Reviewerly/exHarmony huggingface dataset:
Metode K-Means Clustering Dalam Merancang Strategi Promosi Penerimaan Mahasiswa Baru Pada STIE Serelo Lahat

New Student Admission at STIE Serelo Lahat is an annual activity carried out by STIE Serelo Lahat. A marketing strategy with several promotions is carried out as an initial activity to get new students. Marketing strategies are always evolving from year to year by analyzing student data from new student registrations to accepted students stated and used as the basis for analyzing targeted and accurate marketing strategies. Cluster formation is one of the techniques used in extracting the trend pattern of a data. K-Means Clustering is able to find and group data that has characteristics (similarities) between one data and other data and different data in different groups will show unstructured data groups becoming structured. This study applies the K-Means Clustering Method in designing a promotion strategy for new student admissions at STIE Serelo Lahat based on new student registration data analyzed by the clustering method using the K-Means algorithm so as to produce K-Means group information into three parts with variable values that different so that information is obtained that most of the choices of students in the Management Study Program originating from the Lahat District in Domination are from Private SMA / MA and from East Kikim District originating from Private Vocational Schools and the most registration is in the Second Wave. Furthermore, designing a marketing promotion strategy for New Student Admissions at STIE Serelo Lahat can be determined by using a minimal K-Means clustering approach. This approach makes it possible to have a great opportunity to increase the number of new students at STIE Serelo Lahat.Â Keyword : K-Means Clustering, Information, Students Admission
Perancangan Sistem Informasi Pendataan Korban Bencana Alam Dan Bencana Sosial Di Dinas Sosial Kota Palembang Berbasis Website

Handling events that occur, by evacuating, meeting needs, protection are things that must be done by the government and local governments and emergency response. The Palembang City Social Service is a government institution that has many fields, one of which is PJS (Social Protection and Security) which has a Head of Social Protection for Natural and Social Disaster Victims (PSKBA / BS). In collecting data on victims of Natural and Social Disasters, the Social Service of Palembang City has used a computer in its data collection, but the data collection is still using MS Excel where the data can be lost at any time. Therefore, this study aims to design a web-based system that helps in collecting data on victims of natural and social disasters that can minimize data loss. In building information system software, the author uses an object-oriented method with a waterfall approach which consists of several stages, namely Requirements Analysis (requirements), System Design (design), System Implementation (implementation), System Testing (testing), and System Maintenance (maintenance). . The design of the Information System for Data Collection of Victims of Natural Disasters and Social Disasters at the Social Service of Palembang City is a system design process that can later be implemented in programming language which aims to make it easier for officers or admins to collect data and also recap reports quickly and accurately. The design of this system is based on the problems that exist at this time where the data collection process is still using Ms Excel which is considered to be still ineffective. The currently designed system is equipped with a menu of disaster data, command posts, victim data, officers, assistance, and a recap menu. Where these menus can support the system to be maximized and in accordance with user needs.Keywords : Information System, Waterfall, WebÂ
Rancang Bangun Sistem Informasi Tracking Sales dengan Integrasi Kartu Radio Frequency Identification

CV. Multi Banyu Satwa is a distributor of livestock medicines and vitamins where the company sells its products to shops that sell animal needs, especially livestock. In marketing its products, this company uses a canvasing sales system where the salesperson sells for several days by directly bringing the product and will return when the goods brought have started to run out. So that there can be a risk of losing the product if the salesperson is not honest, besides that the company owner does not know the presence of the sales directly. In this regard, the purpose of this research is to build a sales canvasser tracking information system with the integration of Radio Frequency Identification (RFID) cards. The method used in building this information system uses waterfall and needs analysis using PIECES, while the system modeling design uses Unified Modeling Language (UML). This information system is web-based and there are 3 access rights, namely owner, admin, salesman. Based on the test results from testing the sales canvasser tracking information system with the integration of this RFID card using the black-box method, it can be seen that this information system can run well. Meanwhile, from the results of user testing using a questionnaire, the results showed a percentage score of 55% Agree and 45% Strongly Agree.Keywords : Information System, Tracking, Sales, RFID
Perbandingan Akurasi Metode Principal Component Analysis (PCA) dan Correlation-Based Feature Selection (CFS) Pada Klasifikasi Perpanjangan Kontrak Karyawan Menggunakan Metode NaÃ¯ve Bayes

