Reviewerly/exHarmony huggingface dataset:
Go Players Should Not Trust AI Win Rate

The advent of artificial intelligence (AI) has transformed the landscape of various strategic games, including Go. In 2016, the AI-powered engine AlphaGo defeated one of the world’s strongest players. Since then, Go engines have routinely been used by amateur and professional Go players to analyse theirgames. In the early stages of AI analysis, Go players relied solely on the AI win rate, the only available indicator. However, the AI win rate does not accurately reflect the win rate of human Go players and might be misleading. Katago, first released in 2019, is the first engine to provide score predictions in addition to win rates. While it is now possible to evaluate board positions with a score, it remains unclear how this score translates into human win rates. In this work, a large database of online and professional games is analysed to extract the win rate of a human player based on their strength and the stage of the game. As expected, the human win rate is significantly lower than the AI win rate, even for 9dan professional players. A general formula is provided to compute the win rate based on player strength and move number. This feature offers new insights into the relative importance of mistakes and can assist players in making improved decisions during games.
Explaining Go: Challenges in Achieving Explainability in AI Go Programs

There has been a push in recent years to provide better explanations for how AIs make their decisions. Most of this push has come from the ethical concerns that go hand in hand with AIs making decisions that affect humans. Outside of the strictly ethical concerns that have prompted the study of explainable AIs (XAIs), there has been research interest in the mere possibility of creating XAIs in various domains. In general, the more accurate we make our models the harder they are to explain. Go playing AIs like AlphaGo and KataGo provide fantastic examples of this phenomenon. In this paper, I discuss a non-exhaustive list of the leading theories of explanation and what each of these theories would say about the explainability of AI-played moves of Go. Finally, I consider the possibility of ever explaining AI-played Go moves in a way that meets the four principles of XAI. I conclude, somewhat pessimistically, that Go is not as imminently explainable as other domains. As such, the probability of having an XAI for Go that meets the four principles is low.
Analysis of the Knowledge Structure of Go

The potential implications of AlphaGo defeating a human player have not been fully discussed in the epistemological field. AlphaGo does not play in a nearly exhaustive way with a huge amount of computation, but has reached a higher level of “intuition” and “judgment”, which humans once thought was a difficult area for computer languages to break through. This phenomenon prompts us to rethink the structure of Go knowledge. From the perspective of epistemology, what kind of knowledge of Go is indeed reliable? Based on this fundamental question, this paper attempts to analyze the structure of Go knowledge. The main thought processes in the game of Go can be summarized as “intuition”, “calculation” and “judgement”, where rational deduction and empirical induction co-exist. In the past, the simple enumeration of knowledge points became the main focus of Go knowledge learning and teaching, now the nature of these knowledge points are distinguished, particularly the Go knowledge between“quantitative” and “non-quantitative”, moreover, the correlation between knowledge generation and both inherent human cognitive abilities and cognitive limits is presented. This paper analyzes the specific principles of how Go AI surpasses the human level of Go from the perspective of epistemology, provides theoretical support for how human players can leverage AI for new Go knowledge production in the future, and may serve as a bridge between Go and cognitive science research.
Of gods, tricks and weirdos—A perspective related to content, practices and aims in the usage of AR for touristic experiences and spatial storytelling

&lt;p&gt;The complicated and interwoven relation of the tourist as an explorer and in the same time as audience of digital content is the background of this perspective. The topic is strictly based on the work, and its impact, made in 10 years by the group “Komplex” in the field of creation of augmented reality experiences in urban space, mainly for social enterprises funded by cultural agencies. The transformation of citizens in tourists able to discover “further experiences” hidden in the urban environment and also the bridging of this experience with specific imaginary diffused in the web is the scenario that this perspective wants to highlight in order to achieve a multilayered set of impacts such: i) slow tourism, ii) cultural and technological activation of neglected areas, iii) twisting narratives related to specific neighbors, iv) inclusion of slices of the urban society far from the touristic hot spot.&lt;/p&gt;
The Effect of Infrastructure and the Utilization of Information Technology in Learning on the Quality of Education

