Reviewerly/exHarmony huggingface dataset:
Task Based Learning as an Active Retrieval Approach in the Perception of EFL Students: A Case Study at Bridge Education Manado

This study set out to find out how participants at The Bridge Education Manado felt about task-based learning (TBL) as a teaching strategy. The poll findings showed that participants generally agreed, highlighting their favorable opinions of TBL's efficiency in fostering student-centered and interesting language learning experiences that promotes a laid-back learning environment where learners' needs and interests are engaged. They acknowledged how language skills were included into TBL, highlighting how well it covered lesson retrieval and made it easier to remember earlier classes and resources as well as to improve language learning experiences and valued their significance and relevance to the actual world. These favorable opinions highlight the usefulness of TBL as a method of instruction that adheres to the fundamentals of communicative language learning and promotes successful language learning outcomes. It is clear from the survey results that TBL is well-liked by students at The Bridge Education Manado. These findings have effects on how the institution teaches languages. First and foremost, it is essential to keep supporting TBL as a pedagogical strategy and to offer ongoing assistance and chances for professional growth to teachers so they can use TBL techniques in the classroom. They would better comprehend TBL ideas, techniques, and material production as a result of this. Collaboration among educators can also encourage the sharing of creative TBL implementation ideas and best practices. Additionally, getting regular input from students can help to enhance TBL practices and better inform instructional design
Automated Assessment System Using Machine Learning Libraries

Assessment and the grading of students is a task that has been done for as long as school has existed. This was previously done by teachers in primary and secondary, lecturers for institutions like JAMB and lecturers in schools. Up until now students’ marks were influenced by other external factors such as bad handwriting, lengthy paragraphs, roundabout way of speaking rather than going straight to the point and the sheer number of assignments the lecturer has to mark. This has resulted in students getting lower or higher marks than they should be awarded. This project is to create an ML (Machine Learning) powered assessment system that will take the assignment questions and the marking scheme and award the student the marks similar to what the ideal lecturer would have given. This will also reduce the time the lecturers spend on marking and ensure the students get their results on time. This project will be made with Python and machine learning and will be tested with a number of potential answers to the questions and their grading’s. This will enable system to be able to grade assignments as soon as they are uploaded. This research will be limited by the fact that the system can only handle the marking of short sentences accurately and not long paragraphs. The system is also limited by the fact that it can only mark with the aid of the marking scheme and not without it so it is not a truly intelligent model in that regard. The research showed that the system is indeed capable of obtaining the similarity between two paragraphed answers provided but it needs extras to produce the most accurate results.
Sistem Pendukung Keputusan Rekomendasi Pembelian Perumahan Menerapkan Metode MOORA

Housing is a secondary need. For the selection of the right housing, it must be adjusted to the wishes of consumers. When selecting housing or determining where to live, consumers must look for brochures and visit housing sales sites, and do not choose housing at random just because friends or other people offer it, because this can cause regret because it is not in accordance with which are desired. To assist prospective buyers in making housing buying decisions, we need a decision support system that will assist prospective buyers in choosing the desired housing. In order to get the best results, we need a system that can help determine the house in such a way that consumers are satisfied. Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) is a method provided by SPK to facilitate housing selection because this method has good selectivity in determining different goals and criteria. After carrying out the calculations of the MOORA method, the final result is obtained which shows that the alternative with the highest Yi value is A1 with a Yi value of 0.282. In the second rank, there is alternative A2 with a Yi value of 0.277, while the third rank is occupied by alternative A5 with a Yi value of 0.263. Therefore, based on predetermined criteria, alternative house A1 can be considered as the best option.
Pengontrolan Robot Bulu Tangkis menggunakan Mikrokontroller ATmega128 berbasis Android Mobile

In Indonesia, badminton was one of the most popular sport in various circles. Along with the times, robots can be designed as a device that can be used to play badminton. Robominton was badminton robot which is operated manually by human using a remote control or fully automatic. For a robot that controlled by manual-based, bluetooth or cable connection using joystick was used. This refers to the rules that have been set by DIKTI in “Robot Abu Indonesia (KRAI) 2015” Contest. As for the robot control system that we develop, are robotic system with manual control using android as a transmitter and bluetooth module HC-05 as a receiver. There is a robotic navigation control systems, transmission control systems shuttlecock, shuttlecock and servicing of control systems. ATmega 128 processor, four DC motors, with the EMS driver 30A H-Bridges was used as a hardware on shuttlecock transmission syste,. For shuttlecock services, self-designed pneumatic driver with solenoid valve was used. From the test results, the robot was able to navigate premises 11 formation movement, five pieces of shuttlecock transmission, and can serve up and down with a pneumatic
Analisis Sentimen Wisatawan terhadap Taman Nasional Bunaken dan Top 10 Hotel Rekomendasi Tripadvisor Menggunakan Algoritma SVM dan DT berbasis CRISP-DM

