Reviewerly/exHarmony huggingface dataset:
EXPLORING COMPLEX DECISION TREES: UNVEILING DATA PATTERNS AND OPTIMAL PREDICTIVE POWER

This research investigates the development and analysis of decision tree models in the context of classification tasks. Decision tree models were developed without employing pruning or pre-pruning techniques and were tested on relevant datasets. The research findings demonstrate that complex models without pruning achieved the highest level of accuracy in classifying data. This study was inspired by the potential issue of students facing the risk of not completing their studies (dropout), which could lead to a decline in the college's accreditation rating. Therefore, this model was devised to assist in identifying factors that could influence this outcome as a preventative measure. Additionally, we successfully generated clear visualizations of the decision trees, enhancing the understanding of the model's decision-making process. This research provides insights into the adaptability of decision tree models within this specific case and showcases their potential for enhancing decision-making across various contexts. These findings encourage further discussions on the benefits of pruning methods within this specific context and the broader application potential of decision tree models.
Manajemen Pembelajaran Berbasis Android Untuk Peningkatan Mutu Praktik Pemeliharaan Mesin Kendaraan Ringan

The learning process is now progressing very rapidly, especially in the field of technology in the era of the industrial revolution 4.0, therefore there is a need for adaptation to improve learning to use technology such as Diagnostic Trouble Code in vocational high schools whose orientation has a special area of technology expertise. This research uses a qualitative descriptive approach with a case study method. Data collection techniques through observation, interview guidelines and documentation. Based on the results of research conducted regarding Android-based learning using diagnostic trouble code applications implemented in two vocational schools, guided and mentored by teachers who have good competence, it can increase student competence. students can elaborate on the practice of using diagnostic trouble codes easily, this does not require the possibility of opening up opportunities for students to create businesses with independent competitiveness.
Manajemen Pembelajaran Berhitung Angka 1-10 Melalui Media Tikar Bilangan Untuk Meningkatkan Kecerdasan Berpikir Anak Usia Dini

This research aims to get an overview of: planning, organizing, implementing, evaluating, obstacles and solutions in learning to count numbers 1-10. The approach taken is qualitative and the research method is descriptive method. Research techniques use observation, interviews and documentation studies. The results of this research are: the principal and teachers work together to create a numeracy learning program in planning the program to determine the goals to be achieved, selecting materials, methods and media outlined in the RPPH, organizing continues from planning, implementation of learning has gone well despite the results not yet optimal due to various things and obstacles. Learning evaluation is carried out to determine the extent to which children understand learning to count, the teacher has carried out an evaluation/assessment; daily, weekly, monthly and semester. The assessment carried out by the teacher is in the form of observations, recording anecdotes, work results, portfolios, performance. The obstacles are that active children tend to often disturb other children, children do not understand learning activities, learning media are less supportive, learning methods are not varied, human resources are inadequate. low quality, the number of teachers and students is not balanced, the principal and teachers have implemented various solutions by means of children who are active and do not understand the lessons in numeracy being near the teacher, alternating learning media, supervision of the principal, comparative studies, training and workshops on learning, recruiting accompanying teachers to help make learning in the classroom more conducive.
PENERAPAN METODE WATERFALL DALAM PERANCANGAN SISTEM INFORMASI E-LEARNING BERBASIS WEB PADA MADRASAH TSANAWIYAH (MTS) AL-WUSHO RUMAH SETIA RUMAH SETIA

Education is one of the benchmarks for the progress of a nation. One way to advance education is to follow technological developments. And technological developments are currently developing so rapidly, one of the technologies that exist in the world of education today is E-Learning. E-Learning is a form of technological progress that can be utilized effectively and efficiently for the learning process. E-Learning is an education system that uses electronic applications to support the development of teaching and learning activities using internet media. (1) Madrasah Tsanawiyah (MTs) Al-Wusho Rumah Setia is one of the schools in Sukoharjo Regency. At Madrasah Tsanawiyah (MTs) Al-Wusho Rumah Setia the learning process is still traditional, namely the teaching and learning process between teachers and students is only carried out in class meetings and attendance using manual recording. Based on these conditions, an information system is needed that can facilitate the attendance process and can monitor teachers so that they can produce accurate reports. Utilization of information technology today can be used as a solution to overcome these problems. Therefore, as a solution to the problems above, this research provides a solution for making E-learning Information System Design. The National Training and Simulation Association reports that retention of material after learning through e-learning can reach 25-60%, whereas through classical learning it is only around 8-10%.
RANCANG BANGUN APLIKASI RESERVASI HOTEL DEWIZA RESTO &amp; CONVENTION HALL MENGGUNAKAN FRAMEWORK CODEIGNITER

