract— The purpose of this study is to investigate the best 
practices in the transdisciplinary field of knowledge management 
system implementation and measurement of IT Complain in a 
telecommunication company (PT Telkomsel). This paper 
examines three variables of Knowledge Management (People, 
Process and Technology) and IT Complain Variable. This 
research used two methods such as a qualitative and quantitative 
method. Qualitative methods of interviewing and observation 
and quantitative method by gave a questionnaire to respondent. 
As for analysis research used descriptive and verificative method. 
The goal of this research will be used to know how useful the role 
and influence of the knowledge management system for customer 
complaint. This paper is   intended to provide a model to 
measure the effect of Knowledge Management to IT complain 
especially in Telecommunication Company.  
Keywords—Verificative Analysis, Descriptive Analysis, 
observation, IT Service Management Centre, Knowledge 
Management 
I. BACKGROUND 
At PT Telkomsel, Knowledge management plays an 
important role in elevating and reducing job in IT Service 
Management Center Department. IT Service Management 
Center Department is a department assigned to handle any 
customer complaints that need to be addressed in terms of IT. 
The complains that enters into IT Service Management Center 
Department are  the form of a ticket (remedy) which will be 
completed by the IT Service Desk and the solutions will be 
delivered back to the customer.     
IT Service Desk utilizing the knowledge management to 
reduce the remedy ticket incoming by creating problem-solving 
tutorials are included on a website and also conducts 
knowledge sharing among employees so that any updated 
information can be disseminated quickly so that it can help the 
IT Service Desk for resolving complaints incoming 
Therefore, the purpose of this study is to help the 
telecommunications company (Telkomsel) in answering the 
need for the complaint management. The flow of complaint 
handling process as follows :  
 
 
Fig. 1. The Complaint Handling Process 
 
II. LITERATE STUDY 
A. Knowledge  
Knowledge is divided into two interrelated parts, namely 
theoretical knowledge and practical knowledge [1]. Based on 
the type of knowledge is divided into tacit and explicit 
knowledge [2].  
B. Knowledge Management 
Knowledge management involves activities that have 
relevance to capture, user and sharing of knowledge within the 
company [3]. The implementation of knowledge management 
in the organization involves three components: People, 
Processes and Technology. [4].  The notion of the importance 
of knowledge work has also drawn attention to the 
management of knowledge workers [5]. Knowledge  is  
defined  as  a  justified  belief  that  increases  an  entity’s  
capability  for  effective  action [2,6].  There  are  two  
dimensions  of  knowledge in organizations: tacit knowledge 
and explicit   knowledge.   Tacit   knowledge   is   
978-1-5090-3352-2/16/$31.00 ©2016 IEEE 16-18 November 2016, Aston Tropicana Hotel, Bandung, Indonesia 
2016 International Conference on Information Management and Technology (ICIMTech) 
Page 103 
subconsciously  understood  and  applied,  difficult  to  
articulate,  developed  from  direct  experience  and  action [6].  
 
III. RESEARCH METHOD 
The method used to collect data is qualitative method with 
observation, interviews, literature studies, another method is 
quantitative method with questionnaires. In this study, the 
construct being measured is based on the factor people, 
processes and technology that are broken into multiple 
dimensions as follows: 
Table 1. Variable and Dimension [4]  
Variable Dimension 
People 
Knowledge Sharing behavior 
Knowledge Sharing Activity 
Awareness 
Participation in Activities 
Process 
Quality of Knowledge  
Efficiency as a result of new process
Incentive 
Contributor 
Technology 
Active involvement 
Knowledge Structure 
Usability 
IT Complain 
Speed complaint handling 
Problem solving satisfactorily
Ease of filing a complaint procedure
 
Based on the above construction, can be described a model 
for measuring of variables such as the following: 
 
 
 
Fig. 2. Research Model 
Hypothesis: 
The hypothesis of this study are as follows:  
H1 : Variable People affect the IT Complaint 
H2 : Variable Process affect the IT Complaint. 
H3 : Variable Technology affect the IT Complaint. 
H4 : Variable people, process and Technology affect 
simultaneously to IT Complaint. 
Data used for primary data analysis is based on the results 
of questionnaires to the sample of 41 people, according to our 
model. All data were analyzed using statistical analysis, i.e. 
descriptive statistical analysis and verification of statistical 
analysis to explain the influence between variables studied, 
namely the normality test, validity, reliability testing, 
regression analysis. 
 
