Reviewerly/exHarmony huggingface dataset:
Innovation and Development in Sub-Sahara Africa: The Role of Institutional Development and Inter Alia

Science, Technology and Innovation (STI) is gradually seen by countries in Sub-Sahara African as the engine for economic growth and general uplifting of the standard of living. As a result, Innovation is embraced but institutional weaknesses hinder the required outcome. This paper's aim is to examine the connection between innovation and development in sub-Saharan Africa while considering the function of institutes and other elements. This is in light of the fact that institutions act as the lubricant for progress. The Middle East and North Africa are not included in the scope of the paper, which largely focuses on sub-Saharan African nations. Some western nations and developing economies are, nonetheless, occasionally used as comparison points. We analyze data from reputable organizations like the World Bank, Polity IV, and considering a gauge of innovation and GDP per capita, the quantity of scientific publications published as a proxy for development, the Economic Freedom of the World Project will evaluate a panel of 22 economies in sub-Saharan Africa (EFW). Our results from the POLS and GMM IV regression show, among other things, that innovation has a favorable impact on the development of Africa, even though the impact looks insignificant. Although the majority of the nations in the county have established institutional frameworks for science, technology, and innovation (STI), evidence suggests that the slow rate at which innovation contributes to national development is due to obstacles in the design and implementation of STI policies. The outcome highlights the region's little advancement in the technology-capability indicators. To establish and execute STI policies in the region, a lot more has to be done in the area of collaboration between public entities and parastatals.
Strategic Planning and Performance of Women’s Small Sized Business in Rwanda: A Case of Kigali City

This research explored the effect of strategic planning practices on performance of women in small and medium enterprises in Kigali City, Rwanda. Specifically, the study determined effect of vision strategy on women entrepreneurs’ performance in small and medium enterprises from Kigali City, to analyze effect of growth strategy on women entrepreneurs’ performance in small and medium enterprises from Kigali City, and to ascertain effect of competitive strategy on women entrepreneurs’ performance in small and medium enterprise from the Kigali City. The researcher used resource-based view theory, institutional theory, and upper echelon theory. A descriptive and analytical design where the mixed approach was adopted. The target population was 478 persons. The sample size was 218 respondents and five key informants. Results to the first objective revealed a positive association between guiding customers and sales (r=0.320**, p-value=0.001), investment (r=0.317, p-value=0.001). Significant correlation between for clear reason vibrant goal and specific objectives (r=0.408*, p-value=0.048), and with profit (r=0.716, p=0.000). Results on the correlation between vibrant goal and specific objectives and dependent variables, indicate a significant correlations between vibrant goal and specific objectives and sales (r=.407**, p=0.000), investment (r=538, p=0.000). Results to second objectives felt positive association between volunteering strategies with sales (r=0.424**, p=0.000), investment (0.740**, p=0.000), profit (0.484**, p-value=0.000). Findings from the third objective felt significant association between the mark cost concertation and sales (r=0.244**, p=0.013), investment (r=0.322*, p=0.001) with profit (r=0.270*, p=0.006). A positive high significance was established between acquiring same sector with sales (r=0.181*, p=0.063).The study recommends to understand strategic execution in place to attain organization objectives, to endure the unserved efforts to improve skills and willingness. Keywords: Competitive Strategy, Growth Strategy, Performance, Strategic Planning, Vision Strategy
A Novel Heterogenous Dominant Sequence Clustering for Task Scheduling and Optimal Load Balancing Using JSO in Cloud

Cloud computing (CC) is rapidly increasing and being used more and more in information technology (IT) contexts. Among the hottest issues in the world of CC is task scheduling. In cloud datacentres, load balancing is accomplished using a variety of scheduling techniques, although lengthening the parallel time. By taking task duration and VM capacity into account, this study proposes a cluster-based task scheduling paradigm. The makespan and execution duration should be reduced, the suggested system engages in dynamic load balancing. In this study, we suggest a unique method called HDDSC-JSO, which employs the Jellyfish Swarm Optimization (JSO) algorithm for load balancing and heterogeneous Density based dominant sequence clustering (HDDSC) for job scheduling. Using the HDSC technique, It presents a graph of one or more groups representing user tasks, the tasks of users are first clustered. The Adapted Diverse Expeditious Termination Time (ADETT) method is used to score each work after task clustering. whenever the job with the greatest priority is scheduled first. Next, using a JSO algorithm, load balancing is carried out, distributing the load according to the weight and capacity of the server as well as the connection of the client to the server. Task allocation chooses a heavily weighted or unconnected server, lengthening the response time. Finally, measures including response time, makespan, resource consumption, and service dependability were used to assess the suggested architecture.
IMPLEMENTATION OF THE DBSCAN METHOD FOR CLUSTER MAPPING OF EARTHQUAKE SPREAD LOCATION