PT. Oasis Waters International Palembang conducts regular staff performance reviews, the findings of which are utilized to make recommendations for employee contract extension. The Human Resource Department has assigned a numerical value to 25 qualities (HRD). The process of giving a label or class to a number of examples when the value of each characteristic is known as classification. The NaÃ¯ve Bayes technique is a basic classification approach that makes use of probability estimates. Based on the observations, it was discovered that one of the 25 criteria was deemed the most relevant in determining the recommendation for an employee contract renewal. As a result, in this study, a comparison of the pre-processing Principal Component Analysis (PCA) approach and the Correlation-based Feature Selection (CFS) method on the categorization of employee contract extensions at PT Oasis Waters International Palembang will be performed. According to the data, the CFS approach has a positive influence on classification performance, while PCA does not. This is demonstrated by a 30% increase in accuracy when utilizing the CFS approach. Meanwhile, both strategies have a positive influence on the model's dependability. This is demonstrated by a reduction in Root Mean Square Error (RMSE) when using the CFS approach from 0.6325 to 0.1845, whereas using the PCA method results in 0.5123.Keywords : NaÃ¯ve Bayes, Principal Component Analysis, Correlation-based Feature Selection, Confusion Matrix, Root Mean Square Error
Impact of Financial Development on Inflation in Tanzania: Empirical Evidence from the VECM Approach

This study examines the impact of financial development on inflation in Tanzania using time series data from 1980 to 2020. By employing the VECM analysis method, the study contributes to the existing literature on the relationship between financial development and inflation. The findings reveal that financial development has a significant long-run impact on inflation in Tanzania, resulting in a reduction in inflation in the country. However, in the short run, the impact of financial development on inflation is not statistically significant. Therefore, the study recommends that the government implement appropriate regulatory policies and supervise financial institutions to promote financial sector stability. Further, to promote financial sector stability, greater financial inclusion, higher investment, and economic growth, the government should improve financial market infrastructure, expand the coverage of financial institutions, and increase access to credit. Additionally, fostering the development of more efficient payment systems, particularly electronic payment systems, can mitigate expenses and potential risks associated with cash transactions. Moreover, promoting financial inclusion can reduce the need for cash and enhance the efficacy of monetary policy, serving as a preventive measure against inflationary pressures and unnecessary credit growth.
Can Large Language Models Help Augment English Psycholinguistic Datasets?

Research on language and cognition relies extensively on large, psycholinguistic datasets —sometimes called “norms”. These datasets contain judgments of lexical properties like concreteness and age of acquisition, and can be used to norm experimental stimuli, discover empirical relationships in the lexicon, and stress-test computational models. However, collecting human judgments at scale is both time-consuming and expensive. This issue of scale is made more difficult for norms containing multiple semantic dimensions and especially for norms that incorporate linguistic context. In the current work, I explore whether advances in Large Language Models (LLMs) can be leveraged to augment the creation of large, psycholinguistic datasets in English. I use GPT-4 to collect multiple kinds of semantic judgments (e.g., word similarity, contextualized sensorimotor associations, iconicity) for English words and compare these judgments against the human “gold standard”. For each dataset, I find that GPT-4’s judgments are positively correlated with human judgments, in some cases rivaling or even exceeding the average inter-annotator agreement displayed by humans. I then explore whether and how LLM-generated norms differ from human-generated norms systematically. I also perform several “substitution analyses”, which demonstrate that replacing human-generated norms with LLM-generated norms in a statistical model does not change the sign of parameter estimates (though in select cases, there are significant changes to their magnitude). Finally, I conclude by discussing the limitations of this approach and under what conditions LLM-generated norms could be useful to researchers.
Career Development and Employee Performance in Public Institutions in Rwanda: Case of Rwanda Housing Authority

