Conference Presentations by Arda Yunianta
Currently, the Internet is one important part of the campus infrastructure that supports the teac... more Currently, the Internet is one important part of the campus infrastructure that supports the teaching and learning activities. The important part of the internet facility is the provided bandwidth as Bandwidth management to teaching and learning is indispensable. In this study, an analysis and cluster of the university internet traffic is required as bandwidth management decision support. Therefore, Self-Organizing Maps (SOM) as a clustering algorithm bandwidth usage was implemented. The results showed that the SOM method can perform clustering. Furthermore, the clustering result could be a recommendation management bandwidth for network administrator.
Papers by Arda Yunianta
International Journal of Advanced Computer Science and Applications, 2018
Internet of Things has become one of the most challenging issues in many researches to connect ph... more Internet of Things has become one of the most challenging issues in many researches to connect physical things through the internet by creating a virtual identity for everything. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles on Riyadh roads that is resulting in grumbling by residents. Currently, there are few reliable services offered to residents from the traffic department enabling them to access traffic information. A new traffic congestion framework for Riyadh is proposed to help the development of traffic congestion services. This framework aims to benefit from the current Riyadh road infrastructure and apply the Internet of Things paradigm for detecting traffic congestion with Everything as a Service approach. Sensing devices are used to identify the congestion of the traffic flow through providing multiple proposed services such as a vehicle counting, live streaming video and rerouting services. Users are able to access the services by using proposed mobile application connected to the internet, as those services are integrated with public map service. By using the services, the users are able to identify the exact location where congestion occurs and an alternate solution can be provided easily. To achieve this, Business Process Execution Language is embedded as a supporting framework layer. Due to the effectiveness in this layer, executable workflows are designed to combine the proposed services with the legacy Riyadh services as individual model. This approach clearly defines how the services are executed through the proposed models. A quantitative evaluation is provided to support the usability of this research.
Bulletin of Electrical Engineering and Informatics, Dec 1, 2019
Software Engineering (SE) course is one of the backbones of today's computer technology sophistic... more Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a student's performance. Currently, student performance analysis methods just focus on historical achievement and assessment methods given in the class. Need more research to predict student's performance to overcome the problem of student failing. The objective of this research is to perform a prediction for student's performance in the SE using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. This research also investigates the requirements of each student before registering in this course. This research achieved 87.76 percent accuracy in classifying the performance of SE students.
Zenodo (CERN European Organization for Nuclear Research), Dec 31, 2018
Advancing grass development and maintenances is a novel research area in Indonesia. Among many ar... more Advancing grass development and maintenances is a novel research area in Indonesia. Among many areas of grass research, real time monitoring with low cost energy usage is underlined within this paper. In order to support cloud based grass surveillance systems, appropriate video streaming technique is considered be applied according to real time monitoring requirements. This study proposes a new decision analysis model for guiding decision makers to perform selection among existing video streaming algorithms to enhance grass surveillance systems on the cloud. A novel decision analysis model is developed and the guidance for using it properly is also presented.
Penerapan design pattern pada web service situs berita RRI
International Journal of ADVANCED AND APPLIED SCIENCES
A document management system (DMS) is required to handle any documents within an institution effi... more A document management system (DMS) is required to handle any documents within an institution efficiently. However, several important features are lacking in the current DMS, such as security and social media features. This paper proposes a new solution to tackle the issues by developing a new document management system with security and social media features called DocManS. The development process and usability evaluation by users are presented in this paper. The usability assessment is performed with the use of the System Usability Scale (SUS) framework. The results show that the current version falls within the B range of the SUS framework and several enhancements for better usability in terms of social media sharing and privacy are recommended.
Emirates Journal of Food and Agriculture
Harvest drop in rice because of leaf blast is a vital issue in the country’s food stock and socia... more Harvest drop in rice because of leaf blast is a vital issue in the country’s food stock and social life where rice is the primary source of food. Epidemics can cause leaf blasts due to weather conditions or environmental transformation. Therefore, early detection of leaf blast is needed to take precautions action to save the harvest. This research presents a new approach for rice leaf blast detection. It seizes colour distribution and shapes to determine the damaging leaf. Two main features: colour and shape, are key points to measure the similarity of an image by comparing the image query and database. The image extraction uses histogram colour throughout the pre-processing phase. The approach will take the dominant colour of leaf. Since this green colour dominated the leaf, the green will be converted from RGB to the HSV domain with 256 range. The shape feature extraction based on morphology closing will calculate the images’ area, diameter, and perimeter. The process is continued...
Procedia Computer Science
Smart City indeed become a vision of most of the countries. The city will have robots, drone, sma... more Smart City indeed become a vision of most of the countries. The city will have robots, drone, smart car, the house entirely operated Intelligently. However, managing how the human crowd and machine can live together is a challenging task; social and emotional interaction between human may affect the crowd behaviour. Therefore, Crowd simulation has the potential to demonstrate the behaviour of a massive people that gathering on a particular location during a specified period. The size of the crowd, geographical site condition and agent's personality potentially make crowd simulation more believable. This paper aims to observe the potential of reinforcement learning for controlling Socio-emotional crowd behaviour by adding the parameter of emotion towards the crowds. The Tree algorithm more superior compare to other machine learning algorithm that capable of predicting the female agent with accuracy 88.1% and male agent around 85.3%. The simulation performed with the railway station scene that has four platform and six lanes to accommodate a passenger. Simulation is initiated with passengers walking toward the main entrance and went to the desired platform. The train is set up to arrive every minute, and the on-board passenger will move toward the entrance door and exit the central station. The reinforcement learning with socio-emotional control expected to bring the crowd simulation to provide realistic and human mimicked behaviour.
