Reviewerly/exHarmony huggingface dataset:
Model Matematika dan Simulasi Penyebaran Perokok Dalam Suatu Populasi Menggunakan Matlab

One of the social problems that is still controversial is smoking. This is closely related to public health, because smokers have a great risk of spreading disease either directly to smokers themselves or indirectly to other people who do not smoke but are in the same environment or population as smokers, such as cancer, heart disease. , caries, and others caused by the substance content of the smoked cigarettes. The more smokers in a population, the greater the chance of increasing the number of smokers in that population, which directly or indirectly means increasing the spread of the diseases that have been mentioned. The purpose of this research is to construct a mathematical model and simulate the distribution of smokers in a certain population using Matlab. The variables that make up the Mathematical model are divided into 3 classes, namely prospective smokers (), regular smokers (), and ex-smokers (). The method used in this research is the method of literature study and literature related to research and simulation using Matlab. At the end of the study, the value of the basic reproduction number () will be analyzed to determine the dynamics that occur in the population and the simulation results of the mathematical model formed. The results of this study are a depiction of how much influence the presence of smokers has in a population by looking at the parameters that affect changes in the value significantly.
User-Centered Design-Based Approach in Scheduling Management Application Design and Development

The process of manually making and setting course schedules using Microsoft Excel is ineffective, time-consuming, and still prone to errors. This research develops a website-based scheduling management application with a case study at SMK Pariwisata Margarana so that it can solve scheduling problems manually. The UserCentered Design (UCD) method is applied in the application prototype design stage. Open interviews, field observations, simulations, and questionnaires were used as research data collection methods. Three iterations were carried out at the prototype design stage to fulfill all user needs. The high-fidelity prototype in the last iteration is then implemented into an application. Application quality is measured using ISO/IEC 25010 with five characteristics. The test results on usability characteristics show that the scheduling management application obtains an average usability score of 91.2%. The appropriateness recognizability sub-characteristic obtained the highest usability score of 93.53%. UCD can help produce an application that can meet all the user’s needs when implemented in the application design phase.
Predicting the Number of Passengers of MRT Jakarta Based on the Use of the QR-Code Payment Method during the Covid-19 Pandemic Using Long Short-Term Memory

The trend of using public transportation has been rising over the last several decades. Because of increased mobility, public transportation has now become more crucial. In modern environments, public transportation is not only used to carry people and products from one location to another but has also evolved into a service company. In Jakarta, Mass Rapid Transit Jakarta (MRTJ) started to operate in late 2019. Recently, they updated their payment gateway system with QR codes. In this study, we predicted the hourly influx of passengers who used QR codes as their preferred payment method. This research applied machine learning to perform a prediction methodology, which is proposed to predict the number of passengers using time-series analysis. The dataset contained 7760 instances across different hours and days in June 2020 and was reshaped to display the total number of passengers each hour. Next, we incorporated time-series regression alongside LSTM frameworks with variations in architecture. One architecture, the 1D CNN-LSTM, yielded a promising prediction error of only one to two passengers for every hour.
A Transcoding Task Offloading and Routing Decision-Making Scheme in Live Transmission Architecture Based on Computing Power Network

In recent years, there has been a significant increase in the demand for high-bit-rate live broadcast services, which has led to the widespread use of edge transcoding technology. Edge transcoding can effectively reduce the throughput of streaming media transmission, making it a popular and extensively researched technology. However, due to the real-time requirements of live broadcasting, the edge server needs to have the sufficient computing power to ensure low-latency calculations, which makes computing power allocation and traffic distribution become quite difficult. Inspired by the real-time and flexible computing power scheduling ability of the Computing Power Network, this paper explores reasonable edge task offloading and efficient traffic routing path planning to ensure overall low latency. This paper proposes a live stream transmission architecture based on the computing power network to solve the problems mentioned above to some degree. The paper first models the computing power network in the scene and then designs a task offloading algorithm based on Deep Reinforcement Learning (DQN) to determine the device for executing the computing task. Furthermore, a hybrid Simulated Annealing Genetic Algorithm (SAGA) is proposed for routing decisions. The effectiveness and superiority of the scheme are validated through simulation experiments.
APPLICATION OF ETHNO-PRAGMATIC LEARNING STRATEGIES IN INDONESIAN LANGUAGE LESSONS IN HIGH SCHOOL IN THE MERDEKA CURRICULUM (PENERAPAN STRATEGI PEMBELAJARAN ETHNO-PRAGMATIK PADA PELAJARAN BAHASA INDONESIA DI SMA PADA KURIKULUM MERDEKA)

