Reviewerly/exHarmony huggingface dataset:
Analysis of Service Quality and Its Influence on Residents' Satisfaction

This study assessed residents' satisfaction with neighbourhood quality attributes in Port Harcourt municipality, Nigeria.The study ascertained residents' satisfaction with neighbourhood attributes, sanitation attributes and residential quality of life.Neighbourhood attributes were studied in situ without experimental manipulation and at one period in time, i.e. the study adopted a passive-observational research design.The study utilized both secondary and primary data sources.Primary data was collected using face-to-face administration of a largely pre-coded household questionnaire, to a probability sample of 726 respondents, drawn from the 2 neighbourhoods.Data analysis was based on responses from 725 questionnaires retrieved and the univariate analytical method was adopted.The study found that high percent of residents were dissatisfied with neighbourhood quality attributes such as electricity supply, water supply and waste collection and disposal and safety of lives and property.The study found that neighbourhood satisfaction index of the city was moderate.The study further indicated that27.2%of the residents were unhappy with their residential quality and 8.8% of the residents were delighted with their residential quality.The study concluded that in the provision of public infrastructure and services, the perceptions and preferences of the beneficiaries/target population must be seriously taken into account to achieve user satisfaction.The study recommended that government should take advantage of funds available in the National Urban Development Bank, assistance from international development agencies and through private-public-partnership (PPP) arrangement for adequate provision and maintenance of infrastructure and amenities and educate residents on good environmental management.
GEOPHYSICS AND THE BIBLE

There is a misconception that there is disagreement between science and Scriptures. Science is based on facts, not just opinions or preferences. To understand science, we need to consider how science started. It began with people who knew God and who believed that God is a God of order and designs. They believed that the universe He designed would reflect that order and that by studying nature, they could learn more about God and His attributes. Science only deals with nature and not the supernatural or spiritual. When conducting research, scientist use the scientific method to gather measurable empirical evidence in experiments related to a hypothesis, the results of which aim to support or contradict the theory. The basic focus of science is knowledge. It is critical to realize that scientists have not learned everything and that as we gain new knowledge, they must change what they once believed to be true. One example is the understanding of the interior of the Earth. Using earthquake data, scientists originally thought that the Earth had a crust, a mantle, and a solid core. Using earthquake data, they realized that there was also a liquid inner core. More data revealed that the mantle may have different layers. Even with all their tools, scientists have not been able to determine the exact nature of the core, the mantle, or even the crust. Although, we do not yet understand the structure of the core and mantle, scientists have realized that they are essential for life to exist on earth. As scientists have learned more about the mass of the universe and the parameters that control the natural laws of the universe, they have realized that the universe and this planet have been specifically designed to support life here. This has brought many scientists to realize that the universe was specially designed by a Great Engineer.
Heuristic Teaching Methods Of Professional Junior Bachelors In Software Engineering

The article theoretically substantiates the methods of heuristic training of professional bachelors in software engineering. The historical aspect of the origin of heuristics is realized. Scientific and methodological literature on this issue is analyzed. The main definitions of the heuristic learning theory are revealed. The meaning of the concepts: “heuristics”, “heuristic learning” is specified. The main methods and techniques of professional junior bachelors’ readiness formation of in software engineering for heuristic activity in the process of professional training are indicated. The application of heuristic methods of professional junior bachelors in software engineering is argued. The solution of many problems of different CAS and systems of automation of mathematical calculations is defined. The specificity of professional disciplines in the IT field is directly related to abstraction, algorithmic modeling and database structures. The study of educational and methodological literature on the topic of graduation work and the development of existing experience of teachers on this topic and its use in their activities, gave the opportunity to determine the main directions of further work and use the results of this study. preparation of future bachelors of software engineering. The expected pedagogical effect from the use of еру heuristic activities is stated: increasing the motivation of professional junior bachelors in software engineering to heuristic activities; increasing their interest in self-development and self-improvement.
Penerapan Forward Chaining dan Certainty Factor Pada Sistem Pendeteksi Penyakit Hewan Qurban Berbasis Android

