Reviewerly/exHarmony huggingface dataset:
IMPLEMENTASI METODE CERTAINTY FACTOR PADA SISTEM PAKAR DIAGNOSA PENYAKIT AYAM BROILER

AbstractExpert system to diagnose diseases in web-based broiler chickens was built based on the problems of society in general who are still very unfamiliar with the disease and solutions that occur in broiler chickens. Expert system (Expert System) in general is a system that seeks to adopt human knowledge to computers, so that computers can solve problems as is usually done by experts. This expert system uses the Forward Chaining technique with the Certainty Factor method. Data collection methods in the form of literature studies, observations, interviews, literature review and browsing. In the planning of the system described in the form of DAD level 0, then derived DAD level 1. This expert system in diagnosing diseases in web-based broiler chickens supports two users, namely admin and general user. Admin can enter, change and delete symptoms, input news. General users can only consult based on the symptoms experienced by their Broiler chickens and find information about Broiler chicken diseases. The purpose of this thesis is to create a health consultation service via the internet or on-line.
Pengenalan Pola Huruf pada Kata dengan Menggunakan Algoritma Backpropagation dan Hybrid Feature

With the advancement of information technology today, especially in the process of writing words and sentences where a person will be easier in the process of writing using hands and neat but the writing process carried out at this time also cannot be abandoned. Some activities require us to use handwriting manually such as making statement letters or other important documents. In the implementation that will be carried out on the system of letter pattern recognition in words using handwriting will produce a lower level of accuracy compared to the introduction made on systems that is in computers such as Times New Roman, Calibri, and so on. By using Hybrid Features extraction and backpropagation algorithm, it is expected to reduce problems in the process of recognizing one's handwriting pattern. To get a feature pattern, Hybrid Features extraction used from diagonal features, x and y axis gradients and averages are used. The feature will be used is artificial neural networks with the backpropagation algorithm. The test parameters used are the accuracy of the number of written images recognized by the system. Based on models' performance tests, the highest accuracy was 93.86% for uppercase letters with 45 datasets, 80.46% with 30 datasets for lowercase letters and 78.205 with 45 datasets for all letters. The testing of the program made obtained an accuracy value of 72.92% for the image of the new word, 83.33% for the image of the new letter and 82.56% for the image of the letter that had been studied.
Approximation Algorithms for Orthogonal Non-negative Matrix Factorization

In the non-negative matrix factorization (NMF) problem, the input is an $m\times n$ matrix $M$ with non-negative entries and the goal is to factorize it as $M\approx AW$. The $m\times k$ matrix $A$ and the $k\times n$ matrix $W$ are both constrained to have non-negative entries. This is in contrast to singular value decomposition, where the matrices $A$ and $W$ can have negative entries but must satisfy the orthogonality constraint: the columns of $A$ are orthogonal and the rows of $W$ are also orthogonal. The orthogonal non-negative matrix factorization (ONMF) problem imposes both the non-negativity and the orthogonality constraints, and previous work showed that it leads to better performances than NMF on many clustering tasks. We give the first constant-factor approximation algorithm for ONMF when one or both of $A$ and $W$ are subject to the orthogonality constraint. We also show an interesting connection to the correlation clustering problem on bipartite graphs. Our experiments on synthetic and real-world data show that our algorithm achieves similar or smaller errors compared to previous ONMF algorithms while ensuring perfect orthogonality (many previous algorithms do not satisfy the hard orthogonality constraint).
Improving Students’ Reading Comprehension and Writing Ability of Narrative Text through Story Map Strategy

The objective of the research was to describe the process of improving the students’ reading comprehension and writing ability of narrative text through Story Map Strategy at the ninth grade of SMPN 7 Cibeber. The researcher used classroom action research that was conducted in 3 cycles. The subject of the research was 35 students. The result of the research showed a good improvement, it was indicated by the increase of the mean score in every cycle. (1) In the pre-test, the mean score of students’ reading comprehension test was 61. In the 1 st cycle, the score increased by 17% to 71, 4. The 2 nd cycle, the score increased by 31, 3% to 80, 1. (2) In the pre-test, the score of writing test was 63, 8 with only 5 students who passed the mms. In the first cycle, the score. Increased by 6, 1% to 67, 7. In the 2 nd cycle, the score increased by 11, 8% to 71, 3 with. And in the 3 rd cycle, the score increased by 24, 8% to 77, 7. Classically, the students passed the standard minimum score. In conclusion, the students’ reading comprehension and writing ability of narrative text significantly improved trough the story map strategy.
Word Embeddings Based on Spectral Analysis: A Novel Approach

