Reviewerly/exHarmony huggingface dataset:
Blockchain-based Teaching Evaluation System for Ensuring Data Integrity and Anonymity

The significance of student feedback within educational institutions cannot be overstated, as it serves as a pivotal tool for evaluating faculty performance and identifying potential gaps in course content. Blockchain technology has emerged as an increasingly promising solution for diverse digital applications, owing to its distinctive attributes and robust security features. This study endeavors to explore the use of blockchain technology for secure student feedback systems in education, specifically for analyzing faculty performance in a course. However, a noteworthy challenge that plagues existing feedback systems is their inability to ensure complete anonymity, leading to students' hesitancy in providing candid and honest feedback. Furthermore, these conventional systems often rely on databases for data storage, rendering them susceptible to tampering and data breaches. In response to these pressing concerns, the present paper proffers a comprehensive and innovative solution. The crux of the proposed approach revolves around the implementation of a blockchain-based student feedback system, artfully designed to guarantee both student anonymity and tamper-proof data storage, thereby facilitating the evaluation of teaching effectiveness. By leveraging the potential of an Ethereum-based blockchain, a secure and trusted platform is meticulously established, catering to the sensitive realm of student feedback in an impervious and confidential manner. Concomitantly, a user-friendly web application is deftly developed to complement the proposed system, meticulously documenting the implementation process, Smart Contract and project code. It is noteworthy that this cutting-edge feedback system provides an invaluable layer of security, fostering heightened user trust and engendering an environment conducive to genuine and authentic evaluations.
Object Detectors in Autonomous Vehicles: Analysis of Deep Learning Techniques

Autonomous vehicles have emerged as a transformative technology with wide-ranging implications for smart cities, revolutionizing transportation systems and optimizing urban mobility. Object detection plays a crucial role in autonomous vehicles, accurately identifying and localizing pedestrians, vehicles, and traffic signs for safe navigation. Deep learning-based approaches have revolutionized object detection, leveraging deep neural networks to extract intricate features from visual data, enabling superior performance in various domains. Two-stage algorithms like R-FCN and Mask R-CNN focus on precise object localization and instance-level segmentation, while one-stage algorithms like SSD, RetinaNet, and YOLO offer real-time performance through single-pass processing. To advance object detection for autonomous vehicles, comprehensive studies are needed, particularly on two-stage and one-stage algorithms. This study aims to conduct an in-depth analysis, evaluating the strengths, limitations, and performance of R-FCN, Mask R-CNN, SSD, RetinaNet, and YOLO algorithms in the context of autonomous vehicles and smart cities. The research contributions include a thorough analysis of two-stage algorithms, a comprehensive examination of one-stage algorithms, and a comparison of different YOLO variants to highlight their advantages and drawbacks in object detection tasks.
Security Enhanced Operational Architecture for Decentralized Industrial Internet of Things: A Blockchain-based Approach

The remarkable development of the Industrial Internet of Things (IIoT) has undoubtedly elevated industrial operations to a more intelligence and efficiency level, yet it has also introduced a range of security challenges. The widespread of intelligent IoT devices has greatly expanded the attack surface for cyber-attacks. Additionally, the cloud-based centralized management architecture of traditional IIoT is susceptible to single-point-of-failure, which exacerbates the security risks. Nowadays, the secure and decentralized nature of blockchain has been considered a promising solution to address the security and privacy challenges in IIoT. This paper proposes a blockchain-based operational architecture for IIoT (SecureArchi-IIoT) to enhance security and privacy in IIoT operations. Under this architecture, a set of smart contracts are designed to provide operational functionalities that are suitable for actual industrial demands. An operational control policy is designed to realize precise and effective management of the operation permissions with distinct granularity. Furthermore, a reputation-based behavioral punishment mechanism is developed to enhance the security performance of the proposed architecture. The prototype of the proposed architecture is implemented in a private IIoT environment to demonstrate its feasibility and effectiveness. Experimental results confirm that the proposed architecture outperforms the traditional architecture in aspects of security and privacy and maintains acceptable real-time performance.
Pengembangan Video Pembelajaran Berbasis Think Talk Write (TTW) Pada Kemampuan Menulis Siswa Sekolah Dasar

