Reviewerly/exHarmony huggingface dataset:
PERANCANGAN APLIKASI MONITORING KUALITAS AIR PADA BUDIDAYA IKAN NILA BERBASIS IOT MENGGUNAKAN ANDROID STUDIO

Tilapia is one of the fish that has high economic value, easy cultivation method, and relatively affordable price.Tilapia can be kept in the lowlands of brackish water to the highlands of fresh water.However, tilapia is a fish that is very susceptible to disease, and loses its appetite when the water quality in the rearing pond is not maintained. Therefore, we need a tool that is able to monitor water quality in tilapia aquaculture ponds in real time. The use of internet of things technology in the monitoring system makes it easier for monitoring activities to be carried out anytime and anywhere. The monitoring system is built with three main parts, namely Arduino mega 2560 WiFi IoT (Microcontroller), Firebase (Database), and Android Studio (Application). In this study the testing method consists of three stages, the first stage is application testing, testing the speed of data transmission and testing the accuracy of the data. After testing, it was found that the application has been running well, the average speed of data transmission from the microcontroller to the database is 7.85 Mbps with the required time of 5.4 seconds, while the speed of data transmission from the database to the database. application is 9.21 Mbps. with the required time of 1 second, and the data contained in the microcontroller, database and application has a 100% accuracy rate.
PERANCANGAN INTERNET OF THINGS SISTEM MONITORING LEVEL DEBIT AIR MENGGUNAKAN MIT APP INVENTOR DAN WHATSAPP

The surrounding environment requires a technology as a means of providing information to anticipate disasters, especially flood problems. The creation of this water discharge level monitoring system is to produce a monitoring system to find out the possibility of flooding using the MIT app inventor platform which is applied in an application display in the form of water level and water discharge status with a high level of accuracy. The monitoring also uses the WhatsApp application as a notification to the public about the status of the water level. In designing to build an IoT-based water discharge level monitoring system, it is necessary to test a system that uses a test method using wireshark to see network traffic in this water discharge level monitoring system to see theQuality of Service of the WiFi delivery network to the NodeMcu as a data sender to firebase and whatsapp.The test results obtained throughput index results 0, delay 4, packet loss 4 and jitter 3. The results obtained are included in he good category according to the TIPHON standard.
The Impact of Kadatua Dialect on Students' English Pronunciation

This paper presents descriptive quantitative research investigating how the Kadatua dialect can influence the English pronunciation of second-grade students of SMPN 1 Maginti. The subjects of this study were 8 second-grade students at SMPN 1 Maginti with Kadatua ethnic background. The research instrument used was an interview and a test. The test was done by asking students to read a list of several English words to record and analyse their pronunciation. The results show that Kadatua dialect influenced students’ pronunciation of the following sounds: /?/, /æ/, /??/, /??/, /a?/, /??/, /e?/, /??/, /ð/, /?/, and /?/. Although some sounds cannot be pronounced correctly, it does not mean they are affected because these sounds do not exist in the Kadatua dialect alone. This would mean that the Kadatua dialect does not affect the overall students' English pronunciation. Some of the sounds that are not influenced by the Kadatua dialect are as follow: /?/, /?/, /i?/, /u?/, /??/, /??/ /e/, /e?/, /a?/, /??/, /p/, /b/, /t/, /d/, /k/, /g/, /t?/,/d?/, /f/, /s/, /z/, /?/, /h/, /m/, /n/, /?/, /l/, /r/, /j/, and /w/. Although these sounds can be pronounced properly and correctly, it does not mean that all these sounds are only found in the Kadatua dialect. This ease of pronunciation is identified because of the dialect features similarity of Kadatua with English language.
EFFORTS TO IMPROVE TEACHERS' ABILITY TO DEVELOP ASSESSMENT PROGRAMS THROUGH IN-HOUSE TRAINING ACTIVITIES

