Reviewerly/exHarmony huggingface dataset:
Fostering Learning Motivation of Students with Reading and Spelling Difficulties by an AR-Enhanced Gamified Educational App for Literacy Learning

&lt;p&gt;Students with special educational needs benefit from carefully designed learning approaches that consider both their individual learning requirements and the advances in teaching and learning methods and tools. This paper presents the initial exploratory results from a pilot study on the advancement of literacy skills through an innovative Augmented Reality (AR)-enhanced gamified educational app for students diagnosed with reading / spelling difficulties or dyslexia. A sample of 5 teachers and 23 students worked with the AR app for the duration of a school term and filled in standardized scales on student motivation upon completion of the pilot study. The analysis of the results indicates that both groups of teachers and students found the AR app motivating to a certain degree. However, there were challenges within the pilot implementation that impeded the successful app use and potentially delimited the perceived motivational effects. Conclusions and outlooks of research perspectives for further development highlight the necessity for further research in this important field.&lt;/p&gt;
The Effectiveness of LLMs in Mental Health

It has an impact on everyone's health, which is why mental illness should be prioritized in the healthcare industry.However, it appears that this field is developing at a somewhat slow pace.AI (Artificial-Intelligence) technologies have recently received a lot of attention in a variety of fields, including mental health.Advanced AI approaches and machine learning algorithms have made it possible to provide personalized care that primarily focuses on providing emotional support tailored to a specific individual.We explore the possibility of using large language models like OpenAI's GPT3 and Facebook's Llama and Stanford's Alpaca to provide an effective conversational partner to people suffering with such mental health conditions where it may be helpful, such as depression and anxiety disorders.We compare the performance of the chatbots based on their responses to questions from counselchat.comdataset of therapist responses, and use the GPT4-davinci, the largest GPT4 model, as a judge to evaluate the quality of responses.
Factors affecting mothers' activeness in attending classes for pregnant women

The government implemented a class program for pregnant women to reduce maternal mortality. The participation of pregnant women and their families in pregnant women's classes is expected to increase knowledge and influence the behavior of pregnant women. The purpose of this study was to determine the factors that influence the activeness of mothers in attending classes for pregnant women. This research is analytic in nature. The population is all pregnant women in the working area of the Mutiara Barat Public Health Center, totaling 439 pregnant women, and the sample in this study was 81 pregnant women. The sampling technique is accidental sampling. The results showed that there was an effect of knowledge on the activity of the mother in taking classes for pregnant women (p value = 0.001), and there was an effect of family support on the activity of the mother in attending classes for pregnant women (p value = 0.013). (p = 0.006), and there is a motivational effect on the activeness of mothers in attending classes for pregnant women (p = 0.006). It is recommended that pregnant women be active in conducting class visits for pregnant women so that pregnant women can obtain correct information about pregnancy, childbirth, postpartum care, and good baby care.
Virtual Scrapart

Abstract: In today’s world, many art forms are in dying phase, due to lack of interest, recognition of supreme artist and lack of proper organized platform. Moreover, there are many aspiring artists who think there is a lack of marketplace for selling their products. Apart from this, there is a sharp increase in scrap generated from households and industries. According to International Trade Administration in 2020, 32 million tons of ferrous (Iron) scrap was produced as waste. Most of this waste can be reused if refurbished properly. There are many artists and craftsmen who are willing to work on such used products to create useful and reusable products. There are around 10,054 artists around the world who think there should be a proper platform where buying, selling and refurbishing of a product could be performed. With the use of modern technology such a platform can be developed by establishing a Server and developing a Mobile/Web – Application to interact with buyers, sellers and artists to convert waste into prime products.
Optimalisasi Kompetensi Pedagogik Calon Guru PAI Melalui Implementasi Flipped Classroom Berbasis Moodle pada Microteaching

Some students in Islamic Religious Education (PAI) study programs students still have low pedagogical competence. It is deemed necessary to increase the pedagogical competence of prospective PAI teachers, one of which is by implementing a Moodle-based flipped classroom on microteaching. Specifically, this research focuses on 1) how is the implementation of the Moodle-based flipped classroom on microteaching in improving the pedagogical competence of prospective PAI teachers, 2) Describing the effect of the implementation of the Moodle-based flipped classroom on the pedagogical competence of prospective PAI teachers, and 3) Knowing student responses to the implementation of the flipped classroom Moodle-based on microteaching. The results showed that: 1) Implementation of Moodle-based flipped classroom on microteaching at UIN K.H. Abdurrahman Wahid Pekalongan is carried out with e-learning on the http://learning.iainpekalongan.ac.id/ page, 2) Based on the results of the t-test (paired sample test) that the value of t count = [-44,338] or 44,338 while the value of t table = 2.028 so that 44.338 &gt; 2.028, and a Significance value (2-tailed) of 0.000 so that 0.000 &lt;0.05, it can be concluded that there is an effect of the implementation of moodle-based flipped classrooms in microteaching courses on the pedagogical competence of prospective teachers, 3) Student responses to Microteaching courses are included in the category very positive, the Moodle LMS is included in the positive category, and the flipped classroom is included in the positive category.
Sistem Informasi Cuti Pegawai Berbasis Web Pada Universitas Jambi

