Reviewerly/exHarmony huggingface dataset:
Sentiment Analysis of Madura Tourism Opinion Using Support Vector Machine (SVM)

Madura is one of the most popular tourist destinations in Indonesia. It offers a variety of interesting attractions such as beaches, islands and a unique traditional culture. However, like other tourist destinations, Madura tourism also receives different opinions from the community. Some public opinions can be in the form of positive, negative and neutral feelings towards Madura tourism. To find out the public opinion, it is necessary to conduct sentiment analysis using the Support Vector Machine (SVM) method. In this analysis, data was collected from various social media platforms discussing Madura tourism. Reviews from the community are divided into three categories into positive, negative, neutral, which are processed by the SVM method. The purpose of using the Support Vector Machine method for sentiment analysis of public opinion about Madura tourism where the results can be analysed to provide recommendations for improvements to Madura tourism that are useful for improving the quality of Madura tourism based on public sentiment. From the test results carried out using K = 5 fold cross validation, positive sentiment is obtained from as many as 192 tweets and an accuracy of 92.592% using Confusion Matrix.
A PROPOSED ELEVTRONIC MEDIA PLATFORM TO SUPPORT DECISION MARKERS TOERDS ACHIEVING SUSTAINABLE CONSUMPTION OF STRATEGL CROPS IN EGYPT

The aim of the research is to study the handling of environmental issues by specialized electronic media websites related to achieving sustainable consumption of strategic crops in Egypt, especially cereal crops (wheat, rice), edible oils (soybean - wheatgrass), cane and sugar beet. The research also aimed to develop a proposed vision for an electronic media platform that provides data and information that would support decision makers concerned with achieving sustainable consumption of strategic crops in Egypt, This is to direct this type of media towards researching how to provide more in-depth and analytical media content that is commensurate with the nature of decisions related to the aim of the study to contribute to making rational decisions for agricultural development in general and the sustainability of consumption of the most important strategic crops in particular. This research belongs to descriptive research, where the researchers analyzed the content of three websites specialized in agricultural development during a period of six months (from the beginning of July to the end of December 2021), using the content analysis form, conducting in-depth personal interviews with each of the decision-makers in the relevant ministries of Through a sample of (30 items), and those who contact specialists in the field of agriculture in newspapers and various websites, The researchers also conceptualized a proposal for an electronic media platform to serve the purpose of the study. The researchers reached a number of results, the most important of which are: that electronic media needs further development to make the editorial material more specialized and in-depth, there is also weak dependence on the part of decision-makers on the specialized electronic media sites that currently exist, and that there is an urgent need to develop environmental electronic media specialized in agricultural field. The researchers recommended that electronic media should have a role in the participation of all relevant ministries and sectors in decision-making based on a unified collective information awareness that does not accept doubt, duplication and conflict. Keywords: electronic media, consumption sustainability, environmental sustainability, strategic crops, agricultural development.
Penerapan Algoritma Apriori Pada E-commerce Elektronik

Because there are so many advantages to using e-commerce, it is now expanding quickly. E-commerce, particularly for electronic items, makes it simpler for customers to execute transactions without traveling. Because businesses (business actors) do not yet have a pattern and strategy for the products they sell, the use of e-commerce has not yet reached its full potential. As a result, sales occasionally suffer because the supply of products does not meet consumer needs, forcing consumers to leave without purchasing these products, which has an impact on transactions. sales firm. Businesses (businesspeople) must use data mining to implement data processing. For this reason, researchers use an application strategy that is appropriate in this situation: the a priori algorithm. Finding frequent itemsets that frequently show up in the data set with the strongest pattern is frequently done using the a priori algorithm. This algorithm's output can be used to assist management in making decisions. According to the study's findings, the rule "if you buy AA Batteries (4-pack), you will buy AAA Batteries (4-pack), "if you buy AA Batteries (4-pack), you will buy a USB-C Charging Cable," and "if you buy AA Batteries (4-pack) and AAA Batteries (4-pack), you will buy a USB-C Charging Cable" all have a support and confidence value of 100%.
Object Localization and Detecting Alphabet in Sign Language BISINDO Using Convolution Neural Network

