Reviewerly/exHarmony huggingface dataset:
PERANCANGAN INTERFACE E-INVENTORY BARANG BERBASIS WEB PADA UNIVERSITAS MUHAMMADIYAH JAMBI

Inventory is an activity to compile goods or record existing goods or materials correctly. Inventory of goods is also a recording of data related to goods or assets at Muhammadiyah Jambi University. Every item that is to be procured must be recorded properly as well as if the goods that have been procured and distributed must be recorded and reported properly and correctly as asset data. The purpose of this research is to help and facilitate employees in managing inventory of goods to be more effective and efficient, the method used is a prototyping system with the results of this research being the Design of the Goods E-Inventory Interface at Muhammadiyah Jambi University
Kerangka Kerja Indikator Pengukuran Tingkat Kematangan Transformasi Digital Perguruan Tinggi

Strategic planning is an essential part of the college life cycle; a critical aspect of planning is the digital transformation of universities. Digital transformation supports university business processes and is a riving engine for universities to adapt to changes to provide added value for the best services for all stakeholders. To achieve this, universities need an overview of the maturity level of digital transformation that has been achieved today. This research produces a new methodology for assessment in a holistic framework as an indicator of measuring the maturity level of digital transformation.This measuring tool must be easy to use by universities when they will take measurements for all academics and easily understood by all respondents who are determined to provide an accurate picture of the maturity level of digital transformation. The final result is presented in the form of a framework that contains a standard value index of maturity level, and recommendations for digital transformation as a form of self-evaluation for higher education strategic planning
Sistem Analisis Prediksi Penjualan Vitamin di Apotek Menggunakan Metode Trend Moment

The coronavirus pandemic has also paralyzed the world economy, including Indonesia, in several sectors such as tourism and MSMEs. However, other sectors such as health and food remained stable and even experienced a surge in sales, especially sales of vitamin drugs at pharmacy outlets. One of them is Apotek Manjur Marendal, which experienced an increase in sales of medicines such as vitamins during the pandemic. To meet consumer demand and to process the right stock of vitamin drugs so that there is no loss, a prediction technique for vitamin drug sales is needed with data mining. With data mining techniques, Apotek Manjur Marendal can predict sales during the pandemic, so that profits and losses and stock of vitamin drug sales can be controlled. Data mining techniques require methods to make the calculations more complex. Several methods have been created by several inventors, one of which is the Trend Moment method. Based on the prediction results of vitamin drug sales using the Trend Moment method on sales data for 1 year during the 2021 pandemic period, it was obtained prediction results for the next 1 year in the 2022 period that sales of vitamin drugs such as Becom C, Enervon C, Ester C, Hevit C and Vitalong C stable with sales ±5000vitamin drugs sold in total, while the prediction accuracy reached the highest accuracy &gt; 90% and the lowest accuracy 64%.
The Relationship between the Core Competencies and the Adaptation to College Life of College Students: Focusing on DEU-CCDS and DEU-GRIT of D University

This study attempted to examine the association between the core competencies cultivated bycollege students through curriculum and non-curriculum and college life adaptation across academic-, social-, emotional-, and career-adaptation. To this end, D university students were asked to respond using the DEU-CCDS scale for core competency and the DEU-GRIT scale forcollege life adaptation. As a result, there was a significant correlation between all variablesexcept for the relationship between 'democratic communication' of core competencies and'interpersonal competence in school' and 'career activities' of college life adaptation. In addition,it was found that the components of 2 to 8 core competencies significantly explained across allsub-variables of college life adaptation. On the other hand, as a result of deriving the core competency components of continuity-improvement through IPA analysis, the core competencycomponents that significantly explain college life adaptation were mainly distributed in the areas of maintenance and progressive improvement, and some were also distributed in the areas offocus improvement. This suggests that in order to induce college students to adapt well tocollege life, it is necessary to improve and maintain customized curriculur and non-curricularactivities so that they can strengthen their core competency level.
Estimating Inclusiveness of Growth in Sub-Sahara African Countries: a VAR Approach

The study examined the interaction among income inequality, economic growth, and poverty with a view of assessing the extent of inclusiveness of growth in selected African countries. Using a dataset from World Development Indicators (WDI) and Standardized World Income Inequality Dataset (SWIID), the study adopted Vector AutoRegression (VAR) method in its econometric analysis. Its findings show that only "West" African countries exhibit partial traits of inclusiveness of growth. Thus, the study recommends the provision and implementation of distributional and growth-oriented macroeconomic policies, as well as investment in public infrastructure to spread the benefits of growth to all in African countries.
THE PHENOMENON OF ONLINE GAMBLING UNDER THE GUISE OF ONLINE GAMES AMONG COLLEGE STUDENT

