Binus University Repository

Fernando, Erick

form reviewer "Perancangan Aplikasi Komunikasi Penyandang Tunarungu Berbasis Android"

Girsang, Abba Suganda

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Reprint From 
 
 
Electronic ISBN: 978-1-5090-4048-3,  USB ISBN: 978-1-5090-4047-6,  Print on Demand(PoD) ISBN: 978-1-
5386-3824-8 
http://ieeexplore.ieee.org/document/8167092/ 
 
International Conference on Applied 
Computer and Communication Technologies 
(Comcom 2017 ) 
 
 
Implementation application internal chat messenger 
using android system 
 
 
 
Robi Sanjaya1 , Abba Suganda Girsang1,  
1 Master in Computer  Science , Bina Nusantara University, Jakarta 
 
 
 
DOI  
10.1109/COMCOM.2017.8167092 
 
 
 
  
 
TABLE OF CONTENTS 
 
Technical Sessions 
TS – 01 An Analysis of Optimal Capacity in Cluster CDMA Wireless Sensor Network................................................  1 
Dwi Widodo (Bandung Institute of Technology, Indonesia); Adit Kurniawan (Bandung Institute of Technology, 
Indonesia); Arifianto (Bandung Institute of Technology, Indonesia) 
TS – 02 Businesss Incubator Indicator Service Performance - A Systematic Literature Review ...................................  7 
Rido Sarwono (Bina Nusantara University, Indonesia); Agung Trisetyarso (Bina Nusantara University, Indonesia) 
TS – 03 Design of Physical Authentication based on OTP KeyPad ..............................................................................  12 
Benedicto B. Jr. (Bicol University, Philippines); Bobby D. Gerardo (West Visayas State University, Philippines); 
Medina (Technological Institute of the Philippines, Philippines); Yung-Cheol Byun (Jeju National University, 
Philippines) 
TS – 04 Easy Understanding for Mining Discriminant Itemset with Emerging Patterns ..............................................  17 
Harco Leslie Hendric Spits Warnars (Bina Nusantara University, Indonesia); Ford Lumban Gaol (Bina Nusantara 
University, Indonesia); Nesti Fronika Sianipar (Bina Nusantara University, Indonesia); Bahtiar Saleh Abbas (Bina 
Nusantara University, Indonesia); Horacio Emilio Perez Sanchez (Universidad Católica de Murcia, Spain) 
TS – 05 Enhance Capability of Enterprise Systems Using Integration Manager ..........................................................  23 
Verri Kuswanto (Buddhi Dharma University, Indonesia) Santo Wijaya (Bina Nusantara University, Indonesia) 
TS – 06 Estimated Measurement Quality Software On Structural Model Academic System With Function Point 
Analysis ........................................................................................................................................................  29 
Hetty Rohayani (Bina Nusantara University, Indonesia); Ford Lumban Gaol (Bina Nusantara University, 
Indonesia); Benfano Soewito (Bina Nusantara University); Harco Leslie Hendric Spits Warnars (Bina Nusantara 
University, Indonesia) 
TS – 07 Evaluation of Knowledge Management System to Improve the Performance of Employees at PT Data Citra 
Mandiri ........................................................................................................................................................  34 
Fadli Ferdiansyah (Bina Nusantara University, Indonesia); Jarot Suroso (Bina Nusantara University, Indonesia) 
TS – 08 Examining the possibility of using programming language with low-cost drones .............................................  40 
Frederic D. Hoffert (Bina Nusantara University, Indonesia) 
TS – 09 Factors for Imporving Quality Education Startup: a Review of the Literature................................................  46 
Anton Wardaya (Bina Nusantara University, Indonesia); Yosef Dedy Pradipto (Bina Nusantara University, 
Indonesia) 
TS – 10 Folksonomy-Based Image Recommender for Art Commissioning...................................................................  50 
Michelle Devonna Saputra (Bina Nusantara University, Indonesia); Ellen - (Bina Nusantara University, 
Indonesia); Raymond Kosala (Bina Nusantara University, Indonesia) 
TS – 11 Formal Equivalence Classes Model of Fuzzy Relational Databases Using Relational Calculus .........................  55 
Mohammad Deni Akbar (Kyushu University, Japan); Yoshihiro Mizoguchi (Kyushu University, Japan) 
TS – 12 Identification of Key Success Factors and Challenges for ERP S ystems – A Systematic Literature Review ......  61 
Santo Wijaya (Bina Nusantara University, Indonesia) 
TS – 13 Implementation Application Internal Chat Messenger Using Android System ................................................  67 
Robi Sanjaya (Bina Nusantara University, Indonesia); Abba Suganda Girsang (Bina Nusantara University, 
Indonesia) 
TS – 14 Implementation of Incident Management for Data Services Using ITIL V3 i n Telecommunication Operator 