West Java area is located on the Pacific Circum and Mediterranean Circum routes, this causes West Java area to be an unstable area that is characterized by many active working volcanoes and frequent earthquakes. An analysis of the grouping of earthquake data in West Java Province area is urgently needed. The purpose of this study was to classify areas based on the density of earthquake occurrence areas in West Java using Density-Based Spatial Clustering of Application with Noise (DBSCAN). The population in this study are all earthquake events occurred in 2021. While the sample used in this study is data on the location of the distribution of earthquakes in West Java Province in 2021 taken from the BMKG online data website at dataonline.bmkg.go.id. This research began with nearest-neighbor analysis to see patterns of data distribution. If the data distribution pattern is grouped, then DBSCAN analysis can be continued. The DBSCAN algorithm uses a combination of parameters, namely minimum points (MinPts) and epsilon (Eps). Cluster results are evaluated using the silhouette coefficient. Then, in this study, deeper data exploration was carried out in three ways, namely: (1) Clustering based on the highest silhouette value, (2) clustering by lowering the MinPts value, and (3) clustering based on the smallest upper limit (supremum) value of the silhouette coefficient. The data exploration here aimed to form more clusters while still considering the silhouette coefficient value limits so that there are more areas prone to earthquakes but also maintaining the validity of the results obtained. Next, determine the best cluster results by comparing the cluster results obtained. The best cluster results were obtained at Eps=10000 and MinPts=3 which formed 12 clusters with a silhouette coefficient value of 0.713, which means that the clusters have a strong structure. It is hoped that the information regarding the grouping of areas where earthquakes frequently occur can be used as a form of earthquake disaster mitigation and minimize the impact of losses due to the earthquake.
Menelaah Penerapam Total Quality Management pada Lembaga Perpustakaan

This study discusses the Strategy for the Implementation of Total Quality Management (TQM) in the Regional Public Library of South Labuhanbatu Regency. This study aims to determine the TQM planning process at the Regional Public Library of South Labuhanbatu Regency, to determine the process of organizing TQM at the Regional Public Library of South Labuhanbatu Regency, to determine the process of implementing TQM at the Regional Public Library of South Labuhanbatu Regency and to determine the process of TQM supervision at the Public Library. South Labuhanbatu Regency. This type of research is descriptive with a qualitative approach. The techniques used in data collection are interviews, observation, and documentation. While the data analysis technique went through three stages, namely, data reduction, presentation and drawing conclusions. The results of this study indicate that the strategy of implementing Total Quality Management (TQM) at the Regional Public Library of South Labuhanbatu Regency has been going well, both in terms of planning, organizing, implementing, monitoring, and evaluating, but libraries should be able to apply more TQM to improve quality in library services.
CLASSIFICATION OF ARRHYTHMIA DISEASES BY THE CONVOLUTIONAL NEURAL NETWORK METHOD BASED ON ECG IMAGES

Arrhythmia is a heart disorder that refers to an abnormal heartbeat rhythm. Arrhythmia detection uses an electrocardiogram (ECG) to describe the heart's electrical activity. This research aimed to know the performance of the Convolutional Neural Network method in classifying arrhythmia diseases based on ECG signal images. Several stages were used to classify arrhythmias: the pre-processing data stage, CNN model formation stage, model compiling, training, model testing, and evaluation. The CNN model architecture that is formed involves 7 Convolution Layers, 7 Pooling Layers, 2 Dropout Layers, 2 Dense Layers, and 1 Flatten Layer, as well as ReLu and Softmax activation functions. The input variable in the classification process with CNN is an ECG image. The output variable is the classification of ECG signals into 17 classes, including normal sinus and pacemaker rhythms. The processed data are 1000 images; the division scenario is 750 training data and 250 testing data. The result of arrhythmia's classification based on ECG image testing data using the CNN model shows the levels of Accuracy, Precision, Recall, and F1-score levels are 81%, 80%, 71%, and 73%, respectively, respectively. With the F1-score value as a measurement reference, the CNN model performs well in classifying ECG images
SPACED REPETITION CONCEPT DESIGN WITH FUZZY MULTI CRITERIA ANALYSIS AS A MEDIA TO IMPROVE NUMERACY LEARNING FOR ELEMENTARY SCHOOL STUDENTS

