Reviewerly/exHarmony huggingface dataset:
Sistem Pendukung Keputusan Menggunakan WASPAS dalam Menentukan Rumah Kost yang Strategis

A boarding house is a place to stay temporarily when you have to be away from your house or the area where you live. In Indonesia, there are many students who, after graduating from high school or the equivalent, continue their studies outside the city, some even outside the province or island. The choice to continue their studies outside the area is based on several reasons, including because the majors desired and in accordance with their interests and talents are not available in their area of origin. Therefore, leaving the area or city of birth and settling in the area or city where the desired university is located must be an option. The development of a campus or college has an impact on the increasing demand for property by consumers, especially the need for boarding houses. Based on this background, it is necessary to determine strategic boarding houses using the Waspas method. The results of the calculations in determining strategic boarding houses are: 1. Melati boarding house (Q3) 8,700, 2. Anyelir boarding house (Q1) 6,342, 3. Orchid boarding house (Q4) 5,688, 4. Mawar boarding house (Q2) 5,502 . 5. Akasia boarding house (Q5) 5,125.
3D ANIMATION DESIGN "SCIENCE, LANTERNS TO HEAVEN" USING THE POSE-TO-POSE METHOD

In today's era, technology and communication have experienced very rapid development. Islamic values ​​raised through the media are an effort in people's lives today. Including through the media of 3D animated films that rely on entertaining audio-visuals and messages conveyed through animated films can also be easily captured by the audience. In addition, the selection of animated films is based on the number of animated films circulating on social media such as YouTube and other electronic media, and this film can affect the attention of many people. Animated film designed by the author with the theme of the importance of studying can lead to Allah SWT's heaven. Making this animated film will use Blender software version 2.80. The method used is "Pose-to-Pose" by determining each key pose movement to produce a good movement. Using this method makes the work more effective or faster; if there is an error in the pose, it can be easily corrected. The design of the 3D animated film entitled "Science, Lantern Towards Heaven" is expected to be useful for the audience and take the moral message in it, which is to increase enthusiasm for learning or studying
Transformasi dan Pengolahan Data Pelaporan Bank Umum Menggunakan Teknik Data Virtualisasi

The development of data technology and its utilization is very fast, resulting in humans ’ competi tion for innovat ion in the data that can be more easily processed in such a way as to meet user ’s expectations. Data integration is an important aspect to make data and information are connected one and an other. Weaknesses that often arise from the traditional -way of ETL (Extract-Transform-Load) are the complexity of connections from multiple sources, as well as the dependence on temporary data storage to allow data to flow from the source Database to the target Database. The application of data virtualization can provide the right solution to integrate data more effectively and more efficient ly than the use of ETL methods in general. The purpose of this research is that Data Virtualization can provide features and renewable technology, making it easier for users to generate daily or monthly bank reports faster in accordance with the expectations and provisions in the Bank Indonesia (BI) regulations. Therefore, in the process of this research, R&amp;D (Research and Development) is still considered the most appropriate method . T he results of this research are solutions or commercial bank ’ s data processing systems that can issue the result information that will be daily / monthly report ed by the users to Bank Indonesia.
Analisis Learning Obstacles pada Materi Pecahan Siswa Kelas IV Sekolah Dasar

This study aims to analyze the existence of learning obstacles that occur in students, especially in class IV fraction materials and efforts to overcome these learning obstacles. This research uses descriptive qualitative research method. The sample in this study was 17 grade IV students at SDN Kopo 04 for the academic year 2021/2022 with purposive sampling using a sampling technique. The source of data in this study is the primary data source and for data collection the researchers used test and interview instruments. Data analysis was carried out descriptively by reducing data, presenting data, and drawing conclusions. Based on the results of research and discussion, it was found that a learning obstacle in the ontogenic obstacle category was that students did not understand how to operate addition and subtraction on fractions. Students also experience epistemological obstacles if they are faced with a different problem context from the one exemplified by the teacher in the book and misunderstand the meaning of the question. In addition, there were didactical obstacles where students were not able to place the numerator and denominator, students also did not know the definition of fractions and the concept of fractions as part of a whole and fractions as part of a group, because it was caused by inappropriate teacher teaching. It was also found that efforts to overcome learning obstacles were found such as holding remedials, enrichment, using the RME (Realistic Mathematics Education) learning model, often doing practice questions, and being able to use other learning media besides books. Efforts to overcome the learning obstacles found are expected to be realized to minimize the learning barriers experienced by students.
Professional development of teachers and their pedagogical activity in the digital educational environment

