Reviewerly/exHarmony huggingface dataset:
Building a COVID-Safe Navigation App Using a Meta-Model Based Context Server

Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a meta-model based approach can be key to achieving this goal. In this paper, we present our meta-model based methodology, which allows us to define and build application-specific context models and the integration of sensor data without any programming. We describe how that methodology is applied with the implementation of a relatively simple context-aware COVID-safe navigation app. The outcome showed that programmers with no experience in context-awareness were able to understand the concepts easily and were able to effectively use it after receiving a short training. Therefore, context-awareness is able to be implemented within a short amount of time. We conclude that this can also be the case for the development of other context-aware applications, which have the same context-awareness characteristics. We have also identified further optimization potential, which we will discuss at the conclusion of this article.
A Study on Object Detection and Tracking of a Mobile Robot Using CIE L^* a^* b^* Color Space

Autonomous vehicles are increasingly used in daily life and industrial applications. Mobile robot technologies lead to autonomous architectures in these areas. The path planning methods of mobile robots contain differences in the purpose they realize. This trajectory planning from a determined starting point to the target point brings many techniques from image processing to artificial intelligence. In the study, an application with a unique design has been carried out on the tracking of circular objects with different diameters and colors by a mobile robot. Moving object is detected with CIE L^* a^* b^* color space with RGB-D camera by utilizing the ROS server-client architecture. The mobile robot tracks the detected object at a certain distance at a constant speed. Image filtering parameters are processed by the mobile robot in the Matlab environment together with the publisher-subscriber parameters. Thus, two circular objects with different colors, detected because of image processing and determined beforehand, are continuously followed by the mobile robot at a certain speed. Experiments were carried out using different diameter, size tolerance and color parameters in the image depending on the CIE L^* a^* b^* color space.
Penerapan Metode K-Means dalam Pengelompokan Data Penduduk Tidak Mampu di Distrik Oransbari

&#x0D; &#x0D; &#x0D; Proverty is a serious problem, the occurrence of proverty in the community is caused by a condition of the inability of the family economically to meet primary needs. Poor people are found in almost every country, city, and region. One of them is in the Oransbari District, which is one of the areas in Indonesia where the population does not receive assistance evenly. Based on these conditions, clustering is carried out to assist the district in grouping the poor population, so that the assistance provided can be right on target. With this problem, data mining with k-means clustering method used in clustering the poor population to make it easier for the Oransbari District to provide the population so that it is right on target. The data used is the data of the poor population in 2020 which amounted to 1872 with 17 attributes. Based on the results of tests carried out by applying the k-means algorithm, the results obtained with 3 clusters, the first cluster with a population of 471 with the category of poor population with medium priority, the second cluster has a population of 428 with a high priority category of poor population, and the third cluster has a population of 826 a low priority category of poor population. The k-means method is expected to be able to assist the Oransbari District in making decisions so that assistance is more targeted.&#x0D; &#x0D; &#x0D;
Penerapan Metode K-Means untuk Clustering Data Anak Berdasarkan Kepemilikan Akta Kelahiran dan KIA

Having a birth certificate and KIA is very important for every child to have as proof of identity. However, in reality, the number of birth certificates and KIA in Manokwari Regency is not proportional to the number of children. This study aims to classify children's data based on the number of birth certificates and ownership of KIA in Manokwari district by using the K-Means clustering method to produce sub-district groupings with high coverage of non-ownership of birth certificates and KIA, so that it can assist the Department of Population and Civil Registry of Manokwari Regency in provide targeted service programs. This study uses the Davies Bouildin Index (DBI) method to determine the optimum number of clusters used. The optimum number of clusters obtained is 4 with the lowest DBI value of 0.069 so that 4 clusters are formed, namely cluster 0 with a fairly low coverage category, cluster 1 with a fairly high coverage category, cluster 2 in a high coverage category, and cluster 3 in a very high coverage category. The K-Means clustering method succeeded in grouping sub-districts in Manokwari district, as well as informing the number of sub-districts with high coverage that do not have birth certificates and KIA.
Analisis Keamanan Jaringan dari Serangan DoS pada Sistem Inventaris Sanggar Tari Natya Lakshita menggunakan IDS

Information technology is advancing very quickly. Currently, there is highly qualified support for internet facilities. A quality internet service has both advantages and disadvantages for its users. An example of the negative impact of the development of internet technology is attacks from irresponsible parties or often called hackers. Sanggar Tari Natya Lakshita’s Inventory System is a newly built system, so attack testing is needed because network security is important to maintain data integration in the network. The test is carried out using a DoS attack with the LOIC tool. IDS is the method used in research with the Snort tool that functions as an intruder detector. The study aims to determine the results and effects of attacks on the Inventory System and determine how the IDS framework works with the Snort tool in detecting attacks. carried using 1 computer and 1 laptop. The results of the attack on the inventory system showed that Snort succeeded in detecting an attack sent by LOIC by displaying the attacker's IP and IP target through port 80, then the recommendations were given related to the stages of handling network security based on CSIRT guidelines at Sanggar Tari Natya Lakshita that can be implemented.
Imaged Based Authentication System dengan Reduced Difference Expansion

