Reviewerly/exHarmony huggingface dataset:
EVALUASI PROSEDUR PENGELOLAAN DANA BANTUAN OPRASIONAL SEKOLAH (BOS) DALAM MENILAI EFEKTIFITAS DANA PADA SEKOLAH DASAR ISLAM TERPADU (SDIT) BINA AULADI DEPOK

This research , from April 2018 to August 2018, with the title: Evaluation of School Oprational Aid Fund Management Procedures (BOS) in Assessing Fund Effectiveness in Integrated Islamic Primary Schools (SDIT) Bina Auladi Depok. This study aims to produce information in the form of an explanation of the application and evaluation of the procedures for managing funds and contributing suggestions for schools. The analytical method used in this study is to evaluate the procedures for managing funds in the field compared to library research by collecting books that relate to the effectiveness of funds by interviewing the principal or leadership and financial staff. The results of the study show that the accounting information system is particularly effective in managing funds. This can be seen from the organizational structure that is in accordance with the characteristics of the school, adequate and well-designed documents, internal control systems and adequate reports. Key words: evaluation, management, assistance, operations, school.
Implementasi Data Mining Klasifikasi Algoritma C4.5 Dalam Perekrutan Perangkat Desa

This study aims to The office of the Head held a village apparatus recruitment process that was still done manually. The obstacle found in the process of accepting village officials is the number of applicants received is limited. The purpose of this rsearch is to help facilitate the office of the village The method used is the C4.5 algorithm is one method that can analyze large amounts of data or commonly called data mining. In this study an application was made that implements a decision tree with the C4.5 algoritthm , the results of this study are in the form of an application program based on the conditions of the decision tree results that have been found to determine the recruitment of village officials
The Improved Information Technology for Monitoring Recurrent Laryngeal Nerve

The information technology has been proposed and substantiated to detect the location of the laryngeal nerve in the surgical wound during operations on the thyroid gland. The information technology, in contrast to existing, reduces the risk of the laryngeal nerve damage and the time of operation on the thyroid gland due to the developed interval model with radial basis functions. The mathematical models, which basis functions are radial, have a simple generalized structure and their structural identification is reduced to calculating the number of centers of radial basis functions. The main characteristics of the surgical wound tissue during surgery on the thyroid gland are its type and the distance from the point of irritation of the surgical area to the laryngeal nerve. As a result of research and processing of information signals of different patients, indicators of the type of the surgical wound tissue are substantiated. Such characteristics are the spectral components with the maximum amplitude. The patient information signals resulting from the response to muscle and nerve irritation at different distances to the laryngeal nerve have been analyzed. The information signals of patients, which respond to the irritation of the surgical wound with alternating current at equal distances to the laryngeal nerve of different patients, are similar, but the characteristics of the signals are different. The interval data analysis methods to eliminate the uncertainty and heterogeneity of the data sample have been proposed A clustering algorithm of inhomogeneous data samples has been used, which is based on the integration of similar spectral characteristics of information signals into groups described at intervals. The true distance from the irritation point of the surgical area to the back laryngeal nerve is within the constructed distance interval. This approach makes it possible to construct a single mathematical model based on radial basis functions to predict the distance from the irritation point to the laryngeal nerve. The results of the experiments confirmed the efficiency of advanced information technology for the laryngeal nerve monitoring
Combining Self-Aggregation Vector and Indicator Matrix for Improved Object Retrieval

Deep features extracted by convolutional neural networks have demonstrated state-of-the-art performance on image classification and retrieval tasks. Firstly, this work presents a simple and efficient method to select the region of interest based on semantics of features. Then, this work spatially weight deep convolutional features based on analyzing the relations between the self-aggregation vector and the indicator matrix. Based on the two strategies mentioned above, we product a compact global image representation of all images and show the proposed approach outperforms previous strategies based on pre-trained networks on a couple of benchmark datasets, i.e., Oxford dataset and Paris dataset.
AN ERROR ANALYSIS IN USING ZERO ARTICLES ON STUDENTS’ ABILITY AT SECOND SEMESTER ENGLISH EDUCATION STUDY PROGRAM ASAHAN UNIVERSITY