It is necessary to analyze traveler sentiment towards Bunaken National Park and Tripadvisor's Top 10 Recommended Hotels to identify traveler satisfaction with the attractions, accommodation services, and transportation used. Considering this, this study uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework by testing the performance of the Decision Tree (DT) algorithm and the Support Vector Machine (SVM). CRISP-DM has six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Based on the processing of 398 Bunaken National Park destination data and 1793 review data on the top 10 hotels recommended by Tripadvisor, the SVM algorithm performed better. In the context of Bunaken National Park destination data, the performance of the SVM algorithm using the SMOTE operator can produce 100% accuracy, precision, recall, f-measure, AUC, and t-Test values. In addition, in processing the top 10 hotel datasets recommended by Tripadvisor, the SVM algorithm using the SMOTE operator provides an accuracy value of 96.42%, a precision value of 100%, a recall value of 92.83%, an f-measure value of 96.27%, an AUC value of 100%, and a t-Test value of 96.4%. The results of identifying the five words that most often appear in tourist reviews for Bunaken Marine Park tourist destinations are 164 words fish, 165 words island, 193-word dive, 230 diving, and 280 words Bunaken. This indicates the driving factor for tourist visits to Bunaken Marine Park is the beauty of underwater nature, including the diversity of marine animal species, the natural beauty of the archipelago, and diving activities. In addition, the results of identifying the five words that most often appear in traveler reviews for Tripadvisor's top 10 recommended hotels are 1170 great words, 1222 bunaken words, 1550 resort words, 1613 diving words, and 1711 dive words. This indicates that the characteristics of tourists who have the motive of traveling to Bunaken National Tourism Park have the intention to use resort accommodations around Bunaken and have mobility and facilities to support diving activities. Thus, the output of this study can be used as a recommendation for accommodation service managers to prepare supporting facilities for tourists who want to visit Bunaken National Park.
Clustering Content Types and User Roles Based on Tweet Text Using K-Medoids Partitioning Based

In this modern era, the spread of information occurs rapidly through social media. One of the channels for disseminating information is through the Twitter platform. Many Twitter users respond to existing content with positive, negative and neutral responses. One of the hot content to respond to is political content. This content is currently being discussed considering the approaching election of the 2024 Presidential Candidate of the Republic of Indonesia. One of the candidate pairs discussed was Anies Baswedan. With so many responses from Twitter users, it will be difficult to track whether users support Anies Baswedan to run as a presidential candidate due to the large number of responses. This study aims to determine the response of twitter users to the advancement of Anies Baswedan as a presidential candidate. The method used in this study is the K-Medoids Partitioning-Based algorithm based on twitter user text. This algorithm was chosen because it is easy to implement considering the basis of K-Medoids development is the K-Means algorithm but the K-Medoids algorithm can overcome the shortcomings of the K-Means algorithm which is sensitive to outliners. The evaluation will be done using Silhouette Score which produces a value of 0.35 with the number of clusters is 2. Then an analysis of each cluster is carried out by looking at the words in the cluster. As a result, from the two clusters formed, both clusters contain positive content and show that Twitter users support Anies Baswedan to run as a 2024 presidential candidate.
Comparative Analysis of Prediction Results of Decision Support Systems Simple Additive Weighting Method with Preference Selection Index in Determining Scholarship Recipients

Educational Assistance needs to be a concern because currently the majority of students have the potential and ability but are constrained financially so this needs to be taken seriously by the government, currently, the government through the Ministry of Education has been trying to provide financial assistance in the form of scholarships including achievement improvement scholarships academic. Currently, to get a scholarship, each university certainly gets a limited quota. This is done to provide equal distribution of educational assistance, due to the large difference between the quota obtained and students who need assistance, so it is necessary to provide eligibility selection for students who are entitled to get scholarships. This study took sample data from the 2023 even semester scholarship list at Manado State University, especially in the Informatics Engineering Study Program, then normalized the data to use the SAW and PSI methods. After normalization, calculations were carried out using the SAW and PSI methods. predictions from the two methods will then be tested for the level of accuracy using the confusion matrix method. The result is that the SAW method has an accuracy rate of 98.13% and then the PSI accuracy rate is 97.24% based on the results of the prediction accuracy, the SAW method has a higher accuracy rate than PSI.
2024 Presidential Election Sentiment Analysis in News Media Using Support Vector Machine

