Reviewerly/exHarmony huggingface dataset:
K-Means Algorithm and Binary Search on FiBuSI

Purpose: Create an application called FiBuSI (Find Business and Stock Investment) using the k-means algorithm and binary search for data search features. This application is intended for entrepreneurs and investors where they can interact with each other to build a joint business.Method: Using the RAD (Rapid Application Development) Method which focuses on system testing based on user experience related to Blackbox Testing using the Katalon Studio tools for testing functions on the FiBuSI application.Result: Based on the results of testing the FiBuSI application which focuses on the success of application functions and algorithm implementation, that each application function is successfully executed (PASSED) based on testing using the Katalon Studio tools. Meanwhile, testing the k-means algorithm (data filter) and binary search (search for letter data) was also successfully carried out by testing it directly by the user on the FiBuSI application and also using the results from the Katalon Studio tools.State of the art: Based on several studies that have been done previously related to the use of the k-means algorithm and binary search that this algorithm is carried out on 2 different features but in 1 application for business data search. In concept, the FiBuSI application focuses on bringing together entrepreneurs and investors in one platform.
Kelekatan Guru dan Motivasi Membaca

The research background is the lack of teacher attachment in developing children reading interest. Through a survey approach, this study aimed to describe the conditions of attachment between teacher and child toward children motivation to read. The sample was taken randomly, which consisted of 57 students in grade 3 of elementary school and two teachers. The data was collected by questionnaire and analyzed by using descriptive statistics. The results showed that students' reading motivation based on students' perceptions was in the medium category (40%), while based on teachers' perceptions it was in the low category (82.45%). The positive attachment that occurred was in the low category (63.15%), while the negative attachment was in the low category (78.9%). Teachers need to build positive attachment, especially in increasing students' motivation to read.
Agile Corps - A Public Service-Learning Program Part II

Annually, the U.S. government invests $94 billion on IT products and services. The majority of these projects fail--they are late, over budget, canceled outright, or, if delivered, are outdated or not user-friendly. Due to barriers in hiring and training, the government tends to outsource IT talent at a premium through contractors, but outsourcing talent has not changed the results. Inside the government, the small amount of talent that exists tends to be senior, and there currently are very few, viable options for high-quality, junior and mid-level technologists to find a job in government and professionally develop and progress. Agile Corps is a program designed to identify, recruit, train, and retain junior and mid-level technology talent in the government. Agile Corps exemplifies public service-learning, a learning approach and strategy that combines learning objectives, instruction, and reflection with government service for the public. After completing a discovery research process followed by prototyping and testing the program design, we piloted the Agile Corps program at the US Department of Labor. This paper presents the Department of Labor pilot of Agile Corps and the concept of public service-learning, and measures the impact of the Agile Corps pilot at the Department of Labor.
Attitudes of Lecturers and Students of Sriwijaya University-Indonesia and Omdurman Islamic University- Sudan to On-Line Learning in the Pandemic Covid-19

This study aims to determine the response of Sriwijaya University students and Omdurman Islamic University students to the online learning process during the Covid-19 pandemic. This research is a descriptive research with survey method. The learnings carried out by lecturers and students during the Covid 19 Pandemic had previously attended training on the use of the application e-learning Sriwijaya University. This study aims to determine the response of Sriwijaya University students and Omdurman Islamic University students to the online learning process during the Covid-19 pandemic. This research is a descriptive research with survey method. The learnings carried out by lecturers and students during the Covid 19 Pandemic had previously attended training on the use of the application e-learning Sriwijaya University. Learning is also carried out asynchronously and synchronously, with the application Zoom (97%), Whatsapp (64.3%), and Google meet (31%). The general assessment is that lecturers conduct assessments using an online exam system through E-learning (99.1%), by means of lecturers sending assignments to be done by students, or using Google Forms (34.4%), and e-mail (20.1 %). Assessment of students is carried out using an online exam system through E-learning (99.1%), students send assignments to be done by students, or use Google Forms (34.4%), and e-mail (20.1%). students, or using Google Forms (34.4%), and e-mail (20.1%). Criticisms and suggestions for online learning techniques, lecturers should be more active in making various interesting learning strategies, so as not to get bored. Use e-learning more actively to save quota. For the system should e-learning Sriwijaya University better. It turns out that some students want online learning to be maintained, even though the pandemic is over.
A Analisis Tantangan dan Peluang Era Disrupsi bagi Civitas Akademika Universitas Ibn Khaldun Bogor

