Reviewerly/exHarmony huggingface dataset:
ANALISIS DAN PERANCANGAN SISTEM INFORMASI PEMASARAN UNTUK MENINGKATKAN PENJUALAN BERBASIS WEB (E-COMMERCE) PADA PT. SINAR REJEKI CEMERLANG

Current developments In today's era, there are still many companies or businesses that still do not use technology. To be able to provide information, internet technology is needed. Accessing the internet can be done anytime and anywhere if a connection is available. All companies will compete with each other to use this technology to market and sell their products so that companies can develop and are able to continue to compete with other companies. efficient, the means is an online marketing and sales system. Based on this situation, the company decided to develop a website like e-commerce. Then a sales information system was made which is similar to an e-commerce website. To train how to market products and the buying and selling process, we can start using the e-commerce web. Making this system will be able to reduce problems that occur between buyers and sellers because it is done by use a system that is usually connected to internet. In addition, buyers can also view detailed product information and understand the product they want to buy. This system is made using the PHP programming language with the Laravel framework. The Laravel framework is a website development that is formed in the PHP language. The results of this research are in the form of designing a web-based online sales system that can also be used to find out detailed product information. respondents, the results of this questionnaire get a percentage value of 95% so it can be concluded that this online sales system can be used, and makes it easier for users.&#x0D; &#x0D;
Information System for Sales of Spare Parts at Drs. Workshop

Designing a Java netbeans-based sales information system for the Drs. Workshop business. The research method used is a qualitative method, which is a research method based on interviews or in-depth observations of the research subject. With the creation of a sales information system at the Drs. Workshop business based on neatbeans, all activities related to the sales data of goods can run well and smoothly. In this application, the sales data management section can handle inputting data about all sales transactions quickly and can be updated easily. This Drs. Workshop spare part sales information system is made with Netbeans and MySQL as its data base. This information system can be used to manage sales data, incoming and outgoing goods, also to perform sales calculations based on the data that has been inputted, and can be used to print reports. Finally, with this sales information system, the sales calculation process can be done automatically without the need to calculate manually and the sales data obtained are appropriate, provided that all the data entered is valid.
The Design of the Solar System Educational Game Using Forward Chaining Based on a Mobile Application

Technological developments especially in software are not in line with developments in the field of education. This is because most of the modules used by teachers are still in the form of printed books. Some subjects require the help of pictures to provide understanding to children. One of them is natural science subjects, especially the solar system. Therefore, this study aims to design a solar system educational game application using multimedia-based forward chaining. The making of this educational game application uses the Unity game engine with the forward chaining method. The solar system educational game application is a game application that combines games with the explanation of the solar system material in it and is implemented on an android smartphone.
Twitter Opinion Mining Analysis of Web-Based Handphone Brand Using Naïve Bayes Classification Method

Social Media is now very commonly used for the benefit of society. People mostly use social media to convey information, give opinions, even for media to express themselves. One of the social media that is widely used to convey this information is Twitter. From the use of Twitter, a public opinion tweet emerged about a mobile phone product. The more that is posted on Twitter about cellphones, the more public opinion will arise about cellphone brands. From these opinions, a classification is needed that can distinguish Neutral, Negative, or Positive Opinions. Sentiment analysis or opinion mining is one part of text mining that can help with these problems. In connection with the above, an application is designed that can analyze sentiment analysis from Twitter using the Naïve Bayes classification method. The results of the application of the Naïve Bayes classification method will result in a classification of sentiments into neutral, negative, or positive opinions
Analysis of the Design of a Decision-Making System for Assessing Employees and Clothing Products using the Simple Additive Weight Method Web-Based