Authentication is an important step in a system. Text-based authentication is an authentication alternative that is currently widely used. However, text-based authentication has the disadvantage of being ineffective when users have multiple accounts. This weakness can be overcome using image-based authentication. The implementation of image-based authentication can use the Reduced Difference Expansion (RDE) steganography method. application of image-based authentication, utilizing images as authentication media. RDE utilizes the reduced pixel difference as a place to insert credential data. Testing the image in this study, the image has an average similarity of 40 dB, indicating that the image that is inserted with credentials and that is not inserted has a high similarity. The similarity increases the security of the image from theft. The average character capacity that can be accommodated is 21,451 characters, a large enough capacity to accommodate credential data. The image is very sensitive to changes, so there is a slight change in the image, causing the image to not be used for authentication
Analisis Sentimen Opini Publik Terhadap Program Vaksinasi Covid-19 Di Indonesia Pada Twitter Menggunakan Metode Naive Bayes Classifier

The COVID-19 virus emerged in December 2019 in China and actively spread throughout the world including Indonesia in early 2020. Its spread is very fast and has caused millions of deaths. Therefore, the Indonesian government is actively holding a COVID-19 vaccination program to prevent the spread of the virus and make the public immune to the virus. But the program invites pros and cons among the community. Twitter is one of the social media that is famous for being a medium of opinion from the general public. The process of sentiment analysis can find and solve problems based on public opinion on social media such as Instagram. The classification method used in this research is Naïve Bayes Classifier. The dataset can be obtained from data crawling process using Google Collabs and python programming language. The total dataset obtained is 2000. The data the labelled as positive, neutral, or negative. The labelling process result showed 1579 positive data, 277 negative data, and 144 neutral data. Then pre-processing is carried out on the data that has been labeled before, also word weighting process using TF-IDF. After that modelling is carried out using Naïve Bayes Classifier and the last process is evaluation-testing. The high accuracy of the result from fourth experiment which compare 90% data training with 10% data testing produce 86% accuracy. While the result of sentiment test show that positive sentiment more than negative sentiment and neutral sentiment.
Desain Sistem Berbasis Web Penunjang Pemasaran Limbah Ternak Kelinci (LTK) Sebagai Bahan Baku Pupuk Organik

&#x0D; &#x0D; &#x0D; CV. Mitra Ternak Sejahtera packs livestock waste of their broiler rabbits and ornamental rabbits to be sold as raw material for fertilizer. The sale of rabbit manure waste utilizes a network of resellers that already exist related to the marketing of broiler rabbits and ornamental rabbits. Marketing of rabbit livestock waste is done through messaging applications on social media. Conventional marketing and the high demand for rabbit waste products pose a problem considering that the marketing of rabbit waste uses resellers who also market broiler rabbits and ornamental rabbits. Accuracy of order data and guarantee of availability of waste products that are ready to be marketed are a problem. To reduce product order fulfillment errors and make it easier for resellers and general consumers to find out product stock, this study designed a web-based system for marketing kelimci livestock waste. The system design uses the Agile methodology and the Rapid Application Development (RAD) model with the hope that this system can be developed sustainably and adapt to the needs of the system owner&#x0D; &#x0D; &#x0D;
USING SURVEY-QUESTION-READ-RECITE-REVIEW (SQ3R) METHOD FOR READING SHORT STORY IN TEACHING LITERATURE

In the teaching of literature, short stories are often used as instructional materials due to teaching time limit in class. Short story analysis involves the understanding of the story. The objectives of this research are to analyze and describe the use of SQ3R method in teaching literature, especially in short story by O’ Henry’s “The Gift of the Magi”. This research used the classroom action research, conducted within two cycles. The participants of the research are 34 students of Islamic College Jakarta in the academic year of 2020/2021. Techniques of collecting data were test and non-test. The results of this research showed that the application of Survey-Question-Read-Recite-Review (SQ3R) method for reading a short story in literature class can improve the student’s reading comprehension.
Optimasi Algoritma XGBoost Classifier Menggunakan Hyperparameter Gridesearch dan Random Search Pada Klasifikasi Penyakit Diabetes