Company ......................................................................................................................................................  71 
Akbar Nugraha (Bina Nusantara University, Indonesia); Nilo Legowo (Bina Nusantara University, Indonesia) 
TS – 15 Incident Management Implementation Using Continual Service Improvement Method at PT. AOP................  77 
Dionisius Sarasadhi Ilvarianto (Bina Nusantara University, Indonesia); Nilo Legowo (Bina Nusantara University, 
Indonesia) 
TS – 16 Information System Strategic Planning in PT XYZ.........................................................................................  84 
Noviana Christianti (Bina Nusantara University, Indonesia); Harisno Harisno (Bina Nusantara University, 
Indonesia 
TS – 17 IT-based Customer Experience Management: A Systematic Literature Review ..............................................  92 
Prionggo Hendradi (Bina Nusantara University, Indonesia) 
TS – 18 O bject Oriented Metrics to Measure the Quality of Software .........................................................................  97 
Sarwo Sarwo (STIMIK Mercusuar, Indonesia); Leslie Hendric Spits Warnars (Bina Nusantara University, 
Indonesia); Ford Lumban Gaol (Bina Nusantara University, Indonesia) 
TS – 19 Q uality Measurement for Serious Games....................................................................................................... 102 
Louis Khrisna Putera Suryapranata (Bina Nusantara University, Indonesia); Ford Lumban Gaol (Bina Nusantara 
University, Indonesia); Benfano Soewito (Bina Nusantara University, Indonesia); Harco Leslie Hendric Spits 
Warnars (Bina Nusantara University, Indonesia); Gede Putra Kusuma (Bina Nusantara University, Indonesia)  
TS – 20 Q uality Measurement of Android Messaging Application Based on User Experience in Microblog  ................. 106 
Rakhmat Arianto (Bina Nusantara University, Indonesia); Spits Warnars Harco Leslie Hendric (Bina Nusantara 
University, Indonesia); Ford Lumban Gaol (Bina Nusantara University, Indonesia); Benfano Soewito (Bina 
Nusantara University, Indonesia); Horacio Pérez-Sánchez (Universidad Católica San Antonio de Murcia, Spain) 
TS – 21 Revised Coloring Method of Characters for Presentation Slides and Coloring System .................................... 111 
Yui Nonomura (Kyoto Institute of Technology, Japan); Teruhisa Hochin (Kyoto Institute of Technology, Japan); 
Hiroki Nomiya (Kyoto Institute of Technology, Japan); Yukiko Nishizaki (Kyoto Institute of Technology, Japan) 
TS – 22 Smartphone Sensors Selection using Decision Tree and KNN to Detect Head Movements in Virtual Reality 
Application ................................................................................................................................................... 117 
Maria Seraphina Astri (Bina Nusantara University, Indonesia); Yaya Heryadi (Bina Nusantara University, 
Indonesia); Gede Putra Kusuma (Bina Nusantara University, Indonesia); Edi Abdurachman (Bina Nusantara 
University, Indonesia) 
TS – 23 Software Complexity Measurement of Water Poverty Mapping Application with Function Point Method....... 122 
Teguh Wahyono (Satya Wacana Christian University, Indonesia); Harco Leslie Hendric Spits Warnars (Bina 
Nusantara University, Indonesia); Benfano Soewito (Bina Nusantara University, Indonesia); Ford L. Gaol (Bina 
Nusantara University, Indonesia) 
TS – 24 The General Components of Enterprise Architecture Framework in e-Commerce: A Systematic Literature 
Review .......................................................................................................................................................... 127 
Angelina Ervina Jeanette Egeten (Bina Nusantara University, Indonesia); Harjanto Prabowo (Bina Nusantara 
University, Indonesia); Meyliana Meyliana (Bina Nusantara University, Indonesia); Raymond Kosala (Bina 
Nusantara University, Indonesia); Manik Hapsara (Bina Nusantara University, Indonesia) 
TS – 25 The Governance Measurement Of Information System Using Framework Cobit 5 In Automotive Company
 ...................................................................................................................................................................... 133 
Kalvin Rahmat Putra Harefa (Bina Nusantara University, Indonesia); Nilo Legowo (Bina Nusantara University, 
Indonesia) 
TS – 26 Understanding of Data Mining in Computer Science Learning from PILKADA DKI Jakarta 2017 ................. 139 
Harco Leslie Hendric Spits Warnars (Bina Nusantara University, Indonesia); Ford Lumban Gaol (Bina Nusantara 
University, Indonesia); Agung Trisetyarso (Bina Nusantara University, Indonesia); Edi Abdurachman (Bina 
Nusantara University, Indonesia); Dedy Prasetya Kristiadi (Bina Nusantara University, Indonesia); Tokuro 
Matsuo (Advanced Institute of Industrial Technology, Indonesia) 
 COMCOM 2017 Organizing Chairs 
 