Indonesia is a country that is currently developing in technology and internet networks that follow modern times so that people can easily access and explore information needs when people need something, for that several companies and traders have now invested in a web-based program and mobile so that the public can easily access the company's web regarding marketing information on what products are being sold and can compare them to other products, one of which is the Indonesian market place which currently spoils the community in terms of primary, secondary and tertiary needs, DNA.GALERI Boutique is a boutique that is engaged in Muslim clothing products for young women in dynamic and elegant designs adapting to changing times, attracting Muslim women to love to cover their limbs fully in avoiding aurat. Because of the important role of employees, and the development of employees who work with each other and do not know the quality of the employees when selling and serving goods to the maximum or not, employee assessment is needed to measure how productive the work done in selling goods for sales turnover is. Likewise, for products being marketed, it is necessary to measure transparency assessment that has been assessed by the community, which will later be known to the boutique owner which product is the best and make the product worthy of being an option to add stock or be used as a sampling in design developments that will attract public attention. For this reason, a system design was made to support and produce a decision in assessing good employees and assessing superior clothing products from other models of clothing using the SAW method supported by web-based technology in assessing employees and boutique products sold
KEEFEKTIFAN MODEL PEMBELAJARAN QUANTUM (QUANTUM TEACHING) TERHADAP HASIL BELAJAR MATA PELAJARAN IPS SISWA KELAS IV SDN REJOSARI 02 SEMARANG KECAMATAN SEMARANG TIMUR

This study aims to determine the effectiveness of the application of the Quantum Teaching learning model on the learning outcomes of social studies subjects for fourth grade students of SDN Rejosari 02 Semarang. The research used Quasy Experimental Design in the form of Pretest-Posttest Control Group Design. While the population used by this researcher is all class IV A and class IV B SDN Rejosari 02 Semarang. The sample used is the fourth grade students of SDN Rejosari 02 Semarang taken from the saturated sampling technique. From the data, the students' scores increased with an average posttest score of 86.8 for the experimental class and 69.8 for the control class. So it can be concluded that the Quatum Teaching learning model is effective in improving the learning outcomes of fourth grade students at SDN Rejosari 02 Semarang.
OUTLIER IDENTIFICATION ON PENALIZED SPLINE REGRESSION MODELING FOR POVERTY GAP INDEX IN JAVA

Java is one of the islands in Indonesia which has good establishment acceleration. Even though economic growth was good, poverty is still a serious problem. Three of six provinces, including DI Yogyakarta, Central Java, and East Java still have poverty rates above national rates in March 2020. This problem indicates that an imbalance in poverty happens between those regions. Several regions have extreme conditions or known as outliers. Besides that, poverty gap data have a complex pattern so modeling using a non-parametric approach is suitable. This study aims to build an appropriate model to support the success of poverty alleviation in Java and the identification of outliers was carried out using an adjusted boxplot. The best-penalized regression spline model for Poverty Gap Index in Java Island was obtained by Generalized minimum Cross-Validation (GCV) using optimum smoothing parameter (λ) 0,12 and knot combination (1, 2, 4, 1, 5, 3, and 1) for seven predictor variables. The result shows that penalized spline regression model has a higher R2 than OLS regression. The R2 is obtained 69,10%, so the model is feasible to explain the variability of the poverty gap in Java. Moreover, based on the outliers’ identification shows a dependency between outlier in data and residual because some districts/cities are identified as outliers in both.
HILL CLIMBING ALGORITHM ON BAYESIAN NETWORK TO DETERMINE PROBABILITY VALUE OF SYMPTOMS AND EYE DISEASE