The BISINDO sign language is used to help deaf and mute people communicate with other people. However, not everyone is able to understand the meaning of this sign language. A system that implements artificial intelligence methods is created to solve this problem. The system uses a Convolution Neural Network algorithm with object localization techniques to detect and classify the alphabet in each form of the BISINDO finger signal. The Region Convolution Neural Network (RCNN) algorithm is used to process object localization and the CNN algorithm will perform classification process. This system is trained using 64 training data and tested using 16 test data for each type of alphabet. The results of the system testing that have been carried out are able to provide excellent accuracy values, which are above 90 percent for a training epoch of at least 50. These results produce an accuracy of 90.10% and 97.33% respectively.
Face Mask Recognition Menggunakan Model CNN (Convolutional Neural Network) Berbasis Python dan OpenCV

During the COVID-19 pandemic, masks are one of the main measuring tools in carrying out health protocols, masks are also a top priority when carrying out activities outside the home or office. Because masks are quite effective in filtering out disease particles that allow users not to get infected. Therefore, many places have made masks an important requirement in maintaining health protocols during the COVID-19 pandemic. Previously there was a system that had been created to assist the government in implementing the mandatory wearing of masks, but there were still deficiencies. Therefore the authors created a system to detect mask wearing by updating previous researchers using the convolutional neural network (CNN) algorithm. For making this system the author uses the PYTHON and OPENCV programming languages. which will produce four parts in this detection, namely Mask, No Mask, Covered Mouth Chin and Covered Nose Mouth.
The Role of E-Learning in Enhancing the Egyptian Business and Universities Performance Post Covid -19 Pandemic

Despite its reported great potential, in practice, e-learning still fails to dominate the industry. The lack of literature on e-learning philosophy, makes unlocking its potential a real challenge. This calls for debating and examining the theoretical underpinnings of e-learning, and its effect on students and instructors; especially during the pandemic. From the study, it will be concluded how e-learning affects not only students and professors, but also on the business side, on employees and customers. Accordingly, this study's primary goal is to examine the role of e-learning in enhancing the Egyptian business and universities performance post Covid -19 Pandemic.A qualitative research approach was used, in which four different focus group discussions (FGDs) were conducted with a sample of 37 participants in order to gain deep insights from an intentionally selected group of individuals; Students and teachers regarding their personal experiences with e-learning during the pandemic at the College of Management and Technology, Arab Academy for Science and Technology, and Maritime Transport in Egypt. Students and teachers were selected as employees and customers of universities. Focus group discussions were held with 22 students (10 and 12, respectively) and 15 teachers (8 and 7, respectively).Literature has been rich in studies on e-learning from a practical view. Yet, this study is considered novel; as it provides a link between e-learning theories and practice. The study also shows how a pedagogic research study can be utilized to improve the learning process and to assist in curriculum development and course management.
Sistem Pendukung Keputusan Penerima Beasiswa Murid Berprestasi dengan Metode SAW

This research is a Decision Making System research which purposes to find out the scholarship recipient candidate of the feat student through of the SAW (Simple Additive Weighting) method of the MTsN 1 Penajam Paser Utara. The purpose of this research is to provide of the convenience in the alternative solution in the determining scholarship of the feat student, and to apply of the SAW method in assessing of the scholarship recipient candidate . The Data collection techniques in this research were observation, interview, and literature study. The method is used The SAW. Then it requires the decision maker to determine the level for each the attribute, then the total of score for the alternative is obtained by adding up all the multiplication results between the rating (which can be compared across attributes) and the level of each attribute. The rating for each attribute must be dimension-free in the sense that it has gone through the previous of the normalization process. The basic concept is to find the total leveling of the performance rating for each alternative across all the criterias. The SAW method requires normalization of the decision matrix (X) to scale that can be compared with the existing rating. The sample population taken is from 60 students of MTsN 1 Penajam Paser Utara. From the result of determining the priority of proposed the feat scholarship recipient candidate is using the Simple Additive Weighting method, the student who deserves the best achievement scholarship is M. Indra Saputra who has the highest ranking with a score of 0.916 as the best alternative. The system built can help of the selector team to work in selecting outstanding scholarships and can speed up the selection process and reduce error in determining scholarship recipient.
ABC-GAN: Spatially Constrained Counterfactual Generation for Image Classification Explanations

