Reviewerly/exHarmony huggingface dataset:
USING FACEBOOK TO PROMOTE STUDENTS’ ENGAGEMENT IN LEARNING ENGLISH

Learning English as a foreign language in Indonesia is not easy for many students, not only junior and senior high school students but also college/university students. It often makes them unable to be active in the teaching and learning process and have low motivation and false attitudes toward learning English. As a result, they would get low achievement in English. Considering the case, teachers need to think of ways to make students enjoy learning English both inside and outside the classroom. This study aims at elaborating on Facebook as one of the online social media that can be used to attract students’ active engagement in English teaching and learning process. This study employed a literature research methodology (Lin, 2009; vom Brocke et al., 2009) by using qualitative analysis. The findings showed that Facebook, which most people, especially in Indonesia, usually use it only for fun, can also be used as a medium to get students involved in the teaching and learning process. By using Facebook, students are able to participate in learning English whenever and wherever they are. Besides, teachers can monitor, facilitate, and evaluate students' participation by commenting on the student's responses in unlimited space and time. Based on some research findings, Facebook can be used to enhance learning. Finally, Facebook has many benefits for students if it is used and managed well.
Classification and Localization of Arabic Handwritten Text in KHATT Dataset Based on Faster R-CNN

Arabic handwriting recognition is an important research area in computer vision. Due to the complexity of the Arabic script, this is an arduous task. Several approaches have been proposed to address this challenge, including deep learning algorithms. Despite their efficiency, these approaches present some limitations such as the use of lexicon-driven models, the need of a lot of data for training and the huge computational cost. We propose, in this paper, two novel models based on the robust Faster Region-Convolution Neural Network (Faster R-CNN) to recognize Arabic handwritten sentences. The Faster R-CNN is commonly used to detect objects in images and depends on region proposal algorithms. These models use the pre-trained VGG 16 and ResNet50. Moreover, they use a soft non-maximum suppression strategy (Soft-NMS) in the post-processing stage instead of the traditional NMS to increase the detection rate of overlapping items. The models will be trained independently to identify words in the text lines and tested using sentences from the (KFUPM Handwritten Arabic TexT) KHATT dataset. It will be shown that the faster R-CNN models allow greater accuracy and effectiveness in handwriting recognition. They achieve accuracy rates of 99% and 98% for the two networks, VGG16 and ResNet50, respectively
Improving Students’ Mastery of Simple Past Tense By using Real – Life Context Learning Model at Harapan Mandiri Senior High School Medan

Community service is a form of contribution carried out by individuals or groups to enhance well-being and provide positive benefits to the community at large. This activity is undertaken with the aim of assisting, empowering, and offering solutions to various problems or needs faced by the community. This program was inspired from the writers’ desire to improve the students’ understanding and mastery on Simple Past Tense at Senior High School of Harapan Mandiri School Medan in the third grade XII IPA IV in which the students consisting of 36 students. This program was conducted during one week on August 2023. This activity implements real-life context learning model in improving the students’ understanding and mastery on simple past tenses. This program runs successfully and as it was expected. The students undergo the progress after the program conducted, for instance, the students are able to write the composition using simple past tense with theme such as last holiday or past experiences, they also are able to use the simple past tense to be, modals and verbs in speaking. The Real-Life Context learning model has had a significant impact on education like conducted in Senior High School of Harapan Mandiri Medan, as it has contributed to increased student engagement, motivation, and preparedness for getting learning success especially English. &#x0D; Key words: Simple Past Tense; Real-Life Context Learning Model
DRAINAGE SYSTEM EVALUATION OF BANK INDONESIA HOUSING PANCORAN, JAKARTA

The Bank Indonesia housing complex located in Pancoran, South Jakarta has a lower topography than the surrounding area and due to the continued reduction in green open space, this can cause inundation as high as 10 cm – 60 cm which occurs on Jl.Rasamala Raya which is a main road. main access to the Bank Indonesia Complex. To overcome the problem of inundation, it is necessary to analyze the drainage system to determine the causes of inundation. Research requires data in the form of drainage systems, rainfall, existing canal dimensions and existing longitudinal storage capacity. Based on the calculation results, there are 7 channels that do not accommodate the planned 2-year flood discharge, namely 4 channels in the Bank Indonesia Complex area and 3 channels outside the Bank Indonesia Complex area, so 2 alternatives are implemented to overcome these problems, the first is to changes in channel dimensions and the second is the implementation of ecodrainage in the form of infiltration wells in the canal located in the Bank Indonesia complex. From the research results it is known that alternative 1 causes the total volume of water entering the long storage is increase from 3011 m3 in the existing conditions to 3030 m3. If implementing alternative 2, the inundation in the channel on Jl.Rasamala Raya can be overcome and the total volume of water entering the long storage has decreased from 3011 m3 in the existing conditions to 2940 m3
Improving students’ ability in reading comprehension by using herringbone technique