Steering Committee 
Ford Lumban Gaol, BINUS University, Indonesia (Co-Chair) 
Tokuro Matsuo, Advanced Institute of Industrial Technology, Japan (Co-Chair) 
Kiyota Hashimoto, Prince of Songkla University, Thailand 
 
Honorary Chairs 
Harjanto Prabowo, Bina Nusantara University, Indonesia 
Naohiro Ishii, Aichi Institute of Technology, Japan 
 
General Chairs 
Edi Abdurahman, Bina Nusantara University, Indonesia 
Teruhisa Hochin, Kyoto Institute of Technology, Japan 
 
Technical Program Chairs 
Suharjito, Bina Nusantara University, Indonesia 
Taufik, Bina Nusantara University, Indonesia 
Osamu Mizuno, Kyoto Institute of Technology, Japan 
 
International Advisory Committee 
Chang Duk Jung, Korea University, Korea 
Ho Tu Bao, JAIST, Japan 
Kok-Leong Ong, Deakin University, Australia 
Pham Tho Hoan, Hanoi National U. of Education, Vietnam 
Sanparith Marukatat, NECTEC, Thailand 
Takeo Higuchi, IMS Institute, Japan 
Thomas Koehler, Dresden University of Technology, Germany 
Vincent C.S. Lee, Monash University, Australia 
Xijin Tang, Chinese Academy of Sciences, China 
 
Organizing Chair 
Harisno, Bina Nusantara University 
 
 
Workshop Chair 
Fergyanto E. Gunawan, Bina Nusantara University, Indonesia 
 
Publication Chair 
I Gede Putra Kusuma Negara, Bina Nusantara University, Indonesia 
 
Finance Chairs 
Diana, Bina Nusantara University, Indonesia 
Nilo Legowo, Bina Nusantara University, Indonesia 
 
Publicity Chairs 
Jarot S. Suroso, Bina Nusantara University, Indonesia 
Yungcheol Byun, Jeju National University, Korea 
 
Advisory Board Member 
Satoshi Takahashi, University of Electro-Communications, Japan 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 COMCOM 2017 Program Committees 
 
