Reviewerly/exHarmony huggingface dataset:
Development of Geogebra-Based Interactive E-Modules to Improve Students' Digital Literacy Abilities

Many students of Ivet University's mathematics education study program think that mathematics courses are very difficult and boring. This happens because students are positioned as listeners in the learning process so that what happens is that the learning process is too monotonous. So far, teaching and learning activities have only used books as a learning resource, an interactive approach will be able to make students more interested in the learning process. One interactive approach in the learning process is using geogebra-based interactive e-modules. The existence of geogebra-based interactive e-modules will further attract students in the learning process and improve students' digital literacy skills. The aim of this research is to produce a geogebra-based interactive e-module to improve students' valid digital literacy skills. The urgency of this research in learning is very important due to the low level of learning resources used in the learning process and the low level of digital literacy for students. The research that will be carried out will have a big impact on student understanding. It is hoped that the development of this interactive e-module will be able to overcome problems that arise in teaching students. It is hoped that limited learning resources can be overcome by having e-modules as a learning medium to prevent misunderstandings arising when teaching integral material. The result of this research is to produce a geogebra-based interactive e-module to improve students' valid digital literacy skills.
Cash Receipt Information System at Regional Drinking Water Companies Using PHP and MySQL

Manual accounting records have shortcomings in terms of accuracy of recording and slow reporting, as manually entered data has to be recapitulated. In some large companies that have branches of business, the users of technology are no longer strangers, but there are often difficulties in recording temporary cash receipts on their branches. From this background, the author carried out research by designing and building a web-based cash receipt application with PHP and MySQL. The author focused on the cash recording application because this application is allocated to branches of companies that have not implemented the system of financial recording, in this case cash receipts that will later be deposited with the central company because the funds received are temporary. This research helps companies record cash receipts and cash deposits and provide final results in the form of a report of each transaction carried out by the company. Like previous research on cash flow information systems, it suggests that the existence of information systems can help in carrying out financial recording, as well as other research that states that computerized recording is much more effective and efficient and facilitates
ALGORITHM FOR SYNTHESIS OF COMBINATIONAL LOGIC CIRCUITS BASED ON THE EVOLUTIONARY APPROACH

The emergence of new technologies for manufacturing components of digital electronic deviceshas led to the need to improve the efficiency of computer-aided design methods. Increasingrequirements for elements causes an increase in the size of the problems being solved. To solveproblems that were previously impossible to automate, new methods and software applications arebeing developed. Specialists are faced with the task of developing fundamental principles for constructingnext-generation design systems. The development of devices with such characteristics asreliability, survivability, and automatic damage repair is an urgent task. This paper proposes anapproach to solving the problem of synthesizing combinational circuits based on the use of evolutionarydesign methods. Evolutionary design of a technical system refers to the purposeful use ofcomputer models of evolution at all stages of system development. The goal is to enable fully automaticdesign. The main idea of self-reconfigurable hardware systems is to replace generalpurposehardware systems with systems that can adapt to the specifics of the software being executed.The synthesis of a programmable circuit is based on the principle of “bottom-up” design –from the lowest to the highest level. This allows you to configure the hardware individually byprogramming logic elements. To implement this task, evolutionary algorithms are used. Logicfunctions can be described by combinational circuits. One of the advantages of combinationalcircuits is their high performance. The task is to develop the structure of a combinational logiccircuit based on a given truth table and nomenclature of logical elements. The work proposed anevolutionary algorithm for the synthesis of combinational logic circuits. A technique for encodingalternative solutions and modified evolutionary operators for synthesizing new solutions weredeveloped. A software implementation of the proposed algorithm has been completed. The computationalexperiments carried out confirmed the correctness of the chosen approach. The use ofevolutionary methods for the synthesis of combinational logic circuits makes it possible to increasethe intelligence of design systems.
CHARACTERISTICS OF QUANTUM CIRCUITS WITH FUNCTIONAL CONFIGURATIONS OF QUBITS

