Reviewerly/exHarmony huggingface dataset:
IMPROVING LITERACY SKILLS THROUGH STRENGTHENING THE QUALITY OF SCHOOL-BASED EDUCATION

The problem of literacy is one of the problems that must receive special attention from the people of Indonesia. This is because, in the last few decades, the competitiveness of Indonesian people has tended to be less competitive, one of which is due to the crisis of literacy culture. This literacy culture crisis is often related to quality in an educational institution. Thus, this study aims to understand strategies to improve the literacy skills through strengthening the quality of school-based education. This research uses a qualitative approach with a case study type. The data in the study were obtained through observation, interviews and documentation techniques. The data is then analyzed using the Miles and Huberman data analysis technique which consists of data reduction, data display, and verification. The results of the study show that quality improvement oriented towards achieving literacy skills in students is carried out by; 1) reward and punishment for students, 2) teacher competence development, 3) learning orientation based on learning processes and outcomes, 4) teacher mastery of technological media, and 5) library visits.
Aplikasi Location Based Service (LBS) Cafe Berbasis Android Di Kota Bandar Lampung

The cafe has become a popular place to be used as a gathering place with family and friends, because it is an uncomfortable and cool place to be used as a gathering place and a means to socialize, and on the other hand there is still a lack of information media that can be used to find information from an existing cafe. in a city, the android application created in this study can be used as a medium of information in searching for data, coordinates, and distance from a cafe. The goal is to make it easier for local residents and tourists who want to find references for gathering places such as cafes. The author got a solution with the creation of an Android-based mobile application with the title of the report entitled Application Location Based Service (LBS) Bandar Lampung City Cafe Based on Android. The results of the Android-Based Location Based Service Cafe application in Bandar Lampung City can work well while making it easier for the people of Bandar Lampung City and outside the city to obtain information from the café contained in the application.
Aplikasi Game Edukasi Pengenalan Huruf Hijaiyah Untuk Anak Usia Dini Berbasis Android

AbstractFor Muslims, there is an obligation to read, understand, and practice the contents of the Qur'an. But in order to practice and understand the contents of the Koran, you must first be able to read and recognize the hijaiyah letters. To introduce hijaiyah letters to children, it is necessary to use an effective and fun method, which is intended so that children do not experience boredom and stay focused on what is being taught. The case study in the research object was carried out in Babatan village in Katibung District, where the hijaiyah letter recognition method still uses conventional methods, namely using a guidebook called IQRA, besides teaching and learning activities at TPQ are also constrained by rainy weather and holidays that result in learning activities teaching at TPQ will be closed. Based on the description of these problems and increasingly sophisticated technological advances, the researcher proposes to make a game application in the form of educational animation that can make it easier for children in hijaiyah letter recognition patterns, especially ages 3-10 years. The results of this study are the hijaiyah letter recognition educational game application system has been running in accordance with the initial objectives of the study where, the application is able to know and understand the form of letters, distinguish letter forms, how to read letters and sounds of Hijaiyah letters properly and correctly and with the Recognizing Letter Game. The Hijaiyah system is able to attract children's interest in learning at TPQ Al-Muhajirin Babatan Village, Kec. Katibung.
Perancangan Aplikasi QR Code Pendaftaran Perizinan Berbasis Android Pada Dinas Penanaman Modal Dan Pelayanan Terpadu Satu Pintu Kota Bandar Lampung

Based on the research, it is necessary to have an information media that is quite effective of the public registering permits in Bandar Lampung City. The purpose of the research is to make it easier for applicants who register their licenses of permits at Dinas Penanaman Modal Dan Pelayanan Terpadu Satu Pintu Kota Bandar Lampung. So the author makes a solution by making a mobile application with a report entitled "Designing an Android-Based Licensing Registration Application at Dinas Penanaman Modal Dan Pelayanan Terpadu Satu Pintu Kota Bandar Lampung. This application utilizes the QR-Code System which is used for print media applications. The main feature used in this application is the QR-Code feature so that applicants can easily register each application when registering their permits. The system development method uses the waterfall method and the system design uses UML (Unified Modeling Language). In this research, the author makes an android application using react-native.
Sistem Penunjang Keputusan Untuk Evaluasi Kinerja Guru Menggunakan Metode Simple Additive Weghting (Studi Kasus : SMA N 1 Katibung)

