Reviewerly/exHarmony huggingface dataset:
EFL Teachers’ Perceptions Towards the Integration of Literary Texts in EFL Classes

Literary texts have been crucial for many years in English language education. Therefore, using literary texts in This study aims to find out EFL teachers’ views related to the use of literary texts in English language education. A questionnaire and interview questions were used in this data collection process. The data was collected through Google Forms, online meetings, and phone calls. The result of this study indicates that English teachers’ views and attitudes about using literary texts in English language education are quite positive. Most of the participants indicated that they like literary texts and try to use them in their lessons as much as possible according to the interviews. Also, the results of the questionnaire showed EFL teachers believe that the integration of literary texts helps and promotes most of the subjects in English language teaching such as skills, grammar, and vocabulary. In addition to these, it helps not only with language skills but also learning the culture of the target language in accordance with the results. Furthermore, using literature in English language education motivates learners according to the results of the questionnaire. However, most of the participants never or rarely use literary texts in their lessons even if most of them indicate that they like using literary texts in their classes. When the participants were asked the reasons for not using literary texts in their classes, their answers were mainly related to the level of the students and the curriculum. In short, English teachers are aware of the positive effects of integrating literary texts into ELT though they need to be encouraged and promoted to use them more often. Keywords: EFL teachers, English language education, Literature, Literary text. DOI: 10.7176/JEP/14-33-02 Publication date: November 30 th 2023
IOT Implementation Energy consumption for Indoor Orchid Cultivation based on WeMos

Orchids are epiphytic plants with high popularity. Orchid is a plant that can process its own nutrients with the help of other media. Parameters that need to be monitored include air temperature, air humidity, and soil moisture. These parameters greatly affect plant growth. Plants can grow well if humidity, temperature, and light intensity are met properly. Good orchid humidity ranges from 50 – 80%. Humidity should not be too high at night and not too low during the day. In addition to humidity, the temperature where you plant orchids must also be maintained. The ideal temperature for orchids is daytime temperatures between 27-30 degrees Celsius and night temperatures between 21-24 degrees Celsius. Based on these problems, a Design and Development Tool for Monitoring Soil Temperature and Moisture on the Growth of Indoor Orchid Plants is Based on WeMos with Indoor Energy. In this design, the results of sensor readings will be displayed in the form of data which will be accessed via the web server on WeMos. To read the temperature, air humidity, and soil moisture, several sensors are used, namely: DHT 22, soil moisture sensor, and a relay connected to a mini water pump using an indoor cultivation method where the energy source uses UV waves by LED light. From the results of the implementation and testing, the growth period will be obtained more faster than the normal cultivation. hopefully, this research will help people who care for orchid plants to be able to monitor their orchid plants efficiently in indoor conditions so that these orchid plants can always be in the best conditions of temperature, light, and soil moisture.
Frequencies Analysis on Suling Te’dek using Fast Fourier Transform: Ethnic Musical Analysis

The aim of this research was to use the Fast Fourier Transform (FFT) to analyze the frequency of notes produced by the traditional Te'dek flute of the Toraja people in South Sulawesi, Indonesia. The purpose of the study was to contribute to the preservation of the Toraja's cultural history by providing an evaluation of the Te'dek flute's tonal characteristics. The research process included recording the sound of the flute, applying the FFT to the recorded data to extract frequency values, and analyzing these values to determine the frequency of each note within an octave. What sets the Te'dek flute apart is its unique tuning process, where the maker skillfully adjusts the fingerholes' diameter using hand tools and relies on intuition to determine the sound without any external measurement. The results of the study showed that the FFT can be used to accurately determine the frequency of the Te'dek flute and that the strength of airflow in the flute's cavity plays a significant role in determining the frequency of the tone.
Analisis Pendeteksian Fraudulent Financial Statement Menggunakan Beneish M-Score Model Studi Empiris Pada Bank Umum Syariah Di Indonesia Tahun 2020-2021