Togar Alam Napitupulu, Bina Nusantara University, Indonesia 
Tuga Mauritsus, Bina Nusantara University, Indonesia 
Nico Surantha, Bina Nusantara University, Indonesia 
Antoni, Bina Nusantara University, Indonesia 
Abba Suganda Girsang, Bina Nusantara University, Indonesia 
Manik Hapsara, Bina Nusantara University, Indonesia 
Ahmad Nurul Fajar, Bina Nusantara University, Indonesia 
Benfano Soewito, Bina Nusantara University, Indonesia 
Ahmad Nurul Fajar, Bina Nusantara University, Indonesia 
Astari Retnowardhani, Bina Nusantara University, Indonesia 
Ikhwan Jambak, Bina Nusantara University, Indonesia 
Habibullah Akbar, Bina Nusantara University, Indonesia 
Sani Muhammad Isa, Bina Nusantara University, Indonesia 
Sfenrianto, Bina Nusantara University, Indonesia 
Hitoshi Iima, Kyoto Institute of Technology, Japan 
Hiroki Nomiya, Kyoto Institute of Technology, Japan 
Atsushi Nunome, Kyoto Institute of Technology, Japan 
Yuya Yokoyama, Kyoto Prefectural University, Japan 
Sachio Hirokawa, Kyushu University, Japan 
Masao Mori, Tokyo Institute of Technology, Japan 
Arata Koike, NTT Network Technology Laboratories, Japan 
Motoi Iwashita, Chiba Institute of Technology, Japan 
Antoine Bossard, Kanagawa University, Japan 
Atsushi Shibata, Advanced Institute of Industrial Technology, Japan 
Sanggyu Shin, Advanced Institute of Industrial Technology, Japan 
Takaaki Goto, Ryutsu Keizai University, Japan 
Katsuhide Fujita, Tokyo University of Agriculture and Technology, Japan 
Naoki Fukuta, Shizuoka University, Japan 
Yuichi Ono, Tsukuba University, Japan 
Soumya Sen, University of Calcutta, India 
George Anderson, University of Botswana, Botswana 
Yoshihiro Mizoguchi, Kyushu University, Japan 
Shuichi Inokuchi, Fukuoka Institute of Technology, Japan 
Hiroshi Ohtsuka, Ehime University, Japan 
Naruhiko Shiratori, Kaetsu University, Japan 
 


Committee "Implementation Application Internal Chat Messenger Using Android System"

Reprint From 
 
 
Electronic ISBN: 978-1-5386-2330-5, CD ROOM ISBN: 978-1-5090-4047-6,  Print on Demand(PoD) 
ISBN: 978-1-5386-2331-2 
https://ieeexplore.ieee.org/document/8288871 
2017 International Conference on ICT For 
Smart Society (ICISS) 
 
 
Assessment of capability level and IT governance 
improvement based on COBIT and ITIL framework 
at communication center ministry of foreign affairs 
 
 
 
Ardly Ekanata ; Abba Suganda Girsang,  
 
 Computer Science Department, Binus Graduate Program,  
Bina Nusantara University, Jakarta, Indonesia, 
 
 
 
DOI  
10.1109/ICTSS.2017.8288871 
 
 
 
 
  
 
  
 
 
 
 


Committee "Assessment of Capability Level and IT Governance Improvement Based on COBIT and ITIL Framework at Communication Center Ministry of Foreign Affairs"

Furinto, Asnan

Navigating 2018
by Asnan Furinto
Submission date: 26-Nov-2019 10:38AM (UTC+0700)
Submission ID: 1221861855
File name: navigating_2018.pdf (419.59K)
Word count: 3697
Character count: 21631










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Navigating 2018
ORIGINALITY REPORT
PRIMARY SOURCES
library.binus.ac.id
Internet Source
www.sciencepubco.com
Internet Source
Submitted to ICL Education Group
Student Paper
profdoc.um.ac.ir
Internet Source
Submitted to University of Dayton
Student Paper
Submitted to Southampton Solent University
Student Paper
www.emrbi.org
Internet Source



Similarity "Naviganting International Expansion Through Digital Leadership and Innovation For Indonesia Telecommunication State Owned Enterprise"