Recently, deep learning algorithms have gained huge attention. However, such algorithms are not the optimal solution for many tasks. Spectral analysis transformation algorithms, such as wavelet-transform and Fourier transform, have been successfully applied on many NLP tasks. The challenging issue of using spectral analysis is how to construct a meaningful signal from a text. In word2vec models, different types of neural networks have been applied to learn vector representations of words, which carry the semantic similarities of each word in a specific dataset. Training the word embeddings is computationally very expensive and constrained by the available resources. However, this paper provides an optimized computational complexity for developing word embeddings using parallel computing as well as utilizing an upper ontology to represent the main components of the word vector. Moreover, this research shows how to represent a term as a vector to facilitate computing the similarity or relatedness among different terms. Therefore, this research considers the spectral analysis, which also includes the spatial information of the words around the current word.
USERS ATTITUDE TOWARDS BENEFITS OF DIGITAL MARKETING: EVIDENCE FROM DHAKA CITY

This study is on Users‟ attitude towards benefits of digital marketing: Evidence from Dhaka city.‟ The ultimate purpose of this study is to describe the benefits of digital marketing on real field. The study uses primary data collected from the subjects (Professionals of digital marketing) by using various methods like; observation, survey and questionnaire. This research mainly adopts with close-ended questionnaire. This study uses Five Point Likart scale to measure the attitude, impact, and competitiveness of digital marketing in Bangladesh. Frequency distribution, chi square test, and nonparametric test are useful to compute the numeric value of attitude on digital marketing of respondents. Digital marketing strongly and positively affects customers‟ attitude because it is cost effective, it saves time, it requires lower investment, it is useful tool to create and build strong brand, and it is helpful to communicate with mass audience. Overall force of digital marketing on business is positive in Bangladesh. The highest numbers of respondents think that digital marketing in Bangladesh is positive. Better parts of the subjects have agreed that the companies should improve the digital marketing system in Bangladesh. Null hypothesis have been rejected.
ANALISIS SISTEM INFORMASI AKUNTANSI PENGGAJIAN DAN PENGUPAHAN SECARA EFEKTIF DAN EFISIEN PADA RUMAH SAKIT UMUM DAERAH TARUTUNG

In this study, honorary employees received salaries, but there were honorary employees who received wages, such asambulance coordinators and ambulance drivers. They get a reward when there are patients who need an ambulance, andthe coordinator also gets a reward for being tasked with coordinating the use of the ambulance car. All matters relating tosalary and wages shall be supported by forms, records or other supporting evidence in accordance with generally applicableregulations, or regulations made and applicable within the company. Researchers have also conducted preliminary researchand obtained general data on how the process of Payroll and Wage Accounting Information System in Tarutung RegionalGeneral Hospital. The procedure begins with the making of the payroll and wages by the administration, then the payroll andwages are sent to the finance department and then the finance department sends the payroll to the bank and the financedepartment sends the salary to the honorary employees, while for the wages will be directly given to the recipient through anintermediary. Then the finance department will issue cash outgoing evidence that will be used as a basic proof of salary andwage payments to hospital employees. Payroll and Wage Accounting Information System in Tarutung Regional GeneralHospital has not run effectively and efficiently, which has not been effective, because sometimes there are still employeeswho do activities about payroll and wages manually, such as in the process of wages, although there are procedures butsometimes the provision of wages is done manually, because when making wage payments manually, employees consider iteasier and easier to realize than following existing procedures , because wages are rare in this hospital.
Object Identification Using Deep Learning

We present a new dataset to advance the state-of-the-art in object recognition by placing the question of object identification. Our primary goal is to identify the object that will be upload into our web application.As by seeing the image or any object it is difficult to identify the image our system will be helping to recognize the object within the database of our image which contains thousands of images of living and nonliving objects. So it can easily identify the object.
Arefyev Readings as a Means for Activating the Scientific Work of Technical University Students

The growing activity and interest of the students of technical universities in Moscow, Russia and abroad in participating in humanitarian conferences and the influence of these conferences on broadening the horizons, creative potential and general professional culture of engineers are demonstrated on the example of a multi-year cycle of humanitarian conferences held at a technical university.
Английская гравюра, книжная иллюстрация, литература в собраниях сибирских коллекций XVIII–XIX вв.

