Orgeta Gjermëni | University of Vlora (original) (raw)

Papers by Orgeta Gjermëni

Science & Technology Asia, 2024

The annual emissions of CO2 from land-use change in Albania are the main focus of this research. ... more The annual emissions of CO2 from land-use change in Albania are the main focus of this research. The aim is to analyze the presence of non-linearity and stationarity. A mixed-methods strategy is used, which combines descriptive, inferential, and exploratory data analysis in time series data. A data sample was obtained from the Our World in Data website, spanning from 1850 through2022.After the Isolation Forest technique was employed to identify outliers in the time series, the Long-Short-Term Memory modelwas used to impute them. Exploratory data analysis was applied to the original and imputed time series to ensure that the basic characteristics of the initial data distribution were preserved. Non-linearity and stationarity were checked in the imputed time series before and after applying the first differences. Non-linearity was assessed using the BDS test and the Teräsvirta Neural Networktest. In the presence of non-linearity, stationarity was analyzed using the KPSS test, the Zivot-Andrews Unit Root test, and the Breitung test. The first differencing application transformed the non-stationary series into a stationary one, but it was insufficientto eliminate non-linearity. This highlightsthe complex nature of CO2 emissions dataand the need for sophisticated modeling techniques.

Business perspectives and research, Aug 6, 2019

This study aims to explore tourist's satisfaction on the accommodation provided during their stay... more This study aims to explore tourist's satisfaction on the accommodation provided during their stay in Vlore (Albania) touristic structures, and if there are possible associations between different characteristics related to this service and tourists. Lack of studies on analyzing customer satisfaction in the industry of accommodation, especially for Vlore, have prompted us to undertake this study. The study results are important for local government, the accommodation industry, and is a source of information for whom is interested to improve their accommodation services, or to invest in accommodation industry located in Vlore, Albania. "Netnography" is used to collect data for our research purpose from the reviews in TripAdvisor website. Using descriptive and inferential statistics, this study concludes that 64.9 percent of the ratings are "very good" or "excellent," regardless of the accommodation structure chosen. Accommodation structures should have a clear defined idea of what kind of tourist they want to attract in a certain period of the year, in order to offer the quality tourists expect. Furthermore, understanding of tourist satisfaction evaluation is important in implementing successful marketing campaigns.

A collection of data is gathered from surveys held in a Spring Course of the Economic Faculty in ... more A collection of data is gathered from surveys held in a Spring Course of the Economic Faculty in the University "Ismail Qemali" of Vlora, Albania. The data set for each student contains the names of the other students through which he/she have a "social relationship". This relationship includes frequent communications, discussions on exercise solutions, and sitting usually close to each other in the class. We have constructed. At the end of the course, a final network based on this type of relationship. We are particularly interested on the clustering coefficient of this network and assessing it's "significance", in the sense of being somehow unusual or unexpected. Simulated random graph models, using R platform, are used to test the "significance" of the observed clustering coefficient.

European Scientific Journal, ESJ, 2015

The aim of this paper is to analyze a collection of data gathered from surveys held every three w... more The aim of this paper is to analyze a collection of data gathered from surveys held every three weeks in a Spring Course of the Economic Faculty in the University “Ismail Qemali”of Vlora, Albania. The data set for each student also contains the names of other students through which he/she have a “social relationship”. This social relationship includes frequent communications, discussions on exercise solutions, and sitting usually close to each other in the class. We have constructed four social simple graphs and have analyzed them focusing only on degrees. In addition, we fit discrete power law degree distribution on the tail and their evolution through time. In analyzing the data, we employed the R platform.