Ongowarsito, Henkie

Meyliana, Meyliana

Kosala, Raymondus Raymond

Prabowo, Harjanto

English

IT governance contingency factors in cloud computing services

Lumban Gaol, Ford

Check 05. 2017_COMCOM
Quality Measurement of serious
Game.pdf
by Arta Sundjaja
Submission date: 27-Apr-2019 10:46AM (UTC+0700)
Submission ID: 1102514169
File name: 05._2017_COMCOM_Quality_Measurement_of _serious_Game.pdf  (340.87K)
Word count: 3372
Character count: 18810




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Game.pdf
ORIGINALITY REPORT
PRIMARY SOURCES
Louis Khrisna Putera Suryapranata, Gede
Putra Kusuma, Yaya Heryadi, Bahtiar Saleh
Abbas, Lukas, Adang S. Ahmad. "Personality
trait prediction based on game character
design using machine learning approach", 2017
International Conference on Innovative and
Creative Information Technology (ICITech),
2017
Publicat ion
www.tandfonline.com
Internet  Source
Sakul Pavapootanont, Nakornthip Prompoon.
"Defining usability quality metric for mobile
game prototype using software attributes",
2015 6th IEEE International Conference on
Software Engineering and Service Science
(ICSESS), 2015
Publicat ion
Submitted to Universitas Esa Unggul
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"Interactive Storytelling", Springer Nature, 2018
Publicat ion
Mortara, Michela, Chiara Eva Catalano,
Francesco Bellotti, Giusy Fiucci, Minica Houry-
Panchetti, and Panagiotis Petridis. "Learning
cultural heritage by serious games", Journal of
Cultural Heritage, 2013.
Publicat ion
jsiskom.undip.ac.id
Internet  Source


Hasil Similarity "Quality measurement for serious games"

Sanny, Lim

Analysis of online purchase behavior intention in SME in Indonesia

Abdurachman, Edi

Simatupang, boto

Heriyati, Pantri

Check Franchising Performance
from.pdf
by Arta Sundjaja
Submission date: 09-Jul-2019 10:29AM (UTC+0700)
Submission ID: 1102514169
File name: Franchising_Perf ormance_f rom.pdf  (703.5K)
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ORIGINALITY REPORT
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research.binus.ac.id
Internet  Source
Tripathi, V., A. Tandon, and A. Gupta.
"Experiencing Flavourful Fun: Delighting
Customers the RB Way", Global Business
Review, 2015.
Publicat ion
Lim Sanny. "Managing transactional and
relational quality in Indonesia: The franchisees'
perspective", 2014 International Symposium on
Technology Management and Emerging
Technologies, 2014
Publicat ion
ijrrjournal.com
Internet  Source
comdev.binus.ac.id
Internet  Source
Submitted to Universitas Brawijaya
Student  Paper
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Hasil Similarity "Franchising Performance from Franchisee Perspective: Case in Education Franchising in Indonesia"