One of the five human senses referred to as photoreceptors is the eye because the eye is very sensitive to light stimuli. Refractive abnormalities in the eyes are often experienced, which are abnormalities that occur when the eyes cannot see clearly in the open or blurred vision. An unhealthy lifestyle is a trigger for an increase in individuals who experience complaints of eye diseases. In diagnosing a disease, doctors need patient information in the form of symptoms experienced so that patients can be treated immediately. Information in the form of symptoms and types of eye diseases can be used to make conjectures about eye diseases through the structure of BN. The symptom information and type of the disease are represented through nodes, while the relationships are represented through the edge. BN is one of the Probabilistic Graphical Models (PGM) consisting of nodes and edges. BN is also known as a direct acyclic graph (DAG), which is a directed graph that does not have a cycle. The approach method used is scored based on the evaluation process with the bic scoring function. The algorithm used in this study is the HC algorithm. The research data used consisted of 52 symptoms and 15 eye diseases. The results of the study were obtained by the final structure of BN formed by the HC algorithm produced 93 edges and 65 connected nodes, and the probability value of the disease and the symptoms of the disease in the eye.
CREDIT CARD FRAUD DETECTION USING LINEAR DISCRIMINANT ANALYSIS (LDA), RANDOM FOREST, AND BINARY LOGISTIC REGRESSION

The growth of electronic payment usage makes the monetary tension of credit-card deception is changing into major defiance for finance and technology companies. Therefore, pressuring them to continuously advance their fraud detection system is crucial. In this research, we describe fraud detection as a classification issue by comparing three methods. The method used is Linear Discriminant Analysis (LDA), Random Forest, and Binary Logistic Regression. The dataset used is a dataset containing transactions made by credit cards. The challenge in this analysis is that the dataset is highly unbalanced, so SMOTE must perform better on the data. The dataset contains only continuous features that are transformed into Principal Component Scores (PCs). The results show that the binary regression algorithm, the Random Forest algorithm, and the Linear Discriminant Analysis with variables that have SMOTE have AUC values greater than using the original variables. The largest AUC value was obtained by binary logistic regression with 90:10 separation data and Random Forest Algorithm with 60:40 separation data.
BICLUSTERING APPLICATION IN INDONESIAN ECONOMIC AND PANDEMIC VULNERABILITY

Biclustering is an analytical tool to group data from two dimensions simultaneously. The analysis was first introduced by Hartigan (1972) and applied by Cheng and Church (2000) to the gene expression matrix. The Cheng and Church (CC) algorithm is a popular biclustering algorithm and has been widely applied outside the field of biological data in recent years. This algorithm application in economic and Covid-19 pandemic vulnerability cases is exciting and essential to do in order to get an overview of the spatial pattern and characteristics of the bicluster of economic and COVID-19 pandemic vulnerability in Indonesia. This study uses secondary data from some ministries. Forming a bicluster using the CC algorithm requires determining the delta threshold so that several types of delta thresholds are formed to choose the best (optimum) using the evaluation of the average value of mean square residue (MSR) to volume ratios. The similarity of the optimum bi-cluster with the other is also seen based on the Liu and Wang index values. The 0.01 delta threshold is chosen as the optimum threshold because it produces the smallest average value of MSR to volume ratios (0.00032). Based on Liu and Wang Index values, the optimum threshold has a similarity level below 50% with other types of delta thresholds, so the threshold is the best unique threshold. The optimum threshold resulted in six biclusters (six spatial patterns). Most regions in Indonesia (11 provinces) tend to have low economic and COVID-19 pandemic vulnerability in the first spatial pattern characteristic variables.
FLUID FLOW MODELLING WITH FREE SURFACE

Fluid is a substance that can flow in the form of a liquid or a gas. Based on the movement of the fluid is divided into static and dynamic fluids. This study discusses fluid dynamics, namely modelling fluid flow accompanied by a free surface and an obstacle in the fluid flow. Fluid modelling generally makes some basic assumptions into mathematical equations. The assumptions are incompressible, steady-state and irrotational. The steps to obtain a fluid flow model are using Newton’s second law, the law of conservation of mass, and the law of conservation of momentum to obtain the general Navier-Stokes equation, the designing the Euler free surface equation, the Bernoulli equation, then making a free surface representation and linearizing the wave equation so that it is obtained fluid flow model. The resulting mathematical model is a Laplace equation with boundary conditions in the fluid.
NONPARAMETRIK REGRESSION MODEL ESTIMATION WITH THE FOURIER SERIES THE FOURIER SERIES APPROACH AND ITS APPLICATION TO THE ACCUMULATIVE COVID-19 DATA IN INDONESIA

