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ANALISIS FREKUENSI KEDATANGAN BUS TRANSJAKARTA DI WAKTU SIBUK DAN TIDAK SIBUK Taniasi, Wizi Dewi; Wijaya, Hartono; Rackman, Susanto; Gunawan, Fergyanto E.
Industrial and Systems Engineering Assessment Journal (INASEA) Vol 13, No 2 (2012): INASEA Vol. 13 No. 2
Publisher : Industrial and Systems Engineering Assessment Journal (INASEA)

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Abstract

The high road traffic in Jakarta often leads to a massive traffic jam. The problem arises because the volume of vehicles increasing at a higher rate than the road development. To overcome the traffic jam problem, the government introduced bus rapid transit, known as TransJakarta, in 2004. They expects the users of the private vehicle will switch to using TransJakarta, which can further lessen the traffic congestion. However, until now, TransJakarta is still having a low ridership, and is not able to meet the expectation. Passengers often critize the system because of long inter-arrival time between buses, which forced passengers to wait for a long time. TransJakarta operator has to address this issue as quickly as possible before inhabitantsof Jakarta losing their trust on the system. In this study, we analyzed the arrival frequency of TransJakarta buses at the peak-period time and off-peak period time, and also analyzed the factors that affect the frequency.
EVALUASI KEBERHASILAN TRANSJAKARTA DIBANDINGKAN DENGAN BUS RAPID TRANSIT (BRT) KELAS DUNIA E.Gunawan, Fergyanto; Kusnandar, Erwin
Jurnal Jalan-Jembatan Vol 28 No 2 (2011)
Publisher : Direktorat Bina Teknik Jalan dan Jembatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (17097.303 KB)

Abstract

ABSTRAKPerpindahan orang dan barang masih mendominasi prasarana transportasi jalan. Dinegara-negara berkembang, perpindahan dalam jumlah besar ini umumnya menggunakan system transportasi yang kurang efisien seperti kendaraan pribadi. Kota Jakarta, sebagai contoh, masih sangat tergantung dengan kendaraan pribadi. Di kota ini, jumlah kendaraan roda-dua mencapai 11,4juta pada tahun 2010 dan tumbuh secepat 11% per tahun. Jumlah dan pertumbuhan tinggi ini belum bisa diimbangi oleh prasarana transportasi sehingga kemacetan sering terjadi dan menyebabkan system transportasi menjadi tidak efisien. Untuk kondisi demikian, angkutan umum seperti bus rapid transit (BRT) menjadialternatif yang menjanjikan, dan diawal abad ke 21, terlihat penggunaan system BRT dibanyak kota di dunia. TransJakarta adalah system BRT yang di adopsi oleh kota Jakarta, dan telah beroperasi sejak 2004. Wakaupun demikian, setelah tujuh tahun beroperasi, TransJakarta belum berhasil mengatasi kemacetan di lalu-lintas Jakarta. Data memperlihatkan bahwa TransJakarta memiliki tingkat penumpang yang relatif rendah, dan belum terlihat perpindahan moda trasportasi di masyarakat. Penelitian ini pembelajari sistem TransJakarta khususnya dalam aspek-aspek yang berhubungan dengan sistem BRT standar dunia. Standar ini memiliki 30 aspek dalam lima kategori: Rencana Pelayanan, Infrastruktur, Desain Stasiun dan Antar-Muka Stasiun, Kualitas Pelayanan dan Sistem Informasi Penumpang, dan Integrasi dan Akses. Pada akhir paper ini, didiskusikan  aspek-aspek yang perlu diperbaiki oleh TransJakarta. Kata Kunci : Bus Transpor Cepat,Transportasi Umum, TransJakarta, Kemacetan, BUS
An Analysis of Bitcoin Acceptance in Indonesia Gunawan, Fergyanto E.; Novendra, Rizki
ComTech: Computer, Mathematics and Engineering Applications Vol 8, No 4 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i4.3885

Abstract

This research intended to understand the factors affecting the acceptance of Bitcoin technology in Indonesia. It adopted the model of Unified Theory of Acceptance and Use of Technology (UTAUT), which took into account four influencing factors. Those were performance expectancy, effort expectancy, social influence, and facilitating conditions. The factors of gender and age were assumed to moderate the relations between those four factors and use and behavioral intention. The empirical data for those factors were collected by questionnaires from 49 respondents. The statistical significance of the relationships was evaluated by multivariate regression analysis. The result is a model that matches the data with R2 = 0,678. It demonstrates a high level of fitness. The analysis suggests that the performance expectancy factor and the social influence factor greatly affect the behavioral intention to use Bitcoin with the values of t-statistic of 3,835 (p-value = 0,000) for the former factor and 1,948 (0,059) for the latter factor. However, the social influence factor has less profound effect on the behavioral intention.
Factors That Influence Employees’ Intention to Use Enterprise Social Media as Knowledge Sharing Media Gunawan, Jeanifer; Gunawan, Fergyanto E.
CommIT (Communication and Information Technology) Journal Vol 13, No 2 (2019): CommIT Vol. 13 No. 2 Tahun 2019
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v13i2.5627