IV. RESULTS 
Based on the results of descriptive statistical analysis, the 
respondents was 90% (37) male and 10% (4) female. Based on 
the education level 34% (Diploma), 61% (Strata 1) and 5% 
(Strata 2). Based on working hours, 17% (office hour), 83% 
(Shifting). Based on the job, 73% (Agent), 10% (Analyst), 5% 
(Leader), 2% (manager), 10% (Officer). 
All data has been testing the validity and reliability. Only 
valid data is used to take measurements. 
To test the reliability of these three variables, namely 
People, Process, Technology and IT, the result is as follows: 
 
 
 
 
 
Reliability Statistics 
Cronbach's Alpha N of Items 
.744 11 
978-1-5090-3352-2/16/$31.00 ©2016 IEEE 16-18 November 2016, Aston Tropicana Hotel, Bandung, Indonesia 
2016 International Conference on Information Management and Technology (ICIMTech) 
Page 104 
 
 
 
Cronbach's Alpha People variable has a value of > 0.7 
(0.744 > 0.7). Measurement for this variable has a good 
reliability. 
 
 
 
 
 
 
Cronbach's Alpha Process variable has a value of > 0.7 
(0.881 > 0.7). Measurement for this variable has a good 
reliability. 
 
 
 
 
Cronbach's Alpha Technology variable has a value of > 0.7 
(0.786 > 0.7). Measurement for this variable has a good 
reliability. 
As for the hypothesis test is done by using a regression test 
is done partially and simultaneously.  
Based on a model that has been defined above, the results 
of the regression analysis is as follows:  
According to the table above, the value of R Square is 
0.409, indicating that the three variables People, Process and 
Technology provides simultaneous effect of 40.9% of the IT 
Complain. 
While the level of significance of the statistical analysis to 
be obtained the following data: 
 
 
 
 
 
ANOVAa 
Model
Sum of 
Squares Df 
Mean 
Square  F Sig.
Regression 122.212 3  40.737 8.532 .000b
Residual 176.666 37  4.775
Total 298.878 40   
a. Dependent Variable: IT_Complain 
b. Predictors: (Constant), Process, People, Technology
 
Based on the results in the table above, it can be concluded 
that the model used was appropriate F> Ftable (8532> 2.86), 
and the probability value (sig) is 0.000, meaning that the effect 
of these three variables is significant. Based on the statistical 
analysis of data, shows that Hypothesis 4 (H4) is received. 
For partial testing, use the data in the following table:  
Coefficientsa 
Model
Unstandardized 
Coefficients 
Standardized 
Coefficients
T Sig.B
Std. 
Error Beta
1 (Constant) 6.993 3.661  1.910 .064
People .095 .095 .158 1.004 .322
Technology .108 .093 .187 1.164 .252
Process .223 .063 .472 3.547 .001
a. Dependent Variable: IT_Complain 
 
Partial test carried out on each variable People, Process and 
Technology to IT Complaint. Based on data from the statistical 
process can be explained as follows:  
The influence of the People  Variable to IT Complain 
explained that partially the People variable effect on IT 
Complaint (1,004 <2:02), but the effect was not significant 
(0322> 0.05). Based on these data, the Hypothesis 1 (H1) is 
accepted.  
Influence of Technology to IT Complain explained that 
partially the technology effect on IT Complaint (1164 <2:02), 
but the effect was not significant (0.252> 0.05). Based on these 
data, the Hypothesis 2 (H2) is received. 
The influence of the Process variable to IT Complain 
explained that partially the process  affect the IT Complain 
(3547> 2:02), and the effect was significant (0.001 <0.05). 
Based on these data, the Hypothesis 3 (H3) is received. 
 