Currently there are still many hotels that do not have a hotel reservation information system. One of them is the Dewiza Hotel &amp; Convention Hall which is a residence located in Banjarsari, Kec. Cipocok Jaya, City of Serang. Dewiza Hotel reservations cannot be made online, they still use a stand-alone based application, meaning that prospective customers must come directly to the hotel to find out room availability, room rates and other facilities owned by the hotel. So that the lack of convenience in the process of booking room services by prospective customers because they cannot see the updated list of rooms, facilities, and their prices. For this reason, a solution is needed so that hotel reservation services can be done online, so that customers can enjoy room booking services and facilities through their gadgets without having to come to the hotel. The methodology used for system development is the ADDIE method using the PHP programming language. This study aims to produce a website that can be accessed online by hotel customers. This website can make it easier for prospective customers to be able to see a list of rooms and room facilities through a website. Prospective customers can make room reservations and see the status of hotel availability, which is always updated by hotel operators.
SENTIMENT ANALYSIS OF SERVICE PROVIDER ON TWITTER TWEET USING NAIVE BAYES CLASSIFIER WITH PHP

This study aimed to analyze the sentiments of Twitter users towards internet services provided by Indosat, Ooredoo and XL Axiata in Indonesia. Twitter Tweet data is taken using the Twitter API and processed using the PHP programming language. The classification process uses the Naïve Bayes Classifier algorithm to group positive, negative, and neutral categories. The calculation results show that negative sentiment towards Indosat Ooredoo services scores 56%, while sentiment towards XL Axiata services negatively scores 50%. The accuracy of the sentiment analysis system using PHP reaches 78% based on comparison with manual classification results. This research provides benefits in the form of information about user sentiment towards cellular internet service providers, so that each provider can improve and optimize internet services based on this data. &#x0D; Keywords: twitter, sentiment analysis, naïve bayes, php
THE IMPLEMENTATION OF ENGLISH LESSON MATERIAL SOURCE FROM THE RUMAH BELAJAR PORTAL IN TEACHING ENGLISH

Knowledge of English is very important nowadays. in the world of education, a teacher must be creative in choosing teaching materials. Therefore, this must be supported by the skills of the teacher and the suitability of the media in teaching. The purpose of this research is to find out whether the use of the learning house application can make it easier for teachers and increase students' interest. Rumah Belajar portal is a medium that can help teachers and students in the teaching and learning processThe data collection technique in this study is the process of collecting and processing information to evaluate results and use them for research. The research sample consisted of 20 students from eight grade. The results of the analysis The application of English learning material sources from the Rumah Belajar portal is very helpful for teachers in teaching English at SMP Satap 8 Baraka. This can be seen from the results of observations and interviews. The observation results show that teachers are successful in their performance to present their material, have a good influence on influencing students to follow their instructions, create good communication during sharing time, and make the class active. In addition, the results of the interviews showed that the teacher gave positive comments on the implementation of English subject matter sourced from The Rumah Belajar portal.
THE INFLUENCE OF DIGITAL LITERACY ON STUDENT LEARNING

This study aims to determine the influence of digital literacy on the learning outcomes of students of the Educational Technology study program at the Indonesian Christian University of Toraja. Research is a quantitative research type of experiment. This research was conducted at the Indonesian Christian University of Toraja Education Technology Study Program. The sample of this study is all Educational Technology students class of 2021 consisting of 49 students. The total number of samples used was 49 students, using non-random sampling techniques. The results of this study used descriptive analysis and inferential analysis using SPSS 22. The results obtained in this study that in the use of digital literacy of students in producing learning is very releva. From the results of this research, it can be stated that it is significant for student learning outcomes.
Student’s Engagement in English Classroom with Hybrid Learning Environment at Metro Junior High School Makassar

The research aims to describe (1) how the hybrid learning environment influences students' engagement in learning English, (2) how students perceive the difference in their engagement between an online class and a hybrid class, and (3) the factors and challenges that students perceive in the hybrid learning environment that influence their engagement compared to an online-only class. This research was conducted at Metro Junior High School in Makassar. The method used in this study is autoethnography as a qualitative research design. A cluster random sampling technique was used to gain a sample, which included nineteen students and an English teacher who had attended both online-only and hybrid classes. The researcher's instruments included interview guidelines, observation, and documentation. The data analysis technique used was thematic analysis. The results show that (1) the hybrid learning environment positively influenced students' engagement in learning English, (2) students perceived noticeable differences in their engagement between an online class and a hybrid class, and (3) several factors and challenges in the hybrid learning environment influenced students' engagement compared to an online-only class.
Stunting Early Warning Application Using KNN Machine Learning Method

