Reviewerly/exHarmony huggingface dataset:
Penguatan Kegiatan Pembelajaran IPS melalui Social Science Vocabulary Recognition Model through Guessing Games

The rapid development of learning has an influence on the learning process in the teaching unit. In the midst of current conditions, it is undeniable that it has an influence on the decline in student interest in learning. The current learning system process is through the concept of distance learning, of course, this must be followed by students, even though students experience a decrease in interest in learning and begin to feel the point of saturation in the learning process. The purpose of this study is to improve social science vocabulary recognition models through guessing games in the learning process through conditions during the adaptation period of new habits, so that it will lead to students' learning motivation, then to find out the increase in students' interest in learning social studies in the learning process at time to adapt to new habits. The research method used is a qualitative research approach by looking for data in the form of case studies on students, and direct observation on students. Data collection techniques were carried out using interview techniques, documentation techniques and case studies. Data analysis techniques were carried out through data collection, data reduction, data presentation and data verification. The results of this study have a positive impact on interest in learning and increasing social skills for students in understanding vocabulary in social studies learning. So that through learning activities during the adaptation period of new habits through the method of social science vocabulary recognition model through guessing games so that it can restore students' interest in learning during the adaptation period of new habits, especially in current learning.
Klasifikasi Penyakit Diabetes Pada Imbalanced Class Dataset Menggunakan Algoritme Stacking

Diabetes is a disease that has the potential to cause death. Based on a report from the IDF (International Diabetes Federation), it was stated that in 2019 there were 463 million people in the world suffering from this disease. According to the Ministry of Health, Indonesia is a country that is included in the top 10 highest in the world by the number of people with diabetes. Machine learning models can be a solution for the early detection of diabetes based on history and available data. The majority of the research that has been done chiefly uses a single classifier. The single classifier model has a weakness when faced with class imbalance conditions in the dataset. Therefore, this study uses the Stacking Model for the classification and prediction process on the diabetes dataset. The goal is to improve the performance of a single classifier. In addition, the Stacking Model is expected to be one of the solutions for the classification of diabetes in the imbalanced class dataset. Based on two test experiments that have been carried out using two different datasets. The Stacking algorithm can produce an accuracy value of 89%, TPR value of 89%, TNR value of 85%, and G-Mean of 86.98% in the first dataset and can produce an accuracy value of 96%, TPR value of 96%, TNR value of 94%, and G-Mean of 94.99% in the second dataset. These results are better than single classifiers such as C4.5, K-NN, and SVM of the four indicators evaluated in both diabetes datasets. Thus, the proposed algorithm, namely Stacking (C4.5-SVM), can be a solution for classifying diabetes datasets with unbalanced class distribution conditions.
Online Examination System Using Java

Abstract: MCQ based Online Examination System using java is a Test Management Software, which offers a complete solution for Computer Based Test (CBT) .They are used to set up multiple choice tests for set time periods that when submitted are automatically corrected and the results are displayed immediately after submitting the
Penerapan Metode Time Charter Party Pada Sistem Informasi Penyewaan Alat Camping Berbasis Web

Sinar Adventure Store is a shop that provides camping equipment, this store has many customers who want to rent camping equipment such as tents, carril bags, stoves and sling bags. But the camping equipment rental transaction at this shop still uses the conventional process, so there are still many errors that occur in writing information and data reports on this camping equipment rental. This is the author's reference in designing a web-based camping equipment rental information system, with HTML, CSS, and PHP programming languages as the database. This system is designed using the waterfall method and the system follows the flow of the Time Charter Party method. In data processing, such as recording rental transaction data, it is still stored in a ledger storage media so that data security is not guaranteed because there is no more searching for camping equipment data at the Sinar Adventure Store who still has to wait a long time because they have to find one data person in the books. The purpose of creating this rental system is to overcome the problems that are currently happening at the Sinar Adventure Store store. The results of this study are to provide convenience in the processing of camping equipment data at the Sinar Adventure Store store such as admin data, data rental, ordering, checkout and to simplify the data search process in addition to having a more effective and larger storage media.
Fully Communication Oriented Information Modeling On SME Information Systems Development

Information modeling a very important role in the development of information systems today. Information modeling is an activity to create a conceptual model that includes all significant information in business processes. Using information modeling, a machine is needed for implementation, and redundancy and anomaly problems are also common in databases. This problem arises when the database is not normalized. To solve the problem, this research will analyze the SME information system using the Fully Communication Oriented Information Modeling (FCO-IM) method and compare it with the method without FCO-IM made by 12 designers. The results of the analysis, information modeling using FCO-IM method can produce a relational data schema that already meets 3NF normalization and is suitable for implementation in SME information system development so that it can be used as an option in data modeling and can avoid data redundancy problems.
A Novel Image Denoising and Segmentation Using Machine Learning with SRM Strategy

