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A PT X is a state-owned enterprise that provides the largest telecommunications services and network in Indonesia. By the growing challenges in the telecommunications industry, PT X must carefully take care of their customers by improving its services in order to make them satisfied and loyal. One of the effort that can be done by PT X is determining and predicting their customer's category, so that...
This paper proposes an investment in the stock exchange of Thailand (SET) using ARIMA model and support vector machine. Today, the investors are interesting to invest the stock market because it provides for higher profits than ones from deposit banking. Although the stock market can provide a high benefit for investors, it comes with a high risk too. Thus, this is a reason why we are proposing ARIMA...
Corporate financial planning relies on thousands of financial forecasts generated by human forecasters with varying performance (forecast errors). Previous work proposes ARIMA prediction as a competitive benchmark for manual forecasts. However, ARIMA can also produce large errors, and a company needs to understand sensitivity of ARIMA-outcome to time series characteristics before ARIMA-benchmarks...
This paper presents a hierarchical demand-driven planning framework for the fast-moving consumer goods industry. We develop a planning methodology that is more adaptive to changing customer demand than the typical pull-based planning methods while it reduces inventories compared to the typical push-based planning methods. In an industry where forecast accuracy is often poor, our framework can help...
Location-Based services with social networks improve users' experience and enrich people's social live. However, location information is often inadequate due to privacy and security concerns. We seek to infer users' ‘Current City’ on Facebook for coarse location based applications. We first extract users' multiple explicit and implicit location attributes, and analyze correlations of these attributes...
A customer churn analytical model based Bayesian network is built for prediction of customer churn. We propose Bayesian Network approaches to predict churn motivation, mining the result in churn characters in order to help decision-making manager formulate corresponding detainment strategy. Experimental results show that classification performance of both methods is resultful.
In the rapidly changing technological world of today, new technical areas emerge quickly, and new skills related to them garner high demand. In this paper, our goal is to recommend experts for new skills and skill topics. We propose multiple predictive models to utilize data from different enterprise sources: employee assessment data, free-text skill description data, and employee tags from corporate...
QoS-based Web service recommendation is a widely employed way of selecting proper candidate services that can provide better QoS to users. In this paper, based on Matrix Factorization (MF) model, at first, we propose the service neighborhood extended MF model (SN-EMF) and user neighborhood-extended MF model (UN-EMF), in which we integrate two types of valuable information respectively. One is the...
Marketing strategies and relationship management of customers are increasingly important today, so investments for these aspects of the business are growing exponentially. To carry out the above, it is necessary to take a look inside the stored knowledge of any enterprise that could visualize the commercial behavior and preferences of their customers. Telecommunications companies deal with a special...
Within Software Product Lines (SPL) features are well understood and facilitate the communication among SPL developers and domain experts. However, the feature specification task is usually based on natural language, which can present lack of clarity, non-conformities and defects. In order to understand the feature non-conformity in SPL, this paper presents an empirical study to investigate the possible...
With the constant expansion of projects, project management becomes increasingly complex and difficult. This paper illustrates the application of decision support system (DSS) in project management of modern enterprises by an example. By the use of DSS model base, project managers can effectively solve the problem of how to implement projects, control schedule, cost and human resources. It is proved...
Corporate financial distress not only incurs serious financial loss to its creditors but also has a high cost to the society and the country's economy. Consequently, financial distress prediction studies are important to all those involved: owners, shareholders, lenders, suppliers, and government. In this paper, we focus on the corporate bankruptcy prediction for international market using CompuStat...
E-commerce has rapid growth in the last two decades due to the development of information technologies, mobile network services and application of big data. Nowadays, e-commerce has reached a stage in which e-businesses are far beyond the online trading of buy-pay-deliver, but covers a much broader spectrum of line business activities, such as financing, which indicates that e-commerce has been transited...
This paper presents the construction of the ProfileSEEKER the information system for early warning small and medium-sized enterprises from bankruptcy. The developed system is a set of five classifiers, using a variety of topologies of artificial neural networks and Bayes belief network, supported by supervised machine learning methods. System performance was evaluated using the original validation,...
One of the most important things during a project planning is the estimation of the project cost. Many decisions during project estimation and planning are based on previous experience and competency of a manager. Evaluated completed projects provide rich knowledge about similar decisions and reality. This paper focuses on the comparison of two supportive methods for the approach how to estimate value...
For a large and evolving software system, the project team could receive many bug reports over a long period of time. It is important to achieve a quantitative understanding of bug-fixing time. The ability to predict bug-fixing time can help a project team better estimate software maintenance efforts and better manage software projects. In this paper, we perform an empirical study of bug-fixing time...
How can we find data for quality prediction? Early in the life cycle, projects may lack the data needed to build such predictors. Prior work assumed that relevant training data was found nearest to the local project. But is this the best approach? This paper introduces the Peters filter which is based on the following conjecture: When local data is scarce, more information exists in other projects...
A food-processing-and-distribution company typically stores products in a warehouse before shipping them to customers. Inventory management is therefore important to the food-processing-and-distribution industry because of the large amount of products typically stored. Large amounts of stored products increase inventory cost and management cost and can reduce warehouse efficiency. This study is important...
Protecting innovation is an important issue for sustaining economic growth, intellectual property for defining innovation is therefore becoming an emerging research topic. Patent as a type of intellectual property plays importantly in protecting innovation can possibly be used for predicting infringement probability if conventional intellectual property service can be extended innovatively. This study...
Research on the temporary staffing industry discusses different topics ranging from workplace safety to the internationalization of temporary labor. However, there is a lack of data mining studies concerning this topic. This paper meets this void and uses a financial dataset as input for the estimated models. Bagged decision trees were utilized to cope with the high dimensionality. Two bagged decision...
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