Every year, companies publish financial reports that can shows the company's financial condition is good or bad. To know whether Sharia Commercial Banks in Indonesia commit fraudulent report finance in 2020-2021 and analyze the gaps used inThis fraud was researched using the banking sector. Because this sector has many stages in the business process, there are gapsto commit fraud is considered greater than other sectors. This research is descriptive research with a quantitative approach using eight variables Beneish ratio index and M-score based on Beneish's discovery in 1999. The eight variables are DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, and TATA, which are used for detection companies that manipulate or commit fraudulent financial statements. The research results show that all sample companies do not do so financial statement fraud, namely PT. BCA Syariah Bank, PT. Mega Bank Sharia, PT. Bank Victoria Syariah, PT. Bank Negara Indonesia Syariah, PT. Bank Rakyat Indonesia Syariah, and PT. Bukopin Sharia Bank. Detection Fraud is carried out by calculating the eight Beneish ratio index variables 10 sample companies and compare them with the industry average value to detect potential fraud.
Leksikon Flora dan Fauna dalam Peribahasa Nias: Kajian Ekolinguistik

Nias proverbs are a form of communication used by Nias people in conveying feelings, ideas and ideas. Nias people use natural lexicons both biotic and abiotic in Nias proverbs. The relationship between language users and other language users as well as the relationship between language users and the social environment can be seen using the Band and Door dialogue method (1993).This research aimed to identify flora and fauna lexicons in Nias proverbs. The method used in this research was a quantitative method with a quantitative descriptive approach. The source of data in this research were primary and secondary data. The data collection technique used the interview method by applying the free listening method involved being proficient with note-taking techniques. Based on the results of the research, there were lexicons of flora and fauna: gae 'banana', silimo 'kecombrang', dima 'orange', tugala 'broken bone', dawuo 'betel', banio 'coconut', dὂwu 'sugar cane', dalimbo 'oyster mushroom'. ', landöta 'matsutake', mbulu nakhe 'palm leaf', bago 'tobacco', wakhe ' paddy', mbulu mbala 'papaya leaf', and ladari 'pandan leaf, manu 'chicken', mbawi 'pig', mbaewa 'eel ', nasu 'dog', baya komo 'lizard', mba'e 'monkey', mböhö 'deer', laosi 'Mouse Deer', nazese 'bird tledekan', siliwi 'sparrow', mbae'a 'snail', mbo'ole 'turtle', moyo 'eagle', and garawi 'weasel'. The use of the lexicon of flora and fauna in the formation of Nias proverbs has a function as subject and complement.
Evaluating TOEFL ITP Test: A Critical Review

The critical objective of this present study is to conduct substantial evaluation of TOEFL as a language assessment tool. Using a qualitative method, the authors of the present study evaluated various specific issues based on a set of predetermined criteria such as practicality, test reliability, validity, authenticity, and washback impact. The analysis indicates that TEOFL ITP is both feasible and dependable. The TOEFL's dependability is based on these three components. However, unless the ITP test is altered from the previously used TOEFL, the TOEFL ITP is as reliable as the TOEFL PBT. In theory, its trustworthiness is uncertain, and more investigation is needed. It is debatable whether the TOEFL ITP test items can accurately represent this task when utilized for the placement test. TOEFL ITP is a reliable English test. Knowing the TOEFL significance encourages test takers to enhance their English skills as part of the exam. More students want to take lessons to enhance their grades.
The role of the social network in the life of students and its impact on the pedagogical process: analysis on the example of Educational Rehabilitation Institution of Higher Education Kamyanets-Podilsky State Institute

