Reviewerly/exHarmony huggingface dataset:
The Influence of Marketing Communications Through Online Media and Marketplace on Sales Turnover of Pandandwangi Rice Cianjur

The era of digitalization encourages anyone to take advantage of online media to communicate and do business.To increase sales, marketing, and sales communications are carried out through various social media sites and marketplaces.The phenomenon of selling through social media and the marketplace is interesting to study.The purpose of this study was to examine: 1) the simultaneous effect of marketing communications through various types of social media and types of the marketplace on sales turnover of Pandanwangi rice; 2) the partial effect of marketing communications through various types of social media on sales turnover of Pandanwangi rice; 3) the partial effect of marketing communications through various marketplaces on sales turnover of Pandanwangi rice.Path analysis quantitative descriptive method is used to get answers to research objectives.Data were collected from 65 respondents in a cross-sectional survey.The results showed that marketing communications through appropriate online media, accompanied by interesting and informative communication content, were able to increase the sales turnover of Pandanwangi rice.The selection of a marketplace that many viewers have access to as a marketing communication medium significantly increases the sales turnover of Pandanwangi Cianjur rice.Simultaneously, marketing communications through online media and the marketplaces that are visited by many viewers, have a significant effect on increasing sales turnover of Pandanwangi Cianjur rice.It is hoped that the results of this research can be taken into consideration by stakeholders in communicating as well as marketing Pandanwangi rice with geographic indications online.
Low Light Image Enhancement using MIRNet

With the goal of recovering high-quality image content from its degraded version, image restoration enjoys numerous applications, such as in surveillance, computational photography, medical imaging, and remote sensing. Recently, convolutional neural networks (CNNs) have achieved dramatic improvements over conventional approaches for image restoration task. Existing CNN- based methods typically operate either on full-resolution or on progressively low-resolution representations. In the former case, spatially precise but contextually less robust results are achieved, while in the latter case, semantically reliable but spatially less accurate outputs are generated. In this paper, we present a novel architecture with the collective goals of maintaining spatiallyprecise high- resolution representations through the entire network, and receiving strong contextual information from the low-resolution representations. The core of our approach is a multi-scale residual block containing several key elements: (a) parallel multi-resolution convolution streams for extracting multi-scale features, (b) information exchange across the multi-resolution streams, (c) spatial and channel attention mechanisms for capturing contextual information, and (d) attention based multi- scale feature aggregation. In a nutshell, our approach learns an enriched set of features that combines contextual information from multiple scales, while simultaneously preserving the high-resolution spatial details. Extensive experiments on five real image benchmark datasets demonstrate that our method, named as MIRNet, achieves state-of-the-art results for a variety of image processing tasks, including image denoising, super-resolution and image enhancement.
Generating Synthetic Training Datasets using Conditional Generative Adversarial Network to Improve Images Segmentation

Limited amount of training datasets in deep learning research could impact the accuracy of the resulting models. This situation can cause overfit, so the model cannot work correctly. A conditional Generative Adversarial Network (CGAN) was introduced to generate synthetic data by considering certain conditions. This study aims to generate additional synthetic training datasets to improve the accuracy of the object segmentation model of images. Firstly, we evaluated CGAN-based dataset generator accuracy against several open datasets. Then, we applied the generator to train two object segmentation models, i.e., FCN and CNN U-Net. Our evaluation shows that CGAN can generate synthetic datasets well. Complex datasets require more training iterations. It also improves the validation loss and validation accuracy of both segmentation models, although other metrics still need further improvement
A Novel Approach to Web-based Review Analysis using Opinion Mining

The propose an advanced Website Evaluation system that rates the website based on the opinion of the user. Website will be evaluated based on factors such genuineness of the website, timely delivery of the product after online transaction and support provided by the website. User will comment about the website, based on the comment system will rate the website. The system takes opinion of various users, based on the opinion; system will decide whether the website is genuine or not. The system uses opinion mining methodology in order to achieve desired functionality. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user comment is ranked. The system contains keywords related to fraud, genuineness, timely delivery of the product and service meters in the database. Based on these factors system will rate the website.
Alumini Management using Cloud Computing