Objectives: In the last decade, artificial intelligence (AI) and machine learning (ML) have a significant impact on image analysis and segmentation.The most demanding aspect in digital image processing is efficient segmentation to extract the desired features or recognize the hidden patterns of the digital images, which are one of the major challenges.Even in existing segmentation techniques, due to under segmentation issues, particularly in remote or arial image analysis, necessary object features and residual details are not properly segmented.Therefore, the study presents a new method for image segmentation using machine learning, which addresses these limitations.Methods: This article presents a novel approach for arial image denoising and segmentation using unsupervised learning.The Discrete Wavelet Transform (DWT) is primarily used as a pre-processing tool, while edge details of the decomposed image are automatically preserved with the help of machine understanding.The use of a fast Non-Local (NL)-means filter provides a better visual effect for low-frequency image features, and the filtered image is partitioned into the number of clusters by Minimum-Spanning Tree (MST) clustering algorithm.Further, Statistical Region Merging (SRM) is used to eliminate the unwanted regions of the clustered image to give meaningful image details.Finally, the segmented image is projected at the wavelet restoration level.Here, the standard images are extracted from the SIPI database, and the system does not require training prototypes but works in an "unsupervised" way.Findings: The proposed system segment 1014 regions in the first phase and the segmented image features efficiently recognize the hidden patterns of the arial image (7.1.06).However, to track the required object features, statistical Region Merging (SRM) is utilized, a drastic variation in the merging process eliminates the annoying details and brings effective outcomes, which involves 29 essential features with retained residual details at level-2 decomposition and is compared with leading segmentation techniques.The denoising performance of the suggested study provides a 21.73 Peak Signal to Noise Ratio (PSNR) value in 17.96 elapsed time.The
On a random search tree: asymptotic enumeration of vertices by distance from leaves – CORRIGENDUM

Abstract We correct typographical errors in our original paper.
The Role of the Digital Economy in The Economy, Education, and Health in Indonesia

This study examines the digital economy shown by internet users with economic growth, education, health, and inflation.This research examines data from 2000 until 2020 to be able to produce "autoregressive vectors" that may be used to evaluate the causal link between variables. Based on secondary data from the World Bank, the following multivariate regression model was used to investigate the causal link between Internet Users, Gross Domestic Product, Education, Health and Inflation in Indonesia. The results of this study are quite surprising where technological literacy in Indonesia actually suppresses GDP, this shows that the use of the internet for Indonesian people in production is not yet optimal. Or most Indonesians use the internet as entertainment and consume digital products from abroad so internet technology literacy suppresses GDP. However, internet literacy supports education in Indonesia where education in Indonesia uses internet technology massively. Education itself encourages internet literacy in Indonesia significantly. However, the literacy of internet users actually suppresses the health sector where the health sector in Indonesia during the research period was dominated by offline and the health sector did not provide a significant boost to internet literacy in Indonesia. The digital economy in Indonesia has been proven to suppress inflation, although not significantly. This illustrates that the digital economy has the potential to suppress inflation and in the current case of Indonesia, the digital economy is not yet optimal currently the majority of internet users in Indonesia are users or consumers of digital products from countries outside Indonesia so they have not been able to encourage domestic economic growth.
Implementasi Metode Naïve Bayes untuk Pemilihan Pengobatan Tumor Tulang

Decision support system is an interactive system that helps decision making through the use of data and decision models to solve problems that are semi-structured and unstructured. This study implements the Naive Bayes method because this method has advantages compared to other methods, and the Naive Bayes method is a decision-making to predict probability-based using the values entered, in the form of criteria needed. Bone Tumor is a primary malignancy in children and adolescents, which attacks in adolescents aged 10 to 20 years. Treatment of osteosarcoma can be done by radical amputation or limb salvage procedure, depending on the severity of the tumor. The purpose of this study was to obtain treatment information selected by bone tumor patients using medical record data with sample collection method. In the hope that this information can be a consideration for bone tumor patients who are still hesitant to complete treatment in order to be eager to complete treatment. The results obtained the number of cases of bone tumors is as many as 19 cases, and Limb Salvage is the most widely chosen treatment by bone tumor patients. This study also used rapidminer to see the results of validation. The classification results obtained are accuracy value 80%.
Sistem Informasi Penjualan Emas Pada Perusahaan Modern Investasi Berbasis Website