Stunting in toddlers is defined as a condition of failure to thrive due to chronic malnutrition in the long term. The problem of stunting in Indonesia is an issue that is still a concern for the Indonesian government. The prevalence of stunting in Indonesia is still relatively high, coupled with the COVID-19 pandemic, which has impacted the economic sector. For this reason, research on stunting is still a critical topic. This study aims to classify toddler stunting using the k-Nearest Neighbor classification algorithm and build a website-based early detection application for toddler stunting cases. The research results using the k-Nearest Neighbor Algorithm trial obtained a relatively high accuracy of 92.45%. Implementing an early detection system for stunting cases has proven to help health workers classify toddlers as stunted or not. This application is also helpful as an archive and facilitates data reporting. The application has eight main menus: the Puskesmas data menu, Posyandu data, toddler data, weighing, weighing results, development menu, and stunting early warning menu, which contains malnourished and stunted toddlers.
A Study on Enhanced Spatial Clustering Using Ensemble Dbscan and Umap to Map Fire Zone in Greater Jakarta, Indonesia

This research investigated ensemble clustering algorithms and dimensionality reduction for fire zone mapping, specifically DBSCAN + UMAP. We evaluated six clustering methods: DBSCAN, ensemble DBSCAN, DBSCAN + UMAP, ensemble DBSCAN + UMAP, HDBSCAN and Gaussian Mixture Model (GMM). We evaluated our results based on the Silhouette Score and the Davies-Bouldin (DB) index, emphasizing handling irregular cluster shapes, smaller clusters and resolving incompact clusters. Our findings suggested that ensemble DBSCAN + UMAP outperformed five other methods with zero noise clusters indicating clustering results are resistant to outliers, leading to a clearer identification of fire-prone areas, a high Silhouette Score of 0.971, indicating accurate cluster separation of distinct areas of potential fire hazards and an exceptionally low DB Index of 0.05 that indicates compact clusters to identify well-defined and geographically concentrated areas prone to fire hazards. Our findings contribute to the advanced techniques for minimizing the impacts of fires and improving fire hazard assessments in Indonesia.
Application Mobile-Based Augmented Reality for Endemic Animals of Central Kalimantan

The existence of endemic animals typical of Central Kalimantan, such as orangutans and hornbills, is included in the protected species situation because the population numbers have increased slightly along with the clearing of land for the plantation sector, making orangutan and hornbill areas that should be beautiful and natural disappear. Because of this, a medium for conveying information and a unique introduction to the public is needed to know how important it is to know and know the various endangered species in Central Kalimantan to preserve animals. Therefore, this research aims to create an application for Central Kalimantan endemic animals using Mobile-based Augmented Reality to introduce Central Kalimantan's rare animals, starting from the area of residence, characteristics, leading food, and information about animal habitats. The application development process uses the Markerless Augmented Reality (AR) method, which displays 3D objects without using unique markers such as photos or images. The application development stage includes the planning, design, data collection, 3D object creation, application development and application testing using Blackbox testing with the Text Case method, which produces application testing descriptively explaining the application work process. The application for displaying 3D objects was tested in 5 trials, with an average of 5 seconds, and the marker appeared to display 3D objects. This application can have an impact on progress in the field of informatics as a medium for delivering information and learning media using Augmented Reality Markerless.
Extreme Programming Method for Integrated Service System Website Development in Rejosari Village

The Rejosari Village Hall provides a manual letter submission service which is sometimes problematic, including when residents are about to submit an application letter, they have to come directly to the village hall office while the residents are still out of town. Apart from that, there was no media information which resulted when they were going to submit the requirements for the letters they brought were not in accordance, then from the data collection, and the letters were still in the books. Therefore we need a service system for the submission of letters. This integrated service system for residents of Rejosari Village is a web-based information system, the use of technology in the form of a website makes it easier to receive all forms of existing information. The Extreme Programming (XP) method is applied in developing this system, a software engineering process that refers to an object-oriented approach. The stages of this method start from the planning, design, coding and testing stages using black box testing with descriptive analysis techniques, which produce tests in the form of a proportion value of 96.42% and have a possible interpretation. In addition, this system can impact progress in the field of informatics in the form of information media as well as learning materials.
Website Evaluation of The Faculty of Industrial Technology Universitas Islam Indonesia Using the System Usability Scale Method

