Reviewerly/exHarmony huggingface dataset:
Adaptive Neuro-Fuzzy Inference System (ANFIS) Method for Developing a Decision Support System for Determining Landslide Susceptibility

Landslide catastrophes are one of the disasters that frequently occur in Indonesia owing to the weather and climatic features, regional terrain, and geological formations that make this nation prone to landslides. The primary goal of this research is to compare the application of the fuzzy logic technique and the adaptive neuro-fuzzy inference system (ANFIS) approach to landslide detection sensors based on prior research in order to identify landslide-prone locations more easily. The Adaptive Neuro-Fuzzy Inference System (ANFIS) technique analyzes the landslide area using three factors. Rainfall, land slope, and soil moisture are examples of these factors. This variable is used to assess the area's level of vulnerability to landslides: very safe, relatively safe, relatively potential, potential, and very potential. In the study, each piece of data is subjected to a training and testing procedure to identify landslide vulnerability, with the factors and weighting methods aligned with current government standards. This study compares the rules outcomes to those of past studies as well as the system results. Based on the studies findings, it can be stated that the decision support system for the degree of landslide vulnerability utilizing the ANFIS approach is superior to the fuzzy logic method, with an accuracy rate of 86.21%.
THE STRUCTURE OF THE WESTERN PRIOKHOTYE LITHOSPHERE (BASED ON THE INTERPRETATION OF GRAVITY DATA)

A density 3D model was constructed, which made it possible to identify inhomogeneities in the western Priokhotye lithosphere and to obtain geophysical characteristics of the main tectonic elements in the region. Qualitative analysis of the density profiles revealed features of fault tectonics at different depth levels. Oblique faults are shown to prevail in the crust of the region, while orthogonal faults prevail in the lithospheric mantle. It is established that the metamorphic basement of the northeastern margin of the North Asian Craton is divided by active long-lived zones into differently directed blocks. Different-level (mantle-crustal) igneous intrusions and endogenous mineralization are confined to the distinguished zones.
A systematic mapping study of effective regulations and policies against digital monopolies: visualizing the recent status of anti-monopoly research areas in the digital economy

The number of digital goods and services within the field of the digital economy is growing significantly while simultaneously causing management and regulation problems over them. This makes policy-makers find it hard to keep up with effective regulations and policies or devise effective measures related to the fair government of digital economy domains, thereby digital monopolies are avoided and healthy competition is improved in digital markets. To increase the role of government in the digital economy, this study aims to provide an overview of research areas related to anti-monopoly aspects of the digital economy and outline rising trends and gaps in regulations /policies against digital monopolies. In this regard, we cover and classify research in the area of digital monopolies and effective regulations during the advances of the digital economy, following the inclusion criteria based on the most recent and most promising topics of the digital economy: big data & artificial intelligence, the platform economy, digital trade, financial technology, sustainability, and human welfare. Based on a five-step procedure of conducting systematic mapping, Swale's move/step analysis framework, this paper provides a visual summary of the status of policy research areas and research agendas.
Pembelajaran Kooperatif Model TGT untuk Meningkatkan Hasil Belajar Bahasa Inggris Siswa Kelas VIII.A SMP Negeri 6 Mataram

The purpose of this classroom action research is: to find out the increase in English learning achievement through the TGT Cooperative Learning Model for Class VIII.A Students of SMP Negeri 6 Mataram in the Academic Year 2021/2022. This study uses action research (action research) as much as two cycles. Each cycle consists of four stages, namely: design, activity and observation, reflection, and revision. The target of this study was students of Class VIII.A SMP Negeri 6 Mataram with a total of 34 students consisting of 16 boys and 18 girls. Based on all the discussion and analysis that has been carried out, it can be concluded that: By applying the Teams Games Tournament (TGT) cooperative learning model, it can be seen that student learning outcomes in the English subject of narrative text material in class VIII.A of SMP Negeri 6 Mataram have increased. After carrying out several cycles the results obtained using the Teams Games Tournament (TGT) cooperative learning model appear to have increased compared to before using it, namely in the pre-action of 84.44 with students completing 67.65%, in cycle I the average value to 84.71, students who completed as many as 27 students 79.41%, student learning outcomes in cycle II with an average value increased to 87.26, students who completed as many as 34 students 100%.
Meningkatan Keaktifan Belajar Siswa pada Mata Pelajaran IPA melalui Model Tiruan Berbasis Teknologi Informasi di SD 158/III Sungai Abu