Computers provide the right solution in producing the most recent information. As is the case in every company, both government-owned and private companies have a relatively large number of transactions, so a database is needed that can store and process the data efficiently, quickly and can be used whenever needed.Modern Investments located at Jl. Raya Sekopek Plantaran, Kaliwungu is a gold bullion investment company that is very strategic and feasible to facilitate future economic changes to be better or more prosperous than before.In carrying out Modern Investments, employees process data from storage and installment payments still using a program that is still simple, and the marketing party records books for making prospective members, member installments and bookkeeping records in a ledger and then entered into the program.Based on the problems that exist in Modern Investments, the author wants to propose a sales administration application system design to be taken into consideration in helping speed up the process of recording cash and credit sales transactions and can provide the information needed Modern Investments in the form of member reports, cash sales reports, credit sales reports , and installment reports, the sales information system design using the web.Making this application is expected to be one of the efforts that can be made to overcome problems that often occur so that it can increase work effectiveness which of course will have an effect on improving the quality of service to customers.
IMPLEMENTATION OF INTERDISCIPLINARY RELATIONS IN THE PHYSICAL LABORATORY WORKSHOP FOR ENVIRONMENTAL SPECIALTIES

The role of a physical laboratory workshop in the system of training of specialists in ecological profile at International Sakharov Environmental Institute of Belarusian State University is analyzed. The features of conducting laboratory work in physics in the first year are considered. It is shown that the implementation of interdisciplinary connections between physics, higher mathematics, informatics and ecology increases the efficiency of mastering theoretical educational material, obtaining skills in working with physical instruments and equipment, as well as processing, presenting and analyzing experimental results.
File Storage on Cloud Using Cryptography

Abstract: Hybrid cryptography is implemented to provide the multilevel of encryption and decryption at both sender and receiver side which increase the security of the cloud storage. This security model gives the transparency to the cloud user. The hybrid encryption algorithm combines the advantages of fast encryption speed of AES algorithm, easy management of RSA algorithm key, and digital signature to ensure the secure transmission of confidential documents. Data/information is the most valuable asset for the modern electronic communication system. Securing data or information has become a challenge in this competitive world. There are many techniques for securing data/information such as cryptography, stenography etc. In this paper, hybrid cryptography has been applied using AES and RSA.AES and RSA algorithms are implemented to provide the multilevel of encryption and decryption at both sender and receiver side which increase the security of the cloud storage. This approach provides transparency to the cloud user as wellas cloud service provider in order to reduce the security threats. The proposed model is implemented in C and .NET. Data security is increased up to a maximum extent and it takes less time in uploading and downloading the text file as compare to existing system. [1] Index Terms: Hybrid, Symmetric, Asymmetric, Cloud, Cryptog-raphy.
Multi-Site and Multi-Scale Unbalanced Ship Detection Based on CenterNet

Object detection plays an essential role in the computer vision domain, especially the machine learning-based approach, which has developed rapidly in the past decades. However, the development of convolutional neural networks in the marine field is relatively slow, such as in ship classification and tracking. In this paper, ship detection is considered as a central point classification and regression task but discards the non-maximum suppression operation. We first improved the deep layer aggregation network to enhance the feature extraction capability of tiny targets, then reduced the number of parameters through the lightweight convolution module, and finally employed a unique activation function to enhance the nonlinearity of the model. By doing this, the improved network not only suits unbalanced sample ratios in classifying, but is more robust in scenarios where both the number and resolution of samples are unstable. Experimental results demonstrate that the proposed approach obtains outstanding performance and especially suits tiny object detection compared with current advanced methods. Furthermore, in contrast to the original CenterNet framework, the mAP of the proposed approach increased by 5.6%.
ADDRESSING CLASS IMBALANCE IN MULTI-CLASS IMAGE CLASSIFICATION BY MEANS OF AUXILIARY FEATURE SPACE RESTRICTIONS

Abstract. Learning from imbalanced class distributions generally leads to a classifier that is not able to distinguish classes with few training examples from the other classes. In the context of cultural heritage, addressing this problem becomes important when existing digital online collections consisting of images depicting artifacts and assigned semantic annotations shall be completed automatically; images with known annotations can be used to train a classifier that predicts missing information, where training data is often highly imbalanced. In the present paper, combining a classification loss with an auxiliary clustering loss is proposed to improve the classification performance particularly for underrepresented classes, where additionally different sampling strategies are applied. The proposed auxiliary loss aims to cluster feature vectors with respect to the semantic annotations as well as to visual properties of the images to be classified and thus, is supposed to help the classifier in distinguishing individual classes. We conduct an ablation study on a dataset consisting of images depicting silk fabrics coming along with annotations for different silk-related classification tasks. Experimental results show improvements of up to 10.5% in average F1-score and up to 20.8% in the F1-score averaged over the underrepresented classes in some classification tasks.
Enforcing feature correlation on cycle-consistent GAN generated functions: a first step in closing the synthetic measured gap found in SAR images