The paper is an exploration of a new approach to the systematic analysis and classificationof quantum circuits based on the functional configuration of qubits. The article examines in detailthe role of elementary gates in changing the elements of the state vector and highlights the importanceof functional configurations of qubits in the collective modification of quantum states.The main aspects covered in the article include the characterization of quantum circuits with functionalconfigurations of qubits, analysis of the impact of elementary gates on the state of a quantumvector, and determination of the number of possible types of functional configurations.The results of the study could have important implications for optimizing quantum circuits andimproving our understanding of their general properties. A qubit functional configuration is amathematical structure that can collectively classify the properties and behavior of quantum circuits.The development of quantum algorithms with efficient quantum circuits has been a centralpart of quantum computing, which has seen enormous progress both theoretically and experimentallyover the past 30 years. The paper makes a contribution to the field of quantum computing byproviding a systematic approach to classify and analyze quantum circuits based on their functionalqubit configurations. Quantum algorithms are an innovative class of algorithms based on theprinciples of quantum mechanics and using qubits instead of classical bits to process information.Unlike classical algorithms, which operate on bits that take on the values 0 or 1, quantum algorithmscan use the principles of quantum superposition and quantum interaction, which allowsthem to perform many calculations simultaneously. One of the key advantages of quantum algorithmsis their ability to solve certain problems much more efficiently than classical algorithms.However, the design and implementation of quantum algorithms pose significant technical andalgorithmic challenges, such as managing quantum states, minimizing errors, and creating robustquantum gates. Despite these challenges, quantum algorithms offer promising opportunities torevolutionize computing and solve problems that have traditionally been too complex for classicalcomputers
8-BAND HETEROGENEOUS BANK OF FIR FILTERS WITH HIGH COMPUTATIONAL EFFICIENCY FOR HEARING AIDS

This article discusses recursive filters with finite impulse response and filter banks. The filterbank is an array of bandpass filters. The analysis filter block divides the input signal into severalcomponents, with each of the sub-filters carrying one frequency sub-band of the original signal.On the contrary, the synthesis filter block combines the output data of the sub-bands to restorethe original input signal. In most applications, certain frequencies are more important than others.Filter blocks can isolate various frequency components in the signal. This way we can put moreeffort into processing more important components and less effort into processing less importantcomponents. Subband filters can be combined with step-down or step-up sampling to form a bankof multi-speed filters. Filter banks are widely used for speech recognition and speech quality improvement.Currently, filter banks have expanded their application to video and image processing.In addition, filter blocks are very useful in communication systems, including digital receivers andtransmitters, pre-coding of filter blocks for channel alignment, discrete multi-tone modulation andblind channel alignment. The use of these filters for hearing aids is considered. An 8-band heterogeneousbank of recursive filters with finite impulse response (FIR) with high computational efficiencyfor hearing aids has been developed. The computational complexity (BC) of a recursivefilter with a finite impulse response (RCIHF) is also compared with the computational complexityof non-recursive filters with a finite impulse response (NCIHF).
Design and Construction of a Website-Based Online Sales Information System for Cake Products (Case Study: Vavivegga Business House, Halong)

Sales via the internet network can easily make trade connections without any access time limitations and can increase the number or turnover of sales, and can increase the area of marketing locations or product sales accurately. The aim of this research is to design an online sales information system for the Vavivegga business house in order to expand the business that has been created for a long time and to help make the business known to all in the community. Making web applications refers to the RAD Method. The results obtained from the design and development of a website-based online sales information system at the Vavivegga business house can help consumers see the cake products that are made without having to come to the business location, besides making it easier for consumers who want to place orders
Current trends of artificial intelligence and applications in digital pathology: A comprehensive review

Digital pathology is a field that blends various techniques for obtaining, analyzing, sharing, and saving information about pathology. This information often comes from digitized microscope slides. Digital pathology also uses artificial intelligence (AI) to help reduce errors made by humans. This review talks about digital pathology and the new techniques linked to it. Instead of traditional microscopes, digital pathology employs virtual microscopy and whole-slide imaging. It marks a major improvement over old pathology methods, which had several problems. Digital methods use computers and machines to solve these issues. The basic process of digital pathology has three parts: the input stage, the analysis stage, and the output stage, which includes storing the information. This review focuses on two main techniques: object detection and its smaller methods, and the use of AI and its specific approaches like explainable AI (XAI) and deep learning. The paper also discusses various deep learning methods, mainly used to detect different types of cancer. It also acknowledges that not every method is perfect, so we discuss various challenges and limitations of digital pathology techniques that need to be solved before these methods can be widely used.
Implementation of Information Gain Ratio and Particle Swarm Optimization in the Sentiment Analysis Classification of Covid-19 Vaccine Using Support Vector Machine