School development aims to achieve 8 National Education Standards (SNP) Government Regulation (PP) RI No. 32 of 2013 concerning changes to PP No. 19 of 2005 concerning National Education Standards. The achievement of 8 SNPs, specifically for Assessment Standards, is carried out by conducting In House Training (IHT) activities. The purpose of this study is to improve the achievement of 8 (eight) National Education Standards, Provide excellent and optimal services to students and parents and the community. The methods used for initial data collection before IHT and after are: Document mining using the teacher data checklist method that collects education assessment programs before IHT, Interviews, Tests, Postes, Document mining using the teacher data checklist method that collects education assessment programs after IHT. The result was a significant difference from the pretest result of 46.67 and the posttest result of 72.29. Based on the existing results, it can be concluded that the increasing ability of teachers in compiling educational assessment programs, preliminary data before IHT was obtained 6 people did not compile educational assessment programs, 42 people compiled education assessment programs but were incomplete and no one compiled a complete education assessment program. After the implementation of IHT, data were obtained: there were no teachers who did not compile an educational assessment program, 2 people compiled an incomplete but then improved and 46 people compiled a complete education assessment program.
Contextual Market Basket Analysis during Covid-19

&#x0D; &#x0D; &#x0D; &#x0D; One form of Data Mining application to analyze Market Basket Analysis. Market Basket Analysis helps identify buying patterns formed from concurrent transactions. One of the problems with Market Basket Analysis is that customer needs vary according to season and time of day, especially during this covid-19 season. For this purpose, by using the Artificial Neural Network (ANN) Approach that is connected to Market Basket Analysis, it can analyze and compare purchasing patterns and can identify rules that were formed before and after covid-19; several rule changes were found due to changes in people's behavior patterns.&#x0D; &#x0D; &#x0D; &#x0D;
SISTEM INFORMASI MANAJEMEN MASJID BERBASIS WEBSITE (STUDI KASUS : MASJID BAITUL IKHWAN)

The mosque is a place to worship or worship Allah SWT. The function of the mosque is not only as aplace to pray but also as a means of developing Islamic insight. As for one of the problems in the mosque which is known to not have an information system to process activity data, Friday prayer schedules, hallrentals, good and efficient finances at the Baitul Ikhwan Mosque. Based on the problemsdescribed, amosque information system is needed and a Website-Based Mosque Management Information System is needed using the waterfall method. The system tools used include the Unified Modeling Language (UML) such as use cases and activity diagrams, Entity Relationship Diagrams (ERD), and Hierarchy plus Input Process Output (HIPO). Which serves to make it easier for mosque administrators to carry out their duties from adding data, changing data, and deleting data that is no longer used or can print and then save in a computer system. And with this website, it is easier for the public to find information on mosquemanagement, and for mosque administrators it is easier to makea data recapitulation by printing it as a softcopy in pdf form and it will not be difficult to find the data file again in the system when it is printed. The information system built is website-based using a programming language, namely Hypertext Preprocessor (PHP).
Teacher Actions in Improving Early Childhood Literacy to Stimulate Critical Reasoning through Picture Cards

Learning literacy in early childhood is the key needed by children to improve children's critical reasoning skills, with the media used as picture letter cards. because it is in accordance with the standard of learning in children, namely playing while learning and having fun. Accordingly, this research is remembered for its Class Action Research type which means improving children's literacy skills through picture cards by stimulating children's critical reasoning abilities. The results showed that there was an increase in children's literacy skills in Nambokido Kindergarten, Unaaha District, Konawe Regency through picture card games. There is a very significant increase using picture letter cards, which is 61.90% in cycle 1 to 85.71% in cycle II. For this situation, the increase is 23.81%. In line with that, it is very good that it can be assumed that early childhood literacy skills can be improved through picture letter cards games
PENGEMBANGAN SISTEM POINT OF SALE KE PEMROGRAMAN WEB MENGGUNAKAN FRAMEWORK CODEIGNITER