This research looked at career development system through the lenses of personal growth, advancement and challenging responsibilities against Quality of services, Task’s completion, Team work, Dependability and reliability and Creativity of employee performance in Rwanda’s public institutions, with the Rwanda Housing Authority (RHA) case study. It was grounded on the Hertzberg and Vroom Expectancy Theories of career development. The study adopted a mixed design, combining a descriptive quantitative and a phenomenology qualitative design. The target population consisted of 108 respondents from whom 85 were statistically drawn using Yamane 1967 formula. The study found that majority of respondents believe RHA offers significant career growth opportunities and maintains an active career planning policy. The average response score of 4.45 suggests that respondents generally believe that career development efforts at RHA effectively influence employee performance. The regression analysis further quantifies this relationship, demonstrating that career development accounts for 42% of the variation in employee performance, reinforcing the crucial role that such initiatives play. The analysis of variance (ANOVA) corroborates this strong correlation, exhibiting statistical significance that points to career development as a substantial influencer of performance. In terms of specific impact, the coefficient of career development, 0.588, indicates that for every unit increase in career development, there is a near 0.6 unit increase in staff performance. The study recommends it is crucial to significantly invest in and emphasize career development initiatives, considering their key role in enhancing employee performance. These initiatives should include personalized career development plans, mentorship programs, and regular training sessions for all employees. Regular performance reviews and feedback sessions can help identify areas of improvement and direct career development efforts. Furthermore, all employees, regardless of their roles, should have equal access to these career development opportunities, promoting a sense of fairness and building a skilled workforce. It's also important to view career development as a central aspect of strategies aimed at employee retention, given its positive impact on performance and job satisfaction. Lastly, organizations should continually evaluate the effectiveness of career development initiatives, making adjustments as necessary to ensure their impact on performance improvement is maximized. Keywords: Career Development, Employee Performance, Personal Growth, Responsibilities, Quality of Services, Task’s Completion, Team Work, Dependability, Reliability and Creativity
Reflective function impairment and concretism in online self-representation of Anorexia Nervosa sufferers.

Anorexia Nervosa is an eating disorder characterised in part by a compromised reflective function—adults’ ability to envision mental states in themselves and in others. This paper provides evidence that the typographical variant minuscule first-person subject pronoun, hereafter referred to as NS1sg (), is mobilized for its iconic properties by persons suffering from the psychopathology. The results identify the NS1sg as a potential semantic marker for Anorexia Nervosa and are particularly important as concretism is often a barrier to recovery. Objective: To contribute to the understanding of the linguistic repercussions of reflective function loss through the analysis of the non-standard 1sg as a potential marker of anorexia nervosa.Method: Theoretical and empirical. Proposition of a hybridised referential framework composed of a personal and a social triadic function—to better illustrate the representational repercussions of reflective impairment and concretism on self-representation. Linguistic and statistic analysis of a corpus of 27k anonymized tokens taken from a public online Anorexia Nervosa support page.Results: The NS1sg (i) is significantly (p&amp;lt;0.001, at significance level 0.05) more prevalent in discourse from the Anorexia Nervosa corpus than in the control corpus. Lexical analysis shows some promising evidence of intra-utterance code switching as temporal anaphora.
Teaching Social Science Aspects of Information Security

As information security has become increasingly crucial in our daily lives, there is a growing need to teach its social science aspects. This paper explores the challenges and best practices for teaching social science aspects of information security. It begins with the importance of information security and cyberspace and highlights the human aspects of information security. Next, it discusses the role of social science in understanding information security and how social science can help us better design and implement security measures. The paper identifies challenges in teaching social science aspects of information security, such as the interdisciplinary nature of the subject and the need for a standardised curriculum. Finally, the paper outlines best practices for teaching social science aspects of information security, such as using case studies and real-world examples, incorporating interactive and experiential learning, and leveraging existing resources. The conclusion highlights the importance of incorporating social science aspects of information security in education and suggests future research directions.
Assessment of Cyber Security risks: A Smart Terminal Process