2015 UBT International Conference, 2015

Studies on customer’s experience are important to better understand what is offered and to define... more Studies on customer’s experience are important to better understand what is offered and to define what should be improved. The purpose of this study is to measure and observe customer’s satisfaction from the quality of services received from restaurants located in Vlore, Albania. Data is gathered through an online survey which was filled 700 times. Descriptive analysis, Cronbach’s alpha, chi-square test, Cramer’s measure of association, Spearman’s rho correlation coefficient, and generalized linear model are used throughout the analysis. Findings showed that the overall level of customer’s satisfaction was neutral with 37:6 5% followed by satisfied ones with 27:9 5%. There was statistical evidence of a frail relationship at the 1% level of significance between the overall level of satisfaction and gender, employment, monthly income, bill accuracy, fairness of the prices, speed in service, the patience to bring the bill, clear communication, and politeness of the host staff. Further, there was evidence of a negative relationship at the 5% level between the overall level of satisfaction and employment, monthly income and fairness of the price. 66:18% of the variation of the overall level of satisfaction was explained by age, gender, employment, monthly income, patience to bring the bill, bill accuracy, and variety in menu, warm and fresh served foods. The best model predicts 62:25% of the overall satisfaction. These results help restaurant businesses, and whoever wants to invest in this sector, to better understand customer’s satisfaction about service quality and to pinpoint aspects that can be improved.

Data, 2017

This article aims to provide new results about the intraday degree sequence distribution consider... more This article aims to provide new results about the intraday degree sequence distribution considering phone call network graph evolution in time. More specifically, it tackles the following problem. Given a large amount of landline phone call data records, what is the best way to summarize the distinct number of calling partners per client per day? In order to answer this question, a series of undirected phone call network graphs is constructed based on data from a local telecommunication source in Albania. All network graphs of the series are simplified. Further, a longitudinal temporal study is made on this network graphs series related to the degree distributions. Power law and log-normal distribution fittings on the degree sequence are compared on each of the network graphs of the series. The maximum likelihood method is used to estimate the parameters of the distributions, and a Kolmogorov–Smirnov test associated with a p-value is used to define the plausible models. A direct di...

Business Perspectives and Research, 2019

This study aims to explore tourist’s satisfaction on the accommodation provided during their stay... more This study aims to explore tourist’s satisfaction on the accommodation provided during their stay in Vlore (Albania) touristic structures, and if there are possible associations between different characteristics related to this service and tourists. Lack of studies on analyzing customer satisfaction in the industry of accommodation, especially for Vlore, have prompted us to undertake this study. The study results are important for local government, the accommodation industry, and is a source of information for whom is interested to improve their accommodation services, or to invest in accommodation industry located in Vlore, Albania. “Netnography” is used to collect data for our research purpose from the reviews in TripAdvisor website. Using descriptive and inferential statistics, this study concludes that 64.9 percent of the ratings are “very good” or “excellent,” regardless of the accommodation structure chosen. Accommodation structures should have a clear defined idea of what kin...

2016 UBT International Conference, 2016

Nowadays, systematic collection of data has necessitated a detailed statistical analysis as a nec... more Nowadays, systematic collection of data has necessitated a detailed statistical analysis as a necessary tool to make a mathematical characterization of them with the purpose of gathering information about the present or the future. Our aim in this paper is to analyze a landline phone call network graph from the perspective of descriptive analysis. We explore the characteristics and structural properties of the network graph constructed using an anonymous collection of data gathered from a Call Data Records of a telecommunication operator center located in south of Albania. The R statistical computing platform is used for network graph analysis.

International Journal of Applied Physics and Mathematics, 2017

Is a temporal landline phone call network graph series led by the presence of small world phenome... more Is a temporal landline phone call network graph series led by the presence of small world phenomenon? Are order and average vertex degree of the network graphs associated to small-worldness? How are related size and order of the network graphs in this temporal series? A continuously graded notion of small-world-ness is used to study the presence of small world phenomenon. Spearman's and Kendall's correlation coefficients are used to perform a non-parametric correlation analysis between small-world-ness and order/average vertex degree. Linear regression on log-transformed quantities is used to analyse the relationship between size and order. It is achieved by the study that, the presence of smallworld-ness is confirmed in each time step of the series, and there is no significant association between small-world-ness and graph order/average vertex degree. A significant positive power relationship between size and order is found.