The Point Of Sale (POS) business management system is an application program that can facilitate all trading processes, but this system can only be installed on low-spec computers with a fairly complicated installation process. Based on these problems, the authors try to find solutions on how to develop POS application programs into web programming so that they can be installed on all mainstream operating system products. The POS system developed is a management system that can manage several important functions in web-based business management using the PHP programming language with the Code Igniter 3 Framework, Apache web server and MySQL database. The research methodology used is an action research method with data collection techniques through interviews. The waterfall development model is designed using the UML design method, and tested using black box testing techniques. Through this development process, desktop-based POS application programs have been successfully developed into web programming and can be installed on mainstream operating system products such as Windows, Linux and Macintosh.
RANCANG BANGUN SISTEM INFORMASI INVENTARIS KOLEKSI PADA MUSEUM TEKSTIL JAKARTA

The development of information technology is currently very rapid, where computers play an important role invarious fields, one of which is processing inventory data. Inventory is an activity or action to carry out physicalcollection of existing assets (collection inventory) in an integrated manner in the management of propertyownership data. The Jakarta Textile Museum is a cultural heritage that houses various collections of Indonesianfabrics and batik tools, which act as an Indonesian textile sanctuary institution and a documentation and research center for traditional Indonesian textiles. Inventory data processing to create a collection of labels to be exhibited at the Jakarta Textile Museum is still done manually, where the technical and administrative data obtained are entered into Microsoft Excel. In the manual processing of inventory data, problems were found such as insufficient or incomplete data. Based on this explanation, the author makes a Final Project report with the title "Design ofan Inventory Information System for Collections at the Jakarta Textile Museum".
PENERAPAN METODE NETWORK FORENSIK UNTUK ANALISIS SERANGAN DOS PADA PERANGKAT ROUTER

Digital forensics is a part of forensic science that covers the discovery and investigation of matter (data) found on digital devices. At present the use of computer technology is so rapid that it helps human activities with the sophistication of computer network technology, behind all of that problems arise regarding network forensics. The main cause of network forensic problems is the act of misuse of technology by irresponsible people with the aim of utilizing other parties' network facilities for personal or group interests. DoS attacks (Denial of Service) one of the most common attacks on computer networks is a type of network attack Router that cannot service user requests, and ultimately causes the computer network to be down . Kata Kunci − Digital Forensics, Network Forensics, DoS
ANALISIS PENGOLAHAN DATA FORENSIK PADA SOLID STATE DRIVE (SSD) MENGGUNAKAN FRAMEWORK GRR RAPID RESPONSE

The background of this research is to know the data processing on Solid State Drive (SSD) using the GRR Rapid Response framework approach, it will know the data and data processing so that the past data can be known and can be found where the data is, so that it can be used as a reference. Forensic evidence. The problem raised in this research is to try a framework to prove that forensic data can be retrieved and can be used as important data. The method used in this study is to conduct a literature review and conduct trials on Solid State Drives (SSD) using certain methods in order to find out the response of the hard drive in searching data. The purpose and objective of this research is to conduct trials on certain frameworks in conducting forensic data testing.&#x0D; Keywords: Forensic Data, Solid State Drive (SSD), Framework, GGR Rapid Response
Application of Median and Mean Filtering Methods for Optimizing Face Detection in Digital Photo

Locating the facial region is the aim of face detection in digital images.Face detection issues frequently arise because of digital image noise levels.This study uses median and means filtering techniques to reduce noise in digital photographs.A confusion matrix is used to quantify the median and means filtering methods' accuracy, while the parameters Mean Square Error (MSE) and Peak Noise to Signal Ratio (PNSR) are used to assess these approaches' performance.For this experiment, Viola-Jones was chosen as the face detection method since it is one of the face detection methods with the best accuracy and computational power.According to the outcomes of comparing the median and mean filtering techniques using MSE and PNSR on 50 image samples, the median filtering approach produced the lowest average MSE results, with a value of 19.43, and the median filtering procedure yielded a 13.74 value for the highest PNSR score.The fastest average time was obtained from the mean filtering method with a time of 3.18 seconds.As for the accuracy based on the confusion matrix, these two methods get a good accuracy of 90%.These findings indicate that the Median Filtering approach is superior to the Mean Filtering method in terms of error.
Cybersecurity Training in Organization as Human Capital Investment: A Qualitative Grounded Theory Analysis