 
Based on the analysis of data can be created regression 
equation is as follows: 
Y = 6.635 + 0.136X1 + 0.50X2 + 0.240X3 
Where : 
Y   = IT Complaint 
X1 = People 
Reliability Statistics 
Cronbach's Alpha N of Items 
.881 10 
Reliability Statistics 
Cronbach's Alpha N of Items 
.786 11 
Model Summary 
Model R 
R 
Square 
Adjusted 
R Square 
Std. Error of the 
Estimate
1 .639a .409 .361 2.185
a. Predictors: (Constant), Process, People, Technology 
978-1-5090-3352-2/16/$31.00 ©2016 IEEE 16-18 November 2016, Aston Tropicana Hotel, Bandung, Indonesia 
2016 International Conference on Information Management and Technology (ICIMTech) 
Page 105 
X2 = Technology 
X3 = Process  
 
V. CONCLUSION 
Based on the research that has been done on the three 
indicators that exist in knowledge management obtained the 
following results: 
1. Based on the analysis, it can be concluded that the 
variables that exist in knowledge management is people, 
process, technology simultaneously significantly influence IT 
complaint. The influence is 40.9%. Thus the three variables 
must be implemented simultaneously in order to significantly 
affect the IT complaint. 
2. If from each variable not simultaneously applied only the 
process variables that significantly influence IT complaint. 
 
REFERENCES 
 
[1] Kraiger, K., Ford, J., & Salas, E., Application of cognitive, skill-based, 
and affective theories of learning outcomes to new methods of training 
evaluation. Journal of Applied Psychology, 1993, pp. 28. 
[2] Kenneth C. Loudon, Management Information Systems: Managing the 
Digital Firm (12th Edition), Prentice Hall, 2011. 
[3] Ringel‐Bickelmaier, C., & Ringel, M., Knowledge management in 
international organisations. Journal of  Knowledge Management. 2010. 
[4] Shannak, R. O. (2009). Measuring Knowledge Management 
Performance. European Journal of Scientific Research ISSN 1450-216X 
Vol.35 No.2 (2009), pp.242-253. 
[5] Jussi Okkonen. THE USE OF  PERFORMANCE MEASUREMENT  
IN KNOWLEDGE WORK CONTEXT. 2004. 
[6] Chorng-Shyong Ong, Jung-Yu Lai, Developing an instrument for 
measuring user satisfaction with knowledge management systems, 
Proceedings of the 37th Hawaii International Conference on System 
Sciences, 2004.  
 


Similarity "Model of measuring the influence of Knowledge Management system to IT complaints, case study in telecomunication company"

Muljo, Hery Harjono

12. Research grants
management
by Arta Moro Sundjaja
Submission date: 28-Mar-2018 02:14PM (UTC+0700)
Submission ID: 649644242
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Girsang, Abba Suganda

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University Accreditation using Data Warehouse 
A S Sinaga1 and A S Girsang2 
 
 
1 Department in Informatics Engineering, STMIK Pelita Nusantara, Jl. Iskandar Muda No.1, Medan.  
2 Master in Computer  Science , Bina Nusantara University, Jl. Kebon Jeruk Raya No. 27 Jakarta 
 
DOI  
10.1088/1742-6596/801/1/012030 
 
 
 
  
 
 
 
 
 
 
 
 
 