In today's era, there have been many significant changes. These changes also occur due to something entering a country brought by a foreign country. This incoming change can be through a phenomenon known as globalization. With this phenomenon, it can change the order of life in a country, one of which has an impact on the campus structure. Globalization makes it easy for foreign cultures to enter the country. With the influx of foreigners, let alone modern culture with technology, this is a sophisticated challenge for the country itself. This era is called the era of disruption. Researchers have conducted research to examine this problem. Researchers conducted research with qualitative methods by conducting interviews with selected respondents consisting of students and lecturers from Ibn Khaldun University, Bogor. The results of this study prove that the era of disruption has a major influence in the world which creates several challenges and opportunities that greatly affect the progress of the campus itself.&#x0D; Keywords: disruption era, campus, technology
Human Resources Development In Bitung City Library Service

This study aims to analyze Human Resource Development at the Bitung City Library Service. This study uses qualitative research methods. There are 6 (six) informants who were interviewed. The current research results indicate that technical guidance activities are virtual and face-to-face. Technical guidance activities are only carried out 2 (two) times a year for the Bitung City Library Service. The level of education of employees is still not by the positions and competencies required. There is still no librarian, and the achievement of work results from employees who have received training is not optimal. Even the existing facilities and infrastructure at the Bitung City Library Service are still inadequate. The Bitung City Library Service does not yet have educational backgrounds or disciplines about libraries. The service has not yet maximized the impact felt by the service on employees who have received socialization related to the main tasks and functions. There is no reading building for the public at the Bitung City Library Service. There is still no archivist, so there is still a lack of human resources at the Bitung City Library Service. Employees are still not able to complete tasks quickly and accurately. Suggestions from researchers are that the implementation of technical guidance activities must be added and maximized. The level of employee education must be by the positions and competencies required.
An analysis of students’ grammatical errors in translating Indonesian recount text into English made by the first grade of senior high school

This research was aimed at finding out types of grammatical errors and investigating types of errors that were most and least frequently made by students based on Communicative Effect Taxonomy that were found in students’ recount text translation as well as figuring out the causes of those errors. The subjects of this research were the first-grade students of SMAN 1 Pringsewu in the academic year 2020/2021. This research adopted a descriptive qualitative method by using a translation task and questionnaire as the instruments. The results revealed that the students committed all error types in terms of Communicative Effect Taxonomy: global error and local error. Local errors were more dominating than global errors. The possible causes of those errors were problems in the target language, mother-tongue interference, lack of eagerness to learn the target language, lack of confidence, and the absence of error feedback from the teacher. This suggests that the student’s knowledge of English grammar was still low. Therefore, the English teacher is expected to solve it by providing appropriate teaching methods and materials to minimize the errors. Keywords: Error Analysis, Communicative Effect Taxonomy, Translation
Research Management and Productivity: Basis for Research Policy Development Plan

This study aimed to determine the level of research management in terms of organizational structure, research guidelines, capability building, credits and incentives, linkages and extension, utilization and dissemination and the research productivity in Northern Iloilo Polytechnic State College (NIPSC) for the past three years (2015-2018) as basis for the development of the research policy plan. This study employed the descriptive-correlational method using the one-shot survey design. The respondents were the 116 purposively-selected faculty of NIPSC. Data were gathered using the validated and reliable researcher-made survey questionnaires and analyzed using the descriptive and inferential statistical tools such as Frequency Count, Mean, tests, the t-test for Independent Samples, Analysis of Variance (ANOVA), and Pearson-r. The hypotheses of the study were rejected and/or accepted at the 0.05 level of significance. The findings revealed that the level of research management in NIPSC in terms of organizational structure, research guidelines, capability building, credits and incentives, linkages and extension, utilization and dissemination was very satisfactory. The research productivity was low. Respondents who have conducted more researches have higher research productivity. No significant differences were observed in the research management when classified according to sex and number of researches but high significant differences when classified as to academic rank and marital status. Moreover, no significant differences in the research productivity when the classified according to sex, academic rank, and marital status while high significant difference were observed as to the number of research conducted. The research management was not significantly related to the research productivity. A research policy development plan to increase the research productivity of NIPSC was proposed.
Learning of Knowledge Graphs with Entity Descriptions