Every last semester, Katibung 1 Senior High School always got the evaluation about teacher performance that scored by the headmaster or builder of the teacher that chosen by the headmaster, partner of the teacher, and the students that input a questionnaire. Data processing was scored from questionnaire, has been computerized with using a google forms. However no especially apps yet that is processing data . where the is resulting information is not effective and efficient , because needing the time for processing data of the result questionnaire and in the process of the teacher performance determination error may occurred.
Sistem Pakar Diagnosa Penyakit Udang Vannamei Menggunakan Metode Forward Chaining Berbasis Web (Studi Kasus : Petambak Udang Dirawajitu)

One of the causes of failure in pond shrimp farming is disease. The most dangerous disease attacks and causing losses to farmers are due to viral attacks of Myo/Infectious Myo Necrosis Virus (IMNV) of Shrimp, White Spot Syndrome (WSS) of Shrimp, Early Mortality Syndrome (EMS), and Yellow Head Disease. / Yellow Head Disease. The purpose of the research is to build an expert system application that can diagnose pond shrimp disease using the backward chaining method so as to help the community in Rawajitu sub-district in aquaculture shrimp., the system design method used is Unified Modeling Language (UML), the system development method used is Waterfall, and system built using Adobe Dreamweaver 8 tools and MySQL database. The results of this study are the application of an expert system that can diagnose pond shrimp disease using the backward chaining method. The system created later is expected to provide services to shrimp farmers in obtaining information on shrimp disease and accurate disease management solutions.
SISTEM INFORMASI AKUNTANSI ANGGARAN LABA DENGAN METODE A POSTERIORI

Information technology can be used in various human lives, one of which is in the business field. In today's era, it is undeniable that computers with accounting information system equipment are components that must be owned by companies to help ease the task of company performance. One of them is BKM which is specifically aimed at poverty alleviation and community development. UPK itself is a non-profit organization or an organization whose main objective is to support an issue or matter in attracting public attention for a non-commercial purpose, without any attention to things that are for-profit. The allocation has also been divided according to their respective portions.&#x0D; This study aims to simplify the presentation of profit budgeting at BKM which is still not structured and does not provide clarity about the results of the funds that should be used as the allocation of community activities. Profit budgeting is also not carried out periodically and is still manual in recording so that profits cannot be known in detail. In overcoming the problems above, by using a programmed system with the a posteriori method, the institution can easily record every operational budget to the profit budget so that it can allocate funds for community activities in a structured manner
RESPON SISWA TERHADAP PENGGUNAAN MEDIA KOMIK DALAM PEMBELAJARAN IPA MATERI LISTRIK STATIS SISTEM DARING

This study aims to determine the response of students to the use of comic media in science learning with static electricity material which the authors expect to get a positive response from students and can help reduce student boredom in science learning using comic media. By making media that is fun and does not make students bored, students will be more enthusiastic in learning and the learning process can take place well without any complaints from students who feel bored by only using written media. Material static electricity is one of the branches of physics material that is important for students to understand. By using comic book media in delivering static electricity with a few pictures, it can reduce student boredom and it will be more fun than just writing. This research method uses a qualitative method by surveying the opinions of several students in different schools regarding the use of comic media on online system static electricity material using the whats app group. The results of the study showed that many students were interested in the use of comic media compared to only using writing in science learning with static electricity in online systems. Keywords: student responses, comic media, science learning, static electricity, online
The Role of BPOM in the Circulation of Cosmetics With Fake Distribution Permission

This study aims to determine the role of Food and Drug Supervisory Agency (will be referred as BPOM) in the distribution of cosmetics that include a fictitious distribution permit. The method used in this study is an empirical research methodology. This study uses a qualitative approach and sampling using purposive sampling and using descriptive analysis techniques. The results of this study show that the role of BPOM in the distribution of cosmetics that includes a fictitious distribution permit basically continues to carry out Supervision, Guidance, and Prosecution of every producer who violates government regulations related to the circulation of counterfeit cosmetics that include a fictitious distribution permit number and there are several programs that are run to deceive consumers. get the right. In addition, it continues to provide protection to consumers who experience losses by providing administrative sanctions to the perpetrators to be able to pay for the losses suffered by the consumers themselves. Protecting Consumers from the Circulation of Dangerous Cosmetics BPOM has several programs, namely the National Movement to Beware of Illegal Drugs and Food (GNWOMI), GENPOPA, BPOM Checks, Public Warnings, Educational Videos, Community Awareness Index Surveys, Implementing Teams for Quality Improvement of Community Empowerment and Consumer Protection.
Entrepreneurship and Innovation