Abstract

Along with the widespread use of Enterprise Social Media (ESM) by various large companies in Indonesia, this research is conducted to discover what the factors that drive employees’ intention to use ESM as knowledge sharing media are, and what factor is the most dominant in driving employees’ intention. This research is a quantitative research which uses Innovation Diffusion Technology (IDT) and Extended Technology Acceptance Model (TAM) as the research model. Data collection in this research is conducted by the survey method. The questionnaires are distributed to 374 respondents. Based on the data collected, data processing and hypothesis testing are carried out using Partial Least Square Structural Equation Modelling (PLS-SEM). The result of this study indicates that relative advantage, compatibility, and perceived ease of use have a significant influence on perceived usefulness and perceived enjoyment. Meanwhile, perceived usefulness and perceived enjoyment have a significant influence on employees’ intention to use ESM. Furthermore, it is also found that the most dominant factor among those two variables is perceived enjoyment.
Improving E-Book Learning Experience by Learning Recommendation E. Gunawan, Fergyanto; Soewito, Benfano; Candra, Sevenpri
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (183.055 KB) | DOI: 10.11591/eecsi.v4.1024

Abstract

Technology  Enhanced Learning  is one of the  most dynamic   areas   of  inquiry   in  education.   One  form  of  TELs, that  is on-screen  learning,  has  become  the  topic  of interest  of many  works.  It  is  popular mainly  with  young  people  despite all  findings,  which  undoubtedly suggest  that  it  is  detrimental to  learning.   The  method   hinders   learning   experience   due  to the reading spatial  instability,  difficulties  in establishing  mental map,  and  poor  visual  ergonomics.  Currently, many  textbooks are available  in electronic form and a majority of the students  in Bina  Nusantara University  in Indonesia,  for  example,  consider the form to be more convenient  and preferable. In the electronic form,  the  textbooks  are  much  more  affordable.  They  can  be obtained  easier  than  the  printed books.  This  work  intends  to explore   a  method   of  improving   the  learning   quality   of  the electronic textbooks. The improvement is expected to be achieved by  enriching   the  electronic   textbook   with  cues  in  the  form of margin  notes, highlights, markers, lines and arrows,  and navigation  tools provided  by the subject  matter expert.  The idea is implemented on  a  class at  the  university  and  its  effects are assessed.  The  participants are  divided  into  two  groups  having the  same  distribution of the  past  academic  performance where one group  is assigned to learn  using the recommendation system and  the  other  is without  the  system.  After  the  learning,  their understandings are assessed systematically by qualitative  and quantitative methods. The participants with the recommendation system outperform those without  significantly,  which is marked by the values of the Cohen’s  effect size d larger  than  1.20 with the standard deviation  about  0.563.
Smartphone for Next Generation Attendance System and Human Resources Payroll System Soewito, Benfano; Gunawan, Fergyanto E.; Hapsara, Manik
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.9 KB) | DOI: 10.11591/eecsi.v4.1036

Abstract

A wide variety  of current attendance system can be found easily in the market, but there are still some deficiencies in the attendance system;  how the company  will control  employees are  outside  the office building  and  how employees can take  ad- vantage of the attendance system to view a variety of information needed.  The  modern  attendance system must  integrated with a human  resources management and payroll  system. Others  issues with  current  attendance system,  beside  could  not  control  the staff  who  work  outside  the  office are  conventional  attendance system that  spends  a lot of paper  and  a long process  due to be entered  manually  into  the  system  for  processing  payroll,  while the  electronic  attendance system  with  limited  device can  cause queues  at  the  time  employee entry  and  exit the  office building. In  this  work,  we introduce online  attendance system on mobile devices and  is integrated with the payroll  system. It is a system created  to overcome some of the limitations  that occur in manual or electronic attendance system which is often conventionally used today. We utilized Global Positioning System (GPS), microphone, and fingerprint scanner  that available on a smartphone or others mobile  devices. We developed  our application base  on  android platform   because  the  android is the  most  platforms   that  have been using in the most mobile devices. Using our proposed methodology, the employee can do attendance using their  mobile devices and the do not need to be in queue and the employee who work outside the office also can do the attendance. Our  research showed that our proposed methodology can used for the next generation  absence  system.
Detecting the Early Drop of Attention using EEG Signal Gunawan, Fergyanto E; Wanandi, Krisantus; Soewito, Benfano; Candra, Sevenpri
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (292.584 KB) | DOI: 10.11591/eecsi.v4.1077