This study aims to increase students' active learning in science subjects by using an artificial model based on Information Technology. This type of research is classroom action research (CAR). This research was conducted in class V with a total of 6 male students and 5 female students. This research consisted of two cycles and each cycle held two meetings. Data collection techniques using observation techniques, and documentation. The results showed that there was an increase in student learning activeness in science subjects by using a mock model from cycle I to cycle II. The increase in student activity occurred because students had understood the concept of learning science through the steps contained in the Information technology-based artificial learning model, and students were more enthusiastic in participating in the learning process. The percentage of student activity in cycle II increased from 73.8% to 82.9% classically.
Penerapan Discovery Learning Menggunakan Microsoft Office 365 untuk Meningkatkan Hasil Belajar Kognitif Siswa

This study aims to determine the increase in cognitive learning outcomes in science subjects of class VIIA students at SMP Batik Surakarta in the 2020/2021 academic year through the application of the online Discovery Learning model.This research is a Classroom Action Research with the research subjects of class VIIA students in the 2020/2021 academic year totaling 29 students. The data collection technique used a cognitive learning outcome test instrument. The research was conducted in 3 cycles. The analysis technique uses a comparison of learning outcomes. The results of classroom action research carried out through three cycles showed that the application of the discovery learning model could significantly improve students' cognitive learning outcomes by 93.5% of students could achieve completeness of science cognitive learning outcomes in energy material in life systems, this was also accompanied by an increase in average. -a grade learning outcomes. As much as 6.5% of the students were still incomplete due to network constraints and the inactivity of students in following learning in accordance with the provisions.
The Impact of Financial Technology Reform on Corporates’ Growth: Evidence from Panel Data Regression

In China, the problem of difficulty in financing restricts the growth of many enterprises and the development of digital finance may have a positive impact on this phenomenon.This paper aims to explore the relationship between the coverage breadth of digital finance and enterprise growth with the model of OLS and panel fixed-effect estimation.After adding control variables, the result indicates that there is a positive correlation between these two variables, that is, an increase in coverage breadth of digital finance can promote the growth of enterprises.Through heterogeneity analysis, we find that digital finance's impact on different scales of enterprises has a significant variance.Compared with large enterprises, the increase in coverage breadth seems to be more conducive to the growth of small and medium-sized enterprises.Finally, our research has a policy implication that with the purpose of continuous enterprise growth, the regulators in the financial sector should provide incentives to increase the coverage breadth of digital finance.
The Information Technology and Corporate Innovation: Evidence from China’s Listed Companies

In the past few years, the digital economy and digital finance have developed rapidly in China and have had a far-reaching impact on enterprises.By constructing a linear model, this paper evaluates this impact from the perspective of enterprise innovation.The study found that, on average, increasing the coverage of digital finance by one unit will increase the R & D expenditure of enterprises by 0.91%.Heterogeneity analysis found that compared with large-scale enterprises, the development of digital finance has a greater impact on the R & D expenditure of small and medium-sized enterprises.
Cryptocurrency Price Forecast with Use of Time Series Model, Conventional Statistic Model and Machine Learning Approaches

Cryptocurrency is an emerging virtual currency gathering attention from the public, which is difficult to counterfeit or double-spend.One of the most significant discussions in cryptocurrency is its extremely high volatility which brings challenges on price prediction.Therefore, lots of research have been conducted to predict cryptocurrency by implementing different models.In this paper, various time series models, conventional linear models, and machine learning models are compared in terms of predictive performance on BTC-USD prices based on historical 5-year daily information and technical features derived.On this basis, various metrics are adopted including AIC, RMSE, MAE, and R-Square and are respectively evaluated and compared.Time series models, ARIMA and GARCH, have relatively poor predictive performance.For statistic models, linear regression, Ridge and Lasso are evaluated respectively, where both regularized models are not able to outperform the linear regression.Regarding to machine learning models, ensemble tree methods including random forest and LightGBM have relatively better performance than other types of models.Among all models tested for the same split, random forest has the lowest error and highest coefficient of determination, and its predictions are the most accurate.These results shed light on choosing from different models in cryptocurrency price prediction.
DIGITALIZED CURRICULUM IN BASIC EDUCATION: TOWARDS EDUCATION FOR SUSTAINABLE DEVELOPMENT IN NIGERIA