This study aims to find out: The Phenomenon of Online Gambling Clucking Online Games Among Students in Pasar V Tembung Village. The research method used in this thesis is a type of qualitative research using the phenomenology method. The data collection technique used was various data obtained from observations, interviews, and documentation at market V in Tembung Village. The results of this study indicate that the phenomenon of online gambling under the guise of online games among students is that many students are familiar with online gambling in their free time and because there is no activity either on campus, at boarding houses or at home. Online gamblers utilize information and communication technology as a means of modern gambling, making it more profitable for online gamblers because it does not require them to meet in person. The forms are: Slots, Togel, Links, Websites, Poker, Rummy, Football Gambling and Higgs Domino. Where teenagers do online gambling as a form of activity in the process of fulfilling their needs, both psychological and material. The resulting impact affects themselves personally and others, both having a negative impact on academic achievement, the economy, psychology, time and resulting in criminal acts.
Increasing The Students’ Ability In Speaking English By Using Work In Pair Strategy

This research aimed to increase the students’ ability in speaking by using Work in Pair strategy at the grade VII class B of SMP Swasta St. Theresia Lahewa. In this research the researcher applied the Classroom Action Research with some stages namely planning, observation, action and reflection. It has been conducted in SMP Swasta St. Theresia Lahewa at the grade VII, class B, consisted 30 students. This research has been applied in two cycles because in the first cycle the students still did not pass Minimum Competence Criteria (MCC), 75. The instrument of data colection were observation sheets, fieldnote, and test by video recording. After analyzing the data, the result showed in Cycle I there were 6 students (20%) who got mark in renge 40-59. They were classified in low level. Then 21 students (70%) got mark in range 60-74. They were classified in adequate level. And then 3 (10%) students who got mark in range 75-84 classified in good level. The average of students’ mark was 55 while the highest mark was 76 and the lowest mark was 41. Then in Cycle II there were 21 students (80%) who got the mark in range 75-84, were classified as good level and 6 (20%) got mark in range 85-100, were classified in high level. The average of students’ mark was 80. Then, the highest mark was 90 and the lowest was 76. It can be concluded that Work in Pair strategy increased the students’ ability in speaking English.
Designing Locally Relevant Instructional Material for Indonesian EFL Classroom

Meaningful teaching and learning can be achieved when the materials are closely related to the learners' real life. This research focuses on language and culture for the materials suitable for the first semester students of EFL class at the University of Palangka Raya. The design-based research was applied to provide sources consisting of environmental linguistic expressions within the eco-linguistic perspective and using a text-based or genre-based approach by selecting suitable texts for the level. The Product of Instructional Material shows at least two benefits: (1) as the source of the main module of Intensive Course in writing skill for the first-year students of English Education in Central Kalimantan, and (2) the solution for encouraging the teachers to modify the provided material which can cover the national standard (KKNI) as well as promoting the local values to strengthen local cultures to have meaningful teaching and learning process.
Sistem Klasifikasi Penjualan Produk Alat Listrik Terlaris Untuk Optimasi Pengadaan Stok Menggunakan Naïve Bayes

Optimization is a process of solving a problem so that it can provide the best conditions that can provide a maximum or minimum value. In a business, optimization of stock procurement is an important thing, including in terms of product sales. If the stock of a product is empty then the sales potential decreases. Therefore we need a method to optimize the stock so that it can supply consumer demand and ultimately increase sales. Data mining can be applied in the sales system by creating a sales classification model for the best-selling products. In this study, the sales classification of the best-selling products at electronic stores was carried out using Naïve Bayes. The data used in this study is data on sales of electronic products for 3 months. In the early stages, preprocessing is carried out, namely by encoding labels. Model testing was carried out using percentage split and cross validation with several trials. Through the use of percentage split, the best accuracy is obtained at 93.3% with a comparison of 30% of test data and 70% of training data. The best accuracy using cross validation was obtained by 84% for 7-fold. The classification system that has been created is capable of classifying the best-selling products every quarter of a year. Through the use of the best-selling product classification system, the store can find out the best-selling product stock so that the stock is not empty. Thus the procurement of store stock can be more optimal and sales will increase.
Analisis Sentimen Review Produk Skincare Dengan Naïve Bayes Classifier Berbasis Particle Swarm Optimization (PSO)