The goal of this research is to find out if herringbone technique significantly affects to the tenth-grade students in comprehending recount text at SMA Swasta Kampus Nommensen Pematangsiantar. This research is quantitative research with quasi experimental research design. The sample of for this research is taken from two classes namely experimental class (X-3) consist of 30 students that used herringbone technique and control class (X-2) consist of 30 students that used conventional technique selected by purposive sampling. The instruments for collecting data is reading comprehension test. The test is divided into two parts, namely the pre-test and the post-test, which are given to each sample. The researcher finds the total mean score of post-test in experimental group is 79,45 and the total mean score post-test in the control group is 72,22. After calculating the data from all points, the t-test score is 2,120. Then, the researcher consulted the value on the t-table, which has a significance of 5% and the value is 1,672. Therefore, the researcher finds that t-test is higher than the t-table (2,120 &gt; 1,672). It can be concluded that Ha ­is accepted while Ho is rejected. The use of Herringbone Technique is significantly affect to the tenth-grade students in comprehending recount text at SMA Swasta Kampus Nommensen Pematangsiantar. Herringbone technique helps students to improve reading comprehension in developing main idea and finding detail information from the text.
Information System Analysis of the Process of Opening a Savings Account at Bank "XYZ" Using the Cobit 4.1 Framework

Effective money storage and easy access system through the bank. The system used at Bank "XYZ" is still experiencing problems in the opening process. When customer service inputs prospective customer data, the input process exceeds the time specified by the system, the process will stop and return to the login display. Based on these problems, an information system audit is needed regarding the maturity level of Bank "XYZ"'s information system. The aim of this research is to determine the maturity level of the process of evaluating and maintaining ICT performance in information systems. This research uses the COBIT 4.1 framework which focuses on the Planning and Organization (PO), Deliver and Support (DS), and Monitor and Evaluate (ME) domains. The research results show that overall based on the maturity level in COBIT, the information system for the process of opening savings at Bank "XYZ" is at level 2 (repeatable but intuitive), which means the company has carried out a repetitive business process but there is no standard procedure for opening savings. To reach level 3 (define process) Bank "XYZ" needs to make process improvements by implementing the COBIT 4.1 Framework, namely PO, ME and DS which have a number of subdomains.
Penerapan Metode Clustering Dengan K-Means Untuk Memetakan Potensi Tanaman Padi di Sumatera

Rice plants are the primary source of rice, the staple food for the majority of the Indonesian population. Despite the presence of other food alternatives, rice remains irreplaceable for those accustomed to consuming rice. According to data from the Food and Agriculture Organization of the United Nations (FAO) in 2018, Indonesia is the third-largest rice producer in the world, with a total production of 59.2 million tons. However, urban and agricultural spatial planning is not yet fully integrated, resulting in often conflicting decisions in land use planning for agriculture and urban development. To meet the rice demand in Sumatra, efforts are needed to increase rice production in each province. Therefore, this research aims to map the potential for rice cultivation in Sumatra based on production and harvest results from 1993 to 2020. The method used in this study is K-Means, which allows the grouping of rice potential areas into three categories: high, medium, and low. The research results produced three clusters, evaluated using the Davies Bouldin Index (DBI) with a value of 0.3943. The clustering results indicate that Cluster 0 contains 92 areas with a high success rate, Cluster 2 comprises 84 areas with a medium success rate, and Cluster 1 consists of 48 areas with a low success rate. The category of low success rate is found in Cluster 1 with 48 areas. Cluster 0 includes Aceh, North Sumatra, West Sumatra, South Sumatra, and Lampung within certain time periods. Cluster 1 encompasses other areas with different characteristics. Cluster 2 includes the provinces of Riau, Jambi, and Bengkulu.
Prediksi Jumlah Perceraian Menggunakan Metode Support Vector Regression (SVR)

The increasing number of divorces poses an increasingly significant social challenge in Indonesia, including in the city of Pekanbaru. The impact of these divorces on the adolescent population can have negative effects on their emotional and psychological well-being, as well as their ability to interact socially and engage in the learning process. This study utilizes monthly divorce data from 2015 to April 2023 to conduct time series analysis and applies the Support Vector Regression (SVR) method to predict the number of divorces in the city of Pekanbaru. Three types of SVR kernels, namely linear, polynomial, and radial basis function (RBF), are evaluated and compared to find the kernel with the best Mean Squared Error (MSE) results. Through grid search analysis, optimal parameter values for each kernel are determined. The test results indicate that the SVR model with a polynomial kernel provides more accurate predictions with an MSE of 0.010228, compared to the linear kernel (MSE = 0.012767) and the RBF kernel (MSE = 0.010812).
Kombinasi Metode Evaluation Based on Distance from Average Solution (EDAS) dan Rank Order Centroid (ROC) Dalam Pemilihan Konten Layak Tonton Untuk Anak Usia Dini