Due to their ability to capture images in a variety of environmental conditions, Synthetic Aperture Radars (SAR) are of particular interest in the automatic target recognition (ATR) domain. In order to develop SARATR machine learning (ML) algorithms, a large sample set indicative of the underlying population must be used. This is an issue since gathering SAR images, even for a single target, is an expensive and time consuming process. Recently a data set, known as the SAMPLE data set, consisting of synthetic SAR samples has been released. Ideally theses synthetic images can be used in place of real SAR samples. Unfortunately, training SAR-ATR ML algorithms with samples exclusively from the SAMPLE data set produces algorithms with poor performance on real SAR images. This paper is focused on creating new variants of cycle-consistent generative adversarial networks (CycleGAN) to produce a transformation function that maps a synthetic SAR image to a useful approximation of a real SAR image. By introducing a new feature correlation module to the cycle consistent GAN architecture we take the first steps in closing the gap between synthetic SAR images and measured SAR images.
Development of Pragmatic-Based English Learning Material for Front Office

This study aimed at (1) describing the realization of the use of teaching materials in learning English speaking skills in the field of front office services, (2) developing learning materials for English speaking skills in the field of front office services, and (3) examining the effectiveness the learning materials for English speaking skills in the field of front office services with a pragmatic approach. This research was conducted using Research and Development (R&amp;D) research methods and applying Borg and Gall (1983). Based on the results of the analysis, it was found that learning English for tourism and hospitality currently does not include linguistic elements in it. The books or modules available were limited. Based on this reality, this research develops two educational products, namely a pragmatic-based syllabus and module. The syllabus and modules have 12 learning topics that have been adapted to the use of English for hotel front office services. Learning materials for English speaking skills for front office services with a pragmatic approach are effective for use in organizing the teaching and learning process as evidenced by the t-test results, namely 0.001 (0.001 &lt;0.005). In addition, the perceptions of students and lecturers also showed a positive response to the modules developed in this study.
Online Agro Product Shop

Abstract: In this Online Agro product Shop Project we will build a user-friendly website in order to buy and sell agriculture products online. The main purpose to build this store is to facilitate farmers to buy seeds, pesticides, and fertilizers from anywhere through internet connectivity. To facilitate remote area farmers to buy agriculture products, there is a need to build an online agriculture product store. Through the Internet, customers and business owners can communicate with each other, share a different type of information and resource.
A Study on Reading Education Methods of ‘The guest and Mother’ Using Socio-cultural Context: Comparison with Chinese Novel Lu Xun’s ‘New Year Sacrifice’

This paper is a study on the reading education method of Love Guest and Mother using the socio-cultural context. Until now, understanding literary works in foreign language education has been a difficulty for foreign learners. One of the causes is that foreign learners lack the socio-cultural contextual knowledge necessary to understand literary texts. However, learners have knowledge of the socio-cultural context of their own country, although they lack knowledge of the socio-cultural context of Korea. Therefore, by activating the socio-cultural context of their own country related to Korean literature works, learners can build a world of text while fully associating and imagining the socio-cultural context of Korea. Starting with this awareness of the problem, this study first conducted a theoretical review of reading novels using socio-cultural contexts. Based on the theoretical review, the applicability of practical education was sought, and the Guest and Mother and Lu Xun’s New Year Sacrifice were selected as comparative works and the socio-cultural context was compared centering on the motif of widow’s remarriage. The Guest and Mother shows the socio-cultural context of the Korean Peninsula in the 1930s, and New Year Sacrifice shows the sociocultural context of China in the 1920s, and the two countries have something in common in that studying abroad was used as a means of governance. As Confucianism was solidified, the view of virtue inherent in it was also strengthened, and under this notion, ‘mother’ gave up love to avoid home care, and ‘Mrs. Xianglin’ was forced to do so. The motifs of the two novels are different in expression, but they are attributed to similar ethical morality. This study is significant in that it compared and analyzed the socio-cultural context of the two novels, focused on the common ‘remarry’ motif, and presented a reading education plan of "the guest and mother" using the socio-cultural context based on the results of the comparative analysis. (Seoul National University)