Skin care products have become the main needs of all people who are the targets of various brands of skin care products. However, not all skin care products have good quality according to consumer needs. They look for products that have the best quality by looking at reviews from other people, so they have an idea that influences their interest from other people's reviews submitted through various marketplace platforms or social media regarding the results after using these skin care products. Sentiment analysis is one way to analyze and classify reviews into positive opinions and negative opinions regarding the product in question to look for product quality based on public views. The algorithm used in this research is the Naive Bayes Classifier. The Naive Bayes Classifier method was chosen for reasons of ease of implementation, fast and high accuracy. The Naïve Bayes method also has a disadvantage, namely it is sensitive to feature selection, which results in low classification accuracy. Therefore, in this study, the feature selection method, namely Particle Swarm Optimization, was used in order to increase the accuracy of the Naïve Bayes classifier. The dataset used is 800 data reviews and tested using 10-Fold Cross Validation. The results showed an increase in accuracy from 77.96% to 79.85%.
Analysis of Telkom University News Subjects on Popular Indonesian News Portals Using a Combination of Hidden Markov Model (HMM) and Rule Based Methods

News media are often found in everyday life as a means of information for the public about something that is happening. In news articles, it is common to see several sentences that support the object to increase its popularity by being promoted by the subject. Part of Speech Tagging can determine the class of words in the sentence according to Tagsets provided by the corpus. That way, the search for the subject in the news article can be found from the word class obtained from a corpus. This research was focused on finding the subject "who" repeatedly spreading the news about Telkom University by using Part of Speech Tagging with the Hidden Markov Model and Rule Based on a news dataset from popular news portals about Telkom University. The process is taking all news about Telkom University on popular news portals and classifying it using the Hidden Markov Model and Rule-Based. We conducted to enhance the research results by changing the probability estimator on Hidden Markov Model. After running some scenarios, the best results obtained by the Hidden Markov Model and Rule-Based are the Accuracy of 94.96%, the Precision of 94.99%, the Recall of 94.96%, and the F1-Score of 94.95%.
Rancangan dan Evaluasi Usability Pada Aplikasi Website Media Pembelajaran Cyberbullying Menggunakan Metode Gamifikasi

Cyberbullying is bullying act carried out on social media to cause harm the victim. The potential for cyberbullying is very high among teenagers. This is due to high frequency of using social media, increasing cases of cyberbullying, and the lack of education about cyberbullying. Cyberbullying education has been carried out using digital literacy educational activities using digital literacy only focus on introducing and preventing cyberbullying in the form of seminars or lectures. However, using this method has many shortcomings, for example someone easily forgets the material presented and gives less space to develop creativity. Interactive education is needed to increase motivation to learn about cyberbullying. The gamification method is very suitable to be applied in learning because the gamification method involves game elements such as points, leaderboards, badges, challenges, and achievements. In addition to using the gamification methods, visual media such as images and animation video is also suitable for learning. This research utilizes gamification-based learning and visual media to deliver the material as a prototype application for cyberbullying learning sites. This research aims to provide education and increase motivation to learn about more interactively cyberbullying. This research involved 42 respondents with a range of ages between 12-21 years. This research will use System Usability Scale (SUS) to evaluate the prototype's usability. The usability score from the prototype in this research is 77.8, meaning the prototype is acceptable to use.
Prediction of Rainfall Classification of Java Island with ANN-Feature Expansion and Ordinary Kriging

Precipitation is one of the most important climatic variables in many aspects of our daily lives. High rainfall intensity can cause floods, landslides, and other natural disasters. Therefore, rainfall prediction is important for predicting natural disasters, assisting farmers in production decisions, and crop harvesting. In this research, a system is built to create a rainfall prediction map using a machine learning approach and spatial interpolation algorithms in Java, Indonesia. In the field of weather prediction, the artificial neural network approach is a popular machine learning method. The artificial neural network (ANN) method is a method that has the advantage of studying connections in the previously unknown hidden layer between input data and output data through training procedures. By using the ANN method, historical weather and climate data can be applied to create a classification model and predict rainfall classes. The classification of data is determined based on the attributes of historical weather and climate data, namely temperature, humidity, air pressure, evaporation, sunlight, and the level of rainfall in the time range per day and month. From the results of the ANN modeling, it was found that the 5C month model with an accuracy value of 89% as the best monthly ANN model, and the 6C day model with an accuracy value of 81% as the best daily ANN model. After going through ANN modeling, there is a spatial interpolation algorithm that is often used to estimate rainfall, namely Ordinary Kriging. The Ordinary Kriging approach is used to reduce the estimated variance and estimate the rainfall value in the case study area. After going through Ordinary Kriging modeling, a rainfall prediction map for the next six months and seven days is made based on the coordinates as a result of the research. The results of this research are rainfall prediction maps for the next six months and the next seven days on Java Island.
Klasifikasi Emosi Pada Lirik Lagu Menggunakan Algoritma Multiclass SVM dengan Tuning Hyperparameter PSO