This study was aimed at finding out students’ zero articles error . It was conducted in Asahan University on februari until May 2018. The subject was the second semester students of English Education Study Program Asahan University consisting 23 students. This study used descriptive qualitative. Data source was the result of students’ test. The technique of data collection involved data collection and analysis. Based on the findings that students made many errors in using articles the grammar forms around 26 errors. The errors happenned because they were still confused using articles in the sentences. They often turn back and forth using articles . In addition, they still had less ability in grammar caused by the learning which was not maximal. Keywords: Error analysis, students’s ability, zero articles
Spanish Syllables Recognition by Wavelet and Cross Covariance

This paper shows the recognition of syllables through the using of Wavelet Transform and statistical tools such as cross covariance and the Pearson correlation coefficient. The considered syllables in this work are Consonant-Vowel (CV) and Vowel-Consonant (VC) given that they constitute 60% of those present in the Spanish language. The signals of the syllables are processed through a focused analysis with the application of time windows (segmentation the syllables in their respective phonemes) to later perform a multi-resolution analysis using the Wavelet Transform. For the recognition of the CV or VC structure, the cross covariance and the Pearson correlation coefficient are used. The results shows the performance of proposed method in comparison with other methods.
Special Libraries Association Annual Conference 2019

were not only enjoyable but also satisfying.There is something really rewarding about walking out of a presentation and knowing that I can go back to my home library and apply what I heard.Organization continues to be a key to a great presentation.Too often, poor time management made for less valuable sessions and presentations.This led to situations where a rushed presenter failed to cover all the content that was advertised.Additionally, poor descriptions of the content to be covered led to many disappointing sessions.The conference pamphlet gave brief descriptions of each session so that we could decide which sessions we wanted to attend.The brief descriptions sometimes failed to give the format, leading to some surprises for attendees.Similarly, it was frustrating to sit down at a session and realize that the session was actually a vendor presentation.In the future, it might be useful for SLA to include a session type in the descriptions.It might also help to review descriptions of sessions to ensure that they accurately describe the content.
Mining recent frequent cooccurring items from transaction stream

The work presents a simple but novel scheme to determine the recent frequent cooccurring items from transaction streams. It enables to follow the current trend, pattern of occurrence of the items and also help in recommendation. Proposed methodology works on a sequence of transaction forming a time-window. Based on the items present in a transaction, item-sets are formed and encoded. An in-memory structure maintains the frequency of the item-sets. Frequency is time-decayed count that prioritises the recent occurrences. To limit the size of in-memory structure, a pruning operation is carried out to remove the less frequent item-sets. Threshold for pruning is chosen dynamically. Impacts of decaying parameter and window size are also analysed. Experiment has been carried out on two datasets and performance has been compared with two recent works. Proposed methodology provides a better accuracy. Low time and space complexity make it suitable for stream analytic.
PKM Desain dan Konsultasi Rumah Sehat di Desa Mekarwangi, Banten

The houses in Kampung Cilegong, Mekarwangi Village are still far from the standard of Healthy Homes. Although some were built by artisans with the knowledge of "copy-paste" from cluster housing, there were also some that were built by local governments and offices. A healthy home is a well-designed house, especially looking at the local climate context. Natural lighting and air are the main requirements in designing a healthy home. Therefore, the Architecture Study Program at Matana University tries to carry out PKM activities in the form of training, consultation, and mentoring of several houses in Kampung Cilegong. It is hoped that residents of Kampung Cilegong and the people of Mekarwangi Village will be exposed to the knowledge of the Healthy House and obtain design solutions to set an example. This activity involved students of the 2018 class at Matana University and was integrated with the Building Physics course and the Interior Design Studio. The method of implementation is carried out following the design method. The results of the activity showed a positive response and added insight by the community.
Upaya Produktivitas Karya Tulis Mahasiswa di IAIN Tulungagung sebagai Preventif Plagiasi terhadap Qualifed Kalimat Efektif

This study focuses on written literacy in form of scientific writing as one of college tridharma. Lack of interest in reading, has attracted the attention of the people to establish literacy communities that aims to spread literacy early on. Someone is able to write scientifically if he/she read a lot of literature such scientific article or journal as an information resources but many people who write without basis by doing plagiarism. This study used library research with descriptive design and literature approach as data collection technique. The results of this research were: 1) Reflections on reading and writing interest, 2) Alternative of plagiarism among students, 3) Recovery of scientific writing in accordance with EYD or EBI rules.
'Reference Marker' in Official Documents: A Manifestation Of Language Civility:

Politeness of language is an important aspect in an effort to achieve the desire to create a harmonious society of people. The recognition of its interests is scattered through the five principles of the Five Pillars, namely Politeness and Decency. This pure practice is naturally appropriate to be applied by all members of his typical community when interacting in an official context. This working paper will examine the use of language politeness used in official documents issued by elected royal offices. The focus of the study only involves the use of reference markers in the documents relating to documents. The conversation was carried out in a descriptive qualitative manner based on Asmah Hj. Omar (2000). It can be found that issuing official documents that are studied may still increase the politeness stage of the language used. This is because the use of high-level politeness in language is less than the politeness of the principle. There is also a subtle politeness stage that is applied when making a referral.
A general Bayesian bootstrap for censored data based on the beta-Stacy process

We introduce a novel procedure to perform Bayesian non-parametric inference with right-censored data, the beta-Stacy bootstrap. This approximates the posterior law of summaries of the survival distribution (e.g. the mean survival time). More precisely, our procedure approximates the joint posterior law of functionals of the beta-Stacy process, a non-parametric process prior that generalizes the Dirichlet process and that is widely used in survival analysis. The beta-Stacy bootstrap generalizes and unifies other common Bayesian bootstraps for complete or censored data based on non-parametric priors. It is defined by an exact sampling algorithm that does not require tuning of Markov Chain Monte Carlo steps. We illustrate the beta-Stacy bootstrap by analyzing survival data from a real clinical trial.
Highlighting the Core Concepts of Clustering Techniques by Examining Its Algorithm

Clustering is the unmonitored team grouping of patterns [1]. The question of clustering has been discussed in many ways and this replicates its wide appeal and usefulness as one of the measures in the study of data analysis by researchers in a lot of regulation. It paper’s goal is to analyze the core concepts and techniques in the broad cluster analysis sub-set. Where relevant, references will be made to key concepts and techniques in machine-learning and other communities arising from the clustering process. Data mining is the method of processing and summering information in to useful information from different points of view. Data mining is one of the fields that need to be explored in the current days. Data mining clustering analysis is an important research that has its own unique position in a wide range of data analysis and storage.
Big Data Analysis: Theory and Applications

With the continuous improvement of data processing capabilities and storage capabilities, Big Data Era has entered the public sight. Under such a circumstance, the generation of massive data has greatly facilitated the development of data mining algorithms. This paper describes the status of data mining and presents three of our works: optimization-based data mining, intelligent knowledge and the intelligence quotient of Artificial Intelligence respectively. Besides that, we also introduced some applications that have emerged in the context of big data. Furthermore, this paper indicates three potential directions for future research of big data analysis.
Opportunities for developing professional skill in the process of increasing the qualification of teachers

The article poses the problem of the development of professional skills, competencies, teacher techniques in the process of advanced training. The scientific studies carried out in the field of the development of professional activities of teachers, the best foreign practices are analyzed. Also, the characteristics of the terms professional skills, competence, and teacher development are given.
Generative learning strategy and its effectiveness in cognitive achievement and fostering of learning styles in history subject.

The importance of this study is highlighted in the following: 1 - The importance of using the strategy of generative learning in the process of teaching, which is regarded as an effective strategy of learning that focuses on learners as the center of education process. 2. The research aims to activate the theoretical knowledge which develops learners’ thinking skills and planning to organize information. 3. The research presents a procedural model for experimenting with a different strategy in education instead of focusing on the usual method of teaching. 4. The research contributes to encouraging male and female teachers to use generative learning strategies in teaching since it helps students increase their performance and develop their learning methods. In order to achieve the goals and hypotheses of the research, the 11th grade female students were selected as the sample of the research. They were divided into two groups, one experimental who were taught according to generative learning strategy, and another were taught according to the usual method. After the equivalence of the two groups in a set of variables, the post-test of the research tools was applied after verifying their validity and stability. In the light of the results of the research, the researchers drew the following conclusions: 1. The use of generative learning has more positively influenced the achievement of the students of the eleventh grade in history subject than the usual way of learning. 2. The use of generative learning, in teaching history to the 11th grade students, has its own positive unique effectiveness and impact in learning methods compared to the usual method used. 3. The students of the experimental group, who were taught through using generative learning, have been more successful than the students of the current group, who were taught according to the usual learning method. 4 . The two groups (experimental - and current) showed their success in the post-test over the pre-test of the measure of learning methods.
Evaluasi Deteksi Smell Code dan Anti Pattern pada Aplikasi Berbasis Java

