Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis of Bjorka Hacker Using the Naive Bayes and C.45 Algorithms

In 2023, Indonesia was again devastated by a hacker known as Bjorka. Bjorka did not act just once or twice; every time, Bjorka made the entire Indonesian population proud. The 19 million BPJS Employment data belonging to the Indonesian people that Bjorka hacked is the BPJS Employment data belonging to the Indonesian people that Bjorka hacked. Since the release of the Bjorka story, there has been a surge in the number of people criticizing it on social media, particularly Facebook, so the criticism or opinions can be used to conduct sentiment analysis. Based on this, developing a method that can automatically classify beliefs into positive and negative categories through sentiment analysis is necessary. The sentiment analysis process begins with data preprocessing, followed by keyword analysis using the TF-IDF method, algorithm development, and analysis of classification results. The data classification methods used in this study are Naive Bayes and C4.5. The data will be analyzed using text mining and classified using the Naive Bayes and C4.5 algorithms. Based on the results of the tests, the best classification was achieved by Nave Bayes, with a score of 70 percent for the C4.5 algorithm and 68 percent for the C4.5 algorithm. The Nave Bayes algorithm can predict up to 70% data transmission rates for both positive and negative signals.
PELATIHAN PENULISAN ARTIKEL JURNAL BERBASIS HASIL RISET PTK UNTUK GURU

This service activity was carried out with the aim of providing training to teachers in Kampar district to be able to write scientific articles originating from the results of PTK research that has been carried out so that they are suitable for publication in Nationally accredited journals. This activity was carried out in July 2022 at the UPT SMP Negeri One Roof Koto Perambahan school, Kampar District in Kampar Regency. The targets and target of this service are the UPT teachers of One Roof Public Middle School, Koto Perambahan, Kampa District in Kampar Regency and several teachers from SD Negeri 005 Koto Perambahan. In this service activity, a questionnaire instrument was also used to determine the teacher's perception regarding the article writing training activities that had been carried out as well as regarding the benefits of the material in the training presented by the resource person. The achievement of the participant target can be seen from the number of participants who took part in the training activities, namely all teachers and principals from the One Roof Koto Perambahan Middle School took part in the training activities from the start of the activity to the end
EMOTIONAL COMPONENT OF FUTURE CHOREOGRAPHERS’ AESTHETIC CULTURE: ESSENCE, INDICATORS OF FORMATION, RESULTS OF THE DIAGNOSTIC EXPERIMENT

The experimental article highlights the essence of the emotional culture of students of higher education in the specialty 024 Choreography, indicators of the formation of its emotional component (emotional-aesthetic sensitivity, ability to aesthetic pleasure, the aesthetic emotional orientation of the personality), diagnostic methods (test questionnaire B. Dodonov “Emotional Orientation,” questionnaire by B. Bass, questionnaire by M. Rokych, included observation, mini-work “My impressions”) and its results. The levels of formation of the emotional component of the aesthetic culture of future choreographers in the experimental (EG) and control groups (CG) have been determined: a high level was demonstrated by 11.43% of the EG students and 14.71% of the CG; average – 22.86% and 23.53%, respectively; low – 65.71% and 61.76%). The rating of the emotional orientation of the personality in future choreographers is presented, such as praxic, gloristic, hedonistic, communicative, pugnacious, aesthetic, romantic, altruistic, acquisitive, and gnostic. The spaces of emotional preferences of students have been analyzed. It has made it possible to draw up a strategy for the formation of future choreographers’ aesthetic culture in a higher education institution: 1) students of higher education have a rich emotional sphere as a basis for the formation of the studied professional and personal quality in them; 2) aesthetic emotions have an intermediate character in the hierarchy of students’ emotional values, therefore, under favorable conditions of their aesthetic development, they can acquire a higher status, which corresponds to representatives of artistic professions; 3) the dominance in the sample of the practical and gloristic orientation of the personality aims at the application of active methods and techniques, pedagogical support technology based on the student-centered approach in experimental work.
Strategic Blockchain Adoption for Anti-Greenwashing