&#x0D; &#x0D; &#x0D; Classification using XGBoost in this study was applied to diabetes data originating from the UCI Machine Learning website. The initial step in this research is to deal with missing values. Missing value is found in several features. These missing values need to be handled otherwise the XGBoost algorithm will not work. Missing value handling is done by adding a meaningful value as a substitute for the missing value. At the time of modeling, the dataset is divided into training data and test data. The training data used is 80% of the number of patients, while the test data is 20%. In this study, the dataset that had imputed missing values was subjected to three treatments, first without hyperparameters, secondly hyperparameter tuning using gridsearch, and third hyperparameter tuning using random search. In the first treatment, classification using XGBoost without hyperparameters obtained a negative log loss value of 25%, which means that the performance accuracy of the algorithm reaches 75%. As for the second treatment and the third treatment, namely by using gridsearch and random search, it produces the same negative log loss value, which is 5%, which means that the performance of the algorithm reaches 95%. Thus, the performance of gridsearch and random search can significantly increase the accuracy value&#x0D; &#x0D; &#x0D;
Deteksi Tepi untuk Mengidentifikasi Kanker Ginjal Menggunakan Metode Sobel, Roberts dan Canny

Kidneys are organs that function to filter metabolic waste in the blood and dispose of them in the form of urine. One of kidney disease is kidney cancer. Kidney cancer occurs due to gene mutations in kidney cells that cause kidney cells to grow abnormally and uncontrollably. To take an image of kidney cancer using a Magnetic Resonance Imaging (MRI) tool. The purpose of this research is to identify and recognize the pattern object of kidney cancer in the MRI image. To identify kidney cancer images, it begins with collecting image data, image processing, image edge detection, image thinning, and identification processes. Edge detection is used to detect the boundaries of objects in the image. The method used in this research is the Canny and Sobel method. The number of images taken were 23 images of kidney cancer samples. The results of this research show that the Canny method gives better image results than the Sobel image results
WOMEN OPPRESSION AND STRUGGLE IN THE NOVEL MOXIE BY JENNIFER MATHIEU

&#x0D; This study aims to analyze women oppression and struggle in the novel Moxie, this novel tells East Rockport Highschool because sexism and the patriarchy system act as triggers for sexual violence and sexism in schools. The purpose of this study was to determine the typesof oppressions that occur in novel Moxie and to determine women's struggle to the oppression. Using Marion Young's iris theory to find out various kinds of oppressions that occur in novel Moxie and women's resistance using 2 theories of feminism, namely radical feminism by Alison M. Jaggar is used to analyze how the patriarchy system triggers sexual coercion and multicultural feminism. This theory is used to analyze the patriarchy system that triggers sexual coercion that happens because of race and black skin. The research methodology in this research is qualitative descriptive, where relevant data is collected from the text or words found in the novel Moxie. This research resulted in womens oppression such as sexualharrassment, intimidation, and rape as a form of sexual coercion contained in novel moxie. This research also shows how women struggle against oppression that occurs becauseof the patriarchy system and sexism in schools. &#x0D;
ANALISIS PENERAPAN SISTEM INFORMASI AKUNTANSI TERHADAP PENGARUH HARGA PADA USAHA TANAMAN HIAS BUNGA SUBUR

The use of houseplants is growing day by day. This happens because during the pandemic, many residents are required to work and carry out their activities at home or at home. As a result of this the people began to grow houseplants. There are several things that result in an increase in demand for ornamental plants, namely from trends to business opportunities. The more enthusiasts, the need for houseplants is higher. According to the existing problems, research was carried out on the information system for selling ornamental plants using the website. Thus the sellers and buyers have a container to buy and sell plants. The purpose of this study is to find out a good accounting information system in the Fertile Flower Ornamental Plant Business. The form of research carried out in this mini-research is in the form of documentation and obeservation on the Fertile Flower Ornamental Plant business.
LANGUAGE DEVELOPMENT OF AUTISM CHILDREN IN ISLAMIC PSYCHOANALYTIC TREATMENT (Case Study at Southeast Sulawesi Autism Service Center)

Symptoms of autism, in general, are usually detected at the age of children who have not reached three years old, with varying levels in each child, ranging from mild to severe symptoms. These symptoms include constant difficulty in socializing, communicating and interacting with others verbally, difficulty in using and understanding language, and inability in using body language to convey meaning. Therefore, even though they have reached the age when speech development should occur, the children are unable to establish conversations or interactions with other people. Children with autism tend to repeat words or phrases spoken by others without forming their speech style and not developing their language skills. The objectives to be achieved in this study were to describe the language development problems of autistic children who were currently under psychoanalytic treatment at Kendari Autism Service Center and the factors that influenced them. The research findings showed that the language development abilities of autistic children in the phonological form in obtaining vowel sounds and diphthongs were good. However, they were still lacking in obtaining consonants. More practice was needed so that they could pronounce perfect phonemes. Meanwhile, autistic children in Kendari's autistic service could master nouns with more numbers than verbal and adjectives in lexicon skills. However, the phonological process that occurred in autistic children was very slow. This happened because they were sometimes like deaf people who could not hear what people were talking about. If called, they did not want to turn around. They also did not focus on interacting with other people. For example, he would answer if he was being spoken to, but his gaze was not on the person spoken to. Almost more than half of autistic children were unable to speak well. Their speech proned to be echolalia, literal, lack rhythm, lack vowels in the word produced, replacing or removing consonants contained in a word.
Towards a Scalable Permissioned Blockchain Framework for Supply Chain Management