In the current digital era, sentiment analysis has become an effective method for identifying and interpreting public opinions on various topics, including public health issues such as COVID-19 vaccination. Vaccination is a crucial measure in tackling this pandemic, but there are still a number of people who are skeptical and reluctant to receive the COVID-19 vaccine. This public perception is largely influenced by, including information received from social media and online platforms. Therefore, sentiment analysis of the COVID-19 vaccine is one way to understand the public's perception of the COVID-19 vaccine. This research has the purpose to enhance the classification performance in sentiment analysis of COVID-19 vaccines by implementing Information Gain Ratio (IGR) and Particle Swarm Optimization (PSO) on the Support Vector Machine (SVM). With a dataset of 2000 entries consisting of 1000 positive labels and 1000 negative labels, validation was performed through a combination of data splitting with an 80:20 ratio and stratified 10-Fold cross-validation. Applying the basic SVM, an accuracy of 0.794 and an AUC value of 0.890 were obtained. Integration with Information Gain Ratio (IGR) feature selection improved the accuracy to 0.814 and an AUC of 0.907. Furthermore, through the combination of SVM based on PSO and IGR, the accuracy significantly improved to 0.837 with an AUC of 0.913. These results demonstrate that the combination of feature selection techniques and parameter optimization can enhance the performance of sentiment classification towards COVID-19 vaccines. The conclusions drawn from this research indicate that the integration of IGR and PSO positively contributes to the effectiveness and predictive capability of the SVM model in sentiment classification tasks.
Science Mapping of Perceived Organizational Support: A Bibliometric Analysis Approach

The purpose of this study is to obtain related topic and information regarding perceived organizational support. In conducting this study, the researcher utilized Scopus database for data mining and extraction. A total of 816 articles were discovered in the Scopus database accessed on July, 2023. Afterward, VOSviewer is utilized for scientific mapping and analysis of publication performance such as identify the contributions of authors, journals, countries, and author keywords number. Several countries have contributed to publications of perceived organizational support. The data reveals that the US contributes the most to this publishing subject, followed by China, India, the UK, Australia, Malaysia, Pakistan, South Korea, Canada, and Turkey. Most works on the topic are from these nations. The "International Journal of Human Resource Management" has the most important influence on this topic based on article document output. While, "Journal of Management" has the greatest number of citations. This topic's top five authors write the most articles and Stinglhamber F. is the most prominent author in perceived organizational support study. Meanwhile, the most referenced author in this field is Eisenberger R., with 1,300 citations. This research can serve as a point of reference for future research pertaining to POS topic.
Klasifikasi Daun Herbal Menggunakan K-Nearest Neighbor dan Convolutional Neural Network dengan Ekstraksi Fourier Descriptor

The number of herbal plants in Indonesia is 30,000, but only about 1,200 plants are used in medicine. The large number of herbal plants makes it difficult for people to distinguish one type of herbal plant from another. From these conditions, this research has conducted tests to compare the performance of the K-Nearest Neighbor (KNN) and Convolutional Neural Network (CNN) methods using Fourier Descriptor (FD) feature extraction on herbal plants, namely moringa (moringa oleifera) and katuk (sauropus androgynus). The amount of data used is 480 data using image conditions, namely dark and light images which are then divided into 20% testing data and 80% training data. Classification is done using the KNN method using 5 distance calculations (Euclidean, Chebyshev, Manhattan, Minkowski, and Hamming) and CNN with FD feature extraction. From the tests that have been carried out, it is found that the use of FD feature extraction for the KNN method produces the best performance on both light and dark image data. While the use of the CNN method, for dark image data, the best accuracy results are obtained with FD feature extraction and CNN. Meanwhile, for bright image data, the best performance accuracy results are obtained in the CNN method without going through feature extraction. Of these three methods, using FD and KNN feature extraction is more recommended because it produces 100% accuracy in moringa and katuk images with light and dark intensity.
Rancang Sangkar Burung Pintar Berbasis IoT

Raising birds for hobby and breeding is currently trending in the community. With the general business of the public, a common challenge faced by bird enthusiasts is the process of caring for birds, especially providing timely and accurate feeding and watering. To address this issue, research has been conducted to create a smart bird cage. The smart bird cage is designed to automatically provide food and water with remote control via mobile internet. This research applies modules such as ESP8266-01, servo motor, Relay 2 module, water level sensor, mini water pump, ultrasonic sensor, and the Blynk application that can be integrated as a control service using IoT. The result of this research is the specification of the cage for providing food and water that can be controlled automatically with specific measurements so that the feeding and watering patterns can be more organized.
PENERAPAN DATA MINING DALAM MENEMUKAN POLA DATA ANGGARAN PENDAPATAN BELANJA DAERAH KOTA MALANG METODE FP-GROWTH

This study has the aim of applying data mining to find patterns in the Malang city regional income and expenditure budget. This research uses the fp-growth method, which will be used to solve data mining analysis problems in determining budget data patterns, which will later be used to find out a strategy for maximizing budget data. The results of the research show that to maximize the income budget received, it is necessary to increase the budget for personnel expenditure, capital expenditure, and expenditure on goods and services, as well as provide subsidies to district, city, and village governments.
Enhancing Elementary Literacy Skills through a Contextualized Coastal Course Book: A Developmental Study in Bengkulu, Indonesia