Problem definition: This study investigates how green companies can strategically implement blockchain to effectively balance product pricing and greenness levels against brown competitors. We bring in the critical parameters of the blockchain adoption cost, platform greenness penalty, blockchain environmental negatives, greenwashing penalty, and customers' skepticism. Methodology: We develop a game-theoretic model to study the price and greenness competition between a green and a brown company when the latter greenwashes and the former uses blockchain to combat it. Key findings: 1) When blockchain is not adopted, investing in product greenness is an effective defence against greenwashing, but only when market skepticism is relatively high and penalty cost is moderate; 2) When blockchain is adopted, such effectiveness remains viable only if market scepticism is relatively low and penalty cost is moderate; 3) Regardless the adoption of blockchain, higher penalty costs benefit both green and brown company’s profits when the former successfully deters greenwashing; 4) Market greenness level will initially increase and then decrease as penalty level rises if blockchain is not adopted; 5) Intriguingly, blockchain use does not consistently improve customer surplus, environmental, or social welfare. Managerial insights: Adopting blockchain is always beneficial for green companies when the corresponding adoption cost is low. However, as such costs rise, the decision to adopt blockchain hinges on the severity of government penalties for non-compliance. Governments and legislative bodies are advised to implement a balanced approach in enforcing greenwashing penalties with respect to green companies’ blockchain adoption strategy. When no blockchain is adopted in market, this approach should permit a limited degree of greenwashing, recognizing its potential to contribute positively to the expansion of the green market and the broader welfare of society.
Evaluasi Sistem Informasi Akuntasi Penjualan Dalam Meningkatkan Pengendalian Internal Pada PT. Centra Nusa Indonesia

This research aims to evaluate the Sales Accounting Information System at PT. Celntra Nusa Indah. PT. Celntra Nusa Indonesia is a company operating in the field of coal trading (Coal Trading). From the evaluation results of the Sales Accounting Information System, it was obtained. Sales Accounting Information System at PT. Celntra Nusa Indonesia is good but still has several weaknesses. This can be seen from the clear organizational structure, but there are still weaknesses, namely that there is a combination of functions and responsibilities as follows: The cashier section which also doubles as the accounting section. The combination of these two functions can provide opportunities for employees to commit fraud by changing the accounting records to cover up the fraud. done. Division of duties and responsibilities at PT. Celntra Nusa Indonesia still has shortcomings. This can be based on research results which show that there is a division and implementation of duties and responsibilities that are not appropriate as follows: The billing department should be in charge of making extraordinary billing reports and collecting bills from customers. This is because the billing department receives proof of receipt of the invoice from the customer, where information is provided regarding the date it was received, the amount of payment and the time the invoice was paid. If this is done by the invoice department, it is still not completed. Because the invoice department has made daily billing reports.
Examining Eye Tracking Metrics and Cognitive Function in Post-Stroke Individuals: A Comparison of Visual Searching Tasks Between Those with and without Cognitive Impairment

Introduction: After a stroke, individuals commonly experience visual problems and impaired cognitive function, which can significantly impact their daily life. In addition to visual neglect and hemianopia, stroke survivors often have difficulties with visual search tasks. Researchers are increasingly interested in using eye tracking technology to study cognitive processing and determine whether eye tracking metrics can be used to screen and assess cognitive impairment in patients with neurological disorders. As such, assessing these areas and understanding their relationship is crucial for effective stroke rehabilitation. Methods: We enrolled 60 stroke patients in this study and evaluated their eye tracking performance and cognitive function through a series of tests. Subsequently, we divided the subjects into two groups based on their scores on the HK-MoCA test, with scores below 21 out of 30 indicating cognitive impairment. We then compared the eye tracking metrics between the two groups and identified any significant differences that existed. Spearman correlation analysis was conducted to explore the relationship between clinical test scores and eye tracking metrics. Moreover, we employed a Mann-Whitney U test to compare eye tracking metrics between groups with and without cognitive impairment. Results: Our results revealed significant correlations between various eye tracking metrics and cognitive tests (p=&lt;.001-.041). Furthermore, the group without cognitive impairment demonstrated higher saccade velocity, gaze path velocity, and shorter time to target than the group with cognitive impairment (p=&lt;.001-.040). ROC curve analyses were performed, and the optimal cut-off values for gaze path velocity and saccade velocity were 329.665 (px/s) (sensitivity= 0.80, specificity = 0.533) and 2.150 (px/s) (sensitivity= 0.733, specificity= 0.633), respectively. Conclusions: Our findings indicate a significant correlation between eye tracking metrics and cognitive test scores. Furthermore, the group with cognitive impairment exhibited a significant difference in these metrics, and a cut-off value was identified to predict whether a client was experiencing cognitive impairment.
Effect of Electronic and Digital Media Use on the Health of Adolescents in Ondo City.