YouTube accommodates videos on almost any topic, including entertainment, guides, music, personal vlogs, news, short films, documentaries, and other variations. This allows users to access content according to their interests and needs without significant restrictions. However, the issue of unsuitable content for children on YouTube has become an increasingly prevalent topic of discussion. The main issues related to unsuitable content for children on YouTube involve videos containing inappropriate material, violence, abusive language, and false or misleading information. While efforts have been made by YouTube to address this issue, it remains a concern given the large number of videos uploaded every day. In selecting YouTube content for early childhood, there are several criteria, including safety feasibility, interesting animation, interactivity, educational value, and positive value. Thus, this research emphasizes the importance of the existence of a decision support system in helping with the selection of YouTube content suitable for children. Decision Support Systems (DSS) use data analysis methods and various algorithms to process available information and data. The author applies a combination of EDAS (Evaluation Based on Distance From Average Solution) and ROC (Rank Order Centroid) methods to select the most appropriate and safe YouTube content for young children. This approach is used to rank each assessed piece of content. This resulted in the YouTube content "Lagu Anak Indonesia Balita" getting the top rank on alternative A8 with a maximum value of 1.00000, making it highly recommended for early childhood.
Implementasi Alat Pemantau Debit dan Ketinggian Air Sungai Berbasis Internet of Things Untuk Penanggulangan Banjir

The increasing frequency and intensity of floods in Cirebon City demands innovative solutions to reduce the impact of damage and risks to society and infrastructure. requires the latest approaches to risk management and prevention. This research focuses on the implementation of an Internet of Things (IoT)-based river discharge and water level monitoring tool designed to improve flood detection and prevention capabilities in Cirebon City. The main problems faced include accurate measurements, real-time monitoring, and rapid response to river water fluctuations. By combining the latest sensors and IoT technology, this tool is able to provide accurate data about water discharge and river levels continuously. The first stage in developing the Internet of Things (IoT) is identification and study of flooding problems in Cirebon City and analysis of the need for a monitoring system for flood prevention. Second, design a monitoring tool concept that meets the needs and specifications and determine the type of sensors, hardware and IoT technology that will be used. Third, choose a sensor to measure river discharge and water level. Fourth, build a monitoring tool prototype based on conceptual design. Fifth, Testing and Validation. The results of this research are based on river tests in the city of Cirebon, there are 4 rivers that frequently flood and the results of the test are that the Kalijaga River has a height of 20cm in the Safe level category, the Kedung Pane River has a height of 15cm in the Safe Level Category, the Kesunean River has a height of 10cm in the Safe Level Category and the Sukalila River has a height of 17cm in the Safe level category this is influenced by dry weather. Then the data collected from monitoring tools can be used to analyze flood patterns, trigger factors and impacts. Then, from this data, a flood classification analysis can be carried out based on the level of river water discharge, so that it can be classified as light, medium or heavy floods based on the amount of water flowing.
Penerapan Metode Support Vector Machine (SVM) Dalam Klasifikasi Produktivitas Padi

Indonesia is one of the largest rice producing countries in the world. Almost 95% of the Indonesian population consumes rice as a mandatory staple food, so that every year the demand for rice increases along with the increase in population. East Java is known as the largest rice producing province in Indonesia. To optimize rice production, Central Java province can group rice producing cities or districts. This aims to see and find out cities or districts that have the potential to produce rice as well as find out areas that have less than optimal rice production. To see whether the need for rice in East Java province is met, it is necessary to predict rice productivity in the East Java region so that it can be used as a basis for efforts to increase rice yields for the next period. In this research, the Support Vector Machine (SVM) method was used to classify data for predicting crop yields in East Java province. The advantage of the SVM algorithm is that it can be used for classification and regression problems with linear kernels or non-linear kernels. The data used is agricultural statistical data obtained from the website jatim.bps.go.id. The data is then analyzed using a data mining process. The results of this research are in the form of a prediction pattern with a decision tree which can be used as a basis for predictions in estimating harvest results in the next period. From dividing 80% training data and 20% testing data, results were obtained with 80% accuracy when predicting category '0' (not on target), and 100% accuracy when predicting category '1' (on target). And overall, the classification model has an accuracy of 88%. The contribution to be achieved in this research is to provide ideas for data processing in the agricultural sector.
Perbandingan Algoritma Klasifikasi Data Mining Pada Prediksi Penyakit Diabetes