This research was conducted to find the effect of infrastructure and information technology on learning. The problem in this study is the difference in the quality of education in the North Lombok Regency Junior High School, which has a different infrastructure and uses information technology in learning. This study uses a quantitative descriptive approach with comparative causal research methods. The population in this study consisted of 270 ASN teachers spread across 16 public junior high schools in North Lombok Regency. The sampling technique used proportional random sampling in each sub-population, and the sample was determined randomly. The sample in this study amounted to 160 teachers, and hypothesis testing was done using Analysis of Variance (ANOVA). The research results show that the infrastructure is adequate (69.04%). The use of information technology in learning is reasonably sufficient (68.51%), and the quality of education is quite good (81.04%). The results of hypothesis testing with a significance level of = 0.05 concluded: 1) Infrastructure has a positive effect on the quality of education (p=0.001); 2) The use of information technology in learning has a positive impact on the quality of education (p=0.000); 3) There is no interaction effect of infrastructure and the use of information technology in learning to improve the quality of education (p=0.140).
Future of Blockchain: Data Storage, Carbon Calculation, Accounting, and Emissions Trading

The paper explores various aspects of data storage technologies, including Solid-State Storage, Cloud Computing, Edge Computing, and Blockchain, in the context of their implications, advantages, and limitations. Each technology's impact on data storage, performance, security, scalability, and environmental considerations is examined. Carbon Footprint (CF) is introduced as a measure of the environmental impact of data storage methods. The paper then delves into carbon calculation approaches, emphasizing the importance of accurate measurement in a computing environment. The integration of Carbon Footprint and Blockchain technology is discussed, presenting a framework for managing carbon emissions in data storage. Carbon accounting methodologies, including spend-based, activity-based, and hybrid methods, are detailed along with their applications in estimating greenhouse gas emissions. Finally, the paper explores the intersection of Carbon Emission Trading and Blockchain, highlighting how Blockchain's transparency and security attributes can address challenges within carbon trading systems.
Development of Gesture Detection Application for the Exercise System and Accumulation of Reward Points

The COVID-19 pandemic has affected the daily lives of global citizens. Currently, it was reported that COVID-19 would last longer. Therefore, living with the COVID-19 outbreak will be the new normal. The restriction of physical contact leads to less exercise, especially outdoor activity, but more activities online. Although it will reduce the spread of the disease, but it has a negative effect on people's physical and mental health, so our team has come up with an exercise system to collect points and redeem rewards by detecting gestures by using applications to increase the practice of physical activity and enhance the health of personnel in various organizations, even people in residence can have physical activity. There were two types of exercise postures to choose from: squat and bicep curl (arm muscle exercises), which can be divided into two levels: easy and difficult. We concluded that the application could calculate points correctly and was very accurate in counting reps, especially with the bicep curl, but there was still a slight discrepancy in the count of squat reps, which can be further developed to increase accuracy.
PENERAPAN PEMBELAJARAN BERDIFERENSIASI DALAM PERSPEKTIF TEORI BELAJAR HUMANISTIK

This research aims to find out the application of differentiated learning from the perspective of humanistic learning theory. The concept used in this research provides nearly the same concept between differentiated learning and humanistic learning theory because both of them provide an understanding of the importance of humanizing humans to suit their characteristic. This research was conducted on 5th grade students of SD Negeri Kiyaran 2 Cangkringan. The method of this research used descriptive qualitative with a case study approach. The researcher in this research hope to find natural patterns that occur in the application of differentiated learning in the perspective of humanistic learning theory that occurs in the classroom. The researcher of this research observed learning activities starting from planning, implementing, and evaluating during the implementation of differentiated learning. The researcher gathered the data by used diagnostic tests, observation, work method, and final tests. The subjects of this research were the 5th grade students of SD Negeri Kiyaran 2 Cangkringan in the 2022/2023 academic year with a total of 14 students, consisting of 8 boys and 6 girls. The results of this research showed that the used of differentiated learning in the perspective of learning theory has a positive influence on creativity and learning outcomes of students. This is indicated by the increase in the average value of the creativity on students from the initial condition of 67.86 to 80.21. Moreover, differentiated learning in the perspective of learning theory can improve student learning outcomes by showing the average test score which was initially 79.29 increased to 84,86.
Sentiment Analysis of Review Data: A Deep Learning Approach Using User-Generated Content

As information technology progresses rapidly, social media platforms are experiencing exponential growth, accompanied by a surge in online content. Sentiment analysis (SA) of online evaluations has piqued the interest of researchers from various organizations, including academia, government, and private industry. It has become an increasingly hot area of study in the fields of Machine Learning (ML) and natural language processing (NLP). Deep Learning (DL) algorithms are currently being utilized in the same field to achieve remarkable results. Much SA research has been conducted in different languages such as English, Chinese, and Spanish, as well as various Indian languages like Hindi, Malayalam, and Bengali. However, languages like Assamese have received very little attention in this field of research. Hence, this research work provides a novel approach to sentiment analysis by demonstrating the effectiveness of deep neural network models for the less explored and scarce resource language, Assamese. This paper introduces a hybrid model, combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), termed LSTM-CNN, for Sentiment Analysis (SA). Keras word embeddings are employed for vectorization of the data. To achieve outcomes, our proposed models have employed dropout, max pooling, and batch normalization techniques. Experimental analysis is carried out on user-generated review content by translating the Bengali dataset into Assamese. Comparison and evaluation of the built models have been done with traditional machine learning models in predicting sentiment polarity. Comparative analysis shows that all the proposed models outperform with an accuracy of more than 98%.
PEMANFAATAN MEDIA IT PADA MATA PELAJARAN IPA BERDASARKAN GAYA BELAJAR KELAS V SDN GAJAHMUNGKUR 04