Currently, it is increasingly difficult to determine the emotion in a song because the numbers of the songs continue to increase, based on this problem, the researcher makes a classification model using text classification. Based on these problems, this study uses the Multi Class Support Vector Machine (SVM) method with Particle Swarm Optimization (PSO) as a tuning hyperparameter and comparing the effect of 3 datasets (lines, verses, and whole songs) in the case of classifying the emotions of song lyrics. In this case, there are five basic human emotions, in-between love, happiness, anger, fear, and sad. Based on the test results on each model, scenario 2 (SVM-PSO Perbaris) does provide the best model performance with an accuracy value of 92.13%. However, if we look at the performance value, it changes from the evaluation of the training data to the testing data presented in table 4.3, the most significant changes occur in the verses dataset and the whole song dataset. This can happen because the content or value of the per-bait dataset and the whole song has more sentences than the per-line dataset. So that the quality will be better if you use the verses dataset or the whole song. This research has also succeeded in make the classification of emotions so that it can classify the class of emotions from the text of Indonesian song lyrics.
Analisis Sentimen Komentar Pengunjung Terhadap Tempat Wisata Danau Weekuri Menggunakan Metode Naive Bayes Classifier Dan K-Nearest Neighbor

Trip Advisor is the largest travel site in the world that helps tourists in planning and booking travel. One of the recommended attractions on the TripAdvisor website is the Crystal Cave, which is located in Kupang City. Human habit in posting tourist attractions visited is a common thing to present human responses to one of the tourist attractions. Usually there are certain parties who want to know the sentiments and responses to one of the tourist attractions. Therefore, this study will conduct a sentiment analysis of one of the tourist attractions in the city of Kupang is the Crystal Cave. The analysis was carried out by classifying people's sentiments. The calcification method used in this study is Navie Bayes Classifier and K-Nearest Neighbor. From these two methods a comparison will be done to find out the level of accuracy. Sentiment classification consists of positive and negative. The purpose of this study is to provide information about the quality of one of the tourist attractions in the city of Kupang by using sentiment from visitors and determine the level of accuracy of the comparison of the two methods tested. The test results will be tested on the Rapidminer tool showing the level of accuracy of testing both methods.
Sistem Pendukung Keputusan Pemilihan E-Commerce Terbaik Menggunakan Metode MOOSRA

Online transactions are transactions that are very popular with many parties today because of the ease of access, ease of transactions and security possessed by each e-commerce, the number of parties who use e-commerce because of the dependence and availability of smartphones and the habits of the current generation on digital age. Every transaction habit contains its own risk to its users, so it is necessary to know the things that must be fulfilled as a user in choosing e-commerce to reduce the risk that will be accepted in the future. This study uses a decision support system logic in analyzing the selection of the best e-commerce using the moosra method. Consider using the method not only based on decisions made by yourself but based on considerations from several previous studies. The results obtained from this study using the moosra method are the highest value of 3.26323 on e-commerce lazada as the best e-commerce.
Competency of Elementary School Teachers 84 Sinjai District in Writing Teaching Materials

This study aims to describe the influence between knowledge of writing theory and interest in writing on the ability to write teaching materials for teachers at SD Negeri 84 Sinjai Regency. This research is categorized into the type of quantitative infrensial research. The sample of this research is all teachers of SD Negeri No 84, Sinjai Regency for the 2020/2021 academic year, totaling 24 teachers spread from grade I to grade 6. The data in this study was collected through three techniques, namely test techniques, questionnaires, and documentation. Data analysis was carried out using the percentage technique with the formula: n/Nx100 for the range 10-100 and simple and linear/multiple regression test techniques with computer facilities. The results showed that the level of theoretical knowledge of teaching materials has an average value of 66.10, and is in the medium category. Data analysis of the level of interest in writing teaching materials with an average value of 62.30, and is in the medium category. Data analysis of the level of competence in writing Indonesian language teaching materials with an average value of 63.33, or is in the medium category. Hypothesis testing shows that (1) there is a significant effect between the variables of theoretical knowledge of teaching materials on the competence to write Indonesian teaching materials with a large influence 59.70%, (2) there is a significant influence between the variables of interest in writing teaching materials on the competence to write Indonesian teaching materials with a large influence55.29%. (3) there is a joint significant effect of theoretical knowledge of teaching materials and interest in writing teaching materials on the competence to write Indonesian teaching materials with a large effect of 59.66%.