The 2024 presidential election is an event for all Indonesian people to determine their best leader. The presidential and vice presidential candidates are also competing to give their best efforts so that they can be elected as President and Vice President. The news media also provide news related to the 2024 presidential election with various titles that can interest their readers. Not infrequently the titles raised contain words that have sentiments, both positive and negative. In order to facilitate the analysis of the sentiments of these news titles, it is necessary to build a system that can detect the sentiments of these titles. In this study, we built a sentiment analysis system using the Support Vector Machine (SVM) method on news headline data obtained from online news media to detect whether news headlines contain positive or negative sentiments. For feature exctraction we compare the effect of FastText word embedding with TF-IDF for feature extraction. In the SVM method, several experiments were carried out on the attributes of C, kernel, gamma, and the ratio of the test data. The results obtained are a FastText can outperform TF-IDF for feature extraction. Also, combination of Kernel, C, and gamma values that give the best accuracy score of rbf, 1, and auto respectively at a test data ratio of 90:10, with an accuracy score of 99%.
PENGEMBANGAN DUSUN TULAUN MINAHASA SEBAGAI DESA WISATA

The background issue of the Student Community Service Creativity Program (PKM-PM) activity in the village of Tulaun is the underdevelopment of this village as a tourist destination despite its abundant tourism potential. The objective of this community service activities is to provide a solution to the challenges faced by partners in developing the tourist village through the construction of supporting facilities, namely independent energy gazebos. The following are the approach strategies implemented in various stages, including: (1) Survey stage (2) Design planning stage (3) Gazebo material procurement stage (4) Gazebo construction stage (5) Independent energy gazebo facility installation stage. The result of the PKM activity is the introduction and installation of a solar-powered lighting system developed using a 50 WP solar panel capacity. A battery with a total capacity of 10 AH is used to store the generated electrical energy and as a source of energy for supplying power to the independent energy gazebo lighting. The implementation result of the PKM activity includes the enhancement of the Tulaun tourist village facilities in Minahasa and the promotion of renewable energy usage in the village
Implementasi Algoritma A* (A-Star) dan Greedy Dalam Penentuan Routing Pada Wide Area Network (WAN)

The continuous development of the internet has led to changes in routing complexity. In the context of a wide area network (WAN), network flow optimization becomes a major issue in the selection of the fastest route, which involves routing protocols. Algorithms in routing protocols are designed to determine the shortest path. Therefore, studies are needed regarding how to build a routing algorithm that can be used to get the shortest path in each process. This study aims to reduce network workload and compare the computation involved in determining the shortest path using the Greedy algorithm and the A* algorithm. The simulation results show that the A* algorithm is superior to greedy. The measurement results show that the final cost of the Greedy algorithm is 44 and the A* algorithm is 38. Taking into account the heuristic value for each node, the A* algorithm is superior to the Greedy algorithm in determining the shortest path.
Quality Assurance of Academic Websites using Performance Testing Tools

Academic websites play a crucial role in supporting learning activities and academic growth in the digital age. These websites are created and maintained by academic institutions to provide resources, services, and information to the academic community. Academic websites aim to promote the institution, facilitate communication, and disseminate educational content. However, as these websites develop in complexity and draw more visitors, it is crucial to guarantee their efficient operation and satisfying user experience. For academic websites to operate and be reliable, top-notch software development and thorough software testing are required. The performance testing of academic websites using Apache JMeter and the Web Server Stress Tool is the main topic of this study. This study's conclusions are intended to improve software quality and performance for academic website managers and developers. Gathering data, establishing the test environment, planning and creating the test, carrying it out, and evaluating the system in light of the test results are all steps in the performance testing process. The website operates well under heavy traffic, according to the findings of the performance testing done with Apache JMeter. However, the Web Server Stress Tool shows that the website's performance is insufficient under significant user loads. This test gives information about the website's functionality and any potential problems, which can then be used to determine whether speed improvements are required.
Sistem Pendukung Keputusan Menentukan Aplikasi Chat Terbaik Menggunakan Metode OCRA Dengan Pembobotan ROC

In this study, a study was conducted to determine the Best Chat Application, the more we enter the digital era, the more applications and communication media or sending messages that appear. So researchers want to do research to determine which chat application is the best that people can use and unfortunately it is suitable for use today, then a system is applied that can help to decide, namely a Decision Support System (DSS) which can simplify the process of selecting the Best Chat Application by implementing 5 criteria i.e. Security, Number of Downloads, Reviews, Features, Storage. So we need a system that can make decisions by using SPK that applies the ROC and Operational Comprtitiveness Rating Analysis(OCRA) methods in getting the weighting value for each criterion and preference value from the best alternative, namely alternative A¬1 with the name Whatsapp Application with a preference value of 128,3123
Sistem Pakar Deteksi Covid-19 Dengan Lie Detection Menggunakan Metode Circle Hough Transform