Qurbani worship is a worship of the slaughter of livestock carried out on the feast of Eid al-Adha. In Indonesia the dominant livestock used for qurban worship is goats and cows, qurban animals that are allowed to be slaughtered also have conditions ranging from age and most importantly their health. This research is done so that goats and cows that will be slaughtered for qurban worship are free from existing diseases. Some of the problems in the system that will be built is the lack of understanding of the sellers of animals qurban about the diseases suffered by goats and cows from the symptoms experienced by these animals. This study used the method of forward chaining and certaity factor in solving the problems that exist in goat and cow animals, to produce a conclusion in detecting diseases in these animals based on existing symptoms. The process of designing the application of disease detection expert systems in goat and cow animals uses the java programming language and uses a text editor android studio. The authors also tested the comparison of the combination method between forward chaining and certainty factor with the forward chaining and naïve bayes methods that received the highest percentage value results, namely in the forward chaing and certainty factor methods with a value of 9.553%. in scab disease suffered by goat animals and a value of 9.509%in bloating disease suffered by cow animals. Getting the final result on the calculation of detection of goat disease by 91,264% with indicated suffering from scab disease and also in cow animals by 90,432% indicated to suffer from bloating disease, both the final results of the calculation of the type of disease suffered by goats and cows respectively seen from the symptoms that have been inputted by the user.
THE EXPERIENCE OF ACADEMIC MONITORING IN THE SUBJECT OF TEACHING AS A POSSIBILITY OF LEARNING IN UNIVERSITY TEACHING

This work is linked to the field of Didactics and has as its specific theme the academic monitoring, as an experience of initial development of the learning of university teaching.Thus, the objective of this textual production is to reflect on the experiences of monitoring in the discipline of Didactics, of the 2nd series of the Degree in Pedagogy, developed by an academic of the 4th series of the same course, at the State University of Ponta Grossa (UEPG).These activities were developed in 2017 and were guided by the search for articulation between theory and practice, emphasizing the learning of university teaching through the monitoring and intervention of/in the actions developed in the aforementioned Didactics discipline.The methodology is qualitative, interpretive in nature, based on an experience report.To support the analyses, the contributions of the following authors were mobilized: Nóvoa (2022), Cunha (2021), Cunha and Ribeiro (2020), Frison (2016), Frison and Moraes (2010), Dantas (2014), Freire (2014), 2015), among others, in addition to guiding documents such as the Education Guidelines and Bases Law (LDB), Law nº 9394/96.It appears that the exchange of experiences between the mentor teacher and the teacher in training, interspersed with the activities of the Didactics discipline and the contact with other academics, fostered the pedagogical development of university teaching, enriching this process, providing a significant learning opportunity for the monitor in question.
Komparasi Model Klasifikasi Sentimen Issue Vaksin Covid-19 Berbasis Platform Instagram

Information about COVID-19 or regulations regarding it has been massively shared by the Ministry of Health, via kemenkes_ri account. Including the topic of vaccinations. Although health research has been conducted to support the covid-19 vaccine campaign, however there are still people who give negative comments. Sentiment is also found in the kemenkes_ri account. Sentiment analysis is an opinion classification process to determine the responses given are included in the positive, negative or neutral categories. In this study, it is proposed to compare the performance of the SVM and KNN algorithms to classify sentiment in the kemenkes_ri account related to vaccine policy in Indonesia. Sentiment is classified into 3 polarities namely neutral, positive, and negative. The purpose of this comparison is to compare the best classification model on the topic of vaccine issue sentiment analysis, especially the Instagram platform. In this study, the stages started from the comment scrapping technique which resulted in 2,925 records. Preprocessing using NLP technique and weighting using TF-IDF technique. Next, the SMOTE technique was performed to avoid imbalancing class. The ratio of training and testing data is 9:1. The results showed that the best classification is SVM = 98.30%, while the KNN method is 80.03%.
Implementation of eigenface method and support vector machine for face recognition absence information system

The student &lt;span&gt;attendance system is what is needed in the process of recording attendance in learning and the development of student achievement. Currently several modern educational institutions have implemented a student attendance system using QR codes or fingerprints, but many still use the traditional system by calculating the number of students attending class. Based on these problems, the solution that can be given is to implement a student attendance system through face matching in the Android mobile application with Eigenface algorithm and support vector machine (SVM) algorithm. Eigenface using the principal component analysis (PCA) method can be used to reduce the dimensions of facial images so that they produce fewer variables and are easier to handle. The results obtained are then entered into a pattern classifier to determine the identity of the owner of the face. This study used 100 facial data as test data and training data. The system test results show that the use of Eigenface with SVM as a classifier can provide a fairly high level of accuracy. For facial images that were included in the training, 91% of the identification was correct.&lt;/span&gt;
Doc2Vec-based Approach for Extracting Diverse Evaluation Expressions from Online Review Data