Alumni management is an important aspect of any educational institution or organization, as it helps maintain a connection with past members and fosters a sense of community. With the advent of cloud computing, it has become possible to manage alumni data in a more efficient and cost-effective manner. This paper aims to explore the benefits and potential applications of alumni management using cloud computing. By centralizing alumni information in a secure and accessible platform, organizations can streamline their operations, improve communication with alumni, and provide online resources for alumni engagement. Additionally, the scalability and security features of cloud computing can offer significant advantages over traditional on-premise solutions. This paper will also discuss some of the challenges and considerations for organizations looking to implement cloud-based alumni management systems.
THE EFFECTIVENESS OF USING SILENT WAY METHOD WITH SPELLING GAME IN IMPROVING STUDENTS’ VOCABULARY MASTERY

The objective of this research is to find out whether the use of the silent way with spelling games can improve students’ vocabulary in the eighth grade of SMPN 8 Palu or not. The knowledge of the English language in the eighth grade of SMP 8 Palu is still low, especially in vocabulary. This research aims to obtain empirical evidence about the effect of using the silent way method with spelling games. The population were all eighth-grade students of SMP 8 Palu. The sample were 44 students. The research employs a quasi-experimental design. In the experimental class, the researcher used the silent way method with a spelling game, and in the control class, the researcher used the conventional method strategy (memorizing). The researcher used an instrument in the form of multiple choice and matching tests. The instrument was given in pre-test and post-test. The finding indicated that there was a different score of the final significant mean between the classes, the serve of the experimental class was 73,40 while the final mean of the control class was 63,6. The hypothesis test shows that significant level of 5 % t-test 4,255 &gt; t-table 1,682 so, it can be stated that H0 (Null hypothesis) was rejected and Ha (Alternative hypothesis) was accepted. Therefore, it can be concluded that the use of the Silent Way method with the Spelling Game was effective in improving students’ vocabulary in the eighth grade at SMP 8 Palu in the academic year 2021/2022.
Model Pembelajaran Kreatif Produktif untuk Meningkatkan Hasil Belajar Siswa Pada Materi Menulis Puisi Bebas di MTs Negeri 3 Kebumen Tahun Pelajaran 2022/2023

This study aims to improve the learning outcomes of free poetry writing through the application of a Creative Productive Learning Model and assist teachers in evaluating various student and teacher weaknesses in the learning outcomes achieved as a result of the previous teaching and learning process. This research contains efforts to overcome students' problems in learning Indonesian in writing free poetry in class VII-H of MTs Negeri 3 Kebumen in the 2022/2023 academic year. The problem that occurred in this class was that the learning outcomes of free poetry writing were still low. There are 34 students in class VIII-H, consisting of 22 male students and 12 female students. The average score is still 74.91 with a classical completeness of 58.82%. Students still have difficulties in writing free poetry, especially those related to the suitability of content with themes, rhymes, diction, and the use of figure of speech. After the application of the Creative Productive Learning Model there has been an increase in learning outcomes or at the second meeting which can be observed based on predetermined indicators. Evidence of increased learning outcomes in writing free poetry in class VIII-H students of MTs Negeri 3 Kebumen through the Creative Productive Learning Model is shown by the percentage of student learning outcomes that has increased, from before the application of the Creative Productive Learning Model 58.82%, to 94.12% after application of Productive Creative Learning Model. While the average value of learning outcomes also increased from before the implementation of the Productive Creative Learning Model 74.91, to 84.36.
IMPROVING VOCABULARY MASTERY THROUGH CROSSWORD PUZZLE

This research aims at finding out the use of crossword puzzle in improving vocabulary mastery at seven grade students of SMP Negeri 10 Palu. This research applied a quasi-experimental design, in which there were two groups, an experimental and a control group. Seven grade E was the experimental group, while seven grade F was the control group. This research involved 50 students of SMP Negeri 10 Palu. The samples of this research were taken from the population of grade seven students by using a purposive sampling technique. The researcher used tests as the instrument for collecting data. The tests were divided into two; pre-test and post-test which were given to the experimental and control group. The treatment was conducted six times and was given to the experimental group by using a crossword puzzle, while the control group used the other technique. The data obtained from the test were analysed statistically. From the analysis, there was a difference between the achievement of the experimental (85.5) and the control group (44.2). It was based on the hypothesis testing done, by using 0.05 level of significance and 48 degrees of freedom (df), the researcher found that t-counted (6.08) is higher than t-table (2.0126). It means that the hypothesis (Ha) is accepted or in other words, the use of crossword puzzles has a significant effect on students’ learning outcomes in learning vocabulary.
ANALISIS GAYA BELAJAR DITINJAU DARI HASIL BELAJAR SISWA KELAS V PADA TEMA 8 SUBTEMA 1 PEMBELAJARAN 6