Automated Visual Inspection System (AVIS) has the capability to investigate large numbers of manu... more Automated Visual Inspection System (AVIS) has the capability to investigate large numbers of manufactured goods quickly and accurately. In addition, this system operates with a high level of reliability and consistency in their tasks. This study proposed an AVIS for detecting cap situations by using fuzzy logic classifiers. The objectives of this research are to develop an applicable image processing algorithm, together with a feature extraction technique, and to detect the cap for plastic bottles which is based on the average of distances. Three types of classification were compared for detecting the bottle caps. They are Mamdani, Sugeno, and production rule. The system was evaluated in a real time environment. The results are 97.91%, 97.5%, 96.66% accuracy for Mamdani, Sugeno, and production rule respectively.
Summary Advancing grass development and maintenance is a novel research area in Indonesia. Among ... more Summary Advancing grass development and maintenance is a novel research area in Indonesia. Among many areas of grass research, real time monitoring with low cost energy usage is underlined within this paper. In order to support cloud based grass surveillance systems, appropriate video streaming technique is considered be applied according to real time monitoring requirements. This study proposes a new decision analysis model for guiding decision makers to perform selection among existing video streaming algorithms to enhance grass surveillance systems on the cloud. A novel decision analysis model is developed and the guidance for using it properly is also presented.
TEM Journal, 2021
It is imperative for government to constantly improve e-government services through innovative te... more It is imperative for government to constantly improve e-government services through innovative technologies in order to cope with tremendous demands coming from citizen side. Although it is realized that e-services to citizens have to be improved and enriched, the realization is not an easy effort since additional budget allocation is usually considered as a hard decision from economic point of view. Cloud computing offers a sound answer to the issue by offering low cost of infrastructure spending, simplifies e-government development and on demand solution to any requirement from user. Practical implementation of OwnCloud for private data center is discussed. Then, the paper briefly reviews several features of OwnCloud that have been modified according to the need of local government and put required assessment on how to implement them appropriately.
Sustainable Cities and Society, 2021
Abstract Based on technical reports, the high demand of proper tool for load forecasting (LF) and... more Abstract Based on technical reports, the high demand of proper tool for load forecasting (LF) and precise planning in recent combative and challenging markets of electrical energy is highly uprising. Therefore, this paper intends to suggest a creative hybrid deep estimation model for short term LF (STLF) using Generative Adversarial Network (GAN), Auto-Regressive Integrated Moving Average (ARIMA) and wavelet package. To get the stationary behavior, the time series in non-stationary behavior case would be differenced in the required number of times. The appropriate order for the model of ARIMA is found using Akaike Information Criterion (AIC). When the linear part of the electrical demand time series is captured by ARIMA, the remaining nonlinear part would be hard to model. The discrete wavelet transform would be utilized to decompose the residual nonlinear component into its sub-frequencies. To estimate the future nonlinear samples, several GAN models are then applied to approximation and detail components of residual signal. Finally, the results of GAN and ARIMA models would be added together to construct the final signal. The observed experimental results indicate the proper improvement of the proposed accurate LF model.
2019 International Conference on Advances in the Emerging Computing Technologies (AECT), 2020
Educational business intelligence concerns the decision-making in the education sector and this a... more Educational business intelligence concerns the decision-making in the education sector and this article intends to analyse the student’s attributes’ contribution toward graduating within the duration. In this research, the framework identifies the best set of attributes and evaluates the performance of the model with the help of 22 input features. This article discussed the development of the business intelligence (BI) framework for the higher education that is able to explore, analyse and visualize the relevant data into information. This is to assist the top management in improving the methodologies in teaching and learning. In this case study, the framework used metaheuristic algorithm, Ant Colony Optimization (ACO) technique mainly to identify the best set of attributes, and the performance was validated using Support Vector Machine (SVM). The framework consists of four layers which are data source, data integration, analytics, and access layers. In this study, 46,658 input data were processed for the identification of postgraduate students who completed their studies within a specified period. The performance evaluation of the data achieved accuracy, sensitivity and precision of 87.44% for PhD dataset and t-test has been conducted to prove that the selected features are significant. Based on the findings, the results from the proposed educational business intelligence framework produced BI dashboard as an output from the framework is capable to act as a decision-making tool for education management and educational technology system.