The problems discussed in this study are adapting curriculum changes from the 2013 curriculum to the independent curriculum in Indonesian learning in high school. This curriculum is because not all teachers understand the application of the independent curriculum to learning, especially Indonesian learning. For this reason, ethno-pragmatic learning strategies are needed to integrate with the independent curriculum in high school. This ethno-pragmatic learning strategy can accommodate the achievements of the Indonesian learning curriculum in high schools so that character strengthening can be achieved by the independent curriculum policy set in Decree of the Head of Balitbang of the Ministry of Education and Culture, Research and Technology No. 028/H/KU/2021 concerning the learning outcomes of PAUD, SD, SMP, SMA, SDLB, SMPLB, and SMALB in the Driving School Program. The method is carried out with descriptive qualitative to understand students applying the Indonesian language curriculum in high school. Data were collected using observation methods, in-depth interviews, documentation with note-taking techniques, practical matching techniques, and focus group discussions with stakeholders in high school. The results showed that (1) the application of the ethno-pramatics method to Indonesian subjects in high school was able to accommodate the achievement of curriculum objectives in the use of the Indonesian language in a polite manner, and (2) The application of ethno-pragmatics methods to Indonesian subjects in high school can understand various multimodal texts based on context.
Development using the Rapid Application Model of peTrace: Peter’s Poultry Supply Sales and Monitoring Management System

The poultry industry includes other support industries such as feed production and distribution, veterinary and poultry equipment production and distribution, meat and egg processing, marketing and distribution, and so on. Poultry production in the tropics. The poultry supply business is not prevalent in the province of Oriental Mindoro, that has a land area of 588,350 ha that supplies agriculture crops and livestock production, in addition to 286 registered business names, the plurality of which are linked to poultry supply. And one of the towns in Oriental Mindoro is recognized for producing agriculture and aquaculture. Rapid Application Method (RAD) is a software development methodology that emphasizes rapid prototyping through design. This type of testing modifies the software system before it is implemented. And Alpha testing was carried out by the Information Technology Practitioner. The system peTrace was ready for evaluation after several design and functionality issues were resolved. Purposive sampling was applied by the proponents this is to identify the 50 respondents so that the evaluators could have an accurate evaluation result. Information Technology Practitioners, store owners, staff, and clients were among those who responded. Owner, staff utilized the peTrace several times, testing its functionalities and verifying its usability. The proponents adapted the evaluation questionnaire using the ISO 25010 software quality criteria. To modify the five assessment criteria, ISO 25010 quality software standards were used. According to the assessment findings, peTrace is helpful and performs as predicted in terms of functional appropriateness (4.90), performance efficiency (4.85), usability (4.83), security (4.83), and maintainability (4.82). The peTrace system is broad in design, simple to maintain, and adaptable to any portable device independent of operating system, making it suited for any local Feed Store. For future growth, the assessors advise using real-time analysis. A good system will offer continuous monitoring with few, if any delays.
Obfuscation of Discrete Data

Data obfuscation deals with the problem of masking a data-set in such a way that the utility of the data is maximized while minimizing the risk of the disclosure of sensitive information. To protect data we address some ways that may as well retain its statistical uses to some extent. One such way is to mask a data with additive noise and revert to certain desired parameters of the original distribution from the knowledge of the noise distribution and masked data. In this project, we discuss the estimation of any desired quantile and range of a quantitative data set masked with additive noise.
Cloud-Based Picture Archiving and Communication System (PACS)

Revolution in medical imaging systems generate high-resolution images.This revolution has created new challenges in accessing, sharing, archiving, and protecting medical images.The number of these images has also increased significantly over the past decade, which is create another challenge.Recently, the health care industry has started noticing cloud computing as a solution because of its elasticity and scalability, which contribute to avoiding hardware obsolescence, providing universal access to medical images anywhere and anytime, and increasing their availability.This paper introduces the main characteristics of the cloud-based picture archiving and communication system (PACS) and highlights its technical and nontechnical advantages.Moreover, this paper illustrates challenges in cloud-based medical image exchange, regulation, and interoperability as well as how medical image existence can affect cloud users.Furthermore, the paper concludes with directions for future research in medical imaging.
Enhanced PBFT Blockchain based on a Combination of Ripple and PBFT (R-PBFT) to Cryptospatial Coordinate