The use of electronic and digital media has been a growing concern worldwide in recent years. It is associated with some health-related problems, among children and young adults. However, few studies have examined this problem in Ondo city. Therefore, this study investigated the effect of electronic and digital media use on the health of adolescents. The study used an explanatory cross-sectional design. The population comprised 174 students who were randomly selected from 6 secondary schools. The schools were randomly selected from all senior secondary schools in Ondo city. The Electronic and Digital Media Questionnaire (EDMQ) was used. Two hypotheses were tested using an independent t-test and binary logistic regression. The result showed that female adolescents have almost 3 fold the male odds of having poor health outcomes after exposure to electronic and digital media (OR: 2.61; p&lt;0.05). Whereas those who mostly liked mixed channels had 78 per cent lower odds (OR: 0.22; p&lt;0.05) of having poor health outcomes following exposure to electronic and digital media. The study revealed that there is a significant effect of electronic and digital media use on the health of adolescents as well as a significant difference in gender difference regarding the effect of electronic and digital media use on the health of female and male adolescents in Ondo city. The study recommended enlightenment programmes and counselling for secondary school students to address the health-related problems associated with the use the electronic and digital media
Run Length Limited Error Control Codes Derived from Reed Solomon Codes

Abstract Reed Solomon codes were standardized for numerous wireless communication systems. Most practical Reed Solomon codes belong to non-binary linear block codes defined over finite fields with characteristic two. Each linear block code contains one codeword composed of all zeros. The concatenation of this and also other codewords can lead to long, theoretically even infinite, runs of equal symbols. Such long runs do not support synchronization in wireless receivers and therefore are unwanted. In this paper it is shown that extended and some appropriately shortened Reed Solomon codes constructed over finite fields with characteristic two can be transformed into Run Length Limited Reed Solomon codes. The presented method, if applicable, allows for doing it without inserting additional redundancy. Another advantage is that after the transformation, if some round conditions are fulfilled, the decoding does not have to be rebuilt.
A Proposal of a Spike Event Classification Method Based on Ball Trajectory in a Volleyball Video

In this research, we propose a method for classifying a spike event in a volleyball game video. In our method, Person and ball detection and tracking are implemented with the YOLO and the ByteTrack. An action event such as a spike and toss is recognized by focusing on the changes in a player’s bounding box of the tracking result. The spike event is classified from the action events with a trajectory of the ball movement. The precision and recall rates of our method are 95% and 93%, respectively, and it indicates an improvement of 8% over existing method.
Lexical Analysis Implementation by Using Deterministic Finite Automata (DFA)

A compiler is a computer program (or set of programs) that transforms source code written in a programming language into another computer language known as the target language, often having a binary form identified as object code. The compiler has some phases and the main concern of this report is about the implementation of Lexical Analysis using the Deterministic Finite Automata (DFA) that is a finite state machine that accepts or rejects finite strings of symbols and only produces a unique computation of the automaton for each input string.&#x0D; Through building a Finite Automata using a model known as JFLAP and utilizing it to execute some patterns, which were integer number, real number, operators, and some keywords. This model approved that DFA is accurate to produce a unique computation for each input string. In addition, using JFLAP approved that the time-consuming.
Trade-off Between Execution Time and Memory Consumption in Fuzzy Average-Utility Mining

Fuzzy utility mining considers high-utility fuzzy itemsets as valuable knowledge by integrating quantities of items, their profits, and meaningful fuzzy terms derived by quantities according to membership functions. In fuzzy utility mining, the utility value of a fuzzy itemset in a transaction will always be greater than or equal to those of its subsets, so the measurement of fuzzy utility is an unfair evaluation method. Therefore, the fuzzy average-utility mining problem was issued in 2020, and three solutions were proposed to solve fuzzy average-utility itemsets as two-phase fuzzy average-utility algorithm (TPFAU), two-phase method with tree-based structure (HFAUIM) and one-phase approach with tree-based structure (FHFAUIM), respectively. The second and third methods decrease the candidates generated compared to the first. However, the sorting strategy for mining steps for the last two approaches is based on the frequencies of items in a database and then inserting items of a transaction into a tree in descending order of their frequencies, thus spending more computing time on deriving the actual fuzzy utility value of itemsets. To overcome the above-mentioned problem, this paper adopts a different sorting strategy with a tree-based structure and then by using it to design an algorithm named IFHFAUIM to mine high fuzzy average-utility itemsets. It reduces the storage of required fuzzy utility values in tree nodes and recovers them through tree traversal. Computational experiments show that the proposed method could make a good trade-off between execution time and memory usage.
Emotional Dictionary Construction based on Neural Network Models