The nonparametric regression model is applied to regression curves for which the regression curve is unknown. Fourier series estimation is an approach in nonparametric regression, which has high flexibility and is able to adjust to the local nature of data effectively. The purpose of the research is to obtain an estimate of the nonparametric regression model with the Fourier series approach with optimal oscillation values and the model suitability of the positive case of Covid-19 in Indonesia. Research on modeling positive cases of Covid-19 in Indonesia using nonparametric regression with the best Fourier series approach is found in the third oscillation by having a minimum GCV of 78969281 with the best model criteria R2 = 97.86% with influencing factors are the percentage of active smokers, the number of health workers, the number of health service facilities, population density and the percentage of the poor population.
Self-Concept of a Younger Pupil Within the Context of His or Her Personality Development

The effectiveness of primary education saturates a numberof pedagogic-psychological variables and predicts various situations, failure to manage which can negatively affect the self-concept process of the pupil. This self-concept of the pupil affects his or her relationshipto school, learning, school success, but above all, it can affect his or her relationship to himself or herself and can be a fundamental determining factor in the process of development of the pupil's personality. In this paper, we present a partial exploratory analysis of the results of the Piers-Harris 2 (PHCSCS-2) questionnaire survey of the self-concept of the school pupils, who attend thefourth year of the elementary school.
MULTILEVEL REGRESSION WITH MAXIMUM LIKELIHOOD AND RESTRICTED MAXIMUM LIKELIHOOD METHOD IN ANALYZING INDONESIAN READING LITERACY SCORES

The multilevel regression model is a development of the linear regression model that can be used to analyze data that has a hierarchical structure. The problem with this data structure is that individuals in the same group tend to have the same characteristics, so the observations at lower levels are not independent. Education research often produces a hierarchical structure, one of which is PISA data, where students as level-1 nested within schools as level-2. In the PISA 2018 survey, reading literacy is the main focus. The data are sourced from the Organisation for Economic Co-operation and Development (OECD). The survey results show that the reading literacy scores of Indonesian students have decreased, thus placing Indonesia at 74th out of 79 countries. However, it is still very rare to research the reading literacy of Indonesian students' using a multilevel regression model. This study aims to apply a multilevel regression model to determine the factors influencing Indonesian reading literacy scores in PISA 2018 survey data. The results of this study indicate that the factors that influence response variable are gender, grade level, mother's education, facilities at home, age at school entry, student discipline behavior at school, and failing grade, while at the school level are the type of school and school location. The magnitude variance of student reading literacy scores can be explained by the explanatory variables the student level is 11,42% and the school level is 60,66%, while the rest is explained by another factor outside the study.
MENINGKATKAN PERAN ORANGTUA DALAM MEMBIMBING ANAK BELAJAR DI RUMAH

In order to provide information that can be used to improve parental assistance to children, the purpose of this study was to determine the extent to which parents help students study at home. Parents have received many complaints about the prolonged absence of their children since the pandemic. This study uses a qualitative descriptive approach and a non-engaged observation method by observing parents' home-based learning assistance activities without telling children that they are being recorded. The second method conducted five-question structured interviews with parent representatives for each grade level (grades 1, 2, 3, 4, 5, and 6). The study shows that the role of parents in educating their children to study at home is irreplaceable. Parents need to motivate, instill confidence and show compassion for their children to overcome the challenges they face in school. This will affect not only the learning process but also the children's self-confidence, problem-solving skills, independence, and emotional stability. The study found that almost all parents are supportive of their children's learning, but they need to learn how to help their children learn so that everyone can learn comfortably.
INVERSE GAUSSIAN REGRESSION MODELING AND ITS APPLICATION IN NEONATAL MORTALITY CASES IN INDONESIA