The paper explores the works of English art presented in Siberian collections as there is an objective need to study Russian collectors’ interests towards English culture. The article examines a factor of influence of Decembrists’ scientific and educational activities on the development of cultural life in Siberian region. The author studies a collecting phenomenon and a bibliophile’s personality in Russia. The purpose of this study is to determine a general principle in forming collections, though some Siberian assemblages (G.V. Yudin, the Stroganovs, the Basnins’ collections) have been adequately investigated by experts in museums and libraries. English engravings and book illustrations took a significant place in those collections. Graphics and English literature assemblages as well as book illustrations are also analyzed with a view of identifying peculiarities of ideas about engraving collecting. The research is based on the theoretical ground for the history of engraving techniques and comparison of Siberian collections. The study revealed the unity in preference for collecting English literature works. However, the results of collecting graphic works and book illustrations differ in amount of units, quality, masters, and techniques.
Using Academic Genealogy for Recommending Supervisors

Selecting an academic supervisor is a complicated task.Masters and Ph.D. candidates usually select the most prestigious universities in a given region, investigate the graduate programs in a research area of interest, and analyze the professors' profiles.This choice is a manual task that requires extensive human effort, and usually, the result is not good enough.In this paper we propose a Recommender System that enables one to choose an academic supervisor based on his/her academic genealogy.We used metadata of different theses and dissertations and applied the nearest centroid model to perform the recommendation.The obtained results showed the high precision of the recommendations, which supports the hypothesis that the proposed system is a useful tool for graduate students.This job should include a thorough analysis of each professor's curriculum, including the list of scientific publications and all theses and dissertations advised, which can be available in multiple and distributed research repositories.Ray and Marakas (Ray and Marakas, 2007) assert that students' usual criteria are professors' reputation, knowledge, and matching of interests, among others.However, this choice is often made in an unplanned a
Lithofacies Classification Using Supervised and Semi-Supervised Machine Learning Approach

The machine learning approach can help Geoscientists do their work in well log analysis to developing the oil and gas field. Prediction categorical or numerical response variable using a set of predictor variables supervises and semi-supervises learning is an important goal of the machine learning approach in classifying lithofacies using well log data. Semi-supervised classification offers the possibility of exploring the structure of the data without entirely external knowledge or guidance in the form of target or class information, and semi-supervised is very rarely research in the field of lithofacies classification. Well log data in gamma-ray, resistivity, neutrality, and density logs are collected and selected for data processing and transformation. The use of machine learning algorithms such as Naí¯ve Bayes, SVM, and Decision Tree is to find the log pattern or pattern classifications of lithofacies in supervised and semi-supervised to create a model with conditions requiring the change of data and the corresponding requirements. All supervised machine learning algorithms have the best accuracy because algorithms provide useful predictive in classifications based on the target but not if there are no targets given or semi-supervised. This paper compares some of the famous classification algorithms of machine learning, such as Decision tree, SVM, and Naí¯ve Bayes, on classifying lithofacies with supervised and semi-supervised learning. This research found that the semi-supervised learning of Naí¯ve Bayes has performed well in classified lithofacies. In contrast, in supervised learning, Decision Tree and SVM are superior in accuracy and visualization approach based on expert’s interpretation.
THE EFFECT OF WORD SQUARE MODEL ON STUDENTS’ VOCABULARY MASTERY

This thesis entitled The Effect of Word Square Model on Students’ Vocabulary Mastery in eighth grade students of SMP Swasta Darussalam Martubung. The objective of this research was to find out the effect of word square model on students’ vocabulary mastery. The research u sed experimental research design. The population of this research was eighth grade of SMP Swasta Darussalam Martubung, who consisted of 150 students in eighth classes; each class consists of 30 students. The researcher took purposive sampling technique, namely class VIII-1 as experimental class and class VIII-2 as the control class. Experimental class was the class that received the treatment of Word Square Model and control class was the class that did not receive the treatment or only taught by using Conventional method. The instrument of the research was essay test of 25 questions. The result of the data analysis showed that the mean score s in experimental class in pre-test ( 53,73 ) and post-test (89.07) was higher than the score s in control clas s in pre-test ( 47,07 ) and post-test (59.07). And by using t-test, the result of the testing hypothesis indicated that there was significance (2-tailed) 0.003 lower than the level of significance 0.050. The finding showed that the alternative hypotheses was accepted while null hypotheses was rejected. Therefore, it means that using Word Square Model in teaching vocabulary had significant effect on students’ vocabulary mastery.
Comparison of PV potential models for africa and their potential cost implications.