This paper proposes a method for extracting diverse expressions from online movie review texts for a given keyword query. When people watch a movie that makes them cry, they generally do not say ``I cried.'' Instead, they use such euphemistic language as ``I needed a handkerchief'' or ``My makeup was running.''To enable information retrieval based on audience reactions such as ``movies that make me cry'' using review texts, various paraphrased expressions must be collected for arbitrary queries. Our proposed method extracts such expressions from review datasets by applying two extensions to Doc2Vec: 1) it changes the granularity of the training sentences to mitigate a lack of context, and 2) it applies query expansion for similarity calculation in advance.We conducted a large-scale crowdsourcing experiment with 1.29 million actual sentences taken from Yahoo! Movies, Japan. The experimental result revealed that changing the training data granularity and adding the query expansion effectively collect more diverse expressions that have a meaning similar to the given query.
Peningkatan Keaktifan, Sikap Percaya Diri, dan Hasil Belajar IPS melalui Model Pembelajaran Tipe STAD

This study aims to know increasin the activeness, self-confidence, and learning outcomes of students in social studies learning through the application of the STAD type learning model. This research was conducted at SD Negeri Winongkidul. The subjects in this study were sixth grade students of SD Winongkidul. This type of research is classroom action research. Data collection techniques in this study used questionnaires and observation sheets. The data analysis technique used descriptive quantitative with percentages. The results showed that 1) Increasing the activeness of students in social studies learning through the application of the STAD model by the pre-cycle at 13 students (54.17%) increased in the first cycle to 17 students (70.84) and the second cycle to 21 students (87.5%). 2) Increased self-confidence of students in social studies learning through the application of the STAD type learning model in the pre-cycle 14 students (58.33%) increased in the first cycle to 19 students (79.17) and in Cycle II to 23 students (95.83%) 3) Improving student learning outcomes in social studies learning through the application of the STAD model in the pre-cycle 12 students (50%), increased in the first cycle to 16 students (66.67%) and in the second cycle increased to 22 students (91.67%).
Robust Regression Methods in Econometric Modeling in Circulating Money Modeling

This study presents a comparative study on robust regression method via M-estimator and Least Trimmed Square (LTS) estimator against Ordinary Least Square (OLS) estimator in modelling economic indicators in Malaysia. The aim is to estimate the parameters of multiple linear regression model in the presence of outliers and to evaluate the estimator performance of OLS, LTS and M estimation. The coefficient of determination known as R-squared values were used as criteria to evaluate the estimator performance. Research findings showed that LTS estimator outperform M estimator and OLS estimator in terms of maximum of R-squared values.
Detecting Phishing Cyber Attack Based on Fuzzy Rules and Differential Evaluation

Cyber-criminal attacks witnessed various phishing attacks that blindly attract users to use their secret personal information. This research highlights this type of attack and proposes the development of a new model to detect phishing websites. Two aspects of improvement were followed. Firstly, a new feature is inferred from a combination of features with higher classification capability than the original features. Secondly, a novel method has been proposed by using differential evaluation (DE) to select the best rules among the fuzzy rule set; the DE is a viable way to optimize the fuzzy rule, improving the classification complexity. The proposed system was evaluated by applying two malicious and legitimate datasets collected from Phishtank and Alexa websites. Results show the combination feature can include a promising method for detecting phishing attacks according to the evaluation metrics in the precision of 0.973, recall of 0.933, F-measure of 0.947, and accuracy of 0.976.
The Economics of Cryptocurrencies – Finance in Digital Era

Global economic markets are encountering apprehensions and susceptibilities because of rise in global pandemic of COVID-19. Investment patterns are becoming restrained because of uncertain global scenarios and reduced GDP world-wide. World economies are moving towards digital era and investors are becoming more open towards newest forms of investments. During these troubled times of pandemic investors are looking forward for some lucrative forms of investments and Cryptocurrencies are the ray of hope for global investors. Since its inception from last decade, many investors, researchers and financial analyst are trying to explore this digital form of investment. Technology has become an integral part of investment these days, and during the times of pandemic cryptocurrencies can be one of the alluring form of investments. The present study is an attempt to explore the changing dynamics of cryptocurrencies with global crisis.
Blended Bilingual Education Model in Chinese-Foreign Cooperatively-Run Programs in Higher Vocational Colleges With Foreign Language Other Than English as the Target Language