Numeracy Learning activities after the Covid-19 Pandemic has been decline in the quality of learning in a number of elementary school students. This research is limited to learning numeracy for low grade students, namely grade 1,2, and 3, because the basic concept of numeration begins with low grades There are several factors that make difficult for students to understand numeracy, the students often forget about the concepts that have been taught before. An Effective way of memorizing with the conventional way is memorizing with repeat pronunciations. To improve the quality of education, learning concepts that were previously carried out conventionally must be developed in a modern way using application. The purpose of this research is to improve the numeracy learning concept of low-grade students in primary school after Covid-19 pandemic which is more fun and modern by using the concept of spaced repetition based on android flashcards. The analysis of 135 student’s assessment is based on criteria such as tangible, reliability, empathy, responsive, and assurance. The decision support system using Fuzzy Multi Criteria Methods (MCDM) is also used to determine the weighting of the criteria and the effectiveness of learning using spaced repetition concept and it’s application. The result of the weighting using fuzzy multi criteria is obtained defuzzification that tangible 65.18, reliability 56.54, responsive 46.17, assurance 49.13, and empathy 29.62. Tangible has the highest results in this test, it means that the students prefer modern learning with android application with an attractive experienced. The correlation test obtained the result 0.76 which is a high value in decision making and could be accepted.
IMPLEMENTATION OF FUZZY TIME SERIES CHEN FOR FORECASTING INDONESIAN OIL AND GAS IMPORTS VALUE

Indonesia is an importing country that frequently imports goods from abroad continuously every year. Imported goods are oil and gas and non-oil and gas. Oil and gas includes oil and gas. This oil and gas import value data is an example of time series data, where the data is obtained from data recapitulation at the Central Bureau of Statistics (BPS). Time series analysis is a method for predicting an event that will come by looking at data from the previous time. One of the newest methods of time series analysis used in this research is Fuzzy Time Series Chen method. The purpose of this research is to find out how the implementation of Fuzzy Time Series Chen method in predicting the value of Indonesian oil and gas imports and to know the results of forecasting the value of Indonesian oil and gas imports. In predicting the value of Indonesia's oil and gas imports using Fuzzy Time Series Chen method, the results of forecasting the value of Indonesia's oil and gas imports in August 2022 were US$ 3743.213 million with a MAPE value of 19.969%.
RAINBOW VERTEX-CONNECTION NUMBER ON COMB PRODUCT OPERATION OF CYCLE GRAPH (C_4) AND COMPLETE BIPARTITE GRAPH (K_(3,N))

Rainbow vertex-connection number is the minimum colors assignment to the vertices of the graph, such that each vertex is connected by a path whose edges have distinct colors and is denoted by . The rainbow vertex connection number can be applied to graphs resulting from operations. One of the methods to create a new graph is to perform operations between two graphs. Thus, this research uses comb product operation to determine rainbow-vertex connection number resulting from comb product operation of cycle graph and complete bipartite graph &amp; . The research finding obtains the theorem of rainbow vertex-connection number at the graph of for while the theorem of rainbow vertex-connection number at the graph of for for .
DATA MINING STUDY FOR GROUPING ELEMENTARY SCHOOLS IN BOJONEGORO REGENCY BASED ON CAPACITY AND EDUCATIONAL FACILITIES

The implementation of national education must ensure equitable distribution of educational facilities. However, based on data from the Regional Education Balance Sheet (NPD) in 2021, elementary schools in Bojonegoro District still need to meet the criteria for overall equality. It is mainly related to educational capacity and facilities. It is necessary to group elementary schools based on capacity and educational facilities to solve this problem by applying the clustering method. The research aims to conduct a comparative study of three clustering methods to get the best way to be used for clustering elementary schools in Bojonegoro Regency. This study applies three clustering methods, namely K-Means, K-Medoids, and Random Clustering, which are compared to get the best clustering method. The data used is secondary data representing educational capacity and facilities, namely the number of students, teachers, classrooms, and study groups (Rombel) from the Bojonegoro District Education Office. Obtained the resulting comparison of clustering methods with the best way falls on the K-Means method, which forms 5 clusters. It explained that elementary schools with educational capacity and facilities get highly complete 14 schools (cluster_3), complete 236 schools (cluster_2), fairly complete 176 schools (cluster_4), less complete 310 schools (cluster_1), and incomplete 177 schools (cluster_0). The conclusion that comparing Clustering methods obtained grouping of Elementary School data with the best way falls on the K-Means method by getting 5 clusters.
APPLICATION OF EXTREME LEARNING MACHINE METHOD ON STOCK CLOSING PRICE FORECASTING PT ANEKA TAMBANG (PERSERO) TBK