The representing learning makes specialty of knowledge graph and it indicates the difference between different entities. The knowledge graph representing with the low-dimensional space. In fact, most of the method usually concern of description of entity which is hard for existing strategies to take benefit of. Here, we recommend a new representing learning method with knowledge graphs that uses entity description. We evaluate our method on two tasks like knowledge graph and entity classification. Experimental effects on actual-world datasets show that our version plays higher than different baseline fashions, especially under the zero-short setting, which indicate that our technique for novel the entity description.
Study of Neuromarketing: Visual Influence with Decision Making on Impulse Buying

Marketing trends have been increasing in the last few decades. Products need good branding and the right marketing strategy. Various marketing methods have been widely done, and one of them is with the study of neuroscience, especially neuromarketing. Neuromarketing is used to seek the influence of marketing stimuli on consumers and objective data through advances in neurology by utilizing human senses such as restraint, smell, taste, and touch. Measurements of neuromarketing responses to the brain can use electroencephalography signals (EEG). Measurement is done with the visual stimulus of consumers when making decisions. To analyze consumer interests, the majority still using qualitative methods, but it is still considered less effective due to many uncertain factors. In this study, neuromarketing responses were measured to the human brain using (EEG) signal analysis. Data collection was conducted on 11 respondents with a stimulus in the form of different product colors and was affected by changes in light intensity. For pre-processing used bandpass filters to get beta signals in the absence of noise. Then the data will be processed using Fast Fourier Transform (FFT) and energy extraction as characteristic extraction and classification of Support Vector Machines (SVM) in the signal pattern recognition process. The results of testing the best feature combination parameters showed an accuracy value of 72% with a combination of magnitude and phase features. By using the range of phase feature values obtained an accuracy of 67% for signal pattern recognition respondents.
Tic Tac Toe by Minimax Alpha-Beta Pruning Using Arduino

Abstract: Heuristic algorithms are put to the test in games. Because they incorporate an unexpected opponent, two-person games are more challenging than a basic puzzle. In a two-player game, you must presume that your opponent has the same information as you and can use it just as well. As a result, you must presume that your opponent will make the best available move at each level of the game. The minimax method is built on this foundation. The players in minimax are referred to as MAX (the player) and MIN (the player) (the opponent). Both aim to get the most out of their actions. The player, MAX, is attempting to maximise her score. And MIN is the opponent attempting to reduce MAX's score to the bare minimum. It is impossible to stretch the graph to its leaf nodes in most games.The number of layers in the state space is increased to n. The heuristic evaluation function assigns a value to each leaf node in this subgraph. The values are then passed back to the root node. The heuristic value of the best state that can be attained from that node is represented by the value propagated back. The process of alpha-beta pruning is used to reduce the amount of computation and searching required during minimax. Minimax is a two-pass search, with the first pass assigning heuristic values to nodes at the lowest depth and the second pass propagating those values up the tree. The depth-first approach is used in alpha-beta search. A MAX node's initial or temporary value is called an alpha value.Because MAX nodes receive the highest value from their descendants, an alpha value can never fall; it can only rise. A beta value is a value linked with a MIN node that is initial or transitory. A beta value can never increase; it can only go down because MIN nodes are assigned the lowest value among their progeny. Assume alpha = 6 for a MAX node. Then any branches originating from a MIN descendant with a beta value less than or equal to 6 won't be included in the search. So, if you know that the MAX node has an alpha of 6 and that one of its MIN children has a beta of less than or equal to 6, you don't need to look any farther down the MIN node. This is called Alpha Beta Pruning. Keywords: component, formatting, style, styling, insert (key words)
Absolute Scale Estimation Approach for Monocular Visual Odometry

Monocular visual odometry is an effective motion estimation technique that requires to solve for the challenging problem of absolute (metric) scale estimation. Current approaches use information such as the camera height or size of known objects to estimate the scene scale. In this paper, we propose a novel prediction-correction method to estimate the absolute scale of motion using camera height and flat ground assumption. Prediction is provided by a robust relative scale estimation strategy that exploits redundancy in depth information. Correction implements ground patch correlation using subpixel search refinement. The proposed method is tested using the public KITTI benchmark. As result, we derive analytical expressions to determine the absolute scale using a monocular camera. The empirical results shows the effectiveness of the proposed absolute scale estimation strategy in reducing the scale drift in monocular visual odometry.
Movie Recommendation System