Introduction . The article is devoted to the issues of teacher training in the context of the importance of information technology in future professional activity – this is one of the priority tasks of improving modern education. Purpose setting . The author of the article aims to identify the current state of digital competence of a teacher based on the collection and analysis of pedagogical information on the use of digital technologies in the educational process. Methodology and methods of the study . The methodological basis of the study was the formation of digital competence, which is carried out in the process of implementing educational programs of higher education, as well as professional development and retraining programs. Results . The analysis of information collection is carried out, which shows that the level of digital competence of teachers, the degree of readiness and desire of teachers to use digital tools and services in the educational process suggest the need to develop issues of organizing effective online communication of participants in the educational process, productive feedback with students through digital technologies; forming a critical assessment of students’ behavior and correcting their actions when working in a digital educational environment, monitoring students’ independence in performing educational tasks; applying the results of the analysis of students’ digital footprint to eliminate and correct educational shortcomings of individual students; using the potential of digital tools and services in organizing group work and project activities of students, communication and student involvement. Based on the analysis of the list of relevant digital competencies in the field of education, the author suggests the introduction of an additional professional development program. Conclusions . The practical significance of the work lies in the fact that the results obtained can be used to improve the methods of online learning while improving the qualifications of teachers.
Implementation of Linear Regression to Predict New Student Admissions as a First Step to Determine Campus Marketing Strategy

New student Admission is a routine activity carried out by all educational institutions in Indonesia every year. One of the educational institutions in Indonesia is a private university. Predictions of the development of new student admissions so far have only been made based on speculation using data from previous years. Linear regression is one method that can be used to predict good results. Therefore, this study uses a linear regression method. The test results in this study indicate that the linear regression method has a low error value measured by the error rate using the Mean Absolute Percentage Error (MAPE), which is an average of 2.76%. This proves that using the linear regression method can predict new student admissions well so that it can assist universities in developing various strategies to maintain their existence, especially marketing strategies.
Analysis of the impact of man-made harmful waste on the soil by X-ray fluorescence method

As the technogenic load increases from year to year, the soil loses its ability to provide plants with various nutrients, air, water, heat, biological and physico-chemical environment. The reason is an increase in heavy metal compounds in the soil, which leads to its degradation. The presence of heavy metals in the ecosystem, such as Pb, Cr, As, is toxic to humans and biosystems even at low concentrations. Anthropogenic pollution of the environment by heavy metals (industry, mining and smelting of ores, transport, agriculture) increases over time. Currently, soil contamination with heavy metals and its impact on the biosphere are increasingly being studied. This is especially observed in large industrially urbanized regions, where there is a large accumulation of hazardous waste that does not decompose in nature and is stored for a long time. To identify anthropogenic pollution of the environment with heavy metals, samples were taken from various soil horizons of the city of Zhezkazgan and adjacent regions. The chemical compositions of the taken samples were determined by X-ray fluorescence. Analytical work was carried out in the laboratory of the Department of Landscape Geochemistry and Soil Geography of Lomonosov Moscow State University. We analyzed the quantitative content of chemical elements in the soils of Zhezkazgan and adjacent zones I (As, Zn, Cd, Pb, Hg, Se), II (Co, Ni, Mo, Cu, Cr), III (Ba, V, W, Mn, Sr) hazard levels.
UNISWAP - A CASE STUDY OF DECENTRALIZED EXCHANGES ON THE BLOCKCHAIN

The paper takes a close look at an emerging industry - decentralized finance on the blockchain. The goal of this paper is to compare centralized order book (CLOB)-based exchanges to automated market maker (AMM)-based decentralized exchanges (DEX) and analyze the challenges that AMM-based DEXes are facing today using Uniswap as an example.
Data Exploration Using Tableau and Principal Component Analysis

This study aims to determine the dominant chemical elements that may improve the monitoring of the productivity and efficiency of heavy engines in 2015-2021 in the company. The method used is usually Scheduled Oil Sampling. This article proposes a new approach. The research problems are analyzing the recorded chemical elements that are produced by heavy engines and visualizing them through the Tableau program. The basic design of the study is learning the given data after visualization and using the Principal Component Analysis. This method is to obtain chemical elements that affect engine wear during each engine's use in the 2015-2021 period. Because there are three categories in each element in the oil sample, namely wear metals, contaminants, and oil additives, a technique is needed to obtain these elements using Principal Component Analysis. Therefore, Oil Sampling Analysis through data exploration using Tableau resulted in a new approach to data analysis of elements recorded by heavy vehicles. The main findings as a result of the analysis are given by the visualization of Tableau, in which there are five machines analyzed to obtain the main components that cause engine wear. From the visualization results, it is shown that there is one engine coded MSD 012 that experienced wear and tear in 2018 and 2019. This shows where two main components, Ca and Mg, dominate engine wear. These results have been confirmed with the related companies. The company then carried out further studies on the machine to get special treatment because of these results.
Aircraft Flight Movement Anomaly Detection using Automatic Dependent Surveillance-Broadcast