The purpose of this research is to investigate the various learning styles of fifth-grade students at SD N Sawah Besar 01 Semarang, as assessed by their learning outcomes in Theme 8, Subtheme 1, Lesson 6. Learning style refers to the way students absorb, organize, and process information acquired during the learning process. Learning outcomes represent the experiences gained by students, including their cognitive abilities in solving given problems. This study employed a qualitative descriptive method. Data collection techniques included observation, questionnaires, and documentation. The research findings indicate differences in learning styles among fifth-grade students, including visual, auditory, and kinesthetic learning styles.
Empowering State High School 3 Mandau Duri Teachers: Training on E-Book Creation with Flipbook Application

Abstract&#x0D; This community service project aims to train secondary school teachers at SMA Negeri 3 Mandau, Duri-Riau, to create electronic books (e-books) using Flipbook software. The objective is to equip teachers with the necessary skills to develop e-books as online and face-to-face instruction materials. These e-books allow students to access them anytime, anywhere, particularly during remote learning. The training program spanned two weeks and included training and mentoring sessions, with 30 participants in attendance. Flipbuilder and Kvisoft Flipbook Maker were utilized as flipbook maker applications. The training yielded positive results, demonstrating participants' proficiency in creating and designing e-books for online use. The future goal is to enhance these e-books further and publish them as teaching materials with an ISSN.&#x0D; Keywords: e-book, flipbook maker, English material, Senior high School&#x0D;
INOVASI DALAM MANAJEMEN PENDIDIKAN: IMPLEMENTASI PENGGUNAAN CANVA SEBAGAI MEDIA PEMBELAJARAN

To produce quality learning, good management is needed that can support the achievement of educational goals. In management at school, the principal has an important role. The principal serves as a motivator and supervisor of teachers so that they are able to modify the learning that is carried out at school. One of them is the use of technology as a learning medium that is able to facilitate teachers in teaching and provides opportunities for students to be creative according to their imagination. This research is to explore the use of Canva as a learning medium in elementary schools and to discuss the benefits and potential of using Canva in the learning process. The research was conducted using a descriptive descriptive approach with the results of the research namely obtaining information that the supporting factors in implementing Canva as a learning medium include: 1) Infrastructure that supports the presence of a number of chromebooks in schools. 2) Students have a high curiosity and passion for learning. 3) The Canva app is easy to use on PC and mobile devices. 4) Videos for learning can be seen repeatedly. Implementation of Canva as a learning medium in elementary schools has a positive impact on students, including students being able to understand material easily, students are more enthusiastic about learning, and being able to train students to be confident by presenting material through learning media .&#x0D;
Pelatihan SIPAKPRIH untuk Deteksi Dini Preeklamsia sebagai Dukungan Peningkatan Kinerja IBI Kabupaten Cilacap

IBI (Indonesian Midwives Association) Cilacap Regency is a forum for the association of midwife medical personnel in the Cilacap Regency. The performance of midwives can be continuously improved through training that supports all health service activities in the community. One of them is training in the use of information systems to detect the presence of preeclampsia in pregnant women (SIPAKPRIH) from the first to the third trimester by selecting the causative factors experienced by pregnant women. Midwives can take advantage of the expert system to support the performance of midwives in terms of health services for the community, especially pregnant women and the babies/fetus they contain. The solution proposed through this PkM activity is to improve the performance of midwives, especially midwives in Cilacap Regency in supporting health service activities to the community that are useful for monitoring the health of mothers and babies during pregnancy. The output target of this PkM activity is to increase the skills and knowledge of midwives for monitoring the health of pregnant women who are detected with preeclampsia through optimizing SIPAKPRIH.
PENINGKATAN HASIL BELAJAR MELALUI MODEL NUMBER HEAD TOGETHER BERBANTUAN MEDIA PERMAINAN ENGKLEK PADA SISWA KELAS VI DI SD NEGERI SARIREJO