&amp;lt;p&amp;gt;We currently have more than 7500 planned mini grids, most of them in Africa. These will soon connect more than 27 million people and cost about 12 billion dollars &amp;lt;sup&amp;gt;[1]&amp;lt;/sup&amp;gt;. Africa is in a good position for Photo voltaic (PV) mini grid optimization, receiving more than 1800 KWh/m&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; Global Horizontal Irradiation (GHI) every year &amp;lt;sup&amp;gt;[2]&amp;lt;/sup&amp;gt;, for most parts of the continent. However, the lack of a coordinated renewable energy monitoring and distribution network works against optimization of PV potential models &amp;lt;sup&amp;gt;[3]&amp;lt;/sup&amp;gt;. This study shows the accuracy of existing photo voltaic potential estimators like renewables ninja &amp;lt;sup&amp;gt;[3]&amp;lt;/sup&amp;gt;, the National Renewable Energy Laboratory (NREL), International Renewable Energy Agency (IRENA), and the global solar atlas &amp;lt;sup&amp;gt;[2]&amp;lt;/sup&amp;gt;, by comparing the modeled values with long term measurements from ground solar stations. This is done for more than 20 stations distributed over Africa. Our results show best correlations &amp;lt;sup&amp;gt;[4]&amp;lt;/sup&amp;gt; of up to 65.3% from version 2 of the Surface Radiation Data Set from Heliosat (SARAH) derived from the Photovoltaic Geographical Information System (PVGIS). However, we also have correlations as low as 16.2% for models commonly used in off grid simulations. The sensitivities of the modeled cost of a mini grid to the variation in PV potential were tested &amp;lt;sup&amp;gt;[5][6]&amp;lt;/sup&amp;gt; using the statistical range in sourced PV potential from the different estimators, giving us cost variation of more than 2.8% that may arise from the different sources.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;References&amp;lt;/strong&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;1. World Bank, ESMAP - Mini grids for half a billion people&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;2. https://globalsolaratlas.info/map&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;3. doi: 10.1016/j.energy.2016.08.060&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;4. Wikipedia contributors. (2021, January 7). Pearson correlation coefficient. In Wikipedia, The Free Encyclopedia. Retrieved 09:00, January 20, 2021, from https://en.wikipedia.org/w/index.php?title=Pearson_correlation_coefficient&amp;amp;oldid=998963119&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;5. Cader. 2018&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;5. Hoffmann. 2019&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;7. https://doi.org/10.2136/vzj2018.03.0062&amp;lt;/p&amp;gt;
ПРОБЛЕМНЫЕ АСПЕКТЫ СОЗДАНИЯ МОДЕЛИ КОМПЕТЕНЦИЙ БУДУЩЕГО УЧИТЕЛЯ-ЛИНГВИСТА

The article considers some aspects of the formation of competence components in the process of educating future teachers of languages. The relevance of the topic is dictated by the urgent need in society to reform a number of educational positions in the direction of practical use. Emerging new requirements concern changes in methodology and teaching methods. First of all, they rely on intellectual potential and interpersonal skills. Innovations concerning trainees depend on a variety of conditions at the subjective and objective level, without which neither work with information nor the process of self-identification are possible. Competences are still dependent on the results of joint activities of the teacher and the student, subject to implementation by each of them clearly defined goals and objectives.
Dam Behavior Classification System Using K-Nearest Neighbor Based on Temporal Data At the Djuanda Dam

Dam had a vital role in the social and economic communities, including water providers for irrigation, industry, power plant, recreation, and flood control. Besides having various benefits, Dam also holds the potential of disaster. Preventive action in disaster management was necessary. Dam behavior pattern classification with computational assistance was needed to determine the results of determining accurate, fast, and efficient behavior patterns. In this research, the system made by using a K-NN Classifier based on temporal data that formed to predict the behavior patterns of dams in the Djuanda Dam. The system test results produce the best accuracy of 88% for safe labels, 82% for standby labels and 92% for alert labels with the best k value is 8.
Основы совершенствования учебной дисциплины «математика» в подготовке бакалавров по направлению «радиотехника»

Vital task of higher educational institutions is to reasonably select the syllabus content and develop objectified estimation procedures for competencies’ formed level of students and graduates, focused on achieving final goals of training in contexts of implementing Federal State Educational Standards (FSES) and in designing major professional academic programs. The purpose of this article is to demonstrate a possible approach that enables to reasonably develop Mathematics academic subject in system of training Bachelors in technical areas. The research work paper analyzes the content of exemplary program of Mathematics academic subject based on matrix methods of logical connections and expert assessments, and quantitative estimates of educational components’ significance are obtained as well for students to successfully study Mathematics proper and professionally oriented academic subjects of educational training program for Radio Engineering Bachelors. The highlighted topics in the content of the academic subject claim to have a fairly high acquisition level, primarily during practical classes and through the students’ independent work. It is proposed to formulate requirements for the training level in Mathematics for students/graduates and make tools for diagnosing the degree of its achievement at two levels of acquiring educational components – reproductive and heuristic ones, and two types of human activity – reproductive and productive ones should be factored when differentiating these levels into hierarchically organized sublevels. The heuristic level of mastering the content of educational training is focused on the priority of systematic requirements for the graduate's competence, overcoming the mosaic pattern of academic training, and the reproductive level is focused on the implementation of particular standard algorithms, methods, and procedures that are components of system requirements. The proposed approach and the obtained results can serve as an indicative basis for improving the content of Mathematics academic subject as a part of major professional academic programs, for developing teaching package, procedures and banks of assessment tools for diagnosing the training level in Mathematics as per FSES requirements.