The research aims to develop Think Talk write (TTW) based learning videos with writing skills materials for V-grade students that can be used to improve student learning outcomes. Researchers developed TTW-based learning videos using Research and Development research methods, the development of TTW-based learning videos uses 3-D models that define, design, and develop. The feasibility of TTW-based learning videos was validated by 6 experts with an average validation score of 0.88 with material expert details worth 0.91, linguists worth 0.91 and media experts valued at 0.84. with an average based on the interpretation table aiken V validation is in the high category. The teacher's response based on the interview showed a positive response in the "very appropriate" category and the student's response to the TTW-based learning video got a score of 91%. Based on the analysis of the needs of teachers and students, analysis of the feasibility test of experts in determining the feasibility of learning media as well as the responses of teachers and students as users, it can be concluded that the TTW-based learning videos that are compiled and developed are meaningful to be used as an alternative medium for learning Indonesian language learning content. especially writing skills for fifth grade elementary school students.
PENGEMBANGAN BAHAN AJAR DIGITAL BERBASIS POWERPOINT KOMBINASI ANIMASI DAN VIDEO PEMBELAJARAN MATERI ROTASI DAN REVOLUSI BUMI UNTUK SISWA KELAS VI

AbstractThe objectives of this study are (1) to produce digital teaching materials using PowerPoint with a combination of learning videos on the earth's rotation and revolution (2) to measure the feasibility of digital teaching materials using PowerPoint on earth's rotation and revolution (3) To describe the response of teachers and students of class VI to the use of digital teaching materials in online science learning. This development research referred to the stages of research and development of the ADDIE model consisting of four development procedures, which include: (a) the analysis phase, (b) the design phase, (c) the development phase, and (d) the implementation phase. However, this study only implemented three stages since students learned from home. The subjects in this study were sixth-grade students of the public elementary school in Kaur district, with eight males and 14 females. This research produces a product in the form of teaching materials in PowerPoint combined with learning videos in the form of files and links uploaded on YouTube. Based on the validation of the three aspects, digital learning material was valid (feasible), and the sixth-grade students could use it in learning. Six validators in their fields validated the product.
Analisis Kesulitan Guru dan Orang Tua Siswa dalam Implementasi Belajar dari Rumah (BDR) di Daerah 3t (Terdepan, Tepencil dan Terluar) Pada Muatan Pelajaran Bahasa Indonesia Aspek Keterampilan Membaca di Sekolah Dasar

AbstractThe purpose of this study was to determine the difficulties of teachers in preparing learning implementation plans and the difficulties of parents in guiding students in the learning process from home in the aspect of reading skills. The researcher used a qualitative descriptive method. In this study, the data collection methods used were observation and interviews. The results showed that the fourth grade teacher at SDN Napalicin had difficulties in designing learning implementation plans and in assessing student work. The obstacle experienced by the teacher is when designing learning objectives. This is because teachers find it difficult to analyze student needs and student conditions when learning from home. The results of interviews with people on learning from home parents have difficulty in accompanying students while studying. The difficulty experienced is when there are assignments or materials that students do not understand and ask parents, parents do not understand the orders or assignments given. Efforts made by parents vary, some use the internet to find information, some ask neighbors or ask directly with teachers whose houses are close by. Considering that the pandemic situation is still ongoing, it is not possible to conduct face-to-face learning. In this case, it takes the creativity of a teacher in designing lesson plans in order to achieve learning objectives and improve student learning outcomes.
IMPROVING THE STUDENTS’ VOCABULARY MASTERY BY USING WORD SQUARE MEDIA COMPARATIVE STUDY OF USING KWL AND QAR STRATEGIES ON STUDENTS’ READING COMPREHENSION

Reading is a complex activity. Through reading activities, readers have responses like rejection, acceptance, and criticism of what they have read. Therefore, appropriate strategies are needed in reading learning activities for students to facilitate reading comprehension. This study aims to determine significant differences in using KWL and QAR strategies on students' reading comprehension abilities.This study used an experimental method with a post-test-only design. The population in this study were students of class VIII SMPN 5 Banjarmasin. The sampling technique used in this study was using a saturated sampling technique for as many as 261 students. The instrument used was multiple choice questions in the form of a post-test. The data analysis technique in this study was the t-test at a significance level of 5%.The results showed that the student's reading comprehension who were taught by using the KWL strategy was 52.09 lower than those of the students taught by using the QAR strategy of 57.09 with a tcount of 2.251 and a p of 0.025 (p &lt; 0.05 ). The difference in the post-test mean of reading comprehension skills in the KWL strategy group and the QAR strategy group was 5.00. This shows that there is a significant difference in the use of KWL and QAR strategies on the reading comprehension skills of eight grade students at SMPN 5 Banjarmasin.
INFLATION VALUE FORECASTING POST COVID-19 IN DENPASAR USING ARIMA