Leave is one of the employee rights that must be given by a company. Issues regarding the licensing and leave of civil servants have been regulated in Law Number 11 of 2017 about management of civil servants. The process of applying leave at Jambi University is currently still done manually, checking the remaining leave, filing the form, approval and leave reports still rely on paper leave archives. The manual leave management process has several weaknesses. Employees cannot find out the remaining personal leave entitlements and another weakness is that the leave application process is less effective and efficient. The purpose of this research is to improve the deficiencies that exist in the current system and to simplify and speed up the employee leave management. In designing this prototype, the authors use a modeling tool in the form of Unified Modeling Language (UML) with Use Case Diagrams, Activity Diagrams and Class Diagrams.
The influence of competence, motivation and level of education on the performance of archive management in the library and archives office of Sungai Penuh City

This study aims to determine the influence of competence, motivation and level of education on the performance of archive management in the Library Office and the Sungai Penuh City Archives. The research strategy used in this study was to use associative research strategies. The population in this study was 33 employees of the Sungai Penuh City Library and Archives Office. The sample used was 33 people using the full sampling technique or saturated sample. The data analysis technique is multiple linear regression and Coefficient of Determination. The results showed that: (1) Competence has a positive and significant effect on employee performance. (2) Motivasi has a positive and significant effect on employee performance. (3) Education Levelhas a positive and significant effect on employee performance. (4) Competence, motivation and level of education together have a positive and significant effect on the performance of employees of the Library Service and the Sungai Penuh City Archives.
Perencanaan Strategis Sistem Informasi Pada Madrasah Aliyah Nurussa’adah Sarolangun

Madrasah Aliyah Nurussa'adah Sarolangun has a need for IS/IT to be able to adapt to the existing environment. There is no integrated information system development plan so information system development is only based on current needs without considering further development. Based on the existing problems, the author proposes strategic planning of information systems with the Ward and Peppard method where this method emphasizes the analysis on increasing competitiveness and threats. The analysis is carried out using various tools critical success factor, value chain, SWOT, McFarlan Strategic Grid, and five forces. The results of this study are a strategic planning of information systems in the form of a portfolio of future applications that can support business processes, IS/IT management strategies which can help Madrasah Aliyah Nurussa'adah Sarolangun to increase competitiveness, optimize human resources, and utilize information systems and technology. future information for Madrasah Aliyah Nurussa'adah Sarolangun.
Sistem Informasi Administrasi Keuangan Siswa Pada Sekolah Dasar ABC Jambi

The process of managing student financial administration at ABC Elementary School is currently still manual, that is, it still uses books and is not well computerized. This resulted in problems, namely the administrative process took a long time and all parties could not get financial information quickly and accurately. This study aims to analyze and design a student financial administration information system which is expected to make it easier for all parties in the administrative management process. The method used in this research is prototype. Design tools using UML (Unified Modeling Language) and Adobe XD. This system provides services in the form of a menu login, register, upload transactions, manage transactions and print transactions. It is hoped that the design of this information system can be developed so that it becomes an application that can be used and applied to ABC Elementary School and for further research it can design an overall system that is integrated with other Information Systems that summarizes all business processes in school.
Instrument of Augmented Reality Technology Based Biology Practicum: Psychometrics Analysis

Digital literation skills are student’s need in nowadays modern era to refine the information accurately as an education media. Supporting the digital literation is by using the proper application by applying augmented reality (AR) technology. The purpose of the research is to analyze an implementation of AR technology as an effort to improve student’s digital literation skill in Surabaya senior high schools. The method of the research is quantitative with around 500 respondents that consist of students form three non-government senior high schools in Surabaya, Indonesia. The instruments validation to measure student’s acceptance towards AR technology as a teaching media is unexplored yet. This study is to evaluate the questionnaire about AR technology towards digital literation skill. The questionnaire consists of 10 items by google form and sent by online to 500 students in Surabaya. The data is processed by statistics with data analysis using Exploratory and Confirmatory Factor analysis. The whole average scores of questionnaires point that analyzed descriptively around, 60 and 2.63 with deviation standard 0.52-0.77. The scores of Pearson correlation by the whole items is around 0.08 and 0.35. The measurement of sample fairness using Kaiser-Meyer-Olkin (KMO) analysis generate 0.796 (Primely). This study identified three dimensions of total variation explains 51.28% from 10 items. The whole items generate factor loading score 0.5. However there are 2 items that eliminated that is item 1 and item 2.
रोगव्याधि, दोष निवारण र लामो आयुका देवता कुम्भेश्वर {Kumbesheswor the Deity of Long-life, Remover of Illness and Defects}