Supply chains have evolved into vast ecosystems and have grown more dynamic in recent decades, yet they still lack flexibility and scalability. Supply chain management (SCM) applications benefit greatly from the capabilities of blockchain technology (BCT), which enables the creation of a distributed ecosystem. Since the need for blockchain rises, so does the desire for chains that are scalable, flexible, efficient, and economical. Sharding technology has recently been developed to address the issues associated with blockchains. In this work, we propose a blockchain architecture, a scalable and efficient supply chain framework that keeps all information locally, to allow businesses absolute control over data. We are proposing a sharded design, which divides the ledger into multiple chains to enable scalability for processing transaction load. A qualitative analysis has been performed to prove that a scalable network can maintain maximum throughput in a dynamic environment.
Elderly Care Home Robot using Emotion Recognition, Voice Recognition and Medicine Scheduling

The robotic concept is used for several tasks to easier human day-to-day tasks. There are various recreational studies have been done on the elderly people’s care system. In this study, the system can identify the elderly people’s emotional status using thermal image processing that eliminates the halo effect issue in thermal images using a single discriminator Cycle-GAN model, serving medicine to elderly people by moving towards the elderly person while avoiding obstacles using point to point algorithm and obstacle avoidance and identify the semantic analysis by using web ontology based language. The integrated system is evaluated using the Gazebo simulator because the cost is lower than implementing the features in a real robot.
The Quality Criteria of Pahang Fake News Model during Covid-19 Pandemic: According to Uses and Gratification Theory

Fake news spread during the pandemic Covid-19 has resulted in an excessive spread of fake news, which leads the public to believe in something that is not true and also spreads hoaxes among them.The researcher investigates which items are valid or not in this study by using five variables from the uses and gratification theory.Based on the non-probability sampling method, this quantitative study was conducted among Pahang citizen, and the data collected came from as many as 130 respondents.Based on the validity of our measure, the data revealed that Cronbach's Alpha for all variables is greater than 0.90.The KMO index is also greater than 0.60, indicating high convergent validity.
Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals

American Sign Language is a popular language for deaf individuals. Communication is made easier for these people through sign language. However, in a digital era like today, there is a need for these people to be able to communicate online, and even get help from technology to communicate in person with non sign language speakers. This research will present a program able to translate American sign language to plain English. This study aims to use the OpenCV library to recognize hand signals, also a trained model to identify images so that the program can then translate them to words and letters. The program uses a data set of over 2000 images which will be in this case the largest data set available. With over 90\% of accuracy it results in a basic computer program with the largest data set available that would make possible for users to communicate with a wide variety of words and expressions.
The Impact of AI Chatbot on Long-Term Relationships between Customers and Hotels

This article studies the critical determinants toward AI Chatbot (anonymity, convenience, and problem-solving) on quality communication and long-term relationships between customers and hotels. The article employs correlation analysis and structural equation modeling (SEM) to analyze the data collected in the structured questionnaire survey in Vietnam. Empirical results indicate that three chatbot dimensions have a significantly positive impact on communication quality. Problem-solving is found to be the highest influence on both communication quality and long-term relationship. Meanwhile, anonymity and convenience were revealed to have indirect effects on long-term relationship through communication quality. The findings provide an enhanced understanding of how AI Chatbot influences customer experience with hotel’ Chatbot. This paper also contributes several implications for firms post COVID-19 pandemic.
Technology Transfer in Foreign Higher Education Institutions: The Example of Catholic University of Leuven

The convergence of the scientific, educational and business sectors requires the search for new models and tools for the transfer of technology from the university environment to the work of enterprises in the real sector of the economy. On the example of the Catholic University of Leuven, approaches to the commercialization of the results of the intellectual activity of universities abroad are considered. It is shown that the active development of its own technology transfer center, which implements, among other things, initiatives in the field of mergers and acquisitions, has allowed KU Leuven to achieve outstanding results in creating its own innovation environment and take leading positions in the global rankings of world universities. The results obtained can be successfully transferred to the practice of Russian universities.