Artificial neural networks are modeling methods that can capture complex input and output relationships. This method is widely used in forecasting and classification. However, in its application, there are some disadvantages in terms of low learning rate resulting in computational delay. Extreme Learning Machine (ELM) was introduced to overcome these problems. This method is believed to be able to produce more accurate forecasting results with a low level of forecasting error. In Indonesia, stocks are one of the most popular investments for investors. Stock prices tend to be volatile which is influenced by the amount of market supply and demand, so forecasting analysis is needed to minimize the risks that may occur. This research applies the ELM method to forecast the closing price of PT ANTM Tbk shares from January 1, 2018 - October 31, 2022. The data used is secondary data obtained from the official website https://id.investing.com. The ELM method is applied by dividing training data for ELM modeling and testing data used in the forecasting process. The model architecture of the ELM method uses a combination of inputs obtained from the PACF plot, hidden nodes with a range of 5-50, and one output layer. The results of this study show excellent forecasting accuracy in terms of forecasting. This is measured by the MAPE value of 0.0358. The architecture formed in the ELM process is one input, 31 hidden nodes, and one output. Forecasting the closing price of PT ANTM Tbk shares with 1-31-1 architecture produces a forecasting value that shows a low decline, but is quite stable.
INTELLECTUAL DEVELOPMENT AND EDUCATIONAL SUCCESS IN SECONDARY SCHOOLS

In this study, the features of the relationship between the intellectual level of students and their academic success in the training process, improving the quality of training, the special importance of measuring the intellectual abilities of students were investigated.With another expression, starting from the preparatory groups of students for school, their adaptation to the school environment, the formation of their knowledge, skills and habits, and later, in the elementary grades, their completeness, consciousness, systematicity, generality, etc. successes have been captured.The research was conducted in Julfa district of Nakhchivan city.In the article, it is explained in detail about the generalization of the research results, the reaching of the current intellectual limit, the high indicators, and the existence of a serious dependence between the students' success and their intellectual level, it has also been determined from the conducted research that high indicative students can achieve successful results in education.Sometimes the high level of these indicators also shows the high level of training success.The development of individual components of the intellectual structure of students who are applied an individual approach in the training process, mastering other subjects, etc. covered in detail.
Registry Application Design and Development

Registry is a central database that stores configuration settings on an operating system, in this case a Microsoft Windows. Registry on Windows OS usually contains information and settings for hardware, software and the operating system itself, non-system software. These settings are set by Key. In this study, the author makes a Registry system application which can edit, create and delete the Registry. To design this software, the writing uses the Visual Basic 6.0 programming language due to the convenience provided in the design and manufacture of programs
Implementation of the Least Significant Bit Method for Hiding Text in Digital Images

To speed up the process of sending secret messages, we need a medium for small messages that can still guarantee the confidentiality of the messages they contain. GIF (Graphics Interchange Format) is an image format that is one of the most commonly used formats on the web because of its small size and for encrypting the text that is sent. Encryption is carried out at the time of delivery by converting the original data into confidential data, while decryption is carried out at the time of receipt by converting the confidential data into original data. The most common way to hide messages is to use the Least Significant Bit (LSB). This research has succeeded in implementing the LSB algorithm to solve steganography on digital images in GIF format optimally
Applications send and receive SMS with Visual Basic 6.0

Communication technology has become an important part of various areas of life. Because of the many conveniences offered, communication technology can hardly be separated from various aspects of human life. With the rapid development of communication technology, it has had a positive impact on society. In addition, communication technology is capable of shortening distances, saving costs, and being able to penetrate space and time. Short Message Service or better known as SMS is now widely used by the public as a communication tool. The advantages of SMS are low cost, fast and direct to the destination. Starting from children, teenagers, adults to the elderly, almost all of them take advantage of this SMS technology. Initially, SMS was only used for interpersonal communication. But now with the times, SMS users are growing. For example, for polling an audition, accessing lecture scores, sending criticism and suggestions to the mass media for publication and many other uses. To be able to do these things, of course, support from adequate software &amp; hardware is needed
The Critical Determinants of Application of Blockchain Technology in Enhancing Cyber security in the Modern Technology Era

Blockchain is a framework that joins a unique arrangement of properties to ensure network security, straightforwardness, and perceivability, including a decentralized construction, conveyed records and capacity instrument, agreement convention, brilliant agreements, and uneven encryption. The following six factors—cybersecurity, corruption prevention, e-government advancement, effective governance, political stability, and democratic participation—were put to the test for blockchain adoption. The study demonstrates that political stability, government efficiency, and cybersecurity are important determinants. The possibility that a country will adopt blockchain technology is increased by elevated degrees of cybersecurity and effective government. Ironically, more political stability makes it less likely that blockchain technology will be adopted quickly. The Blockchain Drive filled in as the wellspring of information for blockchain reception, but it is important and crucial to systematically compile information on blockchain efforts throughout the world. Further data collection efforts by international donor organisations are required in order to improve the models for blockchain adoption.
Developing a Reinforcement Learning based Chess Engine

Traditionally, chess engines use handcrafted evaluation functions based on human strategy. Recently, machine learning has been used as an alternative to direct position scoring. However, this typically involves training a model on human matches. Reinforcement learning has been shown to be a viable machine learning approach that, when combined with self play, can train a neural network for chess position evaluation without the need for human domain knowledge. This paper discusses our implementation of a reinforcement learning based chess engine, trained using self play.