This study aims to examine the impacts of organization&amp;rsquo;s cybersecurity training program on employees with qualitative data, collected from 33 college students who were attending Norfolk State University while also working either on a part-time or full-time basis participated. Open-ended questions were asked to elicit participants&amp;rsquo; perspectives on cybersecurity training and cybersecurity protocols in organizations. Using qualitative data analysis software Nvivo 12, the authors organized and analyzed the collected data with open coding, and selective coding to recognize the major influencing impacts from cybersecurity training on employees&amp;rsquo; routine work and behavior. Inductive and grounded theory analysis further elaborates connections between employee&amp;rsquo;s cybersecurity training and efficiency of organizations. Our findings suggest that on-the-job cybersecurity training provided by the employer is an effective investment for modern organizations to build on the organizational human capital and consequently to improve the efficiency of the organization. Findings from this study corroborates with the tenet of human capital theory that on-the-job educational program or training is economical and effective to manage the human capital challenge for modern organizations.
STROKE PREDICTION USING A SUPPORT VECTOR MACHINE (SVM)

Based on data from the Indonesian Ministry of Health, there has been an increase in the number of stroke cases by 3.9% from 2013 to 2018. Nationally, the number of stroke cases often occurs in groups that have an age range between 55-64 years and the least occur in the 15-24 age range. A stroke (Cerebrovascular Accident) is a condition where blood flow to the brain is suddenly interrupted or reduced. This can be caused by a blockage or rupture of blood vessels so that cells in the brain area do not get a blood supply that is full of nutrients and oxygen. Early detection is needed which aims to reduce the number of potential deaths from stroke. Stroke prediction is still a challenge in the field of medicine, one of the reasons is the volume of data on medical data which has high heterogeneity and complexity. Machine learning techniques are data analysis models that can be used to predict stroke. Various machine learning models have been proposed by previous researchers, one of which is the Support Vector Machine. This study tries to re-implement the SVM algorithm to get better performance results than previous studies. In this study, the accuracy value was 100% and ROC-AUC values were 100%. Further studies need to be carried out regarding the results obtained to reach 100%.
COMPARISON OF NAÏVE BAYES AND KNN ALGORITHMS IN THE ANALYSIS OF PUBLIC SENTIMENT REGARDING THE IMPLEMENTATION OF GOVERNMENT EMPLOYEES WITH TEACHER WORK AGREEMENTS

Until now the implementation of education in Indonesia cannot be separated from the complexity of the management of educators, one of which is honorary teachers, and bureaucratic reform which has quite an impact on the quality of education and the work climate in it. As a way to increase public service satisfaction through the state civil apparatus (ASN), the Indonesian Ministry of Education and Culture agreed with the Ministry of Administrative Reform and Bureaucratic Reform and the Ministry of Finance to change the recruitment system or appointment of government employee teachers from the acceptance of prospective Civil Servants. Civil servants (CPNS) become government employees with a work agreement (PPPK) which in its implementation there are still obstacles and pros and cons, some agree and some disagree. therefore the researcher conducted research on sentiment analysis in data mining in the implementation of PPPK teachers on social media Twitter as many as 871 data which were then processed into 519 data. the author uses the Naïve Bayes and KNN techniques to determine the predictive effect of the Naïve Bayes and KNN algorithms on public opinion in the implementation of first aid instructors and compares the level of accuracy of the 2 methods. Researchers use the RapidMiner tool version nine.10.1. The prediction results of Naïve Bayes are 328 statistics with positive or agree sentiment and 191 information with negative sentiment, and the last is the prediction result from KNN, namely 315 information with positive sentiment and 204 facts with negative sentiment. analysis of public sentiment on the implementation of teacher first resource on social media Twitter with the Naïve Bayes algorithm achieves an accuracy of 75.53%. And the KNN achieves an accuracy of 73.41%. In this study, the Naïve Bayes method is a technique with a higher level of accuracy than the KNN with an accuracy rate of 75.53%.
A METHOD FOR REVERSING THE EFFECT OF DIGITAL IMAGE BLURRING: A SPACE DOMAIN INVESTIGATION