The previous several decades have seen significant progress in our knowledge of the link between entrepreneurship and development and knowledge on the one hand, and the other. The relationship between entrepreneurship, innovation, and knowledge has also been analysed in more detail. However, a full understanding of the interplay between all of those variables: knowledge, innovation, entrepreneurship, and growth are still inadequate. When it comes to growth, the relationship between microeconomics and macroeconomics is still too crudely described to appreciate the whole range of these complex and conflicting dynamics. This paper's major goal is to shed light on recent developments in our understanding of the mechanisms that support knowledge production, dissemination, and commercialization via innovation, as well as the role of the "entrepreneur in the growth process". Conclusions drawn from current study results are included in this summary. The design of regulations that influence knowledge creation, ownership, entry barriers, labour mobility, and (inefficient) financial markets has substantial policy consequences. To a certain extent, each of these has implications for the effective spread of information by way of admission. Motivating processes to transform knowledge into societal beneficial demands are as important as creating new information itself.
The Role Of The Police In Completing The Practice Of Domino Card Gaming

Abstract: The implementation of this research is to find out and analyze the role of the police in dealing with domino card gambling practices and to find out the factors that hinder the police in dealing with domino card gambling practices and the type of research is empirical research. The results show that the role of police in dealing with domino card gambling practices still has obstacles in the form of an approach to the community, one of which is the lack of socialization from the police even though it is carried out using pre-emptive and repressive measures. Meanwhile, the factors that hinder the police in dealing with the practice of domino card gambling are that the police are still difficult to track down the places where gambling practices occur. carried out by the community, the low level of public awareness is based on the consequences of unsupportive Economic, Knowledge, Entertainment and C,ultur,e and Community Environment factors. Keywords: The Role of the Police, Domino's Card Gambling
Review on Isolated Urdu Character Recognition: Offline Handwritten Approach

Abstract: This paper summarizes a system for recognizing isolated Urdu characters using advanced machine learning algorithms. The system analyzes visual features of Urdu characters, like strokes and curves, to train models such as CNN, SVM, ANN, and MLP. With a large dataset, the system can accurately predict unseen characters. It can be integrated into various applications for real-time character recognition tasks like OCR (Optical Character Recognition) and handwriting recognition. This literature survey explores research papers focused on character recognition in languages like Urdu, Arabic, Persian, and Sindhi, proposing various techniques like feature extraction, deep learning, and machine learning to enhance character recognition technology. The survey highlights specific studies with high accuracy and discusses recognition systems for Arabic characters as well.
Blockchain-IoT supply chain: systematic literature review

Since 2016, the implementation of blockchain in the supply chain has attracted wide interest among researchers. The creation and study of blockchain technology have grown at an exponential rate in the last decade. The supply chain would be a massive technological leap with the combination of blockchain technology that brings major changes to different facets of the industry, such as record immutability, improved traceability, quality assurance, improved knowledge flows, decentralized power structure, and decreased chances of fraud. With the growth in blockchain Internet-of-Thing (IoT) supply chain technologies, the security risk of implementing such technologies and methods to counter it has been largely discussed among researchers. This study analyses peer-reviewed literature attempting to use authentication in the blockchain-IoT supply chain to counter security risks in the technologies and provides a comprehensive analysis of the important feature when creating an authentication technique for the blockchain-IoT supply chain. Finally, the study discusses some of the problems and research objectives in the realm of authentication in the blockchain-IoT supply chain.
Fault-tolerant backup storage system for confidential data in distributed servers

This article addresses the critical issue of securing backup storage for confidential data, a key concern in safeguarding the operations of critical information systems dealing with extensive amounts of sensitive information. The study proposes a novel cryptographic fault-tolerant backup storage system for confidential data, leveraging cryptographic algorithms and protocols. These protocols enable message encryption, ensuring decryption is only possible after a specified time period. The proposed system combines various distributed key generation protocols, proactive secret sharing protocols, asymmetric encryption algorithms, and digital signature algorithms. By employing such cryptographic protocols, it becomes feasible to develop and implement a robust, fault-tolerant service for backing up confidential data.
MyVoice: Arabic Speech Resource Collaboration Platform

We introduce MyVoice, a crowdsourcing platform designed to collect Arabic speech to enhance dialectal speech technologies. This platform offers an opportunity to design large dialectal speech datasets; and makes them publicly available. MyVoice allows contributors to select city/country-level fine-grained dialect and record the displayed utterances. Users can switch roles between contributors and annotators. The platform incorporates a quality assurance system that filters out low-quality and spurious recordings before sending them for validation. During the validation phase, contributors can assess the quality of recordings, annotate them, and provide feedback which is then reviewed by administrators. Furthermore, the platform offers flexibility to admin roles to add new data or tasks beyond dialectal speech and word collection, which are displayed to contributors. Thus, enabling collaborative efforts in gathering diverse and large Arabic speech data.
Evaluating ChatGPT and GPT-4 for Visual Programming