There is a growing interest in methods that explain predictions of image classification models to increase algorithmic transparency. Counterfactual Explanations (CFEs) provide a causal explanation as they introduce changes in the original image that change the classifier’s prediction. Current counterfactual generation approaches suffer from the fact that they potentially modify a too large region in the image that is not entirely causally related to a classifier’s decision, thus not always providing targeted explanations. We propose a new method, Attention Based Counterfactuals via CycleGAN (ABC-GAN), that combines attention-guided object translation with counterfactual image generation via Generative Adversarial Networks. To generate an explanation, ABC-GAN incorporates both a counterfactual loss and the classifier’s attention mechanism. By leveraging the attention map generated by GradCAM++, ABC-GAN alters regions in the image that are important for the classifier’s prediction. This approach ensures that the generated explanation focuses on the specific areas that contribute to the change in prediction while preserving the background and non-salient regions of the original image. We apply our approach to medical X-ray datasets (MURA Bone X-Ray, RSNA Chest X-ray) and compare it to state-of-the-art methods. We demonstrate the feasibility and, in the case of the MURA dataset, the superiority of ABC-GAN in all the measured metrics with the highest percentage of counterfactuals (99% Validity) and image similarity. On the other dataset, our method outperforms the competitive methods in small changes and image similarity. We argue that ABC-GAN is thus beneficial for classification problems requiring precise and minimal CFEs.
Revitalisasi Perpustakaan untuk Meningkatkan Minat Literasi Siswa di SDN Cangkringan, Kabupaten Boyolali

&lt;p class="Abstract"&gt;The literacy rate in Indonesia is meager due to the lack of literacy facilities in schools. One of the schools in Indonesia, precisely in Boyolali, namely SDN Cangkringan, has fewer literacy facilities. This activity aims to improve literacy at SDN Cangkringan by revitalizing the library and creating a Reading Corner. The method used in this research is descriptive qualitative, with data sources obtained from observations, documentation, and literature studies carried out before and before library revitalization activities. The results of this activity showed that the library visit rate from students increased by 42%, with active students increasing by 30% after the revitalization was carried out. The existence of a reading corner gives students their own space to read other than that, with this reading corner, students also become more interested in reading because reading facilities are closer.&lt;/p&gt;
Penerapan Algoritma K-Means Pada Pemetaan Kemampuan Penggunaan Teknologi Informasi Remaja dan Dewasa di Indonesia

In modern-day Indonesia, having access to various forms of technology is regarded as crucial. This is because the IT skills gap will only grow worse if the government does not act swiftly to make technology more accessible to the general public. PISA suggests that schools may gain much more from incorporating IT into their curriculum if they did so. The goal of this research is to establish whether or not there are notable variations in the level of knowledge in information technology across the different provinces in Indonesia. Official data from the Central Statistics Agency for 2019-2021, including information on the number of adolescents and adults aged 15-59 with abilities in the field of ICT at the provincial level, is used in the clustering calculation. The K-means algorithm is one unsupervised learning technique for clustering data into collections with other instances that share similar properties. The results showed that the seventh cluster had the lowest DBI value of the three examined, coming in at -0.357. Cluster 0 has the lowest average percentage of the population with IT skills, at 29.32%. Only in Papua Province will you find this particular zero cluster.
The Effectiveness Of Using Kahoot Application As Media Of Vocabulary Mastery At Tenth Grade Of SMAN 1 Bukittinggi

The aim of this research was to know how the effectiveness of using Kahoot as media of vocabulary mastery at tenth grade of SMAN 1 Bukittinggi. The design of this research was descriptive quantitative research. The instrument of this research was documentation for collecting students vocabulary scores of the students after using Kahoot application. The population of this research was all students at tenth grade of SMAN 1 Bukittinggi which consists of 12 classes. The sample was 68 students which were taken from two classes by using purposive sampling technique. Based on the results of this research, it was concluded using Kahoot application as media of vocabulary mastery at tenth grade of SMAN 1 Bukittinggi was on good category where the students’ mean scores was 77,31 lies on the percentage 66-79 which was effective on rating quality. Furthermore, using Kahoot application was effective to be used as media of vocabulary mastery at tenth grade of Bukittinggi.
Penerapan Metode Naive Bayes Dalam Rekomendasi Strategi Penerimaan Peserta Didik Baru

New Student Admission (PPDB) is a school spearheading activity in getting students, especially for private schools. SMK Muhammadiyah 1 Borobudur as one of the private vocational schools in Magelang Regency. SMK Muhammadiyah 1 Borobudur has problems related to the PPDB promotion strategy. The PPDB promotion that has been carried out has not fully shown a significant promotion growth to increase the number of students registering each year and PPDB information has not yet reached remote areas of Magelang Regency. In determining the promotion media for PPDB SMK Muhammadiyah 1 Borobudur, this study uses the Naïve Bayes algorithm. Naïve Bayes is a classification method using probability and statistics to predict future opportunities based on the past. By using the nave Bayes algorithm which is applied with a ratio of 70:30 for train data and test data, it is able to produce an accuracy of 72%. To maximize the results of data accuracy, this study used the k-fold cross-validation method with k=10 times resulting in an accuracy of 75%. In addition, it can be seen that 3 PPDB information is recommended for promotional media, namely student partners, alumni and Instagram.
Penerapan Metode Certainty Factor Pada Sistem Pakar Diagnosa Penyakit Diabetes Melitus