Abstract. Mobile mapping technology has transformed the way in which we capture and map our surroundings. The widespread use of mobile devices such as smart phones and drones has made data collection more efficient and accessible than ever before. However, the image quality of this data is often compromised due to the static or motion blurs resulting from the device being stationary or moving during the data collection process. This can lead to a loss of information, making the data less useful.To address this issue, an inverse filtering or deblurring method based on the theory of least squares is examined. This method implements a deconvolution process in the space domain and can restore the original image with a high degree of accuracy if the model of the function or filter that blurred the image is known or can be established.The accuracy and validity of the deblurring results are presented in terms of the root mean square error (RMSE) of the differences of pixel intensity values between the original and de-blurred images. In tests using grey-scale aerial images of varying entropies and different types of blurring, the RMSE value never exceeded ±5 pixel intensity values. This discrepancy is due to the rounding of pixel values resulting from image operations.The deblurring method presented in this work is an adaptation and extension of a previously described process, tailored specifically for filtering and restoring images - particularly aerial imagery - affected by static and motion blur. This process could also be applied in image compression processes and techniques of transmission over digital links, where blurring filters can suppress noise and increase the dependence between neighbouring pixel values, thereby improving the compression ratio (CR).
System for Continuous Multi-Dimensional Mobile Network KPI Tracking and Prediction in Drifting Environments

The usage of public mobile radio networks is steadily increasing. At the same time, the number of new and future smart city applications that rely on reliable and fast mobile data connections based on public mobile networks is rising. In particular, mission-critical smart city applications require continuous and reliable mobile network connectivity. However, the fulfillment of KPIs is not given at all locations and varies over time. Thus, use-cases like tele-operated driving profit from and, in some cases, even depend on spatiotemporal connectivity data. Indirectly, connectivity data can also be utilized to calibrate and improve network planning approaches for future network technologies, such as classical ray tracing or innovative datadriven channel modeling approaches.Massive data acquisition is needed to cover vast city-wide areas like the city of Dortmund. Therefore, this paper discusses a system that enables a dedicated, continuous and systematic measurement campaign to solve this challenge. These measurements are realized by a fully automated open-source monitoring application deployed in multiple vehicles of the local waste disposal company, enabling continuous and city-wide data collection. The initial results of this measurement campaign indicate that up-to-date data is crucial for reliable data-driven services.
Digital Tools in Conducting a Linguo-semiotic Study of Tactile Communication: the Potential of the Russian National Corpus

The paper is aimed at studying and describing the potential of the web-page of The Russian National Corpus - https://ruscorpora.ru - as a set of digital tools for linguosemiotic analysis of the verbal delivery methods of tactile communication). The authors analyze modern digital technologies that allow collecting, structuring and processing extensive linguistic information of Main, Media, Multimedia and other corpora data arrays. Specific focus is made on such digital tools as the search for collocations, the classification of corpus materials by historical period, types of texts, genre affiliation, possibilities to parameterize the search context expansion, including those with specified grammatical forms, statistical methods of research and methods of graphical presentation of data. The model of an integrated approach to the study of linguo-semiotic characteristics of verbalized tactile communication is developed with the help of digital instruments of corpus-based linguistics and contemplates the access to statistical data, which help to detect usage patterns of lexical units, objectifying situations of tactile communication.