Inverse Gaussian Regression (IGR) is a suitable model for modeling positively skewed response data, which follows the inverse Gaussian distribution. The IGR model was formed from the Generalized Linear Models (GLM). This study aims to model the IGR with applied to model the factors influencing the infant mortality cases of provinces in Indonesia. Estimation of the IGR model parameters was employed by the Maximum Likelihood Estimation (MLE) and Fisher scoring methods. The Likelihood Ratio Test (LRT) and Wald test were used for hypothesis testing of significance parameters. The IGR model was applied to the infant mortality cases of provinces in Indonesia in 2020. The data for modeling infant mortality cases using IGR were obtained from the Ministry of Health of the Republic of Indonesia and the Central Bureau of Statistics. The result shows that the factors influencing the infant mortality cases of provinces in Indonesia based on the IGR model were: the percentage of pregnant women who received blood-boosting tablets, the percentage of low birth weight, the percentage of complete neonatal visits (KN3), the percentage of toddlers who received early initiation of breastfeeding, the percentage of toddlers who are exclusively breastfeeding, the percentage of toddlers who received complete primary immunization, the percentage of households with access to adequate drinking water, and the percentage of households with access to appropriate sanitation.
Junior Class Preparedness Classification Faces A National Exam Using A C.45 Algorithm With A Particle Swarm Optimization Approach

These studies are counter to a trend of falling students' graduation rates on the national exam. This is because of the way students prepare their readiness to face national tests is inaccurate. On this study the hybrid method c4 algorithm.5 and the swarm particle optimization to produce a class readiness of students with high and accurate accuracy. This research suggests that by using hybridmethodC4.5 andParticle Swarm Optimizationgenerates accuracy as 97.13 %, Precisionas 96,58 %, andRecallas 100 %. Then implemented through a web-based prototype application using programming javascriptlanguage
A Supervised Classifier for Police Reports at the State of Pará, Brazil

This paper describes the development of a supervised classifier constructed upon knowledge extracted from police report public databases, in the years between 2019 and 2021 in the state of Pará, Brazil. The classifier achieved an accuracy of approximately 78% for the prediction of 463 unique labels related to public safety. The resulting model can be used to improve the statistical processes of criminal analysts, both in quantitative and qualitative terms.
Effect of Learning Behavior Style on the Learning of Dental Hygiene Students in Flipped Learning Classes

Objectives: This study was conducted to confirm the difference in learning effect according to the learning behavior style of students in the flipped learning class. Methods: A Self-reported survey was conducted on 50 students of the dental hygiene department in the 3rd year of university located in Cheonan. Data analysis was performed using SAS 9.4 program. Results: The students belonging to the leader type classification showed higher self-direction than the assistant type(p=0.016), and the presenter type showed higher learner confidence and instrument performance confidence than the assistant type(Learning Confidence p=0.027; Periodontal instrumentation Confidence p=0.007). Conclusions: In order to provide effective education for all students during the flipped learning, it is necessary to grasp the learning behavior style in advance and active professor feedback.
A COMPARATIVE ANALYSIS FOR STOCK PRICE PREDICTION USING IMPROVED EXPANSIVE DEEP LSTM MODEL

Due to a lack of clarity and flexibility, prediction leveraging ML models is not well fitted in many sections of commercial decision processes.Proposed model aim to employ deep learning strategy in the stock market pricing area to generate positive risk-adjusted price by analyzing previous transaction data and maintaining greater accuracy with a lower error rate.In this study, the deep learning approach is used, which is capable of handling time-series data.The results are obtained with evaluation of error rate metric MSE & RMSE which express how distant the data points are from the regression line.RMSE measures the dispersion of these residuals.It shows how concentrated the data is on the best fit line.This study compares a unique deep learning methodology with deep LSTM, GA and Harris Hawk optimization.As a part of this analysis results are observed and plotted for the various company stocks dataset, which clearly shows the effectiveness of proposed approach with reduced error rate.