This paper looked at the relevance of digitalized .curriculum, its ease and effectiveness at actualizing the basic education programme in Nigeria; and this informs national development. The author is of the opinion that the basic education which is a mandatory nine years academic programme is an imperative for encouraging mass literacy and numeracy, requisite skills for job creation , and avenue for educational opportunity for a long-life learning for the out of school for formal and non-formal education .However, the paper observes that given the economic realities in Nigeria and its challenge to a regular teacher-student classroom method of service delivery ; the actualization of the basic education programme in Nigeria might become a mirage and the intended skills and job creation that would have been encouraged through the programme and the attended sustainable development in Nigeria elusive. Based on the observations, the author maintains that the digitalized curriculum is a preferable educational approach to achieve sustainable development in Nigeria through the basic education programme ; given the versatility and adaptability of the digitalized curriculum to many and varied learners . The author observes some challenges , such, as power supply, network coverage, finance for data subscription among others as major setback to f implementing the digitalized curriculum in Nigeria .Based on the observed challenges , the author made some suggestions that will be of help to effectively implement the digitalized curriculum at the basic education level to achieve sustainable development in Nigeria .
The Development of Podcast Based Learning Media on Social Studies to Improve Students’ Digital Literacy

Technological developments in the 4.0 revolution affect aspects of life, including the educational aspect. Currently, the learning components are technology-based, such as podcasts as learning media. So that it becomes an opportunity for students to understand digital literacy through podcasts as a learning media in the classroom with social studies subjects. This study aims to describe the creation of podcast-based social studies learning media model to improve students’ digital literacy. The research uses Research and Development with qualitative and quantitative approaches, data collection techniques using observation, interviews, document studies, focus group discussions, and data analysis techniques using regression correlation. The research subjects are students at Universitas Pendidikan Indonesia, Bandung, Indonesia. The results from these studies showed that using digital-based learning media, namely podcasts in social studies subjects, had a good impact and a significant effect on students’ digital literacy skills. The application of podcast-based learning media products will work well if they are supported by several funding elements, namely: 1) the involved issues are contemporary; 2) the use of the latest design; 3) in the design of materials, there is a collaboration between lecturers and students.
Development of Calistung E-Book with Flora and Fauna Character in Indonesian and Mathematics Learning Grade I Muhammadiyah Purworejo Elementary School

This research is a research and development (Research and Development) using the ADDIE development model, which consists of five stages: Analysis, Design, Development, Implementation, and Evaluation. The subjects in this study were grade 1 students of SD Muhammadiyah Purworejo in the 2021/2022 academic year. Data collection techniques in this study were interviews, questionnaires, tests, and documentation. The instruments used are interview sheets, validation sheets, student response questionnaires. The results of the research carried out: (1) Produce the Calistung E-Book using the ADDIE model, (2) The feasibility of the product is obtained from the validity of getting a value of 3.44. Then the practicality of the student's response with a value of 3.75. (3) the effectiveness of the product is seen based on the results of the pre-test and post-test with an effectiveness percentage of 71.4%. Based on this study, it can be concluded that the E-Book Calistung with Flora and Fauna Characters developed in this study is categorized as very feasible and effective to be used as a learning medium in elementary schools
Sistem Pendukung Keputusan Pemilihan Bibit Jagung Unggulan Pada Desa Gumuk Rejo Menggunakan Metode (SAW)

Corn Seed is a very popular commodity plant planted by farmers especially Indonesia because many people use this plant in addition to its many benefits it is also a food crop. Users usually have difficulty choosing Corn Seeds to be bought because of the many types of Corn Seeds, soil construction, and prices. So we need a decision support system that can help users determine the Corn Seed according to the desired alternatives and criteria. In this study, the method used is Simple Additive Weighting (SAW), providing information and assisting farmers in making decisions about the superior corn seedlings they will use. Corn seeds are very important for us because corn seeds are the main factor and determinant of the success of farmers in Gumuk Rejo village. In making the decision support system application selection of superior corn aunt uses the PHP programming language and uses the MySql database.
Quality Analysis Using WebQual Method and Importance Performance Analysis (IPA) Case Study on Learning Management System (LMS) Indonesian Institute of Education (IPI) Garut