PROBLEMS AND PROSPECTS OF TRAINING IN HIGHER SCHOOL: PEDAGOGICAL, PHILOLOGICAL, PSYCHOLOGICAL AND INTERCULTURAL ASPECTS The connection between social media and education is becoming more direct and obvious every year. The consequences of the use of social networks in the lives of students and in the pedagogical process have not yet been fully explored. This research work aims to study the role of the social network in the life of students and its impact on the pedagogical process. The research methodology is based on surveying students in order to find out various aspects of their interaction with social networks, including time spent on them, types of use, motivations and impact on learning. In addition, an analysis of literary sources and research is conducted to obtain a more complete picture of the role of social networks in the pedagogical process. It is expected that the results of the study will help to understand how the use of social networks affects learning and the pedagogical process, and will provide a basis for further research in this area.
Improve the Onion Routing Performance and Security with Cryptographic Algorithms

Onion Routing and Cryptographic Algorithms are two essential components of online privacy and secure data transmission. Onion Routing is a technique used to protect internet users' anonymity by routing their communication through a network of servers, while Cryptographic Algorithms are used to encrypt and decrypt data to ensure its confidentiality. As technology advances, there is a need to consider the development of new cryptographic algorithms for TOR to ensure its continued effectiveness. The combination of Onion Routing and Cryptographic Algorithms has proven to be an effective way to protect online privacy and security. This paper aims to explore the benefits of combining Onion Routing and Cryptographic Algorithms and to propose a hybrid symmetric and hashing algorithm technique to transmit data securely. By the end of this paper, researchers will have a comprehensive understanding of the Onion Routing and Cryptographic Algorithms, their implementation in TOR, and the limitations and risks associated with using such tools.
Study on Risks and Trust in pursuit of a well functioning Persistent Identifier infrastructure

Taken from https://www.openaire.eu/what-is-a-persistent-identifier, the graphic is licenced under CC ATTRIBUTION 4.0 INTERNATIONAL LICENSE by OpenAire Pablo de Castro (University of Strathclyde), Laura Rothfritz, research assistant and PhD candidate at the Berlin School of Library and Information Science at Humboldt University Berlin, Joachim Schöpfel (Université de Lille) and I will do a study on Risks and Trust in pursuit of a well
Transcribing Handwritten Text with Python and Microsoft Azure Computer Vision

Tools for machine transcription of handwriting are practical and labour-saving if you need to analyse or present text in digital form. This lesson will explain how to write a Python program to transcribe handwritten documents using Microsoft's Azure Cognitive Services, a commercially available service that has a cost-free option for low volumes of use.
Building Python Application for Webmail Interfaces Navigation using Voice Recognition Technology

Voice Recognition Technology (VRT) has played a crucial role in technology development, finding extensive use in the development of humanitarian assistance applications, including assistance programs for individuals with disabilities to use smart vehicles and smart homes, as well as websites. This paper discusses implementing a Computer Application (PC-App) for humanitarian assistance written in Python to enable Arabic-speaking elderly and handicapped employees to access and navigate webmail accounts using Arabic Voice Commands (AVC). Furthermore, a survey was conducted for elderly and disabled employees to assess the effectiveness of the application, with participants evaluating that it was useful in addition to improving their interaction with their accounts in Webmail. Ultimately, this application promotes independence and functionality for Arabic-speaking individuals, regardless of their mobility disability levels, by allowing them to independently use the Webmail interface using AVC.
Learning Spline Models with the EM Algorithm for Shape Recognition

This paper demonstrates how cubic Spline (B-Spline) models can be used to recognize 2-dimension nonrigid handwritten isolated characters. Each handwritten character is represented by a set of nonoverlapping uniformly distributed landmarks. The Spline models are constructed by utilizing cubic order of polynomial to model the shapes under study. The approach is a two-stage process. The first stage is learning, we construct a mixture of spline class parameters to capture the variations in spline coefficients using the apparatus Expectation Maximization algorithm. The second stage is recognition, here we use the Fréchet distance to compute the variations between the spline models and test spline shape for recognition. We test the approach on a set of handwritten Arabic letters
Human Violence Detection using Machine Learning Techniques