The study aims to analyze the improvement of learning outcomes of grade VI students of SD Negeri Sarirejo with a total of 25 students. The research method used is classroom action research. The research stage consists of: planning, action, supervision, reflection. Data collection methods of interviews, observations, tests and documentation. Data collection instruments in the form of observations, tests and documentation. Data analysis techniques are qualitative and quantitative descriptive data analysis techniques. The results showed that the learning outcomes of grade VI students of SD Negeri Sarirejo with an increase of 26% from cycles I and II. The results of the First Cycle Analysis showed that 62% of student learning outcomes experienced a significant increase in the second cycle of 88% in the good category. So the use of NHT using crank game media can improve student learning outcomes.
Applying Blockchain Technology and Facial Recognition &#x0D;to Unmanned Stores

In this study, we utilize blockchain to design an information transmission system for unmanned stores.It is aimed to create a network for exchanging information that does not rely on a third party, a so-called decentralized system.To achieve it, a peer-to-peer (P2P) network replaces the master-slave architecture and uses asymmetric encryption to identify the system users.To authenticate the identities of the stores' customers, we use the face recognition network FaceNet developed by Google.FaceNet has several advantages that make it suitable for performing identity authentication in an unmanned store, including its high accuracy and convenience.A database of face images is required to perform facial recognition, but to address privacy concerns, every pixel in all images in the database is encrypted using the Rivest-Sharmir-Adleman (RSA) algorithm.The system proposed in this paper has three identity endpoints: the host end, the recognition end, and the client end.Messages are transmitted through a P2P network, and a directed acyclic graph is used to achieve message broadcasting while avoiding infinite loops when sending and receiving messages.A sidechain is used to change the structure and consensus mechanism of a traditional blockchain so that they can apply to more scenarios, thereby increasing scalability.The simulation results are displayed via the user interface.
EFL Learners’ Reading Comprehension Level: What Do They Portray?

&lt;p&gt;Levelling reading comprehension may help students learning and teacher course designing. This study attempts to portray the level of EFL reading comprehension in a public university in Jambi, Indonesia. The participants were 78 EFL learners who were registered in the academic year 2020-2021. The data were collected through administering a set of adapted reading test and calculated based on the indicator of the scoring system and criteria. These data were classified into each level of reading comprehension which is described in the form of percentage and presented through diagram and chart. The major findings of this study reveal that. 1) there were 77 or (99%) participants can complete most of the literal test items and they just achieved literal level of comprehension of reading skill. 2) there were 24 or (31%) participants were able to answer all inferential test items successfully and they just reach inferential level of reading comprehension. 3) there were 19 or (24%) participants can give their answer critically and they just obtained a critical level of reading comprehension. It is interpreted that numerous students were still in the position of the literal level which is regarded as a very low or basic level of reading comprehension. So, it is strongly recommended that EFL learners at Universitas Jambi require an intensive practice of reading to achieve a highest level of reading comprehension.&lt;/p&gt;
Impact of motivation on employee engagement: A literature review

Motivation is the influencing factor for an effective employee engagement in any sector of work. However, the role, function, influencing impact and outcome of motivation on employee engagement can vary from one industry to another. This review attempts to scrutinize the work done for employee engagement by motivating them in educational sector in comparison to other sectors. The framework used to explain the relation between employee engagement and motivation were, need-satisfaction, demand-resource. The audit finding showed that exceptionally restricted concentrate on zeroed in on the effect of motivation (intrinsic and extrinsic) on employee engagement in the educational sector, although intrinsic and extrinsic motivation separately showed the relation between motivation and employee performance. The study covered different theories of employee engagement and motivation. It was determined that previous work is lacking on various fronts, i.e., personality and crosscultural differences in employee engagement and also the motivation crowding theory effect on employee engagement.
Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

The power output state of photovoltaic power generation is affected by the earth's rotation and solar radiation intensity. On the one hand, its output sequence has daily periodicity; on the other hand, it has discrete randomness. With the development of new energy economy, the proportion of photovoltaic energy increased accordingly. In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation, this paper proposes the short-term prediction of photovoltaic power generation based on the improved multi-scale permutation entropy, local mean decomposition and singular spectrum analysis algorithm. Firstly, taking the power output per unit day as the research object, the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions, and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy, sunny, abrupt, cloudy. Then, local mean decomposition (LMD) is used to decompose the output sequence, so as to extract more detail components of the reconstructed output sequence. Finally, combined with the weather forecast of the Meteorological Bureau for the next day, the singular spectrum analysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather. Through the verification and analysis of examples, the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared. The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator, and has the advantages of simple structure and high prediction accuracy.