Conference Presentations by Orgeta Gjermëni

Innovative Computing and Communications. ICICC 2024. Lecture Notes in Networks and Systems, vol 1038. Springer, Singapore., 2024

This research analyzes landline telecommunication patterns by examining call records from a south... more This research analyzes landline telecommunication patterns by examining call records from a southern Albanian operator across two non-consecutive months. Through cross-sectional analysis, rigorous data filtration, and aggregation, it utilizes statistical techniques such as descriptive statistics, normality tests (Shapiro-Wilk, Anderson-Darling), and the Mann-Whitney U test, along with Pearson’s correlation and visual tools (scatter, time-series plots, heatmaps), to show daily and hourly call trends. The main conclusions present distinct call duration and start time patterns. There is considerable variability, and a significant positive linear relationship between day-to-day changes in daily call volume and daily call duration in both months. Periods of heightened activity were identified during the mornings, late afternoon hours, and weekends. These underscore the complex nature of telecommunications interactions. The research findings improve understanding and network optimization strategies and also highlight the necessity for dynamic, data-centric approaches. The adoption of advanced analytical methods, including artificial intelligence, is supported to augment operational efficiency, shaping the telecommunications sector’s advancement toward a more adaptive, knowledge-based future.

4th International Conference on Social Science Studies (IConSoS), 2024

This study explored the factors influencing academic staff's readiness to use artificial intellig... more This study explored the factors influencing academic staff's readiness to use artificial intelligence (AI) tools and participate in AI-related professional development, utilizing a quantitative approach. Data from 95 academic staff members of the University of Vlora "Ismail Qemali" were gathered via an online survey. The analysis, conducted using univariate ordinal logistic regression, pinpointed key predictors of educational AI tools adoption likelihood and interest in attending AI professional development opportunities. Rigorous evaluation of model fit, influence diagnostics, and cross-validation was conducted to ensure the findings' reliability and accuracy. Results highlight the critical role of interest in AI educational tools development, technological proficiency, and past use of AI educational tools in determining the likelihood of adopting educational AI tools, underscoring the pivotal importance of fostering a genuine interest in AI. Furthermore, the research identifies gender as a significant factor influencing interest in attending AI professional development opportunities, while negative perceptions of AI's role in education tend to reduce such interest. These findings stress the need for targeted efforts to enhance educators' readiness for AI, mitigate gender disparities, and correct misconceptions about AI. By revealing the complex factors affecting educators' willingness to adopt AI technologies, this study advocates for a holistic strategy encompassing a broader range of influences. It provides actionable insights for educational policymakers, curriculum developers, and AI tool creators to create an environment conducive to AI adoption in higher education. Although limited by its use of convenience sampling and focus on a single institution, this research offers essential insights into the dynamics of AI adoption in education. It lays a foundation for strategies that encourage innovation, inclusivity, and a forward-thinking approach to integrating AI into future teaching and learning.

International Conference on New Research and Advances on Computer Science and Information Technology, 2023

This study delves into the perceptions of the Albanian academic community regarding the integrati... more This study delves into the perceptions of the Albanian academic community regarding the integration and effectiveness of artificial intelligence (AI) in education. Employing a mixedmethods approach, the research focused on the academic staff at the University of Vlora, "Ismail Qemali." The analysis, based on questionnaire responses from 95 participants, utilized chi-square and Fisher's exact tests to examine the relationship between AI perceptions and various demographic factors. Contrary to expectations, results indicated a universal consensus on AI's role in education, irrespective of educational background or technological proficiency. Significant associations were observed between perceptions of AI and its impact on personalized learning and intelligent tutoring systems. However, this trend did not extend to AI's utility in virtual or augmented reality and its efficiency in learning experiences. The study also highlighted the influence of current AI perceptions on future usage intentions, particularly regarding its utility for special needs. Gender and technological proficiency emerged as influential factors in shaping AI perceptions in specific educational aspects. This research contributes to the understanding of AI's multifaceted role in educational contexts, emphasizing the need for a comprehensive approach to integrating AI into educational practices.