In this research, we introduce the combination of two Blockchain methods. Ripple Protocol Consensus Algorithm (RPCA) and Practical Byzantine Fault Tolerance (PBFT) are applied to cryptospatial coordinates to support cultural heritage tourism. The PBFT process is still used until the preparation process to ensure a maximum error of 33%, and every node would add a new chain in all nodes, so PBFT has a slower processing speed than other methods. This research cuts the PBFT process. After the preparation process in PBFT, the data was entered into the RPCA node and was calculated using an equation to minimize errors with a maximum limit of 20%. After this process, the was were sent to the commit process to store the data in all connected nodes in the Blockchain network; we call this combination of two methods R-PBFT. Combining the two methods can enhance data processing security and speed because it still uses the PBFT work combined with the speed of RPCA. Furthermore, this method uses a fault tolerance value from the RPCA of 20% to enhance data processing security and speed.
The Effects of Industry 4.0 Integration for Improvement in Project Communication

The emergence of 4IR, otherwise known as Industry 4.0, has introduced new communication technologies focusing on automation, digitalisation, and the global use of information.As a result, this is drastically changing the process of communication in project management.This article offers an exploration of Industry 4.0 concepts and technologies, and their impact on communications in projects.Firstly, 38 relevant studies have been identified.Then, a review has been conducted to identify the effects of Industry 4.0 integration on project communication.It has been determined that Industry 4.0 significantly impacts project communication.The results of this study also revealed that Industry 4.0 has contributed to the improvement of communication systems of projects, which highly affects the completion of a project.In addition, it was discovered that technological advancements are used to improve landscape communication.Finally, the deployment of Industry 4.0-based tools facilitates communication in project management and leads to greater efficiency through digitalisation and the integration of new technologies.The results of this study are intended to guide the project managers and contribute to the field of project management and Industry 4.0.
The Implementation of Instructional Media in Teaching English to Young Learners

This research aims to describe the implementation of instructional media in teaching English to young learners. Types of media are used during the learning process. This research is focused on the implementation of instructional media in teaching English to young learners. In this study, the writer applied qualitative descriptive method. To collect the data, the writer employed observation, documentation, and interview with the teacher. The participants in this study were students of grades 6B, 6C, and an English teacher at MIT MA Mathla'ul Anwar. The result of this research shows that the teacher uses different instructional media at each meeting. The teacher uses three types of instructional media in teaching English. These media are included in the types of print media (textbook), audio, and audio-visual media. Teacher sometimes insert the games that support instructional media in learning activities. The most effective instructional media used are smartphones and infocus. The use of instructional media applied to young learners can make learning interactive, creative, and communicative.
One Explanation Does Not Fit XIL

Current machine learning models produce outstanding results in many areas but, at the same time, suffer from shortcut learning and spurious correlations. To address such flaws, the explanatory interactive machine learning (XIL) framework has been proposed to revise a model by employing user feedback on a model's explanation. This work sheds light on the explanations used within this framework. In particular, we investigate simultaneous model revision through multiple explanation methods. To this end, we identified that \textit{one explanation does not fit XIL} and propose considering multiple ones when revising models via XIL.
Comparison of Graph Embeddings for Source Code with Text Models Based on CNN and CodeBERT Architectures

One possible way to reduce bugs in source code is to create intelligent tools that make the development process easier. Such tools often use vector representations of the source code and machine learning techniques borrowed from the field of natural language processing. However, such approaches do not take into account the specifics of the source code and its structure. This work studies methods for pretraining graph vector representations for source code, where the graph represents the structure of the program. The results show that graph embeddings allow to achieve an accuracy of classifying variable types in Python programs that is comparable to CodeBERT embeddings. Moreover, the simultaneous use of text and graph embeddings as part of a hybrid model can improve the accuracy of type classification by more than 10%.
Data Quality Management Strategy To Improve Remote Sensing Data Quality: A Case Study On National Remote Sensing Data Bank

National Remote Sensing Data Bank (Bank Data Penginderaan Jauh Nasional; BDPJN) is the operational implementer in the field of remote sensing to meet the needs of national data on remote sensing images. Remote sensing images are essential in the Indonesian government for various needs, such as in regional (spatial planning, city boundaries), disaster (forest fires, floods, landslides, earthquakes, volcanic eruptions), plantation, natural resources, and environment sectors. Quality management of BDPJN’s satellite images becomes challenging due to the increasing number of products owned and users annually. For this reason, a data quality management strategy is needed to guarantee and improve the quality of BDPJN data. To develop such a strategy, an assessment of the maturity of BDPJN’s data quality man- agement was conducted from the aspect of data processing by implementing Loshin’s Data Quality Management Maturity Model (DQM3) to find out the characteristics that were lacking. The results were then mapped based on Data Quality Management (DQM) activities in DAMA-DMBOK as a recommendation for data quality management strategies. This study applies quantitative research where data collection was done by distributing questionnaires to 24 respondents who are data stewards of medium, high, and very high-resolution mosaic images. Based on the assessment, BDPJN is in the maturity level of Defined to Managed. The recommendations are 21 DQM activities that can be carried out to improve BDPJN data quality.
Blockchain and Satisfiability Modulo Theories for Tender Systems

