Reviewerly/exHarmony huggingface dataset:
Implementation of the SAW Method in the Decision Support System for Giving Rewards for Honorary Employees

Giving rewards to employees is one way to increase morale and improve performance for employees who excel. At the District Financial and Asset Management Agency. Asahan in choosing the best employees, the workload cannot be used as the only reference for the awarding of these rewards. However, there are several criteria that are also considered in giving rewards. So we need a decision support system to help the selection of the best employees. Temporary employees who are in government agencies have a percentage of 10% of the total number of registered employees. Every year, honorary employees renew their contract letters to continue their work. This is the basis for giving rewards or bonuses so that honorary employees are motivated to work and give the best results in carrying out and assisting civil servants in the government environment. The process of giving this reward was previously carried out manually, which is based on only one criterion, namely only from attendance. This makes it difficult to make decisions about the best honorary employees who are entitled to receive rewards. This consideration process is considered ineffective due to the different workloads of each honorary employee. To overcome the existing problems, we need a system in the form of a decision support system. It is hoped that this research will be able to determine the three best employees who are entitled to rewards in accordance with the performance criteria by calculating each weight of the criteria that have been set.&#x0D;
Komparasi Algoritma Klasifikasi Data Mining Menggunakan Optimize Selection untuk Peminatan Program Studi

The selection of a study program is a unique opportunity for a student. STMIK IKMI Cirebon is now a KIP Kuliah provider, offering three study program. The research problem is the unavailability of a model of student interest in the study program, so it is necessary to carry out an interest in the study program by applying an algorithm to the classification model. The algorithm used as a comparison is the Decision Tree algorithm (C4.5), Naive Bayes, k-Nearest Neighbor and Support Vector Machine. The classification model applies the Optimize Selection operator by looking for the dominant attribute in its influence on the specialization of the student study program. Finally, the comparison model will be tested by parametric t-test in order to test the significance of the algorithm. The results of the algorithm accuracy test obtained that the SVM algorithm has the best accuracy with a value of 80.76%. While the algorithm with the lowest accuracy is Naive Bayes with a value of 74.64%. While the other two algorithms have a sequential accuracy rate of 80.47% for Decision Tree and 76.09% for k-NN. The results of this study are used to classify study preference for students in STMIK IKMI Cirebon which is useful for predicting study interest based on the background of students
Advanced Model Implementation to Recognize Emotion Based Speech with Machine Learning

Emotions are essential in developing interpersonal relationships. Emotions make emphasizing with others’ problems easy and leads to better communication without misunderstandings. Humans possess the natural ability of understanding others’ emotions from their speech, hand gestures, facial expressions etc and react accordingly but, it is impossible for machines to extract and understand emotions unless they are trained to do so. Speech Emotion Recognition is one step towards it, SER uses ML algorithms to forecast the emotion behind a speech. The features which include MEL, MFCC, and Chroma of a set of audio parts are extracted using python libraries and are used to build the ML model. An MLP (Multi-Layer Perceptron) is used which will be mapping the features along with the sound file and predicts the emotion. The project details more about the development and deployment of the model. A technique known as "Speech Emotion Recognition" could identify emotional characteristics in speech signals by computer and contrasts and analysis the characteristics parameters and the emotional change acquired. In current market, speech emotion recognition was emerging crossing field of artificial Intelligence.
Mengoptimalkan Keamanan Jaringan Komputer Menggunakan Snort dan Telegram Bot yang Terintegrasi dengan Mikrotik

The implementation of IDS (Intrusion Detection System) snort and telegram bot that can be integrated with a microtic router on the Uppala Villa Nusa Dua computer network is used to detect attack activities and suspicious activity on the Uppala Villa Nusa Dua computer network and to provide notification in real-time logs of suspicious activity on computer network. The research method used is the SPDLC (Security Policy Development Life Cycle) method which has six stages: Identification, Analysis, Design, Implementation, Testing and Evaluation. The software used on the server computer is Snort, WinPcap, Xampp and BASE (Basic Analysis and Security Engine) while for testing a computer network security system using Nmap, Loic and Brutus tools. The results obtained by the implementation of the IDS (Intrusion Detection System) Snort and telegram bot have been successfully implemented and can be integrated with the microtic router. Based on testing conducted after the implementation of the new system, it was found that 95% of the use of snort and telegram bot can optimize the computer network security system at Uppala Villa Nusa Dua.
Implementasi Algoritma Zhu-Takaoka Untuk Pencarian Nama Obat Pada Aplikasi Katalog Obat Berbasis Android

Medicine is an object that is currently needed by humans, there are many names of drugs with different benefits, making it difficult for many people to find information on the name of the drug and the benefits of the drug. Technology is needed to make it easier for someone to find information on drug names and the benefits of the drug, therefore the author will build an android-based drug catalog application. With this android-based drug catalog application users can easily search for drug names by entering the name of the drug to be searched in the search table, after which the name of the drug with the benefits of the drug will appear.
Penerapan Metode Certainty Factor Pada Sistem Pakar Diagnosa Penyakit Mata

Eyes are one part of the body that has an important role in human life. Eyes are often also affected by a disease that causes patients to go blind. Sometimes patients often experience early symptoms of unknown disease as if these symptoms are normal. This is due to lack of information about eye diseases so that patients do not understand the initial symptoms they experience are symptoms of one of the eye diseases that often occur if left untreated for a long time, eye disease will get worse. The diagnostic process requires an expert and experienced expert in order to produce the right diagnosis. However, the limited time that an expert has sometimes becomes an obstacle for patients who will consult to solve a problem to get the best solution. So for that patients need information about the disease, the researchers created a web-based system and contained expert knowledge so that they could answer what eye diseases they experienced. make a diagnosis in order to easily treat the disease. The application designed is a web-based computer system that is integrated with databases and programming languages ​​such as PHP-MySQL so that it can help sufferers to diagnose the symptoms and types of eye diseases. The application of an expert system in making this decision by analyzing data using the Certainty Factor method to generate true and false values ​​on the new and old knowledge bases and comparing them with the weight values ​​in each frame so that the percentage of the disease type is obtained. From the results of the diagnostic process using this application, the system provides a choice of symptoms that must be answered by the patient based on the symptoms experienced by the patient, namely blurred vision such as foggy, seeing circles around light, and often changing the size of the glasses which results in cataract disease by 100% with a total value cf (Certainty) =26
ASSESSMENT OF THE PRACTICE OF BREAST SELF-EXAMINATION AND ASSOCIATED FACTORS AMONG HEALTH SCIENCE FEMALE STUDENTS OF AMBO UNIVERSITY: CROSS SECTIONAL STUDY

Background: Breast Self-Examination is process whereby women examine their breasts regularly to detect any abnormal swelling or lumps in order to seek prompt medical attention. Breast cancer is the most prevalent cancer among women globally and the second commonest cancer overall. The aim of this study was to assess practice of breast self-examination and associated factors among Health science female students at Ambo University in 2019. Methodology: - Institutional based cross-sectional survey was carried out among Health science female students at Ambo University in 2019. Data was collected by using a pre tested and pretested self-administered questionnaires. The response was systematically tabulated and analyzed using SPSS version 20, and explanations were given separately. Result- A total of 150 respondents participated in the study, of these 80 (53.3%) of them had good knowledge and only 67(44.7%) of the respondents had practiced BSE before. Among study participants whose families had breast cancer, practice BSE 2.12 times more than study participants whose families didn’t have his tory of breast cancer (AOR=2.12; 95% CI, 1.09–3.95, P=0.044). Those who had good knowledge toward BSE were 5.5 times more likely to practice BSE than those who had poor knowledge (AOR=9.5; 95% CI, 5.5–18.8, P=0.002). Conclusions- The overall knowledge of female students towards breast self-examination was 62%. This study showed that only 67(44.7%) of the study participants ever practiced BSE. The independeent predictors of breast self examination was family history of breast cancer and knowledge how to perform breast self examination.
Identify User Behavior Based on The Type of Tweet on Twitter Platform Using Gaussian Mixture Model Clustering

Social media has now become a place for social interaction to exchange information about business, politic, and many other. Twitter is one of the social media platforms that provides services for their users to share information and opinions on certain topics. The topic that will be discussed in this study is about politic by collecting tweet data about the student demonstration movement and SemuaBisaKena campaign. By using the word weighting method TF-IDF Vectorizer and Gaussian Mixture Model Clustering, it is possible to identify whether the user behavior is positive (support) or negative (blasphemy). To achieve the final result, there are several stages that must be passed. Such as data preprocessing, feature extraction using TF-IDF Vectorizer, Gaussian Mixture Model Clustering algorithm and data visualization. The results are there is 1 cluster identified as positive behavior and there are 2 clusters identified as negative behavior.
Topic Modelling Using Non-Negative Matrix Factorization (NMF) for Telkom University Entry Selection from Instagram Comments

The development of information technology is increasingly rapid, such as social media, which has much influence. Social media is a place or media used to express and express various opinions on a topic. One example is Instagram. Instagram is a social media platform with many features, such as posting photos, videos, comments, likes, and others. The comments feature that Instagram has contained much public opinion that can be used as data. Nothing but the post on the SMB Telkom University Instagram account about the entrance to the university. In posts about the entrance to Telkom university, many Instagram users comment on the post. This can be convenient for the marketing team to get topics or discussions that most followers need from Telkom University's Instagram account. Therefore, a topic modelling of Instagram users' perceptions of comments posted on the entrance to Telkom university was carried out using the Nonnegative Matrix Factorization (NMF) method. After doing several research scenarios, the best coherent value was obtained with a coherent value of 0.60628 and the best 4 topics.
Sentiment Analysis of Indonesian Economics News Summary on The ICI using Long Short Term Memory

Many investors use news summary as a reference while deciding whether to purchase, sell, or hold shares as part of their investment activity. The information provided by the news, on the other hand, frequently fails to meet expectations. Therefore, this study aims to classify economic news summary using sentiment analysis method followed by analyzing the results to determine the correlation between Indonesian economic news summaries and Indonesia Composite Index (ICI) trends. The dataset for this study is a collection of news articles from the Kontan online news site. This study begins with the collection of a dataset that includes 1720 training data and 440 test data that have been automatically summarized using the cosine similarity approach and labeled (positive/negative) based on the ICI trend the next day after the data was crawled. We use Term Frequency – Inverse Document Frequency (TF-IDF) as the word weighting technique and Long Short Term Memory (LSTM) method as the classifier to build the model. From the model training process that has been carried out for eight trials by tuning hyperparameters, the training accuracy is 86% and the F1-Score is 89.3%. While the testing accuracy and F1-score are 68.1% and 75.8% consecutively
Evaluation Usage of Interactive Quiz Reproductive Systems Based on Usability in Prospective UKMPPD Students

The use of information technology and interactive multimedia in education is very important. The example of interactive multimedia or e-learning is an interactive quiz. There is multimedia that is easy to use, but sometime it make users confused. High usability of interactive application materials is an important element in ensuring maximum educational impact. This study aims to evaluate the usability, acceptance of interactive quiz media. This research was conducted on 20 student respondents of prospective UKMPPD participants. Interactive quiz media tested using reproductive system materials. Evaluation of interactive quizzes through usability testing with system usability scale (SUS) and user experience questionnaire (UEQ). User acceptance based on SUS is 72 with an acceptability rate in the acceptable category, a grade scale in the "C" category, which is quite good and an adjective rating in the good category. There are three categories of user acceptance based on UEQ with excellent predicates, namely attractiveness, accuracy and stimulation. There are two categories with the predicate good, namely clarity and novelty and one category with the predicate above average, namely efficiency. Assessment based on quality gets results above average on pragmatic quality, excellent on hedonic quality and excellent on overall quality. The measurement of user acceptance with the SUS and UEQ questionnaires obtained “acceptable” in terms of acceptability ranges, C in terms of grades scale, “good” in terms of adjective rating, “excellent” in terms of hedonic quality and “above average” in terms of pragmatic quality.&nbsp
A New Resource Recommendation Method for Experiential Leaching Based on the Completion Degree of Online Learning Tasks

Experiential Learning (ExL) is an effective way to consolidate theoretical knowledge and deepen understandings, and the recommendation of ExL resources needs to also take the effect of students’ theoretical learning into consideration. However, existing studies generally ignore the stage-by-stage assessment of students’ completion of online learning tasks, and the recommendation performance of existing resource recommendation models for ExL is not satisfactory enough. Therefore, the recommendation method needs to be innovated, and the interpretability of recommendation results is facing challenges. To respond to these issues, this paper studied a new resource recommendation method for ExL based on the completion degree of online learning tasks. At first, the paper gave the principle of recommending ExL resources based on the completion degree of online learning tasks, and built an online learning task completion degree prediction model. Then, this paper adopted a bi-directional GRU network model based on attention mechanism to analyze the recent online learning behavior sequence of students and attain the completion degree of students’ short term learning tasks. After that, a knowledge map representing ExL resources and the correlation of knowledge attributes was drawn; by combining the completion degree of both the short-term and long-term learning tasks, the ExL resources suitable for students were recommended to them. At last, experimental results verified the effectiveness of the constructed model.
Analysis of STACK Answer Data Using Pen-Stroke Data from a Calculation Notebook and Item Response Theory

One of the most significant features of STACK, an automatic assessment system for mathematics, is the automatic classification of correct, semi-correct and incorrect answers using the Potential Response Tree, and the presentation of appropriate feedback for each. However, the answers provided by students are only the results of their calculations, and if they are semi-correct or wrong, it is necessary to check the notes describing the calculations to determine where mistakes have been made. We developed a function that allows students to submit their notes at the same time as their STACK answers, thereby creating an environment in which teachers can check where students have made mistakes and where they have stumbled. The note submission can be in the form of saving the results of calculations made with a digital pen on a tablet. This study examines a method of analysing answer data by visualising and analysing pen-stroke data from notes submitted using the latter method, and linking this to correct/incorrect data. From pen-stroke data, two types of visualisation were achieved on the submitted notes. One was to colour-code the strokes according to the writing speed of the digital pen, and the other was to display the strokes as thicker if the stagnant time in which nothing was written was above a threshold value. The difficulty of the problem was estimated from those data. Then, the item response theory is used to verify whether the difficulty is correctly estimated.
Lecciones educativas del COVID-19 para América Latina y el Caribe. La exigencia de repensar un nuevo concepto de aprendizaje

The situation generated by the educational consequences of Covid-19 represents an unbeatable opportunity to rethink some of the paradigms of the pedagogical narrative present to date. The enormous levels of inequality in Latin America and the Caribbean, both within and between countries, make this an unavoidable requirement: rethinking tomorrow has never made more sense than in the exceptional times we are living through. Through a hermeneutic approach, under content analysis of the main reports and documents of international organisations linked to the world of education, an initial urgent review is made of the possible impact of the pandemic on the region's educational backwardness and its impact on the inequality gaps that have persisted for decades. Far from the arrogance of exhausting the subject, a holistic vision is presented, structured in three fundamental areas: what we learning or should learning, how we should learning, and what we should educate for. It is concluded that the deepening of basic learning competences, the integration of the educational challenge of technology and the commitment to the formation of a critical and committed citizenship, apart from other equally decisive pedagogical aspects, should be the pillars of a new concept of learning for the immediate future.
Rancang Bangun Game Bersepeda Berbasis 3D Map Tersinkronisasi Dengan Sistem Kendali Gyroscope Dan Infrared

Body health must be maintained by every individual from children to the elderly. In order for the health of the body to be in prime condition, it takes sports activity. One of the sports favored by children is cycling. Cycling is a good sport because it moves many parts of the body, from the hands on the wheel and feet to pedaling. However, some children are lazy and get bored easily when exercising because there is no motivation. Some children prefer to spend their time playing games, so a tool is needed as a means of sport that is packaged in a game to make it interesting. To form a game that resembles bicycle movements, tools can be made using ESP8266, MPU6050 as steering wheel control sensors, and infrared sensors as pedal controls. This tool will be input into the game with serial communication via a USB cable. Games with bicycle themes are made using Unity 3D coded with Visual Studio Code. The results of tests carried out using the black box method, tools and games can run according to design, starting from connecting hardware to software, calibrating, controlling games with tools, and running gameplay on games. Testing was also carried out using the User Acceptance Test (UAT) method with 60 respondents and obtained an overall score of 94.11%.&#x0D;
Inverse problem to estimate lips parameters values of outward-striking trumpet model for successive playing registers

The objective of this work is to estimate by inverse problem lip parameters values of trumpet model so that the oscillation thresholds for successive playing registers occur for the same blowing pressure as the one measured on several trumpet players. The lips vibration is modeled through an oscillator including unknown parameters such as resonance frequency, quality factor, surface mass, stiffness, and opening at rest of the lips. The oscillation threshold is calculated through linear stability analysis of the outward-striking model including the nonlinear coupling with the bore of the trumpet. It appears that many combinations of parameter values are suitable to obtain the same blowing pressure at threshold as in the experiments. According to the analysis of the possible parameter values, some hypotheses are formulated about the playing strategies used by the trumpeter to select the different registers of the instrument. In addition to the resonance frequency of the lips, controlling the lips opening at rest appears to be a viable strategy to match experimental oscillation thresholds in terms of blowing pressure. Numerical values for the lips parameters are given and through sound synthesis, allow the successive registers of the trumpet to be played.