Nowadays, e-learning has become important supporting tools for effective learning. Therefore, int... more Nowadays, e-learning has become important supporting tools for effective learning. Therefore, integrating a good learning environment in e-learning can improve learning process. Good learning environment can provide new knowledge. Currently, there are many distributed systems and applications on learning environment that involve heterogeneity data in data level implementation. Different learning applications have different system designs and data representations. The main problem on learning environment is that every individual learning application has limited capability to share data and information. Moreover, existing data integration approaches still have weaknesses and there has been less research done on the learning environment of data integration. This research proposes a semantic data integration framework is to handle data heterogeneity on learning environment that integrates various learning information to produce new learning knowledge. This research focuses on semantic d...
International Journal of Electrical Power & Energy Systems, 2021
Abstract In this paper, a new machine learning based framework is developed for the energy policy... more Abstract In this paper, a new machine learning based framework is developed for the energy policy and operation management of the smart grids, utilizing advanced support vector networks in the renewable smart grids (RSGs), considering storage unit, wind and tidal systems and dispatchable units. The proposed system first develops a support vector regression (SVR) for prediction of the tidal and wind units output power with high accuracy. In the second step, an energy policy system is devised which forces the system operator to support renewable sources by guaranteeing the full purchase of their generation. In the third step, the optimal energy management framework is launched which optimizes the operation costs when considering the practical constraints. In the proposed novel framework, a new optimization method based on fuzzy dragonfly algorithm (FDA) is developed to enhance the search performance by creating adjusting fuzzy version this algorithm. In order to handle the uncertainty effects, a reduced scenario based approach is developed which shows high accuracy of 95% confidence level but with trivial computational time. The system quality is assessed on a test RSG system. The results prove the contributing claims of the research, clearly.
International Journal of Advanced Computer Science and Applications, 2021
Driving in an unfamiliar traffic regulation using an unfamiliar vehicle configuration contributes... more Driving in an unfamiliar traffic regulation using an unfamiliar vehicle configuration contributes to increase number of traffic accidents. In these circumstances, a driver needs to have what is referred to as ‘situation awareness’ (SA). SA is divided into (level 1) perception of environmental cues, (level 2) comprehension of the perceived cues in relation to the current situation and (level 3) projection of the status of the situation in the near future. On the other hand, augmented feedback (AF) is used to enhance the performance of a certain task. In Driving, AF can be provided to drivers via in-vehicle information systems. In this paper, we hypothesize that considering the SA levels when designing AF can reduce the driving errors and thus enhance road safety. To evaluate this hypothesis, we conducted a quantitative study to test the usability of a certain set of feedback and an empirical study using a driving simulator to test the effectiveness of that feedback in terms of improv...
Penerapan design pattern pada web service situs berita RRI
International Journal of Advanced Computer Science and Applications, 2021
Games are a unique, interesting, and fun entertainment medium. Games can contain education, intro... more Games are a unique, interesting, and fun entertainment medium. Games can contain education, introduction to certain flora and fauna, work and daily life, intelligence and dexterity. The game built in this study aims to introduce the flora and fauna found in the forests of East Borneo (Kalimantan), Indonesia as the object of a plat former game. Games are built using the Game Development Life Cycle method in order to make good and organized games. The GDLC method contain 6 stages, first is the initiation for the initial idea, second is to preproduction for the asset creation, third stage is production for the system creation, forth is the testing for the trial, fifth is the beta for the external trial, and the sixth stage is to release for publication. The results of the study resulted in the Borneo Wildlife game platform. This game introduces the unique flora and fauna in East Borneo, Indonesia, such as Black Orchids, Ironwood trees, Proboscis monkeys, Mahakam dolphins and Hornbills, as well as how to protect and preserve their nature. The game received 46 downloads from March 1, 2021 to May 24, 2021.
Proceeding of the Electrical Engineering Computer Science and Informatics, 2014
Heterogeneity on learning environment is about different data and applications to support a learn... more Heterogeneity on learning environment is about different data and applications to support a learning process in education institutions. Distributed and various systems on learning environment is the current issues to produce big and heterogeneity data problem. A lot of relationships are formed between elements on learning environment. The element on learning environment consists of learning data, learning applications, data sources, learning concept, and data heterogeneity aspect on learning environment. These elements are interrelated and produce complex relationship between each other. A complex relationship problem between elements on learning environment makes a process of analysis and identification difficult to be done. Existing method to drawing this heterogeneity problem make confuse and misunderstanding readers. To solved this problem, researcher using ontology knowledge to describe and draw a semantic relationship that represent the complexity of data relationship on learning environment. The result of this analysis is to develop ontology knowledge to solve complexity relationship on learning HQYLURQPHQW DQG DOVR WR KHOS UHDGHU ¶V EHWWHU XQGHUVWDQGLQJ WKH complex relationship between elements on learning environment.
Bulletin of Electrical Engineering and Informatics, 2019
Software Engineering (SE) course is one of the backbones of today's computer technology sophi... more Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a student's performance. Currently, student performance analysis methods just focus on historical achievement and assessment methods given in the class. Need more research to predict student's performance to overcome the problem of student failing. The objective of this research is to perform a prediction for student's performance in the SE using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. This research also investigates the requirements of each student before registering in this course. This research achieved 87.76 percent accuracy in classifying the performance of SE students.
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Conference Presentations by Arda Yunianta
Papers by Arda Yunianta