Automatic Dependent Surveillance-Broadcast (ADS-B) is an aircraft backup radar device that transmits aircraft sensor information via radio frequency. This data can be used to detect aircraft changes that occur significantly or abnormally (anomaly). Anomaly detection in this study aims to reduce and prevent flight accidents by analyzing abnormal data on aircraft flights using the Deep Learning (DL) model. Bidirectional LSTM (Bi-LSTM) and Bidirectional GRU (Bi-GRU) models are proposed as DL models which are implemented on ADS-B data using data mining methods. The data is generated from the ADS-B device that records the plane crash incident and is stored on the Flightradar24 community server. Data containing sensor changes from anomalous aircraft movements are studied for predictability on other flight data. The class breakdown is divided into two, anomaly and normal, based on information on the time span of anomaly occurrences in the accident investigation report of each aircraft using the sliding window technique in the data mining methodology. In evaluation, the confusion matrix measurement method is used to predict predictive analysis of the tested data. The results of the model evaluation performance show that the Bi-LSTM proposed in this study has the best accuracy of 99.44% and the f1-score of 99.51% is slightly superior to the Bi-GRU model. The model in this study can be applied in the ADS-B device to detect aircraft movement anomalies and as material for reviewing technicians in periodic maintenance and measuring the accuracy of the ADS-B device used as a backup radar.
Solving Hungarian natural language processing tasks with multilingual generative models

Generative ability is a crucial need for artificial intelligence applications, such as chatbots, virtual assistants, machine translation systems etc.In recent years, the transformer-based neural architectures gave a huge boost to generate human-like English texts.In our research we did experiments to create pre-trained generative transformer models for Hungarian language and fine-tune them for multiple types of natural language processing tasks.In our focus, multilingual models were trained.We have pre-trained a multilingual BART, then fine-tuned it to various NLP tasks, such as text classification, abstractive summarization.In our experiments, we focused on transfer learning techniques to increase the performance.Furthermore, a M2M100 multilingual model was fine-tuned for a 12-lingual Hungarian-Centric machine translation.Last but not least, a Marian NMT based machine translation system was also built from scratch for the 12-lingual Hungarian-Centric machine translation task.In our results, using the cross-lingual transfer method we could achieve higher performance in all of our tasks.In our machine translation experiment, using our fine-tuned M2M100 model we could outperform the Google Translate, Microsoft Translator and eTranslation.
A Critical Pragmatic Approach to Aggression in Moriatry's Big Little Lies

People are supposed to use language harmoniously and compatibly. However, aggression may characterize much of human communication. Aggression has long been recognized as a negative anti-social issue that prevails in most personal interactions. If it abounds in familial communications, it is more dangerous due to its harmful effects on individuals, and consequently on societies. Aggression refers to all the instances in which we try to get our way without any consideration for others. Moriarty’s novel (2014), Big Little Lies, is argued to represent the patterns of aggressive communications. This study aims to find out the motivations behind aggressive language in familial communication in this best-seller novel. It aims to identify the pragmatic strategies that are utilized to convey aggression in the data under scrutiny. As aggression is a critical social issue, it is studied in terms of the critical pragmatic paradigm. It is hypothesized that aggression is motivated by psychological factors and negative speech acts as well as impoliteness characterize all instances of aggressive communications. The analysis of data verified the two set hypotheses.
The k-nearest Neighbor Classification of Histogram- and Trapezoid-Valued Data

‎A histogram-valued observation is a specific type of symbolic objects that represents its value by a list of bins (intervals) along with their corresponding relative frequencies or probabilities‎.&#x0D; ‎In the literature‎, ‎the raw data in bins of all histogram-valued data have been assumed to be uniformly distributed‎. ‎A new representation of such observations is proposed in this paper by assuming that the raw data in each bin are linearly distributed‎, ‎which are called trapezoid-valued data‎.&#x0D; ‎Moreover‎, ‎new definitions of union and intersection between trapezoid-valued observations are made‎.&#x0D; This study proposes the k-nearest neighbor technique for classifying histogram-valued data using various dissimilarity measures‎.&#x0D; ‎Further‎, ‎the limiting behavior of the computational complexities based on the performed dissimilarity measures are compared‎.&#x0D; ‎Some simulations are done to study the performance of the proposed procedures‎. ‎Also‎, ‎the results are applied to three various real data sets‎.&#x0D; ‎Eventually‎, ‎some conclusions are stated‎.
Peningkatan Literasi Keuangan melalui Perencanaan Dana Pendidikan Anak