Kumbheshwar Temple of Patan has been famous since ancient times, but it has not been thoroughly studied. A study has been done to highlight the cultural significance of this temple. In it, the history, architecture and worship methods of the temple have been studied. A qualitative method has been adopted in this. Qualitative data is collected from observation, Interview, group discusses, key informant and published and unpublished book, Journal, Report. The data has been analyzed through inductive method. This temple was famous since ancient times. Inside the temple there is a big Sarveshwar image of small five-faced Shivlinga Kumbheshwar. This is a Nepali style temple has five floors built on a three-level plinth. There are 108 Bhairavas on the Tundals (struts). The roof of the temple is supported by 6-6 struts in all four directions of the temple and four struts at the four corners. Nitya Puja (everyday worship) and other regular pujas are performed withen the temple every day. On Mukhashtami, it is customary to crown the Panchabuddha created by Tamadhara on the Kumbheshwar Shivling. On Guru Purnima, Nagainag is seen wearing the crown of Vere. Those who become new Jhakris (Shaman) offer water from Gosai Kund to Kumbheshwar. Sage Agastya (saint) is believed to have founded Kumbheshwar. People go to Kumbheshwar to get long-life, diseases and defects. The study brings to light that Kumbheshwar is an ancient temple.
Comparison of Feedforward Neural Network and Classical Statistics Methods: Application in Finance

The flexibility and elevated accurateness of the statistical machine learning method makes this method widely applied in various fields. One of the statistical machine learning methods is the neural network, which can be used for data analysis. The great performance of the neural network method can be used in the field of finance. In this study, the neural network method was used to predict Non-Performing Loans (NPL) data and forecast credit receivables. In the NPL prediction, the banks used are State-Owned Banks, Regional Government Banks, and National Private Banks with a main capital of more than 6 trillion rupiahs in March 2021, i.e. 26 banks with the period of March 2018 until March 2021. In predicting NPL, a moving window scheme involves several different periods. In the forecast of the number of credit receivables, the data used is the number of financing receivables. The period from November 2012 to December 2020 is used as training data, while data for the period from January to June 2021 is used as testing data. The results of the analysis show that the neural network for NPL prediction and credit receivables forecasting shows better performance compared to classical methods such as multiple linear regression and ARIMA. A comparison of methods for banking NPLs prediction is based on the RMSE data testing values, while forecasting credit receivable is based on RMSE, MAE, and MAPE data testing values.
Implementation Vector Autoregressive (Var) On Rice Production and Rice Productivity Data in Indonesia

Vector Autoregressive (VAR) is a statistical model used to analyze multivariate time series, especially in time series where the variables have a relationship that influences each other over time. This study aims to determine the relationship between rice production and rice productivity in Indonesian. The data used in this study is secondary rice commodity data based on rice production and rice productivity in Indonesian from January 2014 to December 2018. The Augmented Dickey-Fuller method in this study was used to carry out a stationary test on the data. The ACF and PACF graphs show that rice commodity data based on rice production and rice productivity can be modeled using VAR. Based on the VAR(1) model, that rice production and rice productivity influence each other. The R2 and Adjusted R2 values for each partial equation of the VAR model (1) tend to be small so that the diversity of the models for each equation cannot be explained by the variables of rice production and rice productivity in Indonesian.
Multinomial Logistic Regression To Model The Combination Of Phdi Status And Hdi Status Of Districts/Cities In Kalimantan Island

Multinomial Logistics Regression (MLR) is a regression model developed from the Binary Logistics Regression (BLR) model. The response variable of the RLM model has three or more categories and has a multinomial distribution, with the data scale being nominal. The response variable in this study is a combination of the Public Health Development Index (PHDI) status and the Human Development Index (HDI) status of districts/cities in Kalimantan Island, 2018, divided into four categories with category one as a comparison. The predictor variables used were the number of the public health center, the percentage of poor people, economic growth, the pure junior high school participation rate, and the percentage of the population with a minimum of junior high school education. The MLR parameter model was estimated using the Maximum Likelihood Estimation (MLE) method and Newton-Raphson iteration. The hypothesis testing of the MLR model was used by the Likelihood Ratio Test (LRT) method and the Wald test. The best model selection in this study uses the backward method, and the interpretation of the best MLR model uses the odds ratio value. The results showed that the best MLR model is a model that has three predictor variables. The factors that significantly influenced the combination of PHDI status and the HDI status of districts/cities in Kalimantan Island in 2018 were the percentage of poor people, economic growth, and the percentage of people with the minimum level of education in junior high school.
SECURING DIGITAL INFORMATION THROUGH IMAGE WATERMARKING WITH LSB ALGORITHM: A COMPREHENSIVE OVERVIEW AND IMPLEMENTATION USING MATLAB