This paper presents an evaluation result of smell code and anti pattern detection in java based application development. The main objective to be achieved in this research is to determine the proper way in the detection of smell code and anti pattern in the development of java based software, and to evaluate the impact of using code inspection tools and software metrics to refactoring code in java based software development. Smell code to be detected in this research is Long Parameter List, Large Class, Lazy Class, Feature Envy, Long Method, and Dead Code. Anti pattern that will be detected is The Blob / God Class and Lava Flow. The selection of smell code and anti pattern is based on the definition, characteristics, detection factor, and software metrics. To support the research process is done through the evaluation stage of a case study java based application as a sample for inspection of code for the detection of smell code and anti pattern and calculation software metrics. Case studies of selected applications as sample applications are E-Commerce applications with functional master data management of goods and customers as well as management of sales and payment transactions. The detection of the smell code and anti-pattern on the case study is done in stages so it can be determined whether or not to refact. As well as ensuring the technique of making the program better fit the characteristics and rules of object-oriented programming.
Modeling of fuzzy logic controller and membership functions for humanizing synthetized music data in multimedia applications

Multimedia applications, especially those that synthesize music data, are designed to operate based on algorithmic composition models. One of such models is the Hybridized Interactive Algorithmic Composition (HIAC) model. Algorithmic composition models are known to generate and synthesize music devoid of the natural human emotional dynamics. Such synthesized musical themes are considered mechanical in nature because they are precision driven. However, human composed music is driven by certain degree of uncertainty and approximations as emotions help in creating dynamics such as very soft, soft, medium, loud and very loud notes. Therefore, this paper is proposing the use of fuzzy logic in humanizing computer generated and synthesized music notes. This shall help multimedia application designers and developers to create software that will generate and synthesize natural sounding music.Keywords: Fuzzy Logic, HIAC Model, Membership Functions, Multimedia Applications, Music Dynamics and Soft Computing
The issues of development of creative abilities in French classes

This current research comprehensively examines differences in creative thinking abilities between students, and the views of the university educators on creativity characteristics and standards.While the primary purpose is to offer further research to add to the body of knowledge, there is also the opportunity to find evidence connecting the level of scholastic achievement with the resources available to students elsewhere.The aim of the offered literature review is to discuss the elements of creative thinking, which lead to a conceptualization of the phenomenon.This research is essentially an examination of the work of scholars who seek to define creative thinking from their varying perspectives and disciplines, following on the postulation of corresponding theoretical constructs that have been tested and refined over time, and utilizing the means of measurement for creative thinking and methods of data collection under those models.The relevance of the research problem can be explained by several circumstances.The main direction of modernization of a comprehensive and vocational education at the present stage of development provides, first of all, to improve the quality of assimilation of general and professional knowledge, practical and creative training of graduates.French language, as a general educational subject, can and should contribute to the development of students' creative abilities.Possessing a vast upbringing, educational and developing potential of students' creative abilities, French language can realize it only through the implementation of the practical goal of learning, that is, only if the student in the process of communicative-cognitive activity in another language (listening, speaking, reading, using writing) will expand their educational horizons, develop their thinking, memory, feelings and emotions; and if in the process of French language communication social and value qualities of a person will be formed: worldview, moral values and beliefs, character traits (Artemyev, 1987).
IoT- A Technological Boon in Natural Disaster Prediction

Internet of Things [IoT] is a boon for natural disaster prediction in current scenario. No one can predict the disasters but the least that one can do is to be prepared for it. Disasters may be both man-made and natural and it occurs frequently throughout the universe. When disaster happens, it renders some horrific results. Disturbance of life, loss of property and changes in the environment are few of the outcomes of the disasters. Effective management techniques should be designed and implemented for minimizing the damage and risk factors involved with disasters. Growth of Technology is not reflecting in the area of emergency management. Internet of Things (IoT), rapidly evolving to Internet of Anything and Everything, can be introduced to manage disaster generated by the natural disturbance. Recently, IoT perspective has given the new dimension to identify and overcome the problems belongs to agri-informatics, enterprise, cyber security, and telemedicine because of potential attributes, like interoperability, heterogeneousness, flexibility, and soft-weight. Rescue operations can be attached through IoT for effective management approach. Disaster alarming systems, rescue techniques, follow-up, and regulation method can be coupled for this task. This paper introduces an architectural system for effective disaster management using IoT techniques which overcome the fatal disaster phenomenon. It also depict the necessities for arranging salvage task for such cataclysmic events and proposes an IoT based answer for cater the distinguished necessities.