This study aims to analyze the use of IT media in science lessons in terms of visual, auditory, and kinesthetic learning styles, as well as analyze the factors that influence student learning styles. Researchers use a type of descriptive narrative qualitative research. The source of the data in this study were fifth grade students at SD N Gajahmungkur 04. Data collection techniques included interviews, observation and documentation. While the data analysis techniques in this study are data reduction, data display, and conclusion drawing/verification. The results of this study are; (a) Students with a visual learning style with image orientation. Students will easily remember material through visual associations. IT media used in the form of PowerPoint and pictures and videos; (b) Students with an auditory learning style are students who are reactive to sound. IT media that can be used are tape recorders and videos; (c) Students with a kinesthetic learning style read material with a pattern of moving their lips. The kinesthetic characters that exist in students with kinesthetic learning styles include liking to learn through manipulation and practice. IT media that can be used is in the form of learning game applications; (d) Factors that influence student learning styles are internal factors and external factors.Â Keywords: learning styles, media, IT
Usability Testing Kualitas Desain UI Pemahaman Literasi Digital Anak-Anak

In 2023, digital literacy has increased to be discussed which navigates human interaction with the current digital environment. The purpose of this study is to determine the relationship between digital literacy and user interface (UI) design quality using a usability testing approach. The study involved collecting data through a series of trials with participants representing different levels of digital literacy. The main focus of this study was to assess the extent to which the UI design could improve the digital literacy understanding of the users, namely school children. The parameters evaluated involved aspects of digital literacy, such as the ability to understand and evaluate digital information, as well as usability elements such as interface clarity, navigation efficiency, and user engagement level. The approach used is the design thinking method which focuses on the end result only. Usability testing is an important evaluation method in measuring the effectiveness, efficiency, and user satisfaction of a user interface (UI). This research focuses on the use of usability testing to assess the quality of UI design in the context of understanding digital literacy. The results of this study can provide insight into how the level of digital literacy can affect the user experience in using digital applications and contribute to the development of UIs that are more user-friendly and accessible to various levels of society.
Sistem Informasi Administrasi Surat Berbasis Web Pada Kantor Desa Menerapkan Metode Waterfall

A web-based mail administration information system is used to manage the administrative service process for submitting correspondence. The process of submitting correspondence to Rojopolo Village is still done manually using the Microsoft Word application. The obstacle faced by service officers is when they need data reports on letter submissions from residents, because letter data is only in the form of archival paper which carries the risk of losing data, besides that the manual letter submission process takes a long time so that the letter administration service is less effective and efficient. To overcome this problem, a Web-based Mail Administration Information System will be built at the Rojopolo Village Office so that it can improve the performance of the village service department in processing data so that services are more effective and efficient. The system development method uses the waterfall method and system design uses unifield modeling language (UML) diagrams. Based on the results of black box testing, the features built (such as letter submission, letter list, population registration, master data, reports) work 100%. The system was built using the Visual Basic .Net programming language and MSSQL Server database.
Perancangan Sistem Informasi Presensi Online Karyawan Berbasis Website dengan Face Record dan Geo Location

This research discusses the development of an online employee attendance system in the context of the company. Attendance data includes employee attendance, arrival and return information, as well as absence status such as sickness or clearance. Traditionally, some organizations still use physical methods to collect attendance data, which is considered less efficient and effective. The research uses classical waterfall development method to facilitate the process of system development up to release. With face recognition and geo location methods, an online attendance system is proposed with IT infrastructure using private hosting and virtual machines with Red Hat Enterprise Linux 8.7 Operating System as a web server. With the implementation of this system, it is expected that benefits will be realized in the ease for employees to conduct attendance and management capabilities in managing employee attendance data in a structured manner.
Sistem Informasi Perangkat Desa (SINPERDES) Berbasis Website Dengan Metode Waterfall Dalam Pelaksanaan Pembangunan Desa