To maintain and improve the quality of the website of the Faculty of Industrial Technology (FTI), Universitas Islam Indonesia (UII), usability testing is performed on the website using the System Usability Scale (SUS). This study aims to evaluate usability and analyze the user experience on the FTI UII website so that the faculty can follow up on it. Respondents consisted of 41 active FTI UII students. Respondents were asked to complete scenarios on the FTI website while being watched by examiners. They then filled out the SUS questionnaire with ten statements and a Likert scale for answers. Using the SUS method, the test scores were 69.32. Based on these results, the acceptability of the FTI web is in the MARGINAL HIGH range, the adjective rating is at an OK level close to GOOD, the grade scale is in class C, and the Net Promoter Score (NPS) could be passive on website users. Based on these results, it can be concluded that the usability of the FTI UII website is acceptable to users but has not yet attained a maximum score; therefore, a user has not yet recommended the site to other users. This confirms that the FTI website requires additional enhancements.
Latent Dirichlet Allocation for Uncovering Fraud Cases on Twitter

Fraud is a phenomenon that continues to exist in society with a modus operandi that continues to evolve with the times. The mode of operation of fraud is continually evolving with technological advancements, globalization, and consumer behavior shifts. In today's digital age, social media is important in spreading information regarding fraud. Twitter is a social media platform that is widely used. Twitter provides easy and fast access to relevant information. As a result, to raise fraud awareness, it is critical to study the mode of operation of fraud spread on social media, particularly on Twitter. The Latent Dirichlet Allocation (LDA) approach is used in this work to classify and identify fraud issues often addressed by Indonesian Twitter users. By applying LDA modeling, this study aims to understand more comprehensively the fraudulent topics that often appear on Twitter. The research found that seven fraud topics are most commonly discussed by Twitter users in Indonesia, with the highest cohesion value of 0.491899.
Covid-19 Social Aid Admission Selection Using Simple Additive Weighting Method as Decision Support

The process of receiving Covid-19 social assistance to residents who are recorded as social aid recipients in the RT.07 RW.10 Kp. Sukapura Jaya area is still uneven. The second problem is that there is no particular mathematical calculation to determine the value of the weight of the criteria, especially for residents who are recorded as receiving Covid-19 social aid in the RT.007 RW.10 Kp. Sukapura Jaya area. The gradual decline in social aid programs so that the number that falls does not match the data of social aid recipients. This caused a polemic for RT administrators in distributing social aid programs. The decline in social aid programs does not match the number of citizens recorded. It overcomes citizens who cause social jealousy—analyzing the problems experienced by the RT management in the distribution of Covid-19 social assistance, especially the RT.07 RW.10 Kp. Sukapura Jaya area to residents who are recorded as recipients. Selecting Covid-19 social assistance recipients, especially in the RT.07 RW.10 Kp. Sukapura Jaya area. So the application of methods as decision support is needed, and it is needed to help determine the weight of particular criteria for citizens who are recorded as more in need. This study proposes a decision support method using the Simple Additive Weighting (SAW) method, which is expected to help decision-making in solving problems for selecting Covid-19 social aid recipients in the RT.07 RW.10 Kp. Sukapura Jaya community. The purpose of the study is to select residents who are recorded to receive social aid who are more in need first will get Covid-19 social aid.
Comparison of KNN and SVM Algorithms in Facial Image Recognition Using Haar Wavelet Feature Extraction

To process all the pixels in the face image, feature extraction can be performed using the Haar Wavelet method so that it processes identifiers with lower dimensions. However, a classification algorithm must separate the distance between classes with minimal data to classify low-dimensional facial images. KNN and SVM algorithms are classifiers that can be used for facial image recognition. When classifying images, SVM creates a hyperplane, divides the input space between classes and classifies based on which side of the hyperplane the unclassified object is placed when it is placed in the input space. KNN uses a voting system to determine which class an unclassified object belongs to, taking into account the nearest neighbor class in the decision space. When classifying, KNN will generally classify accurately, resulting in some minor misclassifications that plagued the final classified image. This study aims to compare the two algorithms on image identifiers with low dimensions resulting from haar wavelet extraction. The research results obtained are facial image classification using the haar wavelet extraction method using the SVM algorithm to obtain an accuracy of 98.8%. Whereas when using the KNN algorithm, the accuracy obtained is 96.6%. The results of this study show that the SVM algorithm produces better accuracy in facial image recognition using haar wavelet feature extraction compared to the KNN algorithm. The SVM algorithm can recognize facial images even though it uses image training data with various face poses and sizes, resulting in higher accuracy.