Soewito, M.Sc., Ph.D, Benfano

Simanjuntak, Echo

E. Gunawan, Fergyanto

Smart Mobile Attendance System Using Voice
Recognition and Fingerprint on Smartphone
Benfano Soewito
Master of
Computer Science
Bina Nusantara University
Jakarta, Indonesia 11530
Email: bsoewito@binus.edu
Ford Lumban Gaol
Master of
Computer Science
Bina Nusantara University
Jakarta, Indonesia 11530
Email: fgaol@binus.edu
Echo Simanjuntak
Master of
Computer Science
Bina Nusantara University
Jakarta, Indonesia 11530
Email: solar medan@yahoo.com
Fergyanto E. Gunawan
Master of
Management of Information Systems
Bina Nusantara University
Jakarta, Indonesia 11530
Email: fgunawan@binus.edu
Abstract—The attendance system has been known for a long
time, ranging from manual system to automated and complicated
system such as attendance system using biometrics. All those
attendance system have several weakness, especially to control
of employees who work outside the ofﬁce. In this paper we
introduced a attendance system that can be used to record
the attendance of employees who are duty outside the building.
Our system is also integrated with payroll system that make
accounting department can easily calculate and report the salary
included the overtime cost. The proposed attendance system
used smartphone to verify the employee. The system provide
two options for doing veriﬁcation, such as ﬁngerprint and voice
recognition. In this research, we ﬁnd that ﬁngerprint veriﬁcation
has false positive 95% and the false negative of voice recognition
is 5.88%.
I. INTRODUCTION
Along with the growing number of smartphone users,
the number of applications available on smartphones also
increased. But there has been no application for attendance
system on a smartphone that is easy to use and integrated
with the management attendance system tool controlled by
the personnel department. On the other hand, there are many
disadvantage in attendance systems currently available such
as a long queuing in front of the attendance machine at the
time come to work and after work, monitoring employees who
work out side of ofﬁce, the organization has to spend on the
device as well as badges, and difﬁcult to maintain and repair
the devices.
Some companies also need to monitor their employee
who working outside the ofﬁce or out of town. In order to
calculate the employee’s salary who work outside the ofﬁce,
the personnel and ﬁnance department need to know how many
hours the employee come to work. The problem is there is no
tool that can monitor working hour of employee outside the
ofﬁce. Most of the time the employee just feel the sheet of
paper to write down name and time by their self without any
control or monitor. Therefore an automatic attendance system
using voice recognition and ﬁngerprint on smartphone would
provide the new solution.
In this paper, we developed attendance system that inte-
grated with system payroll so that overtime can be calculated
automatically, while also providing feature to monitoring
employee who working out of ofﬁce. Our attendance system
also can generate reports and monitor the employee who late
and leave work early. We developed an application that can
be installed on smartphone for client and an application that
can be installed on PC for admin. The information of date,
time, unique number of android system, smartphone number,
and GPS (Global Position System) coordinate will be sent by
smart phone to database server along with the ﬁngerprint of
employee. The employee must login to their account before
sending the information. The process of login or authentica-
tion process can be done either by voice recognition or by
ﬁngerprint.
We used minutiae and texture features algorithm for match-
ing the ﬁngerprint in authentication process [1]. The minutiae
features are ridge ending, bifurcation, and short ridge. The
number of these minutiae features are unique for each person.
In ﬁngerprint matching algorithm for authentication process,
we compared the number of minutiae features of employee.
We took the ﬁngerprints of employee who participate in our
research and we save the number of minutiae features in a
server as a template.
At this time not all smartphones have the ﬁngerprint sensor,
therefore we also developed voice recognition technique for
authentication process. The algorithm for matching voice is
random alphabet. We record 26 alphabet characters for every
person who has participated as a template and we save them in
server. The ﬁve characters will be generated randomly at the
time the employee do the authentication process. They have
to read clearly the ﬁve characters on their smartphone. If the
frequency match with the template then the employee pass
authentication process.
II. RELATED WORKS
A number of research have been done to develop attendance
system such as Shoewu, [3], Rao [4], Josphineleela [5],
Masalha [6], and Ashok [7].
Shoewu et. al [3] developed an attendance management
system to manage student attendance using biometrics. Student
have to put the ﬁngerprint on the ﬁngerprint sensor and
the student’s matriculation number were sent to database. At
the end of semester the reports can be generated to know
2016 International Seminar on Intelligent Technology and Its Application
978-1-5090-1709-6/16/$31.00 ©2016 IEEE 175