Website-Based Village Information System (SINPERDES) Using the Waterfall Method in Implementing Village Development The Village Information System (SINPERDES) is a technological solution designed to optimize the implementation of village development through the use of the Waterfall method in its development. The Waterfall method is a software development approach that focuses on sequential stages, starting from planning, analysis, design, implementation, to maintenance. This research aims to develop SINPERDES which is able to support village officials in managing information and village development processes more efficiently and effectively. Website-based SINPERDES was chosen as a platform to enable easier access for village communities and related stakeholders. This study involves analyzing the needs of village officials, system design, website development, and implementation in several villages as case studies. The results of this research show that Website-Based SINPERDES using the Waterfall method has succeeded in increasing information accessibility, monitoring village development, as well as coordination between village officials and the community. In addition, the use of the Waterfall method in SINPERDES development provides clarity and order in the software development process. The successful implementation of SINPERDES provides an opportunity to improve the overall quality of village development
Naïve Bayes Classifier dengan Particle Optimize Weight Forward pada Dataset

Classification is the process of identifying and grouping objects into classes or categories based on their characteristics. In data mining, there are two processes, namely classification and clustering, which are used to group objects based on similarities. In the classification process, various methods such as K-NN, SVM, and Naïve Bayes are often used and developments are made in the method. The Naïve Bayes classifier is proven to have advantages, such as faster calculation and better accuracy. However, this method has limitations in the attribute selection process. To overcome this limitation, the Particle Optimize Weights Forward algorithm is used to improve accuracy by assigning weights to attributes in the Naïve Bayes method. This approach improves the efficiency and effectiveness of the Naïve Bayes classifier in data classification tasks.
A ANALYSIS OF PREPARATIONS FOR THE IMPLEMENTATION OF ELECTRONIC MEDICAL RECORDS AT RSJ PROF HB SAANIN PADANG USING THE DOQ-IT METHOD

According to PMK No. 24 of 2022, a medical record is a document containing data on patient identity, examination, treatment, actions, and other services that have been provided to the patient. Through this policy, health service facilities are required to run an electronic patient medical history recording system. The transition process is carried out until no later than 31 December 2023. This type of research uses quantitative methods. Quantitative research methods are used to determine the picture of hospital readiness. The method used to analyze hospital readiness is DOQ-IT with indicators of organizational culture readiness, governance and leadership readiness, human resource readiness, and infrastructure readiness. Based on the results of the research that has been carried out, information can be obtained that in the aspects of human resources, organizational work culture, leadership governance, and infrastructure as a whole can be seen from the answers of 18 ready respondents (46.06%) and very ready as many as 20 people (49.87%) then with the respondent's answer not ready as many as 1 person (2.22%) the answer is very unprepared as many as 1 person (0.35%) and for the answer hesitant as many as 1 person (1.44%), it is confirmed from the informant that the preparation for the implementation of electronic medical records is ready to be implemented.
Klasifikasi Citra Cuaca Menggunakan Inception-V3 dan K-Nearest Neighbors

Weather imagery has a crucial role in various sectors, such as aviation, maritime and agriculture. Weather conditions have a big impact on activities in these fields and greatly influence operations. Classifying weather images can be done by analyzing weather image data, which can be used to predict the type of weather that may occur. The results of these weather predictions have significant value in daily decision making in these various sectors. One method for classifying weather images can be done by first extracting weather image features using Inception-V3 which is then calculated using the K-Nearest Neighbors method. This research uses 1748 weather images with 4 categories to carry out training which produces a model with Accuracy 91%, F1 91%, Recall 91%, Precision 91%, and uses 8 weather images with 4 categories to carry out testing which produces classifications with all correct values. every image.
ANALISIS PELAYANAN RUMAH SAKIT UMUM DENGAN PERBANDINGAN ANTARA METODE ALGORITMA KMEANS, DAN K-MEDOIDS CLUSTERING

Hospitals are part of a health system that aims to provide comprehensive individual health services. Services include inpatient, outpatient, and emergency care. Hospitals must provide high-quality services according to existing standards and serve all levels of society. Understanding customers' needs, wants, and demands will provide Another factor that affects the quality of health services is the availability of resources and service facilities during the insurance period. Lack of continuity of service affects the efficiency and quality of the relationship. The quality of health services is also strongly influenced by the ease of information and timeliness of public hospital services. Based on data from 341 hospital service quality surveys, the results obtained from the K-Means algorithm method are 2.701288, while the results obtained in the K-Methoids Clustering method are 2.17, where the General Hospital service questionnaire is a very satisfied category. A comparison of the results of the K-Means and K-Medoids methods aims to make it easier to measure customer satisfaction.