Database Systems Journal

ISSN 2069 - 3230

The journal is published under the sponsorship of
The Bucharest University of Economic Studies
and it is produced by the university's own publishing division,
The Bucharest University of Economic Studies Publishing House


Database Systems Journal, Vol. XII, 2021


Open PDF Journal


CONTENTS


1. The Improvement of Decision-making Process using Business Intelligence Solutions (p. 1-11)
Adelina TANASESCU, The Bucharest University of Economic Studies, Romania
The aim of this paper is to present the benefits of using Business Intelligence solutions for the improvement of decision-making process. Data and information are extremely important in the development of a business and in its process of becoming the leader of the market. Business Intelligence solutions offer the opportunity of using descriptive analysis in order to make informed decisions for businesses. These solutions offer the possibility of data visualization, which helps to obtain various benefits.
Keywords: Business Intelligence, data, information, descriptive analysis, data visualization, decision-making process
2. Churn Prediction in Telecommunications Sector using Machine Learning (p. 12-20)
Andreea-Maria COPACEANU, The Bucharest University of Economic Studies, Romania
In these days, due to the increasing competition, churn prediction has gathered greater interest in business, especially in the telecom industry, since gaining new customers is more expensive than retaining the existing ones. The primary objective in telecom churn analysis is to accurate-ly estimate the churn behavior by identifying the customers who are at risk of churning. Another objective is to identify the main reasons for customer churn. This paper focuses on various ma-chine learning algorithms for predicting customer churn, though which we build classification models such as Logistic Regression, Random Forest, Decision Tree, and Support Vector Ma-chine. Prediction performance of the classifiers is evaluated and compared through measures such as Area Under the Curve (AUC), accuracy, and recall rate. Such predictive models have the potential to be used in the telecom industry for making better decisions in customer management.
Keywords: Churn Prediction, Machine Learning, Retention, Telecommunication, Decision Tree
3. Differentially Private Data Release for Data Analytics - A Model Review (p. 21-31)
Peter N. MUTURI, University of Nairobi, Kenya
Andrew M. KAHONGE, University of Nairobi, Kenya
Christopher K. CHEPKEN, University of Nairobi, Kenya
To leverage on the potential of data analytics, enabling private data release is needed. The challenge in achieving private data release has been balancing between privacy and analytical utility. Among the models that seek to solve the challenge, ε-differential privacy promises to achieve the balance by regulating the epsilon (ε) value. The choice of the appropriate epsilon value that achieves the balance has been a challenge, making the ε-differential privacy not practically applicable by many. A practical and heuristic method to estimate this privacy parameter needs formulation. The variable to estimate appropriate privacy parameter that is not provided in heuristic manner is the reidentification probability. Previous research has based that probability on released data sets and linkage data sets, with less focus on data analysts. This paper proposes a causal relationship model for estimating the reidentification probability, which adds the analyst's aspect to the model.
Keywords: Privacy, Data Utility, Differential Privacy, Big Data, Private release, Anonymization
4. String Aggregation Techniques in Oracle ListAgg - Details, Limitations, and Alternatives (p. 32-39)
Cristian DUMITRESCU, IBM Romania
This paper proposes several ways to overcome the ORA-01489 result of string concatenation is too long error in early versions of Oracle Database (before 12c). Each proposed alternative is presented with pros and cons and may be applied only in specific cases, depending on the requirement or cause.
Keywords: Relational Databases, Oracle, ListAgg, ORA-01489, User-Defined Functions
5. Appointment Scheduling System for a Primary Hospital (p. 40-55)
Norman GWANGWAVA, Botswana International University of Science and Technology, Botswana
Kgalalelo D. NTESANG, Botswana International University of Science and Technology, Botswana
Many primary hospitals in developing countries face serious shortages of equipment and skilled personnel to handle cases reporting to them. This article focuses on a primary hospital constructed in the 1970s, with 29 facilities reporting to it. Patients referred to the hospital are usually ferried in ambulances if they are exhibiting critical conditions. Patients deemed uncritical are given referral letters. However, patients are exposed to long waiting times that put their lives at risk or worsen their conditions. The research aims to establish improved ways in which the patient waiting times can be reduced. An appointment scheduling framework for the primary hospital is conceived as a better approach. This is an SMS based queue management system. The system reduces the waiting time of patients in the hospital's outpatient department. A patient registration device that contains a GSM module and a microcontroller which sends messages to and from the patient when booking an appointment for consultation are developed. This queue management system has the potential to reduce patient waiting times by more than 95%.
Keywords: Queuing System, Queue Management, GSM, Outpatient, Healthcare, Patient Appointment, Scheduling
6. Challenges and Ethical Solutions in Using the Chatbot (p. 56-68)
Ionut-Alexandru CIMPEANU, The Bucharest University of Economic Studies, Romania
Artificial intelligence is making its mark on more and more different areas of our lives. No matter what business we are talking about, a smart application offers customers solutions and added value in a more digitalized and automated world. In business, those who do not participate in the development and implementation of innovative solutions exclude the company from the market. However, it uses these necessary IT solutions and ethical challenges related to applicable AI applications, managing and responsibly using the information stored in the applications, the content of the messages, and the way users relate to other users and the chatbot. The paper is structured in four sections. In the Introduction, we talked about the chatbot, about its necessity and usefulness, and about the permanent appearance of some ethical challenges related to the use of the chatbot in different fields of activity. In the next section, we listed a number of ethical challenges that chatbot developers / users face detailing these challenges and setting an example of concrete ethical / unethical approaches. Section III offers solutions to some of the ethical challenges found in the paper. The conclusions provide an overview of the topics addressed in the paper and the directions of perspective in the ethical approach to the issue.
Keywords: Chatbot, ethics, business, challenges, solutions