A tender process consists in competing offers from different candidate suppliers or contractors. The tender winner is supposed to supply or provide a service in better conditions than competitors. Tenders are developed using centralized unverified systems, which reduce transparency, fairness and trust on the process, it also reduces the ability to detect malicious attempts to manipulate the process. Systems that provide formal verification, decentralization, authentication, trust and transparency can mitigate these risks. Satisfiability Modulo Theories provides a formal analysis to prove correctness of tender offers properties, verified properties ensures system reliability. In addition, one technology that claims to provide decentralization is Blockchain, a chain of distributed and decentralized records linked in a way such that integrity is ensured. This paper presents a formal verified and decentralized proposal system, based on Satisfiability Modulo Theories and Blockchain technology, to make electronic procurement tenders more reliable, transparent and fair.
Improved Facial Identification Using Adaptive Neuro-Fuzzy Logic Inference System

Objectives: To suggest an efficient pose invariant face recognition system (PCA-ANFIS) based on PCA and ANFIS.Methods: Using a dual-tree complex wavelet transform technique, face image improvement is obtained.ORL and YALE B data sets are used in this process.To train and test the network to recognize the person, two sets of photos were used.The system will return recognized if the test image matches one of the image's training sets.The system will report not recognized if the test image does not match one of the image's training sets.Accuracy, specificity, sensitivity, precision, and recall are the criteria taken into account.The suggested approach is then evaluated and compared to other known, gold standard facial recognition algorithms, including PCA, WP&LDA, GOBER WAVELET, SVM, and Bayesian Classifier methods.Findings: The study results indicated that the image accuracy, specificity, sensitivity, precision, and recall are enhanced toa level of 90, 85, 95, 86, and 95 per cent respectively when compared with the test results of other known gold standard facial recognition algorithms viz., PCA, WP &LDA, GOBET WAVELET, SVM and Bayesian Classifier approaches by which it can be concluded that it is an efficient approach for facial identification.Novelty : Both the feature extraction strategy and the classification approach play a strong emphasis on these factors.Principal component analysis is used for feature extraction, while an Adaptive Neuro Fuzzy Inference System is used for classification.The study proposed a novel neuro-fuzzy system-based face recognition method that is proposed in this study correctly that identifies the input face photos with a higher recognition rate Compared to the existing reports.
PENGARUH PENGGUNAAN METODE CONCEPT MAPPING TERHADAP HASIL BELAJAR SISWA KELAS IV SEKOLAH DASAR PADA MATERI JENIS-JENIS PEKERJAAN

The background of this research study is because of the low student learning outcomes, especially on the material types of work. This can be seen from the number of students who do not understand the material types of work. Many of the students are still confused about the type of work that produces goods and services. In fact, many of the students get low grades. Seeing this, the researchers tried to provide solutions to the student's problems by using the concept mapping method on the learning outcomes of fourth grade elementary school students regarding the types of work. This research is an experimental quantitative study with a posttest-only control design.This study used two classes, namely the experimental class and the control class with different treatments. This study aims to determine the effect of using the concept mapping method on the learning outcomes of fourth grade elementary school students regarding the types of work. The number of students in this study were all fourth grade students consisting of two classes, namely class IV B as the experimental class, totaling 29 students and class IV A as the control class, totaling 31 students, the total population was 60 students.The results of research using the concept mapping method on student learning outcomes in the subject of types of work indicate a change in the average score of students. The average score of the students in the experimental class given the concept mapping method was higher than the average score for the control class given the lecture treatment. This shows that the concept mapping method has an effect on the learning outcomes of fourth grade students.
Decoding twisted permutation codes

We consider twisted permutation codes, a class of frequency permutation arrays obtained from finite groups with multiple permutation representations of the same degree, introduced by Gillespie, Praeger and Spiga (and later studied by Akbari, Gillespie and Praeger), and develop a decoding algorithm for such codes based on earlier work of the first author for permutation group codes. In particular, we show how to implement this algorithm for an infinite family of groups considered by Akbari, Gillespie and Praeger.