This activity aims to provide knowledge, understanding, and skills to the community through training in planning for children's education funds as an effort to increase financial literacy. The method used is by training and practice. Evaluation of the training, among others, by looking at: (1) Participants' understanding of the material provided based on the results of the participants' pre-test and post-test evaluations; (2) the enthusiasm/response of participants in participating in the activities; (3) the ability of participants in practice; (4) Clarity of the speaker in delivering the material. The long-term target to be achieved in this activity is to make the community through PKK cadres able to manage family finances so that they can plan and prepare children's education funds in the future. Overall, the average score of participants before the socialization activities was carried out was 24.67 and increased to 71.67 after the training activities were carried out. An average increase of 47 points. The highest pre test score is 30 and the lowest score is 10, while for the post test session the highest score is 80 and the lowest score is 50. Based on these results, it can be concluded that this service activity is able to have a positive cognitive impact on knowledge about how to prepare children's education funds. . Meanwhile, in terms of affective awareness, willingness, and ability of participants in implementing family financial management so that they can plan and prepare funds for children's education in the future.
ALGORITHMS FOR TRACKING OBJECTS ON A VIDEO STREAM

Algorithms for monitoring moving objects are of great interest in the field of computer vision. The paper presents the results of the development and research of image analysis algorithms for monitoring vehicles in a video stream. Currently, the monitoring of vehicles, especially in production areas, is performed manually by operators. Developing practical applications of video analytics will reduce operator workload, increase speed and accuracy of decision making, and automate the process of collecting and generating reporting statistics on plant transportation. Research was conducted and a video analysis system was developed that includes detection algorithms, classifications by vehicle type, color, and model, and vehicle tracking in the video stream. It should be noted that the architecture of existing solutions, as a rule, is monolithic and does not allow to refine and embed new unique modules to solve emerging problems. In modern conditions, in order to cover new requirements in the field of object recognition and detection in large vehicle flows, it is necessary to develop and implement new solutions. The results of the work of the algorithms on real images of existing datasets and the developed own dataset are presented. In this case, the objects are under different lighting conditions, in different angles, are rebuilt in the stream, there is an overlap of objects. The developed system has a microservice architecture, which allows to adapt the solutions to specific tasks.
Question Entailment on Developing Indonesian Covid-19 Question Answering System

Despite the severe impact of COVID-19 on humans has already decreased, people still need to be aware of the recent disease information. A continually updated Frequently Asked Questions (FAQ) system could help the public get valid and relevant information. To maintain a FAQ system manually needs much effort, hence an approach to develop the system automatically is needed. Question Answering System (QAS) is a system that can accept input in question sentences and produces an answer quickly, concisely, and relevantly, and could be used to provide COVID-19 information to the public. One method on developing a QAS is Recognizing Question Entailment (RQE). RQE is a form of relationship based on a cause-and-effect relationship between two pieces of text called text (T) and hypothesis (H). We present a study on developing Covid-19 QAS in Bahasa Indonesia using RQE. The datasets are collected from reputable sources and consist of 725 pairs of questions and answers. The experimental results show that the best performance results were obtained using the Logistic Regression model in training set 1, which contains 54.2% of positive question pairs and 45.8% of negative question pairs with an f-measure value of 83.65%. These results indicate that the RQE method can identify the entailment between new questions and questions in the dataset well.
Analisis Penerapan Metode Ensembled Learning Decision Tree Pada Klasifikasi Virus Hepatitis C

Hepatitis C virus is a deadly virus that attacks the liver. This virus can cause chronic infections, even 80% of sufferers have experienced an illness. To minimize the risk of exposure to disease caused by the hepatitis C virus, consultation with a doctor or using an intelligent detection system can be conducted. Of course, if used a smart strategy, our need data that already contains parameters related to hepatitis C. This study uses a public dataset that the public can access. So, the purpose of this study is to classify patients with hepatitis C virus using a tree-based algorithm. The results obtained by applying the proposed algorithm are 93% accuracy, 92% precision, and 91% recall. This study also performs comparisons with other methods, namely naive bayes. The results show that the tree-based way is superior.