Over the years, researchers have been intrigued by the concept of information hiding, which involves concealing secrets and protecting information. Digital watermarking and steganography tools have been developed to achieve this objective, particularly in the realm of digital rights management. Digital watermark technology functions by embedding copyright information into the carrier, with the aim of safeguarding it. The digital watermark serves as a linkage between the hidden data and carrier data. In most instances, the carrier data is distorted during the concealment process, and cannot be restored to its original state. This study provides a comprehensive overview of image watermarking and the various security concerns surrounding it. The Image Watermarking technique using the Least Significant Bit (LSB) algorithm has been adopted in this work for embedding images/messages/logos into images. The study has been executed using MATLAB.
Testing Memes as a Teaching Tool

In the age of technology, communication through emojis and stickers was replaced by memes and gifs in the blink of an eye. As teachers, the authors of this paper have asked themselves how these swift changes might affect our classes. If students communicate more and more through memes, would integrating them into our lessons lead to a better comprehension? To investigate this possibility, we built a concise grammar exercise involving two meme templates and had the students build two passive voice memes.
Literasi Menulis Sekolah Dasar (Studi Kasus di SD Plus Rahmat Kota Kediri)

Research Purpose. The research conducted by the author aims to describe the stages of wiritng liletacy in SD Plus Rahmat Kediri. Methods. This study uses a qualitative method, with the type of case study research at the 4-6 grade level at SD Plus Rahmat Kota Kediri. The number of informants was 8 people consisting of teachers, students, librarians, and school principals using the purposive sampling technique. Data collection techniques are carried out by observation, Interview and Documentation. Data Analysis. The data analysis technique uses the concept of Miles and Huberman: Reduction, Presentation and Drawing Conclusions. Result and Discussion. The results of the study show that there are 3 stages in writing literacy, namely (1) the Habituation Stage, where students get used to resuming books they have read by writing the author's name, title, and contents. (2) Development Stage, availability of reading spots in the school environment. (3) Learning Stage, literacy classes are provided which are directly given by librarians who teach about writing.
Multiple-local Feature and Attention Fused Person Re-identification Method

Abstract Person re-identification (ReID) is widely used in intelligent security, monitoring, criminal investigation and other fields. Aiming at the problems of local occlusion, scale misalignment and attitude change of pedestrian images in actual scenes, we propose a Multi-local Feature and Attention fused network (MFA) used for person re-identification task. Firstly, Channel Point Affinity Attention module (CPAA) is embedded in the backbone network to enhance the ability of the network for extracting local details. Then, the feature map output from the backbone network is horizontally segmented into four local feature maps, and further four branch networks are concatenated to the feature map of the backbone network. The four local feature maps are used to guide the four branch networks to pay more attention on different areas of pedestrians through Global Local Aligned loss (GLA) function. Finally, the pedestrian feature vector containing multi-local features is obtained. The mAP of the network on Market-1501 and DukeMTMC-reID datasets were 88.6% and 81.4%, and the Rank-1 is 95.8% and 90.1%, respectively. In addition, the model also obtained 73.2% and 68.1% of Rank-1 on partial dataset Patial-REID and Patial-iLIDS, respectively. Compared with other ReID methods, our proposed methods achieved a competitive performance for ReID task.The code was available at github:git@github.com:ISCLab-Bistu/MFA.git.
A Hybrid Text Recognition Approach based on Involution Operators and Graph Convolution Neural Networks

Abstract Scene text recognition as a subsequent task of text detection is to convert the detected text regions into computer readable and editable characters, words or text lines. To improve the recognition of long text, a text recognition method based on the involution operator and graph convolutional network (GCN) is proposed. The method builds a new feature sequence extraction network based on the involution operator, which can extract text features within a larger sense field and generate feature sequences. Furthermore, the addition of gate recurrent unit (GRU) and GCN can help the model to remember useful text features while forgetting useless visual information, and enhance the contextual semantic information of feature sequences from multiple perspectives. Comparative experiments on ICDAR (International Conference on Document Analysis and Recognition) 2013, ICDAR 2015 and SVT (Street View Text) datasets show that the method can effectively recognize multi-scale ambiguous and adherent text. The F-score reaches 94.2%, 89.7%, and 93.8% without lexicon supervision, respectively.