International Workshop on Big Data and Information Security (IWBIS)
2018 International Workshop on Big Data and Information Security (IWBIS)
12-13 May 2018
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Welcome Message from the Dean of Faculty of Computer Science, Universitas Indonesia
Publication Year: 2018,Page(s):i - ii
IWBIS 2018 Program Schedule
Who is Alice? Privacy Risk, the Case of Regression (Extended Abstract)
Publication Year: 2018,Page(s):i - vi
Cited by: Papers (1)
While there seems to be no turning back from data becoming a commodity, news headlines and scandals recurrently exacerbate a general concern for privacy. Can Alice’s data be collected, analysed and the results meaningfully published and shared without compromising Alice's privacy? How can organizations assess the privacy risk before disclosing data or the results of their analysis of data? We disc...Show More
Profit Prediction Using Regression Model for Travel Agents
Publication Year: 2018,Page(s):7 - 12
Cited by: Papers (2)
Public interest in the air transport by aircraft occurs year by year is increasing, so this opportunity can be exploited by travel agents to improve transactions and corporate profits. The increase is proportional to the number of transactions from the sale of flight tickets to conventionally processed by travel agents and is not used anymore. Airline ticket sales history data from various airline...Show More
Cross-Project Defect Prediction For Web Application Using Naive Bayes (Case Study: Petstore Web Application)
Publication Year: 2018,Page(s):13 - 18
Cited by: Papers (9)
Predicting defect in software is a complicated process and time-consuming. AI-Based software defect predictor can predict 75% defect in software and help developer team to detect and to fix defect module before performing unit testing/system testing by quality assurance. Some research tried to construct prediction model using other project datasets, which is called cross-project defect prediction....Show More
Hierarchical Spatial Pyramid Pooling for Fine-Grained Vehicle Classification
Reza Fuad Rachmadi;Keiichi Uchimura;Gou Koutaki;Kohichi Ogata
Publication Year: 2018,Page(s):19 - 24
Cited by: Papers (2)
In this paper, we proposed a hierarchical spatial pyramid pooling mechanism for improving fine-grained vehicle classification problems. Our proposed method created by removing the last layer of convolutional neural network (CNN) classifier, attaching the hierarchical spatial pyramid pooling at the end of the network, and fine-tune the CNN classifier. Our hierarchical spatial pyramid pooling consis...Show More
Decision Tree Ensemble Vs. N.N. Deep Learning: Efficiency Comparison For A Small Image Dataset
Publication Year: 2018,Page(s):25 - 30
Cited by: Papers (13)
This paper presents a study of the efficiency of machine learning algorithms applied on an image recognition task. The dataset is composed of aerial GeoTIFF images of 5 different vineyards taken with a drone. It presents the application of two different classification algorithms with an efficiency comparison over a small dataset. A Neural Network algorithm for classification through the TensorFlow...Show More
Mail Order Pharmacy is an online pharmacy service which has been widely applied in developed countries. Mail Order Pharmacy has many advantages, especially in long-term treatment patients. In this experiment, Mail Order Pharmacy data of one country in Europe will be used to descriptive and predictive analysis. Descriptive analysis by building data mart basedt on the list of available decisions. Th...Show More
The Dynamic of Banking Network Topology Case Study: Indonesian Presidential Election Event
Publication Year: 2018,Page(s):37 - 42
Cited by: Papers (5)
Information and communication technologies have brought major changes in data storage and processing. Various types and high volume of data has been digitalized and support mining-based data processing to provide knowledge in a modern and efficient way. Banking transaction data has been stored digitally and suitable for the mining process especially in network science model. Understanding transact...Show More
Improving wind power prediction with retraining machine learning algorithms
Mariam Barque;Simon Martin;Jérémie Etienne Norbert Vianin;Dominique Genoud;David Wannier
Publication Year: 2018,Page(s):43 - 48
Cited by: Papers (17)
This paper presents a 48-h prediction methodology for wind power production using a machine learning algorithm and focuses on the optimization of the input dataset. While power-grid operators have to keep the production equal to demand, wind power depends on meteorological conditions. Therefore, the main issue of power-grid operators is to predict the wind production as precisely as possible. Our ...Show More
Comparing Index Structures for Completeness Reasoning
Publication Year: 2018,Page(s):49 - 56
Cited by: Papers (2)
Data quality is a major issue in the devel- opment of knowledge graphs. Data completeness is a key factor in data quality pertaining to how broad and deep is information contained in knowledge graphs. As for large- scale knowledge graphs (e.g., DBpedia, Wikidata), it is conceivable that given the vast amount of information contained in there, they may be complete for a wide range of topics, such a...Show More