Diabetes Mellitus is a disease that occurs in metabolism at a chronic level. Diabetes Mellitus has always been a frightening disease for the community, this is because diabetes mellitus is a disease that causes death with a fairly high risk of death. Early diagnosis of diabetes mellitus or the community to find out diabetes mellitus is very important. Early diagnosis that is carried out causes early problems, especially for the community. This is because to carry out an examination of diabetes mellitus, laboratory tests must be carried out in hospitals, carry out an overall body examination and the costs are quite high. In addition, there is also limited information by the public on the signs or symptoms that allow a person to be indicated for diabetes mellitus. Therefore, it is necessary to solve these problems to assist in the early diagnosis process by the community. An expert system is a system that is already part of computerization. Computerized expert systems can diagnose certain diseases based on the knowledge stored in the expert system. The certainty factor method is one method that can be used in the process of solving the expert system. The certain factor method can produce an accurate value based on the symptom weight value that has been selected by the patient. The results of the study found that the accuracy value obtained from the process of diagnosing diabetes mellitus was 94,78%.
Pengaruh Penggunaan Metode Active Learning Tipe Card Sort Terhadap Hasil Belajar Siswa Pada Mata Pelajaran Fiqih Di MTs PN 4 Medan

The learning method is a method used by educators in the learning process to facilitate students in receiving learning material according to the objectives, the Active Learning Method is an alternative method that is used to increase the activity of student learning outcomes, especially by using the Card Sort type which is proven to be effective in facilitating students' understanding of the concepts being taught. The activeness of students in studying Fiqh is very important because Fiqh is a scientific discipline that studies Islamic rules and laws that must be obeyed. the existence of active learning for students, namely understanding the material taught by the teacher which is then manifested in everyday life. The active learning methodology encourages student participation during the teaching process so that students become more involved, creative, and able to express their own opinions about the material being taught. In this study, the active learning method was applied using card sort. The card sort type is a form of activity that involves students in the learning process, in the card sort type, students are asked to categorize a number of concepts or information into several related groups. The concept or information is usually written on small cards that students can arrange or arrange.
Lung Cancer Classification Using Random Oversampling and Gradient Boosted Decision Tree

Lung cancer has the highest number of sufferers in men, especially in Indonesia. An unhealthy lifestyle, smoking, and pollution also aggravate the patient's condition. In this study, a diagnosis was made of patients with suspected lung cancer. For an experiment, the data from public datasets, “Cancer Patient," “Survey Lung Cancer,” and “Cancer_Data.” The research phase includes exploratory data analysis (EDA), pre-processing, and classification. EDA aims to know data types, missing values, correlations between attributes, and outliers. Pre-processing consists of data cleaning and data discretization. In the next process, we use randomized oversampling to overcome imbalanced data. The final step was classification using Gradient Boosted Decision Tree (GBDT). The experiment scenario uses imbalanced and balanced data. For the testing scenario, the variation in learning rate and the number of trees were used with Randomized Search Tuning. The distribution of training and testing data uses 5-fold cross-validation. The result shows that using balanced data between classes is better than imbalanced data. In addition, we also classify the dataset with the k-nearest neighbor and support vector machine. The GBDT produces better performance for two datasets.
Pengembangan Aplikasi Animasi Kinemaster Sebagai Media Pembelajaran Interaktif Bagi Guru SD Negeri Pakuan

The research results are to develop the KineMaster application to create an interactive learning media for Pakuan State Elementary School teachers. Research design uses a descriptive quantitative approach with data collection techniques through questionnaires and interviews. The results of the study have obtained the need for interesting and interactive learning media, students have difficulty consulting with teachers, especially for lessons that are considered to require deeper explanation and understanding. To overcome this, the use of learning media using the KineMaster application can be a very easy and effective alternative for teachers in carrying out learning. During the covid-19 pandemic, this application can be a solution for teachers in replacing teachers’ conventional classroom methods in the room. Kinemaster application presents a fairly simple look, but stores quite complex features. This condition can help students in understanding the learning materials. Creating learning media through animated videos using the KineMaster application is quite easy. Thus, Kinemaster applications can be used in developing materials and teaching materials for elementary teachers.