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Fraud in public companies has a large financialimpact, and yet is only weakly detected by those who look for it, many incidents have been detected only when whistleblowers have come forward. We examine the problem of detecting fraud from the textual component of the quarterly and annual reports that public companies are required to file. Using an empirically derived set of words, we achieve prediction...
Stock exchanges have a major impact on Indonesia economy condition as well as on the global economy. Stock activities forecasting is still a challenging issue which is a high demand for stock actors. Therefore, there is still a need to develop an application that is capable to accurately predict directions of stock price movement. This research proposes a data mining technique to model relationship...
Data concerning of the IC work in process (WIP) can be classified into paired and unpaired, according to whether the corresponding input and output times of the WIP are correlated with each other. To handle these different classes of data, this study presents a production output forecast scheme that can predict the distributions in the next-period and simulate the production outputs of a semiconductor...
Recommender systems now tend to gain popularity and significance. The proliferation of many recommender systems leads to the difficulty of locating a good recommender system. The algorithms contained in the recommender system determine the efficiency of the recommender systems. The question now is to find the most appropriate algorithms to meet users' needs. So far, the research carried out has focused...
Data creditability plays a very important role in the complex system simulation creditability. From the point of how to evaluate and improve the complex system simulation data creditability, the concept of the data quality modeling is advanced and the three-dimension data quality modeling space is founded. Based on which, a multiple attributes decision making theory based data creditability evaluating...
Today's school and college textbooks are full of static, multimodal content. This research investigates which of the three modalities -- text, table or graph -- is more efficient in conveying a given message to students. For fixed content, we hypothesized that graph representation is better of the three for comprehension. Experiment results (N=25)suggest that graphs are indeed 25.5% faster to understand...
The development of business failure prediction system to prevent the significant loss of social costs caused by the companies' unexpected bankruptcy is a popular investigation issue. Because of the constraint on the statistic assumptions, the forecasting models established by traditional statistic methods have some limits in its identity. Therefore, in recent years various algorithms imitating of...
This paper proposes and tests a methodology for selecting features and test cases with the goal of improving medium term bankruptcy prediction accuracy in large uncontrolled datasets of financial records. We propose a Genetic Programming and Neural Network based objective feature selection methodology to identify key inputs, and then use those inputs to combine multi-level Self-Organising Maps with...
Order picking is the process of collecting items from an assortment in inventory. In previous studies, we focused on carefully-controlled, internally-valid studies comparing the speed and accuracy of various versions of mobile order picking systems. However, such studies lack the ecological validity of testing on a manufacturing line with experienced employees fulfilling actual orders under time and...
The aim of the work presented in this article is to make sales forecasting as accurate as possible through the use of BP artificial neural network. Firstly, this article introduces the basic principles of BP artificial neural network, and constructs a sales forecasting model based on the theory of BP artificial neural network. Then, with the help of MATLAB, we obtained the predicted sales data using...
The main goal of Transmission Network Expansion Planning (TNEP) is determination of the number, time and location of new lines to be added to transmission network. Up to now, different methods have been used to solve the static TNEP (STNEP). In most of them, this problem is implemented regardless of power loss and the uncertainty in the load demand. With respect to the importance of these two parameters...
Data De-duplication has being used comprehensively within Disk-based Backups, Archives and Disaster Recovery. This technology's high data reduction ratio and satisfied performance in secondary data storage system has aroused huge interests in other fields. The primary storage system is indeed a field being long for data reduction. Data de-duplication maybe a chance to alleviate data redundancy problem...
Nowadays, classifying sentiment from social media has been a strategic thing since people can express their feeling about something in an easy way and short text. Mining opinion from social media has become important because people are usually honest with their feeling on something. In our research, we tried to identify the problems of classifying sentiment from Indonesian social media. We identified...
Machine learning algorithms, such as the genetic algorithm, have often been applied to financial problems, but not enough is known about how to systematically incorporate financial knowledge into these generic learning algorithms. The general hypothesis of this paper is that semantic similarity among financial concepts can be exploited in a hybrid genetic algorithm. A Knowledge-guided Genetic Algorithm...
We consider a new text classification task: classifying enterprise email messages into sensitive business topics. The identification of sensitive topics in email messages is important for enterprises to safeguard their critical data such as intellectual properties and trade secrets. We introduce the incremental PCA (Principal Component Analysis) to email representation, which can learn a feature subspace...
It is advantageous for a QS to be efficient in producing bills of quantities from measurement. Measurement software applications, as a useful IT tool, can help a QS to speed up the measurement works. In relation to the measurement software application for BQ preparation among Malaysian quantity surveying firms, the objectives of the study are to determine the level of usage, identify the problems...
The number of product-related environmental regulations has been dramatically increasing over the last few years. This is especially true for the number of laws concerning restrictions of hazardous substances (e.g. REACh or RoHS). A lot of companies have decided to implement a management system to cope with the challenges of hazardous substances in their products. Nearly all companies lack the competencies...
This article proposes a novel method for comparison among interval-valued intuitionistic fuzzy values (IVIFVs). Two distinctive score functions are utilized to distinguish IVIFVs based on the boundary values of interval-valued membership and non-membership. The uncertainty included in the numerical intervals of membership and non-membership for an IVIFV is well treated as uniform potential instead...
In recent years, there are more and more Open APIs available on the Internet that can be invoked by independent users for their innovative applications. With the development of cloud computing, the number of Open APIs in clouds is also increasing. With the number increasing of functionally-equivalent Open APIs in the cloud, optimal API selection is becoming more and more important. In this paper,...
Prevention of financial risk is one of the major tasks that construction companies have to pay attention to. Using derivatives to avoid such risks is a practical strategy, but is heavily dependent on the traders' skills and accuracy of predictions. The purpose of this study is to develop an automatic expert model using a rule extraction based approach that provides practitioners with a prediction...
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