Fig. 1. System Architecture
the percentage of student attendance. They have developed
a ﬁngerprint attendance system included its hardware and
software components. The result is manual attendance system
took 17.83 second for 80 student compare to 3.79 second for
ﬁngerprint attendance system.
Rao and Satoa [4] developed automatic attendance system
using ﬁngerprint veriﬁcation technique which done by extrac-
tion of minutiae technique. The study was conducted using a
quantitative approach by designing a questionnaire as the data
collection instrument based on ﬁngerprint matching biometric
technologies. The process was divided 3 phases; Phase 1:
Fingerprint scanning and registration, Phase 2: Fingerprint
recognition or authentication, and Phase 3: Attendance update.
In Josphineleela [5], a novel ﬁngerprint reconstruction al-
gorithm is proposed to reconstruct the phase image, which
is then converted into the grayscale image. Algorithm consist
several stages: Preprocessing, minutiae extraction, Fingerprint
reconstruction, and Fingerprint recognition.
Masalha and Hirzallah [6] introduced a student attendance
system using QR Code. The QR Code is a type of two
dimensional bar code that has square shape with black square
dot on white background. The lecturer has to generate an
encrypted QR Code and student have to scan the QR Code
(Quick Response Code) to do the attendance process. Student
can scan the QR Code by their own devices such as cellular
phone, smart phone, tablet or any devices that has a camera.
Ashok and Begum [7] compared three ﬁngerprint match-
ing algorithms by conducting the election using novel EVM
(Electronic Voting Machine). The three ﬁngerprint matching
was direct matching, minutiae matching, and matching based
on ratio of distance. The authors measure matching accuracy
and time then they select the best algorithm for EVM. They
conclude that the minutiae matching is better than direct
matching and ratio of distance in terms of memory and time.
III. PROPOSED DESIGN
In this research, we used android smartphones that have
ﬁngerprint scanner, because attendance system that we devel-
oped used biometric methods to identiﬁcation users, in this
Fig. 2. Minutia of ridge ending, bifurcation, enclosure and ridge dot
research we used ﬁngerprint and voice. So we have to take
the ﬁngerprint and voice of 100 volunteers (participants) as
well as personal data for identiﬁcation test and attendance
system itself. Then we start developed algorithm ﬁngerprint
matching and voice matching. Once this is done, then the
research can be continued with tested applications. The system
architecture can be seen in ﬁgure 1 that has ﬁve components:
smartphone, parser, server, desktop and printer. The users or
employee can do attendance from their own smartpohne after
they download and install our application and register their
smartphone to administrator. When they do attendance, the
application will send the information such as GPS coordinate,
date and time, unique number of android operating system
and the ﬁngerprint or voice for authentication to parser. If
the authentication process succes, then all those information
will be saved in the application server. The administrator can
process the information to make report or to calculate the
overtime.
A. Fingerprint Matching Based on Minutiae and Texture Fea-
tures
In our system the ﬁngerprint identiﬁcation and matching
based on minutiae and texture features. This work has been
done and discuss in [8] and [9]. Generally, ﬁngerprint match-
ing algorithm to verify the identity of a person is based on
lower level features that matching of ﬁnger ridge patterns
called minutiae. Minutia matching is the most popular ap-
proach to ﬁngerprint identiﬁcation and veriﬁcation.
Fingerprint matching usually consist of two procedures:
minutia extraction and minutia matching [10]. The perfor-
mance mostly depends on the accuracy of the minutia extrac-
tion procedure. Usually, the most important features to match
are ridge ending and ridge bifurcation as we can see in ﬁgure
2 taken from [11]. The steps of ﬁngerprint matching in our
attendance system follow the diagram in ﬁgure 3.
In our work we used algorithm ﬁngerprint matching based
on minutiae and texture features that have been introduced
by Anil [1]. Firstly, we calculated the minutiae point on the
templates and input used method in [2]. Using this method
will generated two input, ﬁrst is a set of minutiae points,
each characterized by its spatial position and orientation in
the ﬁngerprint image, second is local ridge information in the
176
Fig. 3. Algorithm of ﬁngerprint matching
Fig. 4. Algorithm of voice matching
vicinity of each minutiae point. The two sets of minutiae points
are then matched using a point matching algorithm. The detail
algorithm can be seen in [1]
B. Voice Recognition
Voice Recognition is a technology that uses voice, phrases,
and words spoken by someone and transformed into electronic
signals, then the electronic signal is converted into a voiceprint
or spectogram. The next voiceprint or spectrogram is stored
as a table in the form of sequence of numbers in which each
dominant frequency in each segment expressed as a binary
number. From here we already have a sound template that can