Diabetes is a chronic disease that attacks humans. One of the causes of diabetes in humans is that sugar intake is too high which the body cannot balance due to absorption or activities carried out. Diabetes is often considered a common disease among people, but the impacts caused by this disease are very detrimental to humans. Based on this, it is necessary for everyone to know whether they suffer from diabetes or not. Therefore, this problem must be resolved appropriately, where it is necessary to predict whether someone will have diabetes or not. The prediction process is carried out to determine whether someone has diabetes or not by knowing the patterns or possible symptoms that cause someone to suffer from diabetes. In this research, the pattern formation process is based on data stored in the past collected in a dataset. A dataset is a collection of past data that occurred in fact and was then collected over a certain period of time on a large scale. Data mining is a method used to process data based on collections of past data, whether in datasets or others. In data mining, the data processing process is carried out using various techniques, one of which is the solution technique in data mining is classification. In this research, the Naïve Bayes algorithm, the K-Nearest Neighbor (K-NN) algorithm and the C4.5 algorithm will be used. In the data mining classification process, there are 3 (three) algorithms used, namely Naïve Bayes, K-Nearest Neighbor and C4.5. From the results of the tests that have been carried out, the accuracy performance results for the Naïve Bayes algorithm are 75%, accuracy for the K-Nearest Neighbor algorithm by 80.60% and the C4.5 algorithm by 91.80%. In this case, it indicates that the C4.5 algorithm has better performance compared to other algorithms. Therefore, the pattern results produced by the C4.5 algorithm are used to make predictions about diabetes.
Perbandingan Penggunaan Certainty Factor dan Pendekatan Dempster-Shafer dalam Sistem Expert untuk Mendiagnosis Kasus Cacar

Varicella, another name for smallpox, is a viral infection that primarily affects children and can cause an itchy rash on the skin and fever. Smallpox should be diagnosed as soon as possible to stop the spread of the disease and provide appropriate treatment. The aim of this study was to compare the Dempster-Shafer and Certainty Factor (CF) approaches for diagnosing smallpox. The main aim of this study was to evaluate the effectiveness of both methods in detecting smallpox and to determine which is more accurate and reliable in the diagnosis process. The CF method is an approach in artificial intelligence that uses confidence factor values to describe an expert's level of confidence in an event or statement. Meanwhile, Dempster Shafer is a combined theory that can overcome uncertainty in decision making by modeling the level of confidence in various aspects. This research will outline the basic concepts of the Certainty Factor method and Dempster-Shafer Theory, as well as analyze their application when making a diagnosis of smallpox. The level of precision, dependability, and effectiveness of each technique will be compared. It is hoped that health professionals can improve smallpox diagnosis and make better clinical judgments with the help of the results of this study. The results of this research will help medical personnel and health practitioners make better decisions in diagnosing smallpox. Apart from that, this research can also help reduce diagnostic errors and speed up the treatment process. The calculation results from this research show that for Shingles, the Dempster Shafer approach produces a success rate of 86%, while the Certainty Factor method offers a success rate of 99%.
Data Mining Perbandingan Algoritma K-Nearest Neighbor dan Naïve Bayes dalam Prediksi Penerimaan Beasiswa

One of the goals of the Indonesian State as stated in the Constitution of the Republic of Indonesia is to make the nation's life more intelligent. The government, through the Ministry of Education, Culture, Research and Technology (Kemendikbudristek), is implementing a 12-year compulsory education program. The Indonesia Smart College Card program will start to be implemented in 2021, where initially this program was called bidikmisi. The Indonesia Smart College Card program is intended to help children who experience economic difficulties or are constrained by the costs of continuing their education at tertiary level. Beneficiaries of the Indonesian Smart College Card program will receive full tuition fees from the start of admission to completion of the course within the agreed time period. This aims to ensure that children who have been selected to become students no longer have to worry or feel afraid about their survival when studying. Placing limits on the number of recipients of the Indonesia Smart Tuition Card for Private Universities (PTS) is a problem that must be resolved properly and carefully. The selection process for prospective students who register at the target university aims to find recipients who are worthy of assistance from the Indonesia Smart College Card program. The selection process for prospective students who register at the target university aims to find recipients who are worthy of assistance from the Indonesia Smart College Card program. The results obtained from the application of the research were that from comparing the results of the K-NN and Naive Bayes algorithms, the same results were obtained for the test data, namely Acceptable.