Forecasting is used to predict something that will happen in the future so that appropriate actions can be taken. ARIMA is a time series forecasting method that was developed where the observation data in a time series data interact. Inflation instability in Denpasar City in the future will make it difficult for the central bank and the government to determine policy. The Covid-19 pandemic has an impact on the value of inflation in Denpasar City. The purpose of this study is to estimate inflation in Denpasar City after Covid using the best ARIMA model. Inflation data was taken from BPS Denpasar City from January 2020 to August 2022. ARIMA analysis was carried out according to the Box-Jenkins procedure, namely searching the data, estimating parameters and significance tests, and determining the best ARIMA model. The results of the analysis show that the best ARIMA model is ARIMA (0,1,1). The results of this study indicate that monthly inflation in Denpasar City is likely to continue to increase. Based on these results, it is hoped that appropriate policies will be made to reduce inflation.
Algoritma Stemming Teks Bahasa Batak Angkola Berbasis Aturan Tata Bahasa

The Angkola Batak language is a variety of Batak languages, to be precise in the southern Tapanuli area, which is still used and maintained as an everyday language. Until now, the resources of the Angkola Batak language are not yet available in digital form that can be used by researchers in the analytical stages of human natural language processing. Natural language processing (NLP Taks) for the Angkola Batak language must follow the stages of text processing starting from tokenization, lexical analysis, syntax, semantics, and phragmatics. This study conducted natural language processing in the first stage, namely lexical analysis. At the lexical analysis stage, one of the most important NLP tasks is stemming. Stemming is the process of determining root words from affixed words. In this research, an analysis and design of the Angkola Batak stemming algorithm have been carried out based on grammar rules. The stages in this research are starting from collecting the grammar rules of the Angkola Batak language, collecting basic words in the Angkola Batak language as a database dictionary, and removing affixes from root words. The output of this research is the stemmer of the Angkola Batak language in the form of PHP. Based on tests conducted on 450 words originating from the Batak Angkola folklore, 448 test words were correct (99.56%) and 2 test words were wrong (0.44%). The wrong test word is obtained because the root word is not found in the dictionary.
Expert System Hama dan Penyakit Tanaman Bawang Merah dengan Certainty Factor

This study aims to produce an expert system using the Certainty Factor (CF) Method for Diagnosing Pests and Diseases on Shallot Plants. The background of this research is to obtain information about pests and diseases. Expert System or expert system of Shallot Pests and Diseases with Certainty Factor is an expert system developed to identify pests and diseases in shallot plants. The development method used in the development of this system is the waterfall method. In the early stages of development, a needs analysis is carried out with the aim of understanding the requirements of the expert system, including the types of pests and diseases that must be identified, the associated symptoms, and the required expert knowledge. Furthermore, system design is carried out to design the system architecture and rule structure as well as the Certainty Factor weights that will be used in the diagnosis. In applying the certainty factor method, it gets a value of 46% for armyworm pests. After the design is complete, the implementation phase begins. At this stage, the expert system is designed and coded based on the designs that have been made before. The required modules, such as the inference module and the knowledge base module, are developed according to predetermined specifications. After the implementation is complete, the testing phase is carried out. using the black-box testing technique, with a score of 4.0 from the expert and 3.7 from the implementation of the beta user graph with a valid category. This test aims to ensure that the system provides an accurate diagnosis according to the symptoms observed in shallot plants.
Classification of coastal shrimp species using deep learning InceptionResNetV2 with data augmentation

Coastal areas that are rich in shrimp natural resources usually have a strong fishing industry. Shrimp consumption can contribute to the local economy. Several types of shrimp have higher utilization potential in the fishing industry and human consumption. Classification helps sort out shrimp species in coastal waters. Deep learning technology helps identify and separate shrimp species through deep learning with the Convolutional neural network. The seven classes observed were Vaname Shrimp, Tiger Shrimp, Jerbung Shrimp, Giant Prawns, Red Shrimp, Ronggeng Shrimp, and Prawns. The data used is 50 per class, so 350 images are used. Due to dataset limitations, the proposed contribution is an initial Resnet architecture with augmentation. Resnet helps perform in-depth training to save training computation time, and improvements add variety to limited amounts of data. The result is that the average accuracy of the model is 99.4%, with an average training computation time of 7 and a half minutes. The MSE misclassification value was 0.0143, RMSE was 0.1195, and MAE was 0.0086. Testing tests and testing data on the model only takes 1-2 seconds. Prediction accuracy ranges from 90.01%-99.8%.
One Line Plus Soft Keyboard Layout for Smartwatches Text Entry