The number of health workers infected with Covid-19 in Indonesia continues to grow amid the coronavirus pandemic. Not only doctors, nurses and other medical support staff have been exposed to Covid-19. To date, IDI has recorded more than 180 health workers who have died from Corona. Health workers are dying because of a lack of Personal Protective Equipment (PPE) and fatigue. Prevention of direct contact between asymptomatic patients and health workers is a way to prevent health workers from contracting COVID-19. An expert system for diagnosing COVID-19 with lie detection is proposed to be used for patients who wish to seek treatment at a health center before they meet face-to-face with health workers. Several previous studies have proven that the certainty method can be used to diagnose COVID-19 with an accuracy of up to 90%, provided that the patient answers questions honestly. In this study, control questions and pupil detection were added using the circle hard transform to find out whether patients who wanted treatment did not lie when answering questions about symptoms of exposure to Covid, travel history and family history of exposure to Covid. The combination of an expert system and lie detection is expected to be the first protective alternative for health workers from asymptomatic patients. Based on the results of the application testing carried out, it can be seen that the movement of the patient's pupils when answering questions.
The Development of an Interactive Science Literacy Model Based on Folk Stories for Chinese Children Using Dialogic Reading Techniques

This research was conducted to analyze the needs of the Interactive Science Literacy Model based on Chinese children's folktales using dialog reading techniques among preschool students. This study uses a design and development research (DDR) approach. The data analysis technique used in this study is qualitative and quantitative data analysis. The research respondents for phase one were qualitative, consisting of 9 teachers from Chinese preschool and data for quantitative consisting 89 teachers from Chinese preschool. This study uses document analysis instruments, interview protocols and questionnaire. The research objective for this study is to analyze the needs of an Interactive Model of Science Literacy based on Chinese children's folktales using dialogic reading techniques among Chinese preschool students. Atlas. t.i version 4.1 software is used for analyzing interview transcriptions, developing themes, categories and subcategories and SPSS version 22 software is used for analyzing questionnaire. The researcher has analyzed content validity and reliability on the interview protocol instrument and questionnaire using Cohen's kappa index. For questionnaire, two of the three experts showed a kappa value of 1.0 and it shows a very good interpretation. An expert has given a kappa value of 0.96 and the interpretation is also very good. Next, for interview protocol, the kappa value after being assessed by experts are two of the three experts showed a kappa value of 1.0 and it also shows a very good interpretation. The results of need analysis show that Chinese preschool teachers give a positive response and really need a Science Literacy model to help and support them in teaching. One of recommendations for the development of the model when teachers and students will switch roles while reading using this dialogic reading technique so that children can learn to be storytellers with the assistance of adults who act as active listeners and questioners.
Resource Description Framework Query Languages : Comparative Study

Over the period of time, the data on the web grows by leaps and bounds that becomes unmanageable to store and retrieve. As a result, the concept of semantic web comes into existence. Nowadays, various components of semantic web stack become mature such as Resource Description Framework (RDF). Due to the higher adoption rate of RDF in both industry and academia, it becomes crucial to design such systems that can store and retrieve RDF formatted data. Since last decade, various query languages for RDF data retrieval were proposed mainly based on either graph query language or on relational algebra. However, none of them become mature enough that can overcome majority of challenges. Therefore, there is an utmost need for the comparative study of available languages in literature. In this paper, a comparative study based on various parameters was conducted that provides a better insight about the literature.
Penerapan Algoritma Naïve Bayes Classifier Dalam Klasifikasi Status Gizi Balita dengan Pengujian K-Fold Cross Validation

Nutritional status is a condition related to nutrition that can be measured and is the result of a balance between nutritional needs in the body and nutritional intake from food. In Indonesia, there are still many nutritional problems such as malnutrition and other nutritional problems. This research will use the Naïve Bayes Classifier algorithm with K-Fold Cross Validation testing. The data used is data on the nutritional status of toddlers in August 2022 at the Rambah Samo I Health Center. Attributes in this study include Gender, Birth Weight, Birth Height, Age at Measurement, Weight, Height, ZS BB/U, BB/U, ZS TB/U, and TB/U. Determination of the nutritional status of toddlers in this study was based on the BB/TB index which consisted of 6 classes, namely severely wasted, wasted, normal, possible risk of overweight, overweight, and obese. From the research conducted, it was found that the Naïve Bayes Classifier algorithm with K-Fold Cross Validation can correctly classify the nutritional status of toddlers. From data processing using 10-Fold Cross Validation on the Naïve Bayes Classifier algorithm, it is known that the highest accuracy value is 82.94% in the 5th iteration, while the lowest accuracy value is 65.88% in 6th iteration. With an average overall accuracy value of 75.47%. Meanwhile, the average precision value obtained is 81.36% and the average recall value is 75.47%.