Abstract: Over 7.9 deaths per 10,000 persons worldwide occur as a result of human violence annually on average. Most of this human violence happens abruptly or in a remote location. Stopping these crimes is severely hampered by the information delay in this case. This work employs the detection technique to address this issue. One of the most efficient computer vision algorithms is the one for moving object detection from CCTV. These days, every street has CCTV cameras, which are highly useful for solving crimes. Computer vision uses some deep learning approaches to anticipate and identify actions and attributes in videos. Police arrive at violent locations in real time and begin checking CCTV video before doing additional investigation. The purpose of this study is to identify violent
DESIGN OF HYBRID ADAPTIVE MODEL FOR IMAGE DENOISING

This thesis work proposes a new denoising algorithm based on Particle filter and Wavelet (Curvelet) transform combination, particle filter generates weights through SIR algorithm to cancel the interference of noise present in the image, while curvelet transform is used to shrink the remaining segments of noise, so this method can both remove image blurr and maintain good texture as well. The PF+Clet Image Denoiser is successfully designed and implemented, which is a new approach in image enhancement and Interference cancellation. This thesis concludes that it is quite efficient algorithm among other adaptive filtering techniques. Experimental results also show that proposed algorithm performs extremely well when noise density is increased, as obtained image is completely visible. This approach comprises of generation of particles by performing weight normalization, resampling and update state. Therefore, for large number of particles execution time is more when compared to other adaptive filtering approach. Key Words: Particle Filter(PF), Curvelet(CLet), Wavelet(Wlet), Peak signal to noise Ratio(PSNR), Deblurring.
Youth Perception in Using Virtual Reality Technology in Science Learning

The shift to online education and the closure of physical learning institutions showed critical challenges for youth learners that rely heavily on hands-on practical experience. Analysing youth perceptions of using virtual reality (VR) technology in learning science subjects is reflected as the starting point towards a more effective and engaging learning environment. Previous research highlighted that the latest technology, such as smartphones, wearable technology, augmented reality (AR) technology, and virtual reality (VR) technology, can help close the gap in learning practical subjects via online platforms. Due to this, this study found a research gap in improving the usage of VR technology in science learning. This study aims to identify the youth learners' perceptions of using VR technology to support the teaching and learning process, specifically in hands-on practical subjects like science. This study adopted the case study methodology approach with quantitative analysis. The instruments used in this study include the SUS questionnaire and SUS scoring analysis. A total of 65 youth learners were involved in this study. The result of the SUS score resulting in a total of 75.04, which can be concluded as the acceptable range, achieves a grade of C on the grade scale, and has an adjective rating of "good." This reflected that the suggested VR application for learning science had demonstrated positive results regarding system usability for its effectiveness, efficiency, and satisfaction for respondents when learning science subjects. In the future, this study will target implementing the proposed model on another science topic.
SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN CALON PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN METODE FUZZY MAMDANI

Decision Support Systems (DSS) have become essential tools in complex and data-driven decision-making processes. In the context of identifying beneficiaries for the Program Keluarga Harapan (PKH), the fuzzy Mamdani method has proven effective in addressing uncertainty and complexity by evaluating the eligibility of recipients. The fuzzy Mamdani method employs fuzzy logic principles to handle uncertainty by establishing connections between input variables (e.g., household income, number of dependents, education level) and output variables (PKH recipient status). Fuzzification and defuzzification processes enable the mapping of vague input values to comprehensible output values. This study discusses the implementation of the fuzzy Mamdani method within a DSS for determining PKH recipients. Real-world data collected from potential PKH recipient households is utilized to develop the fuzzy Mamdani model. Model development steps encompass defining input variables, membership functions, fuzzy rules, and the defuzzification mechanism. Consequently, the utilization of the fuzzy Mamdani method within a DSS for PKH accuracy 87%, recall 91% and precision 90%. However, further research and the development of more intricate models may be necessary to optimize the performance of this method in broader and diverse scenarios.
Programming with Python