Abstract: Now a day’s recommendation system has changed the style of searching the things of our interest. This is information filtering approach that is used to predict the preference of that user. The most popular areas where recommender system is applied are books, news, articles, music, videos, movies etc. In this paper we have proposed a movie recommendation system named MOVREC. It is based on collaborative filtering approach that makes use of the information provided by users, analyzes them and then recommends the movies that is best suited to the user at that time. The recommended movie list is sorted according to the given to these movies by previous users and it uses K-means algorithm for this purpose. MOVREC also help users to find the movies of their choices based on the movie experience of other users in efficient and effective manner without wasting much time in useless browsing. This system has been developed in PHP using Dreamweaver 6.0 and Apache Server 2.0. The presented recommender system generates recommendations using various types of knowledge and data about users, the available items, and previous transactions stored in customized databases. The user can then browse the recommendations easily and find a movie of their choice. Keywords: Recommender System, Machine Learning, Collaborative Filtering, Content based Filtering
Moderasi Persepsi Kegunaan dan Kemudahan Pembelajaran terhadap Pengaruh Minat Belajar pada Tingkat Pemahaman Akuntansi

This study aims to determine the moderating ability of the perceived usefulness and convenience of online learning media at OASE Udayana on the influence of accounting students' learning interest on their level of accounting understanding. The primary data of this research is the distribution of questionnaires using purposive sampling method. The collected data is first tested for the fulfillment of the classical assumption requirements, then analyzed using the technique of moderated regression analysis (MRA). The results of this study are that interest in learning statistically affects the level of accounting understanding, perceptions of the usefulness of online learning media are not able to strengthen or weaken the influence of interest in learning on the level of accounting understanding and perceived ease of moderating the effect of interest in learning on the level of accounting understanding.&#x0D; Keywords: Learning Interests; Perceptions of Usefulness; Perceptions of Ease; Level of Accounting Understanding.
Efficacy and Safety of Autologous Platelets Concentrate in the Treatment of Crow's Feet Photo Aging

Introduction: Platelet rich plasma (PRP) is an autologous serum that contains high concentrations of platelets and growth factors. It is currently a versatile therapy in dermatology; however, few studies objectively evaluate its efficacy. Objective: To evaluate the efficacy and safety of intradermal microinjection of autologous platelet concentrate (APC) in the treatment of crow's feet rejuvenation. Method: An observational, analytical and longitudinal study was carried out in 60 patients from the Hospital Clínico Quirúrgico: “Hermanos Ameijeiras”, in the period between March 1, 2017 and March 31, 2020. The treatment was applied monthly. for 1 year. The final evaluation was carried out 3 months after the end of the treatment. Results: 60 women with an average age of 45 ± 4.3 years were treated. After treatment, there were significant changes in the Glogau Photo Damage Scale (P = 0.0022), in the Photonumeric Scale to assess the severity of crow's feet (P = 0.0111) and in the Global Aesthetic Improvement Scale. (P = 0.0033). The adverse events found were pain, inflammation and ecchymosis. The degree of satisfaction reported by the patients was good (16.6%) and very good (83.3%) (P = 0.0021). Conclusions: The autologous platelet concentrate proved to be effective and safe in reducing the signs of cutaneous aging of crow's feet, associated with a high degree of patient satisfaction.
Virtual Machine Task Classification Using Support Vector Machine and Improved MFO Based Task Scheduling

The processing of data in Big data computing necessitates a significant number of CPU cycles and network bandwidth. Dataflow is a huge data processing programming model that comprises of jobs structured in a graph structure. Scheduling these jobs is one of the most active study fields, with the primary goal of allocating tasks based on available resources. It is critical to efficiently schedule jobs in a way that minimizes task completion time and maximizes resource utilization. In recent years, many research works on task scheduling problems in cloud computing and various heuristic approaches have been evolved which the thesis focuses upon. Most of these efforts are focused on improving the performance such as minimizing the makespan and efficient utilization of cloud resources that benefits the cloud users and the providers. In this paper, Big Data analysis processing in cloud environment for efficient dynamic task scheduling by using different techniques as machine learning classifier and optimization approach. In machine learning classifier as Support Vector Machine (SVM) for classification of virtual machine task classification. In this classifier can classify the incoming request efficiently and reduce the makespan and execution time. Further, we used moth flame optimization technique for allocating the classified task from SVM classifier. In this proposed system have classification of virtual machine (VM) task and evaluate the resource allocation decision making procedures. In this experiment, we carried out by using cloud simulation environment to evaluate and analysis the proposed method. In this proposed scheme can efficiently reduce the makespan time and load balancing to improve the better VM Classification. And aslo we compare the proposed moth flame optimization (MFO) with min-max algorithm and particle swarm optimization to compare the performance respectively.