Teaching materials designed using local contexts are important in improving students' literacy skills. The lack of teaching materials to support these skills causes low student literacy achievements in elementary schools. This study aims to design a course book, grounded in the coastal context of Bengkulu, to enhance the literacy skills of elementary school students. The research employs a developmental approach using the ADDIE model, which encompasses five stages: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. The subjects of the study are fifth-grade students from elementary schools in Bengkulu City. The study is conducted in three phases: expert trials, limited trials, and wide-scale trials. Data is collected through both tests and non-tests. The instruments used for data collection include product validity sheets, practicality questionnaires, and literacy test instruments. Descriptive statistical analysis is utilized for data analysis. The result of the research suggests that the course book, based on the Bengkulu coastal context, meets the criteria for validity, and practicality, and effectively enhances the literacy skills of elementary school students. Teaching materials that integrate with coastal contexts have been proven to support students' thinking skills, one of which is mathematical literacy.
Hubungan Kualitas Tidur Dengan Prestasi Belajar Murid Kelas X-Xii Di SMA Muhammadiyah 7 Yogyakarta

Introduction: Learning achievement is a student's effort to achieve mastery of knowledge, abilities, habits and skills and attitudes after following the learning process which can be proven by test results. Learning achievement is very important in the world of education because it evaluates the achievement of changes in accordance with learning objectives or not. One of the factors that influence learning achievement is sleep quality.&#x0D; Purpose: This research aims to determine the relationship between sleep quality and the learning achievement of students in grades X-XII at SMA Muhammadiyah 7 Yogyakarta.&#x0D; Method: This research is quantitative research with correlation studies and cross-sectional data collection. The research subjects were 79 students in class X-XII at SMA Muhammadiyah 7 Yogyakarta with with a simple random sampling method. Data collection was measured using the PSQI questionnaire and documentation data on student learning achievement was analyzed using the Chi-Square test.&#x0D; Result: The research results showed that 58 respondents (73.4%) had good sleep quality and 21 respondents (26.6%) had poor sleep quality. It was found that 67 respondents (84.8%) had good learning achievements and 12 respondents (15.2%) had poor learning achievements. It was found that there was a significant relationship between sleep quality and the learning achievement of students in grades X-XII at SMA Muhammadiyah 7 Yogyakarta (p=0.000, r=0.703)&#x0D; Conclusions: Based on the research results, there is a significant relationship between sleep quality and the learning achievement of students in grades Therefore, students can maintain and improve sleep quality such as sleep duration and sleep start time.
Studi Perencanaan Irigasi DAS Malaya di Kecamatan Lemong Kabupaten Pesisir Barat Provinsi Lampung Berbasis Sistem Informasi Geografis

Pesisir Barat Regency has large land potential in agriculture sector, especially for rice cultivation, including in the administrative area of Lemong District. To increase the productivity of paddy fields at Lemong District, it is necessary to analyze the irrigation water needs. Therefore, research was carried out on the analysis of rice irrigation water needs and the river water discharge needed for irrigation. The research was carried out in analysis stages including analysis of water balance using SWAT models which is integrated in the geographic information system, analysis of plant water needs, analysis of water irrigation needs, minimum discharge needed for land irrigation and analysis of water resource adequacy. The research result show that the potential water resource in Lemong District can meet the irrigation water needs of rice cultivation in two planting seasons with coverrage area that can be developed of 76.42 hectares. Meanwhile, in the third planting season for planting of secondary crops, the potential of river discharge is only sufficient for 19 hectares and in order for the target planting area of 76.42 hectares to be archieved it is necessery to add irrigation originating from ground water (pump irrigation) with discharge of 0.51 m3/sec. Keywords: Geographic information system, Irrigation, SWAT.
Theme-Rheme And Thematic Progression Analysis Of Joe Biden’s Speech On Israel-Hamas And Russia-Ukraine Wars

The study mainly focuses on Theme-Rheme and Thematic Progression in the speech of Joe Biden on Israel-Hamas and Russia-Ukraine Wars. The objective of this study is to examine the type of Theme-Rheme and Thematic Progression pattern found in the speech text. To examine the data, the study employed a qualitative method with a descriptive design. The data is derived from Biden’s speech on the United States’ Response to Israel-Hamas and Russia-Ukraine Wars. The data was analysed using Halliday’s theory (1994, 2004) to analyse the Theme-Rheme and Paltridge, (2006) to analyse the Thematic Progression pattern. Based on the study, it shows that Participant as Topical theme is the most dominant, while, Constant theme is the most dominant in Thematic Progression patterns.