After the successful comprehension of the different aspects of Python and its applications in ML, it's now the time to look at how they can be combined and put to work using common examples. This will surely increase the reader's comprehension of the intricacies of Python and demonstrate the efficiency of the language in making the programming simple.
Exception Handling

In this chapter, we introduce the concept of exception handling in Python. They are used to specify the alternate sequence of actions the program needs to jump to at the occurrence of the event. For example, if we want to print several pages from the printer and somewhere in the middle of the job the paper gets stuck in the printer. In such as situation we would want to jump to the function that aborts the printing and handles this situation by instant shut down of the printer. In such events comes the exception handling. When the program jumps to the exception handler part the current sequence of commands is abandoned and the commands given to the exception handler are executed. After the exception is tackled the programming returns to the point where the marker left.
PERANCANGAN APLIKASI MONITORING PATROLI SECURITY PADA PT. PLN UP2D PALEMBANG MENGGUNAKAN SOFTWARE DEVELOPMENT LIFE CYCLE (SDLC)

Patrol activities carried out by PT. PLN UP2D Palembang is currently still using manual reporting which often results in poor communication, intentional or not. Such as a lack of focus and deliberately not carrying out tasks as they should, which are expected to be optimal but beyond expectations. For this reason, the company needs to improve the way it monitors PT security officers. PLN UP2D Palembang so that patrol activities can be more efficient, systematic and structured. The aim of this research is to design an e-patrol security application that has added value, namely features that can make it easier for security officers to carry out reporting and communication activities between security officers more quickly. Furthermore, this application also provides guarantees for companies that security officers are really working according to their duties well and the reports sent by security officers are real time and can be checked immediately. The finalresult of this research is a design for an Android web-based patrol application that is run according to the rules and schedule, division of tasks, and available patrol routes.
PENERAPAN DATA MINING PENJUALAN BARANG TOKO BANGUNAN H.UBED MENGGUNAKAN METODE ALGORITMA APRIORI

Process Sales activities on material goods so that they continue and so the data generated is increasing over time. Larger data will not be useful and useful if left alone. The Apriori Algorithm is one of the methods of Data Mining, namely data collection to determine the highest frequency pattern with the highest data collection and to determine transaction data, calculating the total number of transactions. The use of old data is used to find the results of the sale of the most and the fewest goods. The result of this data mining process is to find items that are often sold simultaneously. One of the benefits of using this method is to facilitate the preparation of goods to be separated in certain places such as items that are often sold. The a priori algorithm method in data mining is very efficient and speeds up the process of combining patterns of sales results from building stores. The data used is data on the sale of goods that are often sold. The list of building materials that have the most stock sold is Cement, White Cement, Sand, Wall Paint, Wood Paint, Ceramics, Wood, Bricks, Nails, Concrete Iron, and Wire
PENGEMBANGAN APLIKASI WEB UNTUK OPTIMALISASI MANAJEMEN TOKO SURYA MAS 2

This study focuses on the development of a web-based application for Surya Mas 2 Store, with a primary emphasis on automating store operations and improving inventory efficiency. The application targets the roles of cashiers, managers, and warehouse employees, encompassing essential features such as role-based login, sales transactions, inventory management, note-taking, and transaction reporting. Users can access the application with role-specific functionalities, ensuring secure and efficient store operations. The web application streamlines inventory management by enabling the recording of incoming and outgoing products. Additionally, it provides transaction reports that aid in decision-making processes. The Rapid Application Development (RAD) methodology was employed for the application's development, allowing swift adaptation to changing requirements. The benefits of the application include enhanced operational efficiency through process automation and improved inventory management. Opportunities for future development lie in refining the user interface and expanding the reporting capabilities. Ultimately, the application positively impacts the business of Surya Mas 2 Store by saving time and resources through automation and efficient inventory management.