Ensemble Support Vector Machine and Neural Network Method for Speech Stress Recognition
Publication Year: 2018,Page(s):57 - 62
Cited by: Papers (9)
This paper has proposed a system that can be analyzed of speech stress recognition. The proposed method (ensemble SVM and NN) is analyzed comparatively proven to have high accuracy. The ensemble method has been applied to improve machine learning ability in identifying with a small number of datasets. It is caused; due to stress is one of the unconscious emotions. Stress can be recognized by speec...Show More
Support Vector Slant Binary Tree Architecture for Facial Stress Recognition Based on Gabor and HOG Feature
Publication Year: 2018,Page(s):63 - 68
Cited by: Papers (9)
The facial stress recognition with histogram information is discussed in this paper. The patterns of facial stress are recognized into three stages, these include a registered image, feature extraction, and classification. The registered image process takes three important parts of the face (the pair of eyes, the nose, and the mouth). While the histogram method such as Gabor filter and HOG feature...Show More
Performance Comparison of Rank Aggregation Using Borda and Copeland in Recommender System
Publication Year: 2018,Page(s):69 - 74
Cited by: Papers (13)
The rapid development of e-commerce will certainly be followed by an increasing number and more varied marketed products, making it confusing and time-consuming for users to choose from a large number of desired products. Consequently, a recommendation system is required to give products suggestion to the users with high accuracy. One of the most commonly techniques for the recommendation system i...Show More
Visulization of Indonesian Bibliography : A Scientometrics Approach
Harry T. Yani Achsan;Wahyu Catur Wibowo;Wahyuningdiah T. H. Putri;M. Muhtar Baswara Achsan
Publication Year: 2018,Page(s):75 - 80
Cited by: Papers (3)
In our research, we found that there were no extensive study about library’s collection in Indonesian language due to the lack of library of things metadata. As the consequence, the Government of Republic of Indonesia has no depiction of the output oflndonesian authors. The aim of this paper is to describe Indonesian bibliography by tools of visualization. In absence of the needed metadata of Indo...Show More
Predicting Bank Financial Failures using Random Forest
Publication Year: 2018,Page(s):81 - 86
Cited by: Papers (13)
In 1994, there was an economic crisis in Turkey. Many banks were declared failed because of the negative impact from the crisis. The failure of individual banks has a huge impact on the real sector, households and can even cause knock-on effects for other banks. Therefore, it is important to predict bank failure. The 2009, Boyacioglu, Kara, and Baykan had predicted bank failures in the period 1994...Show More
Browsing Behavior Analysis from Wi-Fi Logs Based on Community Detection: Case Study on Educational Institution
Mei Silviana Saputri;Ari Wibisono;Adila Krisnadhi;Adhi Yuniarto Laurentius Yohanes;Teuku Amrullah Faisal;Alvin Wardhana Utama;Muhammad Azmi Malik Ariefa;Andre Ramadhani;Aminur Muda
Publication Year: 2018,Page(s):87 - 92
Cited by: Papers (1)
As the growth of technology, the need of internet increases. Wireless internet technology or called Wi-Fi is dominate. Hence, monitoring the usage of Wi-Fi is crucial. Community detection is a technique which can be used to understand browsing behavior analysis. Using this approach, a website is represented as a node in a graph and the transition over websites is represented as an edge where the w...Show More
Ensemble Learning on Large Scale Financial Imbalanced Data
Publication Year: 2018,Page(s):93 - 98
Cited by: Papers (14)
This study focused on evaluating the performance of ensemble learning on handling imbalanced data. Imbalanced data is a special problem in classification task where the class distribution is not uniformed. Resampling (SMOTE and ENN) is employed to improve the classifier performance. Four metrics is applied for performance evaluation i.e., precision, recall, specificity, and F-1 score. Based on the...Show More
Performance Comparison of Bitcoin Prediction in Big Data Environment
Publication Year: 2018,Page(s):99 - 106
Cited by: Papers (3)
In today’s world, everything is transforming to digital forms. These yield large amount of data. A good analysis of these data can lead to new knowledge about the present situation as well as the future insight. While many advantages could be obtained from these large data, the issue on how to run the Machine Learning on a large dataset as effective and efficient as possible remains an open proble...Show More
New Polynomial Based Bit-Level Serial GF(2m) Multiplier for RS(15,11) 4-bit Codec Optimization
Publication Year: 2018,Page(s):107 - 112
Reed Solomon Codec has been optimized by applying a new bit-level serial multiplier in the computation process of RS(15,11) 4-bit. The new multiplier took advantage of partial decoding process with fewer delay, and hence able to proceed in higher cycle rate. The RS Codec involves dominant multiplications which have been replaced by Fully Serial In Parallel Out (FSIPO) multiplier and implemented in...Show More
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