Generative AI and large language models have the potential to drastically improve the landscape of computing education by automatically generating personalized feedback and content. Recent works have studied the capabilities of these models for different programming education scenarios; however, these works considered only text-based programming, in particular, Python programming. Consequently, they leave open the question of how well these models would perform in visual programming domains popularly used for K-8 programming education. The main research question we study is: Do state-of-the-art generative models show advanced capabilities in visual programming on par with their capabilities in text-based Python programming? In our work, we evaluate two models, ChatGPT (based on GPT-3.5) and GPT-4, in visual programming domains for various scenarios and assess performance using expert-based annotations. In particular, we base our evaluation using reference tasks from the domains of Hour of Code: Maze Challenge by Code-dot-org and Karel. Our results show that these models perform poorly and struggle to combine spatial, logical, and programming skills crucial for visual programming. These results also provide exciting directions for future work on developing techniques to improve the performance of generative models in visual programming.
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning

We present a novel unified bilevel optimization-based framework, \textsf{PARL}, formulated to address the recently highlighted critical issue of policy alignment in reinforcement learning using utility or preference-based feedback. We identify a major gap within current algorithmic designs for solving policy alignment due to a lack of precise characterization of the dependence of the alignment objective on the data generated by policy trajectories. This shortfall contributes to the sub-optimal performance observed in contemporary algorithms. Our framework addressed these concerns by explicitly parameterizing the distribution of the upper alignment objective (reward design) by the lower optimal variable (optimal policy for the designed reward). Interestingly, from an optimization perspective, our formulation leads to a new class of stochastic bilevel problems where the stochasticity at the upper objective depends upon the lower-level variable. To demonstrate the efficacy of our formulation in resolving alignment issues in RL, we devised an algorithm named \textsf{A-PARL} to solve PARL problem, establishing sample complexity bounds of order $\mathcal{O}(1/T)$. Our empirical results substantiate that the proposed \textsf{PARL} can address the alignment concerns in RL by showing significant improvements (up to 63\% in terms of required samples) for policy alignment in large-scale environments of the Deepmind control suite and Meta world tasks.
SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents

Deep reinforcement learning algorithms (DRL) are increasingly being used in safety-critical systems. Ensuring the safety of DRL agents is a critical concern in such contexts. However, relying solely on testing is not sufficient to ensure safety as it does not offer guarantees. Building safety monitors is one solution to alleviate this challenge. This paper proposes SMARLA, a machine learning-based safety monitoring approach designed for DRL agents. For practical reasons, SMARLA is designed to be black-box (as it does not require access to the internals or training data of the agent) and leverages state abstraction to reduce the state space and thus facilitate the learning of safety violation prediction models from agent's states. We validated SMARLA on two well-known RL case studies. Empirical analysis reveals that SMARLA achieves accurate violation prediction with a low false positive rate, and can predict safety violations at an early stage, approximately halfway through the agent's execution before violations occur.
Designing a Deep Learning-Driven Resource-Efficient Diagnostic System for Metastatic Breast Cancer: Reducing Long Delays of Clinical Diagnosis and Improving Patient Survival in Developing Countries

Breast cancer is one of the leading causes of cancer mortality. Breast cancer patients in developing countries, especially sub-Saharan Africa, South Asia, and South America, suffer from the highest mortality rate in the world. One crucial factor contributing to the global disparity in mortality rate is long delay of diagnosis due to a severe shortage of trained pathologists, which consequently has led to a large proportion of late-stage presentation at diagnosis. The delay between the initial development of symptoms and the receipt of a diagnosis could stretch upwards 15 months. To tackle this critical healthcare disparity, this research has developed a deep learning-based diagnosis system for metastatic breast cancer that can achieve high diagnostic accuracy as well as computational efficiency. Based on our evaluation, the MobileNetV2-based diagnostic model outperformed the more complex VGG16, ResNet50 and ResNet101 models in diagnostic accuracy, model generalization, and model training efficiency. The visual comparisons between the model prediction and ground truth have demonstrated that the MobileNetV2 diagnostic models can identify very small cancerous nodes embedded in a large area of normal cells which is challenging for manual image analysis. Equally Important, the light weighted MobleNetV2 models were computationally efficient and ready for mobile devices or devices of low computational power. These advances empower the development of a resource-efficient and high performing AI-based metastatic breast cancer diagnostic system that can adapt to under-resourced healthcare facilities in developing countries. This research provides an innovative technological solution to address the long delays in metastatic breast cancer diagnosis and the consequent disparity in patient survival outcome in developing countries.