Abstract

The capability   to detect the drop of attention as early as possible has many practical applications including for the development of the early warning system for those who involve in high-risk works that  require a constant level of concentration. This study intends to  develop such the capability on the basis of the data of the brain   waves: delta, theta, alpha, beta, and gamma. For the purpose, a number of participants are asked  to participate in the study where their  brain waves are recorded by using a low-cost Neurosky Mindwave EEG sensor. In the process, the  participants are performing a continuous performance test from which their attention levels are directly measured in  the form of the response time in conjunction to those waves. When the response time is much longer than  a normal one, the participant attention is assumed  to be dropped. A simple k-NN classification method is used with the k = 3. The results are the following. The best detection of the attention drop is achieved when  the attention features are extracted   from the earliest stage of the brain wave signals. The brain wave signal should be  recorded longer than 1 s since the time the stimulus is presented as a short signal  leads to a poor categorization. A significant drop in the level of response time is required to provide the brain signal that better predicts the change of the attention.
Face Recognition on Linear Motion-blurred Image Fergyanto E. Gunawan; Jeklin Harefa; Nobumasa Sekishita
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.5480

Abstract

Most face recognition algorithms are generally capable to achieve a high level of accuracy when the image is acquired under wellcontrolled conditions. The face should be still during the acquisition process; otherwise, the resulted image would be blur and hard for recognition. Enforcing persons to stand still during the process is impractical; extremely likely that recognition should be performed on a blurred image. It is important to understand the relation between the image blur and the recognition accuracy. The ORL Database was used in the study. All images were in PGM format of 92 × 112 pixels from forty different persons, ten images per person. Those images were randomly divided into training and testing datasets with 50-50 ratio. Singular value decomposition was used to extract the features. The images in the testing datasets were artificially blurred to represent a linear motion, and recognition was performed. The blurred images were also filtered using various methods. The accuracy levels of the recognition on the basis of the blurred faces and filtered faces were compared. The performed numerical study suggests that at its best, the image improvement processes are capable to improve the recognition accuracy level by less than five percent.
Vibration-Based Damaged Road Classification Using Artificial Neural Network Yudy Purnama; Fergyanto E. Gunawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.7574

Abstract

It is necessary to develop an automated method to detect damaged road because manually monitoring the road condition is not practical. Many previous studies had demonstrated that the vibration-based technique has potential to detect damages on roads. This research explores the potential use of Artificial Neural Network (ANN) for detecting road anomalies based on vehicle accelerometer data. The vehicle is equipped with a smart-phone that has a 3D accelerometer and geo-location sensors. Then, the vehicle is used to scan road network having several road anomalies, such as, potholes, speedbump, and expansion joints. An ANN model consisting of three layers is developed to classify the road anomalies. The first layer is the input layer containing six neurons. The numbers of neurons in the hidden layer is varied between one and ten neurons, and its optimal number is sought numerically. The prediction accuracy of 84.9% is obtained by using three neurons in conjunction with the maximum acceleration data in x, y, and z-axis. The accuracy increases slightly to 86.5%, 85.2%, and 85.9% when the dominant frequencies in x, y, and z-axis, respectively, are taken into account beside the previous data.
Predicting the Level of Emotion by Means of Indonesian Speech Signal Fergyanto E. Gunawan; Kanyadian Idananta
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.3965

Abstract

Understanding human emotion is of importance for developing better and facilitating smooth interpersonal relations. It becomes much more important because human thinking process and behavior are strongly influenced by the emotion. Align with these needs, an expert system that capable of predicting the emotion state would be useful for many practical applications. Based on a speech signal, the system has been widely developed for various languages. This study intends to evaluate to which extent Mel-Frequency Cepstral Coefficients (MFCC) features, besides Teager energy feature, derived from Indonesian speech signal relates to four emotional types: happy, sad, angry, and fear. The study utilizes empirical data of nearly 300 speech signals collected from four amateur actors and actresses speaking 15 prescribed Indonesian sentences. Using support vector machine classifier, the empirical findings suggest that the Teager energy, as well as the first coefficient of MFCCs, are a crucial feature and the prediction can achieve the accuracy level of 86%. The accuracy increases quickly with a few initial MFCC features. The fourth and more features have negligible effects on the accuracy.