be used to match on the authentication process.
Figure 4 shows the algorithm of voice matching that we
used in our work. The algorithms voice recognition will be the
measurement of the percentage of compatibility or matching
between the template voice are stored in a database on a
server with 100 sample other voices. It is done to obtain more
accurate threshold percentage that will be used to determine
whether the voice data was regarded as a person who has
voice that is stored as a template in the database or not.
In addition, this is done to determine whether the algorithm
Fig. 5. Percentage of false positive ﬁngerprint matching
voice recognition is used is relatively safe and difﬁcult to be
penetrated using a recorded voice or not [12]. The process of
analysis of the algorithm voice the recognition can be seen in
ﬁgure 4.
The voice recognition algorithm is divided to several process
as follows:
1) The system will generate random characters to be used
as a challenge to the user.
2) Random character will be displayed on the screen and
the user must immediately pronounce the characters in
a certain time period.
3) Upon completion character is spoken, then the incoming
voice will be identiﬁed.
4) If the character is pronounced the same as the characters
that are generated by the previous system, the stage will
be continued on the voice feature matching template in
the database, otherwise it returns to the login screen.
5) The process of matching the voice with the template
feature is done, if the features match with the template,
it will display the home screen, otherwise it will go back
to the login screen.
6) The matching process is done with relation one-to-one,
where the android device id is used as a data identiﬁer
voice templates on the server.
IV. RESULT AND DISCUSSION
Our attendance system has two options to verify the identity
of user such as ﬁngerprint and voice. We took 40 students as
respondents to proof that the ﬁngerprint matching algorithm
that we developed can be work properly. Each respondent
perform ﬁngerprint authentication on a account that was not
belong to respondent as many as 20 times. The result can be
seen in ﬁgure 5. In the ﬁgure show that 95% respondents can
succes to login to the account and 5% of respondents could
not login the account.
The steps to test voice veriﬁcation as follow. Firstly, we took
100 samples of voice for each person, each person has to speak
the 26 characters of alphabetic. Then we used these voice as a
template to be matched in the authentication process. We also
177
Fig. 6. Screenshot of identiﬁcation using voice regconition
made an experiment Here are the results of experiments using
voice of other people. The goal is to get the percentage value
of how much the voices of different people who should not be
considered matching the voice but it is considered matching
by the system or in other word, we calculate the false negative.
We calculated it used following formula:
number of matching invalid voice
Total sampling
X 100%
From the test results obtained percentage of invalid voice
that considered valid is 5.88%.
Figure 6 show the screenshot on the smartphone. The user
or employee has to tab record button and speak the character
L W X E D U Q A in order to do attendance. If the voice
match with the template in the data server then the user will
success to do attendance as showed in ﬁgure 7. Every time the
employee want to do attendance, the character will be changed
randomly.
V. CONCLUSION
Attendance system in this study using ﬁngerprint and voice
as a method of identifying and recording the coordinates
GPS to ensure the user’s location when do attendance. This
Fig. 7. Screenshot of matched identiﬁcation
will prevent the user manipulation of the attendance system,
especially the user or employee who work outside the ofﬁce.
The attendance system use smartphone or mobile devices can
prevent the queue as when using other attendance system,
especially at peak hours (at the time come to ofﬁce and out of
ofﬁce) where the number of users and the number of devices
attendance system has a ratio that is not balanced. With the
attendance system based smartphone or mobile device, each
person have android-based mobile device can be mounted ab-
sences application so no need to queue in electronic attendance
device or the manual system provided by the company.
ACKNOWLEDGMENT
The authors would like to thank Directorate General of
Higher Education (DIKTI), Republic of Indonesia for their
support in making this research possible. This research was
supported by Competitive Research Grant scheme 2016.
REFERENCES
[1] A. Jain, A. Ross and S. Prabhakar, Fingerprint Matching Using Minuate
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[2] A. K. Jain, L. Hong, S. Pankanti, and R. Bolle, An identity authentication
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[3] O. Shoewu and O. A. Idowu, Development of Attendance Management
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[4] S. Rao and K. J. Satoa, An Attendance Monitoring System Using Bio-
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Smart mobile attendance system using voice recognition and fingerprint on smartphone

Thoha, Nurianna

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