Bilingual teaching modules are commonly seen in Chinese-foreign cooperatively-run classes with English as the foreign language. In Chinese-foreign cooperatively-run classes with foreign languages other than English, blended bilingual education model is suggested with different bilingual education models applied in different courses and terms. This model may also face the challenges like comparatively high learning objectives and inefficient learners as well as limited bilingual teaching resources. To ensure its quality, both external and internal quality assurance schemes are suggested.
Lehmer Encoding for Evolutionary Algorithms on Traveling Salesman Problem

The traveling salesman problem is a well-known NP-hard permutation optimization problem. It is often successfully solved by nature-inspired metaheuristics such as differential evolution (DE) and particle swarm optimization (PSO). Both algorithms are originally designed for real-parameter optimization in a continuous space. The crucial problem is an appropriate solution representation - a mapping between continuous search space and discrete permutation space. In this work, we study the popular random key (RK) encoding and its properties. We point out its typical issues (solution redundancy, sorting) and propose a novel permutation representation based on the Lehmer code (LC) encoding and its factorial representation. Both encodings are tested with DE and PSO metaheuristics on popular TSP instances. The results are very promising as the LC often significantly overcomes the performance of the RK.
Peningkatan Hasil Belajar Muatan Pelajaran IPS Peserta Didik melalui Model Pembelajaran STEAM

This study aims to improve the learning outcomes of social studies lesson content using the STEAM learning model by VI grade students at SD Negeri Majir in the 2021/2022 academic year. This type of research is classroom action research. The subjects in this study were VI grade students at SD Negeri Majir, totaling 24 students. The stages in this research include 4 stages, namely planning, implementation, observation, and reflection. Data collection techniques in this study used documentation, questionnaires, observations, and tests. The data analysis technique used descriptive quantitative with percentages. The research results are the use of the STEAM model can improve the learning outcomes of social studies lesson content by VI grade students at SD Negeri Majir in the 2021/2022 academic year. It is indicated by the increasing number of students in the category of minimally high social studies learning content learning outcomes, from 70,83% in the pre-cycle, to 83,33% in the first cycle and 91,67% in the second cycle. The research ends in this cycle, because it has met the writer's expectations.
Surface structure errors on undergraduate students’ writing

Students will make an error in the process of acquiring a foreign language. Errors made by students in the process of learning need to be analyzed carefully so that it can help the learning process. This study aims to analyze the surface structure errors made by undergraduate students. The method used is a qualitative method which took a sample of 30 undergraduate students' writings which were writing assignments for English subject. The data were analyzed by looking at the taxonomy of the surface structure in 4 classifications, namely addition, omission, misformation, and misordering. The results of this study found that the most errors were misformation as much as 53%, followed by omissions as much as 23%, additions as much as 17% and misordering being the least errors found with a total of 7%. Misformation errors that often occurred in this study were in the tenses category where the use of morphemes was not in accordance with the rules of English grammar. The results show common errors made by undergraduate students and are expected to be a benchmark for learning outcomes. In addition, it can also show what indicators of English learning should be improved so that students no longer make repeated errors.
EVALUATION OF CAPTCHAs

CAPTCHAs are known as Captcha which stands for Completely Automated Public Turing test to tell Computer and Human Apart. CAPTCHAs are used to prevent automated scripts from harvesting email addresses from publicly accessible forms on the internet and submitting them to spammers. CAPTCHAs are mostly utilised because computers have a difficult time deciphering the text concealed behind distorted visuals, but humans have an easier time deciphering the information hidden behind the distortions. As a result, the optimal response to a CAPTCHA assignment is considered to be a human return, and the individual is permitted entry to the website in question. The CAPTCHA is a useful tool for determining which clients are human and which are computer programmes.
Digital Learning Media Needs Analysis for English Reading Comprehension Class

Technology has become an unavoidable part of education and must be used. The purpose of this study was to obtain the need for digital learning media for reading comprehension English classes. This research is a qualitative descriptive study that was conducted using a survey method. The participants were students (38 boys and 22 girls) and 2 teachers. Data collection techniques are documents, observations, interviews, and questionnaires. Data analysis consists of three steps, namely data reduction, data presentation, and concluding. Furthermore, the data analysis technique used expert judgment. The results of the study concluded that digital learning media had not been used comprehensively by teachers and students during online teaching and learning activities. From the results of data analysis, the digital learning media needed varies according to the function or role. For online discussion activities, you can use the zoom or google meet. Delivering material and assignments are LMS, google classroom, social media, reading sources are learning websites and electronic textbooks, exercises using online or manual, and communication processes using WA groups.