Committee 
Honorary Chair 
Prof. Dr. Runtung Sitepu,S.H., M.Hum. (Rector University of Sumatera Utara, Indonesia) 
International Board 
Prof. Hiromi Homma (Toyohashi University of Technology, Japan) 
Prof. Dr. Masashi Daimaruya (Muroran Institute of Technology, Japan) 
Prof. Dr. Rahmat Budiarto (Al Baha University, Saudi Arabia) 
Muhammad Fermi Pasha, B.Comp.Sc., M.Sc., Ph.D (Monash University Malaysia, Malaysia) 
Steering Committees 
Prof. Dr. Hideki Kawai (Muroran Institute of Technology, Japan) 
Prof. Zainal A.Hasibuan, Ir., MLS, PhD (University of Indonesia, Indonesia) 
Prof. Dr. Opim Salim Sitompul (University of Sumatera Utara, Indonesia) 
Drs. Mahyuddin K. M. Nasution, M.IT, PhD (University of Sumatera Utara, Indonesia) 
Prof. Dr. Herman Mawengkang (University of Sumatera Utara, Indonesia) 
Prof. Dr. Saib Suwilo (University of Sumatera Utara, Indonesia) 
Dr. Ir. Rinaldi Munir, MT (Bandung Institute of Technology, Indonesia) 
Prof. Dr. rer.nat. Dedi Rosadi, M.Sc. (University of Gadjah Mada, Indonesia) 
Benny B. Nasution, Ph.D (Politeknik Negeri Medan, Indonesia) 
Dr. Fitri Arnia, M.Eng.Sc (Syiah Kuala University, Indonesia) 
Chair 
Dr. Eng. Himsar Ambarita (University of Sumatera Utara, Indonesia) 
Co. Chair 
Romi Fadilah Rahmat, B.Comp.Sc., M.Sc. (University of Sumatera Utara, Indonesia) 
Suherman, Ph.D (University of Sumatera Utara, Indonesia) 
Executive Members 
Dr. Erna Budhiarti Nababan, M.IT (University of Sumatera Utara, Indonesia) 
Emerson Sinulingga, Ph.D (University of Sumatera Utara, Indonesia) 
Dr. Fahmi F. (University of Sumatera Utara, Indonesia) 
Mohammad Fadly Syahputra, M.Sc (University of Sumatera Utara, Indonesia) 
Muhammad Anggia Muchtar, ST, MMIT (University of Sumatera Utara, Indonesia) 
Dani Gunawan, S.T, M.T (University of Sumatera Utara, Indonesia) 
Tau_q Bin Nur, S.T., M.Eng (University of Sumatera Utara, Indonesia) 
2 
Local Members 
Prof. Dr. Muhammad Zarlis (University of Sumatera Utara, Indonesia) 
Dr. Poltak Sihombing, M.Kom. (University of Sumatera Utara, Indonesia) 
Dr. Syahril E_endi, M.IT (University of Sumatera Utara, Indonesia) 
Dr. Sawaluddin, M.IT (University of Sumatera Utara, Indonesia) 
Dr. Elviawaty Muisa Zamzami, S.T., M.T., M.M. (University of Sumatera Utara, Indonesia) 
Dr. Maya Silvi Lydia, M.Sc. (University of Sumatera Utara, Indonesia) 
Amalia, S.T., M.T. (University of Sumatera Utara, Indonesia) 
Ainul Hizriadi, S. Kom, M. Sc (University of Sumatera Utara, Indonesia) 
Indra Aulia, S.TI., M.Kom (University of Sumatera Utara, Indonesia) 
Dedy Arisandi, S. T, M. Kom (University of Sumatera Utara, Indonesia) 
Dian Rachmawati, S.Si., M.Kom. (University of Sumatera Utara, Indonesia) 
Baihaqi. S.T., M.T. (University of Sumatera Utara, Indonesia) 
Ivan Jaya, S.Si, M.Kom (University of Sumatera Utara, Indonesia) 
Jos Timanta Tarigan, S.Kom, M.Sc. (University of Sumatera Utara, Indonesia) 
Sarah Purnamawati, S.T, M.Sc (University of Sumatera Utara, Indonesia) 
Mohammad Andri Budiman, S. T, M.Comp.Sc., M.E.M (University of Sumatera Utara, Indonesia) 
Ul_ Andayani, S.Kom, M. Kom. (University of Sumatera Utara, Indonesia) 
Sri Melvani Hardi, S. Kom, M. Kom. (University of Sumatera Utara, Indonesia) 
Amer Sharif, S.Si., M.Kom. (University of Sumatera Utara, Indonesia) 
Seniman, S.Kom., M.Kom. (University of Sumatera Utara, Indonesia) 
Conference Information 
Dates : December 14 - December 15, 2016 
Organizer : Faculty of Computer Science and Information Technology 
University of Sumatera Utara 
Venue : Hotel GranDhika Setiabudi Medan 
Jalan Dr. Mansyur no. 169 
Medan, Sumatera Utara 
Indonesia 
Phone : +62-61-42081234 
Fax : +62-61-42081234 
Email : reservation@grandhika-hotel.com 
Website : www.grandhika-hotel.com 
O_cial Language : English 
Secretariat : Faculty of Computer Science and Information Technology 
University of Sumatera Utara 
Jalan Universitas No. 9A, Kampus USU 
Medan, 20155 
Sumatera Utara, Indonesia 
Email : iccai@usu.ac.id 
Conference Website : http://iccai.usu.ac.id 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
  
 
 
  


Committee "University Accreditation using Data Warehouse"

Meyliana, Meyliana

Check 21. Potential Threats of
Information.pdf
by Arta Sundjaja
Submission date: 12-Sep-2019 11:31AM (UTC+0700)
Submission ID: 1102519018
File name: 21._Potential_Threats_of_Information.pdf (128.88K)
Word count: 4366
Character count: 24562











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