In Finland, the connections to global maritime transportation logistics systems are an essential part of the national critical infrastructure. As a part of maritime logistics systems, the port's operations are important elements for global maritime traffic and the transportation supply chain. Digitalization of seaport services makes it possible to increase the efficiency of terminal systems in the logistic processes. At the same time, port logistic processes can notably reduce its CO2 emissions by optimizing port operations. The improvement of port processes relies very much on the development of Information and Communication Technology (ICT) and Industrial Control Systems (ICS) or Operation Technologies (OT) systems. In port environment there are parts that are controlled (ICS/OT) from the cyber environment but directly interact with the physical surroundings. These are called Cyber-Physical Systems (CPS). In this environment, the cyber security aspects of the port logistic need to be addressed. In Finland, the Port SMARTER research program has been on the way since 2021. The aim of the program is to create port services within new technology solutions, and that way improve cargo and people flows while improving the experience for all stakeholders. However, this development increase also complicated system dimensions in the use of ports and makes port operations complex systems of systems environment characterized by a conglomeration of interconnected networks and dependencies. This paper describes a practical approach to risk assessment work regarding the SMARTER research case. It provides a comprehensive cyber security investigation approach to port operations at the system level. In risk assessment work, the paper emphasizes the importation of description of probabilities to defend the system element against estimated probabilities of cyber-attacks at all parts of port processes. The findings of the study are related to the comprehensive cyber security architecture of the SMARTER research goals. The following research interests are related to the issue: "How a comprehensive cyber security investigation can be conducted in smart ports operations?” This paper emphasizes cyber security risks assessment work should be covered from services for operation, information flows in and between systems, as well as electricity supplies to achieve holistic risks assessment in the smart terminal process.
Designing an Email Attack by Analysing the Victim’s Profile. An Alternative Anti-Phishing Training Method

According to Thomson-Reuters the top cyber threat today is phishing in which people are tricked either to click a malicious link or give out personal information. It’s a fact that 96% of these phishing attacks comes from emails, which amount to more than 3.4 billion daily, as reported by Cisco. Austrian aerospace company FACC, Belgian bank Crelan, Acorn financial services and many other companies were recently fell victims of phishing emails losing millions of dollars. Even if experts provide lists of signs that users should seek in an email in order to understand if it is legitimate or scam, the attackers have elevated the quality of the email messages making them believable and very hard to discern them. In order to respond to this elevated threat, unconventional user training is required, focusing on recognizing a phishing email. Knowing how an attacker thinks and prepares the attack vector against a target, we claim that it will make users more suspicious when they receive one. In this regard, an innovative education intervention (consisted of two phases) was designed and developed. In the first phase, 98 participants were asked to visit an artificial social media profile and prepare a phishing email in order to persuade the victim to click a link. Then, the participants were presented with an innovative guided workflow to prepare a spear phishing email which was based on social media intelligence. In the second phase, they were asked to prepare one more email for the same person applying this time the guided workflow. Comparing the two different emails created, we found that the guided workflow led to the creation of more authentic emails which could potentially trick the victim easier. Based on the theory of active learning, we believe that by teaching users how attackers exploit their personal information in order to develop their attack vectors, it will increase their awareness not only for the typical phishing emails but also for more sophisticated spear phishing attacks.
A Cyber Counterintelligence Competence Framework: Developing the Job Roles

In recent years, there have been intensifying cyber risks and volumes of cyber incidents prompting a significant shift in the cyber threat landscape. Both nation-state and non-state actors are increasingly resolute and innovative in their techniques and operations globally. These intensifying cyber risks and incidents suggest that cyber capability is inversely proportional to cyber risks, threats and attacks. Therefore, this confirms an emergent and critical need to adopt and invest in intelligence strategies, predominantly cyber counterintelligence (CCI), which is a multi-disciplinary and proactive measure to mitigate risks and counter cyber threats and cyber-attacks. Concurrent with the adoption of CCI is an appreciation that requisite job roles must be defined and developed. Notwithstanding the traction that CCI is gaining, we found no work on a clear categorisation for the CCI job roles in the academic or industry literature surveyed. Furthermore, from a cybersecurity perspective, it is unclear which job roles constitute the CCI field.&#x0D; This paper stems from and expands on the authors’ prior research on developing a CCI Competence Framework. The proposed CCI Competence Framework consists of four critical elements deemed essential for CCI workforce development. In order of progression, the Framework’s elements are: CCI Dimensions (passive-defensive, active-defensive, passive-offensive, active-offensive), CCI Functional Areas (detection, deterrence, deception, neutralisation), CCI Job Roles (associated with each respective Functional Area), and Tasks and Competences (allocated to each job role). Pivoting on prior research on CCI Dimensions and CCI Functional Areas, this paper advances a proposition on associated Job Roles in a manner that is both intelligible and categorised.&#x0D; To this end, the paper advances a five-step process that evaluates and examines Counterintelligence and Cybersecurity Job Roles and functions to derive a combination of new or existing Job Roles required for the CCI workforce/professionals. Although there are several cybersecurity frameworks for workforce development, establishing the CCI Job Roles is specifically based on the expression of the Job Roles defined in the National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework.