Reviewerly/exHarmony huggingface dataset:
Glasser-Based Poetry Writing Training for Private Junior High School Students RK Star East Management

The problem faced by students in writing poetry is less poetic. Original student write poetry regardless of its visual form: typography, stanza arrangement, diction, and style language. This can be seen from the results of poetry written by students, which do not have poetic power. Student not enough imaginative, intuitive, and not enough think synthetic. In side that system the learning is oriented on the teacher. Based on these problems, students need to be encouraged by learning methods interesting in writing poetry. One of the best ways is to use Glasser's learning model, namely learning which done by utilizing environmental object as a learning medium. Glasser's model is "Learning" which This is done by directly seeing or using the object according to the material lessons and learning objectives”. Especially with the current uncertain condition of Covid-19 when it ends, then the learning model is efficiently carried out online with an application Zoom if plague the not yet ends later. So with a community service entitled "Poetry Writing Training" Glasser-Based on Private Middle School Students RK Bintang Timur Pematangsiantar” is expected student more skilled and creative in in writing poetry.
Sulfide Chemistry at the Fenelon Gold Deposit, Québec

The Abitibi Greenstone Belt in Canada hosts several worldclass gold deposits and is an important gold producer globally.Most of the known deposits are in the southern Abitibi along large east-west trending structures including the Cadillac-Larder Lake and Porcupine-Destor fault zones.The northern Abitibi hosts a similar structure called the Sunday Lake Deformation Zone that is known to host significant gold mineralization along the Detour-Fenelon Gold Trend.The Fenelon Gold Deposit is the focus of this research project.Until recently, there has been minimal research and exploration conducted in the northern Abitibi due to thick overburden and lack of infrastructure.Since 2018, the Wallbridge Mining Company Ltd. has made significant advances in the exploration of this region, with focus on the Fenelon Gold property.This presentation discusses the sulfide chemistry related to gold mineralization based on results from a combination of spot, line, and map analyses by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS).This presentation focuses on the two main styles of gold mineralization observed at the Fenelon Gold property, known as Area 51 and Tabasco.Area 51-style mineralization is hosted in smoky quartz veins and is often associated with pyrite, chalcopyrite, and lesser amounts of pyrrhotite and arsenopyrite.These veins crosscut the Jeremie Diorite (2697 Ma), the main intrusive body at the property.Tabasco-style mineralization is shear zone hosted along the contact between the Jeremie Diorite and the surrounding sediments.Tabasco mineralization is dominantly associated with pyrrhotite and chalcopyrite with trace amounts of pyrite.In both the Area 51 and Tabasco zones, trace element analyses of the pyrrhotite were insignificant, however analyses of the pyrite show correlations between gold, arsenic, and bismuth.The sulfide chemistry shows the relationship between sulfide and gold precipitation at Fenelon and highlights the importance of geochemical analyses for developing a more complete understanding of mineralization on a deposit-scale.
The Association of Socio-Demographic Characteristics of University Students and the Levels of Their Digital Entrepreneurial Competences

This paper aims to provide empirical evidence on the levels of digital entrepreneurial competences (DEC) that university students acquire during their university education and the association of their socio-demographic characteristics and the levels of DEC. The first competence area (Identification of opportunities) of the DEC competence framework EmDigital together with its three sub-competence areas ((Search for and analysis of information, Creativity and innovation, and Prospecting), was assessed, and the association of the DEC levels with different socio-demographic characteristics of university students was investigated using logistic regression. The results show relatively low DEC levels of the participating students for the first EmDigital competence area. Location, field of studies, level of studies and employment status proved to be statistically significant for the DEC university students' acquisition, while variables age and gender have little impact. The results of this research represent a step towards creating a DEC online assessment tool (using the Digital Competence Wheel as a role model) which the universities and other stakeholders could use to assess the levels of DEC their students acquire during university education. This research represents the first study to assess the DEC university students acquire during their university education and the impact of different socio-demographic characteristics of university students on the levels of their DEC.
Perancangan Alat Identifikasi Wajah Dengan Algoritma You Only Look Once (YOLO) Untuk Presensi Mahasiswa

Presence is an important thing in educational world especially higher education. One of students’ success keys is in their presence because it has correlation to the learning quantity carried out by a college student. Some colleges whose learning conducted face to face still use conventional way by using attendant list sheet until this system is felt less effective in the middle of digitalization development marked by the increase of technology usage. Face recognition attendance technology is a technology which can be adapted from one of artificial intelligence science namely machine learning. Machine learning with deep learning branch becomes the solution which eases human’s work. In its process, face recognition requires certain accurate face detection with certain algorithm. In this research, the method used was You Only Look Once (YOLO) algorithm where to follow some research which had been conducted previously it has high accuracy in face prediction. The test results obtained an average accuracy of 0.9793 by paying attention to parameters such as lighting and real-time sending to the website. Through this research, it is hoped that the attendance process will be more effective and can be monitored by lecturers.
UPAYA PENINGKATAN KEMAMPUAN KOLABORASI PESERTA DIDIK MELALUI PLATFORM GOOGLE CLASSROOM DALAM PEMBELAJARAN DARING MATEMATIKA

Penelitian ini bertujuan untuk mengetahui upaya peningkatan kemampuan kolaborasi peserta didik melalui platform google classroom dalam pembelajaran daring. Penelitian ini menggunakan jenis penelitian tindakan kelas (PTK). Subjek dalam penelitian ini yaitu siswa kelas XII MIPA-1 SMA N 07 Kota Bengkulu dengan jumlah peserta didik 36 anak. Desain penelitian yang digunakan dalam Penelitian Tindakan Kelas (PTK) ini empat komponen yaitu: (1) perencanaan (planning), (2) tindakan (acting), (3) pengamatan (observing), dan (4) refleksi (reflecting). Pada model ini, komponen tindakan dan pengamatan dilaksanakan pada waktu yang sama. Hasil dari penelitian ini terlihat pada persentase observasi kolaborasi peserta didik seluruh indikator yang semakin meningkat dari pra siklus presentase 47% dengan kategori kurang kolaborasi, pada siklus I presentase kolaborasi peserta didik sebesar 60% dengan kategori cukup kolaborasi, pada siklus II presentase kolaborasi peseta didik 73% dengan kategori kolaborasi, dan pada siklus III presentase kolaborasi peseta didik 95% dengan kategori sangat kolaborasi. Kata kunci: matematika, google classroom, PTK, kolaborasi, daring Abstract This study aims to determine the efforts to increase students' collaboration skills through platform google classroomThis research uses classroom action research (CAR). The subjects in this study were students of class XII MIPA-1 SMA N 07 Bengkulu City with a total of 36 students. The research design used in this Classroom Action Research (CAR) has four components, namely: (1) planning, (2) acting, (3) observing, and (4) reflecting. In this model, the action and observation components are carried out at the same time. The results of this study can be seen in the percentage of student collaboration observations of all indicators which is increasing from the pre-cycle percentage of 47% with the less collaboration category, in the first cycle the collaboration percentage of students is 60% with sufficient collaboration category, in the second cycle the collaboration percentage of students is 73 % in the collaboration category, and in the third cycle the percentage of students' collaboration is 95% with the highly collaborative category. Keywords: mathematics, google classroom, CAR, collaboration, online
Peningkatan Motivasi Belajar Siswa dalam Pembelajaran Microsoft Excel melalui Pembelajaran Kooperatif Tipe STAD di MAN 2 Yogyakarta

This research aims to describe the application of cooperative learning using the STAD model in increasing student learning motivation at MAN 2 Yogyakarta. This research uses an action research method consisting of 4 stages, namely; planning, implementation of actions, observation and reflection. The subject of this study is class X IPS 2 students of the 2019/2020 school year with a total of 24 people, consisting of 7 male students and 17 female students. Data collection techniques use interviews, observations, documentation. The results showed that the application of STAD-type cooperative learning can improve student learning outcomes and activities in informatics subject excel materials. This can be proven by the percentage of achievements to student activity increased from 32.75% in the first cycle to 92.75% in the second cycle and can be declared successful because it has reached performance indicators.
QUALITY MANAGEMENT OF TEACHING STUDENTS OF THE FACULTY OF MUSIC AND PERFORMING ARTS ON THE BASIS OF A COMPETENCE-BASED APPROACH

For a number of years, a significant trend in Russia and around the world has been the "Europeanization" of education, and the main goal of the XXI century in many institutions of higher education has been "survival in new conditions", which has pushed into the background the quality of education, training and professional growth of future musiciansperformers. This led to the blurring of the boundaries of education, reorientation to the immediate needs of society, the values of which were largely brought up by the Western system. However, the rapid change in the geopolitical situation in the world has had a significant impact on the socio-cultural situation in Russia. Unprecedented external pressure caused an unexpected reverse effect for many foreign "partners" - the growth of patriotic sentiments in Russia, the growth of national consciousness, an appeal to the historically established values of Russian education and its quality. The article discusses aspects of the training of future musicians-performers, taking into account the principles of a competence-based approach that allows you to manage and control the quality of education at the university.
A Robust Exploration Strategy in Reinforcement Learning Based on Temporal Difference Error

Exploration is a critical component in reinforcement learning algorithms. Exploration exploitation trade-off is still a fundamental dilemma in reinforcement learning. The learning agent needs to learn how to deal with a stochastic environment in order to maximize the accumulated long-term reward. This paper proposes a robust exploration strategy (RES) based on the temporal difference error. In RES, the exploration problem is modeled using Beta probability distribution to control the exploration rate. Moreover, the most promising action is selected during the exploration with a view to maximizing the accumulated reward and avoiding un-rewardable wrong actions. RES has been evaluated on the k-armed bandit problem. The simulation results show superior performance without the need to tune parameters.
Novel method of detection of systematic copy move forgery based on SURF algorithm

In trend, the breakthrough of various software’s and technologies to make betterment of photographs has led to misuse of the discoveries. In turn, there is a higher chance of destroying the actual view of the image and produce duplications. In the proposed system, using Speeded Up Robust Feature (SURF) algorithm to abstract feature points on the images and match them to detect the occurrence of fraudulent in the image. SURF works in three phases. Firstly, the images are scanned, features are extracted, followed by feature description and finally the features are matched. Fraudulent is detected with the help of matched Features. Further to study the efficiency of algorithm, SURF and SIFT are implemented and the time taken to process the image is calculated. SURF seems to be faster than SIFT in processing and feature matching which speeds up forgery detection. Thus, SURF is speeder than SIFT.
Sweet Drinks App: Innovative Technology App to Buy Fresh and Healthy Drinks

Buying a drink is a necessity for everyone in this world. but there are some drinks that we often encounter and are consumed by humans. This drink, of course, comes from a variety of ingredients, one of which is fruit. all the drinks we make are quality drinks and affordable prices. We also use a variety of fresh and new beverage ingredients. As technology evolves, it becomes easier for people to access everything including buying fresh and healthy drinks, and now you can use the “SweetDrinks” ordering platform. This app relates to people ordering drinks. The name of this app is Sweet Drink. Why is it called a sweet drink? because this app tries to help people find a variety of drinks, and also comfortable with the services provided. This application can be used by everyone for free. This application can also be developed via android. The logo used uses the concept of millennial children's drinks with a doodle aesthetic to attract buyers. This logo was also created to draw the attention of shoppers towards their drinks as well as the services provided by the app. SweetDrinks is an application that is intended for people who want to easily buy drinks such as juice, coffee, and some other fresh drinks, no longer need to go to a shop or cafe to buy drinks. the way this application works is the same as other platforms in general, the buyer can choose the drink to be purchased then the buyer can also determine the number of drinks to be purchased, after that the buyer will be directed to fill in the address, after that the buyer can make a payment, after making payment for the goods already purchased will be immediately processed for delivery to the destination address.
Desain Informasi Cara Bayar Penerimaan Negara menggunakan Pemodelan Finite State Automata

The government modernizes the state revenue system by launching the State Revenue Module (MPN), which connects the billing code generation system with the payment system at the collecting agent. This study aims to develop an information system on how to pay state revenues to assist the public in depositing state revenues through payment channels at the collecting agent by applying the Finite State Automata (FSA) modeling concept. The system development uses the waterfall model while collecting the agent's data. The FSA design and testing phase uses the JFLAP application, while the application design stage uses the Laravel framework. System testing uses the black box testing method to determine how far the functioning of the components or menus on the system has come. In addition to making it easier for the public to deposit state revenues, this study also shows that automata theory can help design a payment information application system. This application design offers a website display of information on how to pay state revenues that can run well. Every menu on the system, when used, has no errors so that this system can be utilized by users and developed in applications based on Android and iOS.
Prediksi Curah Hujan Wilayah Provinsi Yogyakarta dengan Algoritma Neural Network

Emerging inaccurate information about the rainfall system can affect aspects of life. Inaccurate precipitation forecasting can be problematic, so it is necessary to predict precipitation with a high level of accuracy. Therefore, this study proposes a method with a neural network algorithm to predict rainfall to benefit the community. The data used in this study is daily precipitation from 2016 to 2021 from BMKG. Based on the test results, the data shows that the best neural network (NN) model is obtained from input layer 31, hidden layer 4, training cycle 1500, learning rate 0.01, and momentum 0.9, resulting in an error of 0.828. Based on the results with the smallest error, using the neural network method can be used to predict future precipitation with good accuracy.
Model Of Physics Experiments Using Smartphone Sensors In Senior High School 1 Pangkalpinang

The aim of this research is to develop a model physics experiment manual in high school by utilizing sensors on smartphones as a source of observing data on physics experiments to increase students' level of understanding. The research method used is research and development. The teacher arranges physics experiments manual so that students can use it. Retrieval of data in the experiments uses the Research Based Learning (RBL) method so that students get the freedom to be creative using smartphone sensors.The results of the study are expected to help students understand the concepts of physics through experiments data using smartphone sensors
Implementing the Cooperative Learning Model Team Game Tournament Type in Improving Students’ Vocabulary at MTSN Nurul Falah Jambi

The purpose of the research was to improve students’ vocabulary ability through cooperative learning model Teams Game Tournament type at second year students of MTs NurulFalah Jambi. The target of this research is hoped that cooperative learning model teams’ game tournament type can be one of model that can be used by the English teacher in teaching vocabulary. This research used classroom action research. This research conducted in MTs NurulFalah Jambi, and the subject of research was the second-year students with total of student are 34 students in academic year 2018/2019. The researcher used observation, test, and questionnaire to get the data. The procedure in this research is referring to classroom action research that consists of four elements: planning, acting, observing, and reflecting which did in every cycle. The researcher did cycle 1, and then the researcher arranged the action plan on the result of the reflection at the first cycle. There was the improvement of students’ vocabulary ability, the test score at cycle 1 was 14,49% and at cycle 2 was 31,54 %. There are 6 teams, 3 teams got the award as “Super team” they are group 3, 4, and 5. 2 Teams got the award as “Great Team” they are group 2 and 7. While 2 teams got the award as “Good Team” they are group 1 and 6. This research has revealed that Cooperative Learning Model Team Game Tournament Type can be an alternative to solve the students’ problems in vocabulary.
Complex Metal(loid) Deportment in Porphyry Ore Sulphides - Insights from LA-ICP-MS Mapping

With the global transition to low-carbon technologies, porphyry Cu deposits are gaining in importance, not only as a Cu supplier, but also as a source of other critical raw materials.Enhanced Cu production will promote the recovery of byprodcut commodities, such as Ag, Au, Te, Co, Ga, Ge, In and PGEs, some of which are key consituents in modern energy technologies.It is critical to understand the mineral-metal(loid) associations of the ore to ensure recovery of these by-product commodities.In porphyry Cu ores, chalcopyrite, bornite, digenite, chalcocite, pyrite and where present, sulfosalts, electrum and tellurides are generally identified as hosts of critical metal(loid)s.However, mineral replacement and exsolution processes can lead to more complex metal(loid) deportment in Cu-sulfides with challenges for mineral processing.We present LA-ICP-MS maps that reveal metal(loid) redistribution through exsolution in hypogene and through partial replacement in supergene Cu ores.Hypogene examples show digenite lamellae that are enclosed in bornite, which is widely interpreted as an exsolution product from a Cu-rich bornite solid solution [1].Element distribution maps show that the exsolution processes can result in a distinct trace element fractionation between digenite and bornite.Silver, Au and Te are markedly enriched in digenite over bornite, while In, Sn and Bi are mainly retained in bornite.We further present examples of complex metal(loid) deportment in Cu sulfides from a supergene zone, developed over hypogene ore.The ore samples show supergene chalcocite that is partially replacing hypogene chalcopyrite along its outer grain margins.The replacing chalcocite is distinctly enriched in Ag and Au, but depleted in In, Sn, Se and Bi relative to chalcopyrite.Supergene fluids most likely introduced elevated precious metal contents, but also remobilized In, Sn, Bi and Se as chalcopyrite was altered to chalcocite.Our element mapping results highlight the complex mineral-scale distribution of metal(loid)s in Cu ores.This spatial information can be integrated into metallurgical models to improve recoveries of critical raw materials.[1] Phase relations in the Cu-Fe-S, Cu-Ni-S and Fe-Ni-S systems.
Analisis Sentimen terhadap Peluang Kerja di Indonesia selama Masa Pandemi COVID-19 dengan Metode Klasifikasi Naive Bayes

The impact of the COVID-19 pandemic is very broad, one of which is in the business sector. This has resulted in an impact on job opportunities during the COVID-19 pandemic in Indonesia. This study aims to conduct in-depth learning related to job opportunities in Indonesia during the COVID-19 pandemic using the Naive Bayes model. The data source used comes from Twitter. The results of this study indicate that the largest AUC score falls to the Random Forest model (79.40%), but for more accurate precision falls to the Naive Bayes model (87.88%). In addition, there is a confusion matrix which shows that the Naive Bayes model trial is running well.
ERROR ANALYSIS OF THE STUDENTS IN USING SIMPLE PRESENT TENSE WRITING DESCRIPTIVE TEXT

This research is about Error analysis of using simple present tense made by the students in writing descriptive text at grade II in junior high school Pematangsiantar. The problem is to find out the In this study, the researcher uses qualitative method. The students of grade VIII SMP Negeri 2 Siantar is 20 students taken the subject. The instrument types of error analysis found on the students’ writing descriptive text. The researcher asks the students to write descriptive text in using simple present tense. The result of the research is there are four types of error made by the students writing in using simple present tense based description of error, they are: (1) omission (45,23%), (2). error of addition (8,33%), (3). error of misinformation (20,23%), and ()4. error of misordering (26,19%). From the results of the analysis, it was found The two errors that have the highest number is omission(45,23%). The conclusion is there are still many students who do not understand how to make sentences using the simple present tense in descriptive text and practice again to using tobe (is, am are) in sentence, use of verb –s/-es and regular and irregular verb. For students, they should learn more again and discuss with their friends in group and practice it.