With the development of technology, there are also tools to help humans complete all work. For example, what students do in supporting lecture activities. Looking for references to increase knowledge of a course, see lecture tutorials and many others. Technology in learning activities that has been known is the use of a Learning Management System (LMS) which can make lecture activities via online or commonly called e-learning. Especially in the present era of the pandemic and the spread of the covid-19 virus, people are not allowed to leave the house let alone go to school, but learning cannot be abandoned so that e-learning activities cannot be avoided. The quality of the use of media for learning can affect the quality of learning as well, whether it can be a barrier to learning or on the contrary, it can actually be the main supporter in achieving achievement. Therefore, in this study, we will analyze the quality of the Learning Management System (LMS), especially those used by students at the Indonesian Institute of Education (IPI) Garut with the WebQual method by assessing a product or website based on user perceptions and Importance Performance Analysis (IPA) based on analysis. the quadrant. The results obtained are that the quality of the Learning Management System (LMS) has not been said to be good because there are many points that still need to be improved, such as information that is not up to date, ease of use and the most prominent can be seen from the monotonous appearance so that it can be used as material. evaluation to be able to reconstruct the design, update information and streamline the use of the Learning Management System (LMS) Indonesian Institute of Education (IPI) Garut.
Synchronizing Analog - Discrete Nonlinear Systems

Abstract Using nonlinear chaotic systems for secure communication is an application field presented in recent published research. This paper aims at improving the security of signal transmission using chaotic encryption. The proposed approach uses a combined analogue and discrete-time structure, for both chaotic emitter and synchronizing receiver. The prototype system used is similar to the Lorenz nonlinear oscillator. Our study presents the emitter dynamic properties, develops the receiver synchronization using the emitter partitioning method, and designs a linear equalizer at the receiving end of the communication chain in order to improve the demodulated signal.
The value of NVR (Network Video Recorder) as a helping hand in criminal investigation

The purpose of this paper is to understand the available closed circuits television available for the purpose of surveillance and to choose the best options to fulfil the higher requirements by providing the best in features that could provide better evidence during an investigation procedure.The main purpose of this paper is to detect the weakness of the digital video recorder technology though which is cost effective but the amount of data provided is ineffective and to highlight the features of network video recorder the successor of DVR which would cover its shortcomings thereby providing higher degree of functionality.The end goal of this project was a fully working wireless network, with appropriate hardware chosen for this task and better video surveillance ensuring security in most vital points.
Sistem Pendukung Keputusan Pemilihan Anggota Kelompok Tani Terbaik Pada Desa Sinar Semendo Menggunakan Metode (SAW)

Farmers can be interpreted as someone whose field of work is farming or it can also be interpreted as someone who is engaged in agricultural business primarily by managing land with the aim of and maintaining crops such as rice, flowers, fruit and others in the hope of obtaining the results of these plants to use alone or sell it to others. This application was created using the SAW (Simple Additive Weighting) method. The basic concept of the SAW method is to find the weighted sum of the performance ratings for each alternative on all attributes. The SAW method can help in the decision making of a case, but calculations using the SAW method only produce the greatest value that will be selected as the best alternative. The calculation will be in accordance with this method if the chosen alternative meets the specified criteria. Using the decision support system for selecting the best Farmer group members in the Sinar Semendo village using the Simple Additive Weigtihng (SAW) method helps Sinar Semendo Village to determine the ranking of Farmer Group members from the results of the specified criteria weights, thus providing additional information when determining a selection. This decision support system is based on a website with PHP programming language and MSQL database for data storage.
Efficient email classification strategy based on semantic methods

Emails have emerged as one of the foremost packages in each day life.The continuous increase in the wide variety of email users has led to a huge boom of unsolicited emails, which might be also known as junk mail emails.Managing and classifying this large variety of emails is an important challenge.In this paper, a green email filtering approach based totally on semantic techniques is addressed.The proposed technique employs the Word Net ontology and applies exceptional semantic-based totally strategies and similarity measures for lowering the huge number of extracted textual features, and as a result, the gap and time complexities are reduced.Most of the approaches delivered to remedy this trouble treated the high dimensionality of emails by the use of syntactic feature selection.Moreover, to get the minimal most appropriate features' set, function dimensionality reduction has been integrated using characteristic selection strategies which include the Principal Component Analysis (PCA) and the Correlation Feature Selection (CFS).Experimental results on the usual benchmark Enron Dataset showed that the proposed semantic filtering approach combined with the function choice achieves excessive computational performance at high area and time discount rates.A comparative study for numerous classification algorithms indicated that the Logistic Regression achieves the very best accuracy in comparison to Naïve Bayes, Support Vector Machine, J48, Random Forest, and radial basis function networks.By integrating the CFS characteristic choice technique, the average recorded accuracy for the all used algorithms is above 90%, with more than 90 reductions.Besides, the carriedout experiments showed that the proposed paintings have a highly sizeable overall performance with better accuracy and much less time in comparison to other related works.