The "One Line Plus" soft keyboard layout inspired by One Line and T9 layouts. This innovative design condenses the button layout into a single line, maximizing button size for ease of use. The implementation includes essential features like enter and autocorrect buttons to enhance user experience. Performance testing involving 31 participants was conducted to evaluate the effectiveness of the layout. The results showed an average words per minute (WPM) of 8.8 and a total character count of 43.48, with the highest WPM of 16 and character count of 89, and the lowest WPM of 4 and character count of 16. The analysis grouped participants based on their background, experience with smartwatches, and typing intensity. Notably, the group with frequent typing experience on smartwatches achieved the highest WPM of 11.3 and character count of 53.4, indicating the layout's efficacy for proficient users. The System Usability Scale (SUS) evaluation yielded an average score of 89.35, indicating the layout's successful usability. These findings demonstrate the potential of the One Line Plus soft keyboard layout for enhancing text entry on smartwatches.
Penerapan Metode Certainty Factor Dalam Mendiagnosa Penyakit PES

Plague is the oldest plague known to mankind and will continue to plague the world. Black Death is an infectious disease caused by the bite of Yersinia pestis, which breeds on rats. Human-to-human transmission occurs through droplets containing bubonic plague. Expert systems are a branch of artificial intelligence and a branch of knowledge that emerged with the development of computer science today. In this study, the expert system was implemented as a system for information or output to pursue certainty in diagnosing the type of bubonic plague felt by the patient based on the symptoms felt by the patient. Its use on the user's system must be combined with methods so that it runs correctly and optimally. In this study, the authors used the certainty factor (CF) method. CF is the internalization of uncertainty in professional thinking proposed by Shortliffe and Buchanan in 1975. Based on the results of the computational process using the CF method, information is generated that the patient suffers from multiple symptoms of bubonic plague, and the patient is diagnosed with pneumonic plague (P3) with an expression confidence level of 0.993 or 9.93%.
The Imperative Role of the Library in Health Insurance Information Needs in Nigeria

This study provides a springboard for stakeholders in health, Health Maintenance Organizations (HMOs) and library (information professionals) to undertake a possible and effective way to improving health insurance literacy and participation in Nigeria. The authors in this study posited creative approaches to using Libraries in Nigeria to improve the awareness of Nigerians on the benefits of the compulsory new Health Insurance Programme through viable partnership with governments at all levels, local and international Non-Governmental Organizations, based on the fact that libraries have succeeded in partnering with the stakeholders in the health sector in different countries of the world to achieve HI needs. Opinion Piece was used as method of research to buttress the clarity of the research perspective. The paper illuminated on some of the roles of the library in Health Insurance Information Needs such as availability of information resources on health insurance, health insurance literacy workshops, reference and research services, assistance with online insurance forms, partnerships with organizations, language and cultural accessibility, confidentiality, education and outreach.
Implementasi Algoritma Brute Force Pada Sistem Pertanahan di Balai Desa

Development epoch in era globalization like current information systems utilizing computer technology which is very sophisticated and modern will facilitate data processing which can save time and cost. Result information obtained will facilitate data processing which can save or agencies that utilize artificial intelligence humans or is often called artificial intelligence (AI). Processing data and information fast and efficiently are important things which are needed by an agency, one is office hall village. Processing or archiving books C or Letter C this village still uses manual methods with recording or writing data at books archives villages and views reworked sequence number parcel book C or Letter C previous: to record numbers on owners of old land and owner new land. The way is certainly not efficient because it will require a lot of books and take a lot of time to record data on ownership of land. Objective of this study i.e. implement algorithm brute force to facilitate the search owners land previous on archive electronic. Method development on a system which is used in research is a brute force algorithm in searching for land data, string matching is a part of the string search process. The resulting land data is very dependent on the technique or algorithm carried out in matching the string. In this study, the algorithm used in string matching is brute force. This algorithm performs matching strings with shifts one by one patterns and adjusts them to text so that between Pattern and Text have patterns which are equal. Results analysis of studies This is in the form of trials trial matching strings-with algorithms brute force with studies case using search or search engine with programming language PHP to matching strings.
Clay mineralogy and heavy metal geochemistry of the Tigris River sediments in selected area of northern Iraq

Thirteen samples of sediment were collected from the Tigris River between Hammam Al-Aleel and Fat'ha area, northern Iraq to determine the texture of these sediments, clay mineral assemblages and concentrations of some heavy metals. The grain size analysis of the samples revealed that the silt fraction is the most dominant type in the studied samples, and the size decreases down-stream in accordance with the river's morphology and gradient. The clay fraction was examined by employing XRD to recognize the clay mineral types. It was found that montimorillonite is the most dominant mineral, in addition to illite, palygoriskite, kaolinite and chlorite. The heavy metal elements were determined by Atomic Adsorption Spectrum (AAS) instrument and they included Zinc (Zn), Copper (Cu), Cobalt (Co), Cadmium (Cd) and Lead (Pb) in the clay fraction. However, due to human activities like fertilization of soil and industrial water, such elements as Pb (163 ppm), Zn (121 ppm), Co (33 ppm) were higher than the normal concentration, while the concentration of Cu (42 ppm) was lower than the normal.