In response to the current lack of emotional dictionary in the field of online medical fields, this article proposes a method of building emotional dictionary construction in the field of online medical fields: obtains the collection of emotional words by fusion of existing general emotional dictionary and target website comment data, and build word vector model expansion expansion Emotional words, constructing neural network models to judge emotional words and emotional tendencies, and integrate emotional words to obtain emotional dictionaries in the field of online medical care. Compared with the experimental verification of the effectiveness of this method, it has played a certain positive role in subsequent online medical analysis research.
Delayed Feedback with Selection Bias in Recommender Systems

One challenge for online advertising companies is the lack of time-sensitive data, as users may not buy the product immediately after clicking on the ads. Wanting to improve the performance of their products, advertisements companies can constantly train on the real-time data stream. Without fully generated data, this approach will lead to few biases. In this paper, we discussed non-parametric models regarding delay distributions and three estimators for the training model. In the end, we proposed the Dual Learning Algorithm. While training on 100000 data points and different sets of hyper parameters, we achieved the overall best set of F1 and AUC scores: 0.55 and 0.70.
A Recommendation Algorithm for Optimal Analysis of Audit Path

The audit path is the development of the audit department, and in the process of investigation or evidence collection, the professional ability of the staff and the means of evidence collection will affect the results data and reduce rate of the audit in system. So as, this paper want to recommendation compyer to the audit path all, evidence collection. The data results are then evaluated comprehensively. To continuous monitoring the data is used to screen the audit system path and putout the final plan data. The recommendation algorithm can accurately optimize the audit path, improve the overall level of the system, and the rationality is greater than 95% by the recommender system method. Therefore, the recommendation result can take the requirements that the audit system path, which is suitable for the continuous analysis in the development about the audit department.
Research on Underwater Surface Crack Detection Technology of Concrete Dam Based on Image Processing

The traditional method of manually detecting concrete surface cracks has the disadvantages of low efficiency and large error. Therefore, it is necessary to adopt non-contact underwater crack detection and identification method for concrete dam based on image processing technology. In this paper, the pixels of the image information collected by the system are calibrated applying MATLAB program. After image grayscale conversion, denoising and segmentation, the crack feature information in the image is extracted and its width is calculated. Finally, the identification accuracy of the detection technology is verified and the detection efficiency of underwater surface cracks of concrete dams is improved.
Evaluation of Bearing Mechanical Fault Safety Diagnosis Method Based on Improved PSO Algorithm

With the development of the times, the problem of mechanical failures in bearings has gradually become prominent. If this problem cannot be solved, it would cause significant safety hazards, so new technologies are needed to solve this problem. The research in this article was an analysis of the bearing mechanical fault safety diagnosis method based on the improved PSO (Particle Swarm optimization) algorithm, which aimed to improve the accuracy of bearing mechanical fault safety diagnosis by using the PSO algorithm. This article tested the accuracy of bearing mechanical fault diagnosis using PSO algorithm through experiments, with a maximum of 85% and a minimum of 80%. The accuracy of traditional bearing mechanical fault diagnosis was as high as 60% and as low as 50%. From this experimental data, it could be seen that the accuracy of bearing mechanical fault diagnosis was significantly improved using the PSO algorithm, indicating a good fit between the PSO algorithm and bearing mechanical fault diagnosis.
A Blockchain-Based Interoperable Architecture for IoT with Selective Disclosure of Information

With the improvement of Internet of Things (IoT) technologies, services, and applications, there is a proliferation of access to smart devices in everyday life. However, granting access and controlling access rights for each resource is challenging in highly dynamic and large-scale IoT deployments. In particular, multiple access information may need to be provided to an entity when granting access rights to several resources. The situation becomes more complex when an entity is required to share its identity attribute to receive the access information. These raise the question of what identity information an entity needs to provide to obtain the required access to a particular resource and, subsequently, what access information needs to be provided when accessing that resource. That said, there is a need for a flexible approach where an entity can share a distinct identity and access attributes for accessing a resource without revealing additional information. Such flexibility in sharing information is significant given the privacy risk of an entity’s identity. This paper presents an architecture that delivers access rights to an entity with selective disclosure of information. Our approach ensures the minimum exchange of information (identity and access attribute) to enhance an entity’s privacy when granting access rights to an entity. We use blockchain to provide data authenticity (i.e., tamper-proof), transparency and automatic execution of access rights based on shared attributes using smart contracts. We implement a proof of concept of the proposed system using Hyperledger fabric as a permissioned blockchain network. Our results demonstrate the feasibility of the proposed system showing efficiency in granting access rights.