Reviewerly/exHarmony huggingface dataset:
INVESTIGATION OF AN OPTOELECTRONIC SYSTEM FOR DETECTING SMALL-SIZED AND INCONSPICUOUS OBJECTSUNDER THE INFLUENCE OF GEOMETRIC NOISE OF A MATRIX PHOTODETECTOR

The basis for reducing the accuracy of obtaining coordinate and non-coordinate information in an optical-electronic system with a matrix photo detector is geometric noise caused by uneven sensitivity and topology of the photodiode matrix. The presented mathematical model of a matrix photodetector based on the geometric array of photodiodes takes into account the main geometric parameters of the topology of the photodiode matrix. The questions of the accuracy of determining coordinates for small-sized and hardly noticeable light objects comparable to the size of a raster by the method of continuous wavelet transforms of signals from a photodiode array are considered. The possibility of geometric noise filtering by the method of continuous wavelet transform is shown by excluding from the scalogram the range of wavelet transform scales corresponding to the period of the geometric raster. It is shown that the algorithms of continuous wavelet transforms provide an increase in the accuracy of extracting the information component of small-sized and inconspicuous objects observed by an optoelectronic system with a matrix photodetector. A software prototype in the NI LabVIEW application development environment is presented. A technique has been developed for carrying out computational experiments to estimate the accuracy of determining the coordinate depending on the position of a small-sized light object relative to the topological raster of a matrix photodetector, as well as to estimate the detection sensitivity at a given noise level of photodiodes. An assessment of the accuracy of obtaining coordinate and non-coordinate information by a matrix photodetector under the influence of geometric noise has been carried out. It has been established that the filtering of geometric noise provides an increase in the detectivity of the optoelectronic system for detecting small-sized and inconspicuous light objects by more than one and a half times.
Audit Sistem Informasi Penjualan Pada UMKM MAM Menggunakan Framework Cobit 5

Information Technology (IT) has been applied by MAM MSMEs in marketing their products. The application of IT can certainly cause various problems such as what happened to MAM MSMEs, including problematic applications, product delivery accuracy, company human resources in it, and the use of technology that supports sales transactions. Based on these problems, an information system audit was conducted using Cobit 5 which focused on the EDM04 domain Ensure Resource Optimization, APO04 Manage innovation, APO07 Manage Human Resources, BAI08 Manage Knowledge, DSS01 Manage operations, MEA03 Monitor, Evaluate and Assess Compliance with External Requirements. The results of the study indicate that overall, based on the MAM MAM Cobit maturity level, it is at level F or Fully Archived. From the results of the GAP calculation, it was found that for all domains they had not reached the target level and needed improvements as well as improvements. Sales information system audit on MAM MSMEs using all domains has not reached the expected target level. For the calculation of the average maturity level of the six sub domains, namely 1.30 or 130%, which when viewed from the rating scale, it is included in level F, which has reached the Fully achieved value and from the rounding scale of the mapping index the condition of the model capability is at level 1, namely Performed. Process
PERANCANGAN SISTEM INFORMASI DATA APARATUR SIPIL NEGARA BERDASARAKAN URUTAN KEPANGKATAN BERBASIS WEB DI BAPPEDA KOTA JAMBI

At the Bappeda Office (Regional Development Planning Agency) Jambi City has 75 ASN (State Civil Apparatus) employees. So far, in the process of processing employee data, it is still in the conventional way with Microsoft Excel office applications and the data is not yet centralized, it is still scattered in each field, to obtain information or edit employee data, especially the focus of this research is on rank data information which is constantly available. changes, to obtain this information, it must take 2 to 3 days because they have to collect data from their respective fields, then the data is submitted to the Head of the Sub-Division of Personnel and Households, this makes the author think of creating an information system that is realtime and efficient in order to facilitate the performance of a Head of Sub-Division of Personnel and Household. System design is done by using DFD and ERD to model data and processes. With this system, it is hoped that it will make it easier for all ASN employees within the Jambi City Bappeda and related and interested agencies who have access to get the latest information.
SISTEM JADWAL PEMAKAIAN LABORATORIUM KOMPUTER PADA UNIVERSITAS MUHAMMADIYAH JAMBI

The laboratory is an academic support unit in an educational institution, in the form of a closed or open room that is permanent, managed systematically for teaching and learning activities, research, experiments as well as for practical and learning activities both individually and in groups. The laboratory at the Muhammadiyah University of Jambi has limited capacity, equipment and numbers because it is not proportional to the number of students, so students cannot master this value. These limitations can be overcome by scheduling the use of space. The current schedule for computer laboratory practicum can only be seen on the paper attached to the laboratory room and for the process of borrowing the laboratory, lecturers and students must come directly to the laboratory to communicate the laboratory loan to the head of the computer laboratory to see if there is an empty schedule. From the problems above, the purpose of this study is to design a Laboratory Usage Schedule System to make it easier for lecturers and students, especially the head of the laboratory, to access laboratory usage schedules regarding borrowing empty laboratories and substitutes for learning with the prototyping system method which results in increasing the effectiveness and efficiency of implementation to overcome existing problems
Penerapan Algoritma Support Vector Machine Pada Analisis Sentimen Hashtag Twitter

The development of the creative industry in Indonesia is marked by the emergence of content creators such as YouTubers and celebrities. With the emergence of content creators, people in these professions must be more creative and come up with new things in accordance with community trends in accordance with applicable laws in Indonesia. Twitter is one of the social media that can be used to share online and provide information in accordance with the prevailing trends in society. Hashtags or hashtags on Twitter are often used by users to add comments so that when the hashtag is used a lot it will become a trending topic. By analyzing sentiment on trending topics, positive and negative tendencies will be obtained that can help the content creator profession to create content. This study uses the Support Vector Machine (SVM) method to conduct a sentiment analysis process about the twitter hashtag. The data used is hashtag data on twitter. The data that has been obtained is then carried out by text preprocessing, then weighting, and finally sentiment analysis using SVM. This study uses tweet data taken on October 29, 2022 as many as 21 data, namely “BeliPulsaDiGrab” which has two sentiment classes, namely positive sentiment as much as 99% and negative 1% data
Pengembangan Model Machine Learning Regresi sebagai Web Service untuk Prediksi Harga Pembelian Mobil dengan Metode CRISP-DM

Along with the increasing public demand for car transportation modes, car sales businesses are also increasing. Efforts to exist and be competitive are carried out such as by applying machine learning models to determine the car’s selling price based on its specification. Businesses can also stimulate sales by actively offering customers. The effectiveness of the active and massive offerings can be increased by personalizing the offers provided. This research uses a machine learning-based approach to learn customer profile data to predict the car’s price they would buy. The research was conducted by adopting the CRISP-DM framework and developed using the Google Colaboratory and Azure Machine Learning platforms. The modeling stage developed six regression models, those are linear regression, Lasso, Ridge, Random Forest Regressor, Elastic-net, and Support Vector Regressor (SVR). After the evaluation stage, the Lasso regression model with the performance of R-squared (R2) of 0,99958 and Mean Absolute Error (MAE) of 2.284.865,29 deployed as a web service endpoint so it could be accessed in real-time. The web service required the customer’s “Gender, Age, Annual Salary, Credit Card Debt, and Net Worth” to return a response of the recommended car price range prediction for the customer to buy. In further development, predictions obtained through web services can be implemented in public applications to display personalized car sales offers or pages based on customer profiles
Sentimen Analisis Opini Masyarakat Terhadap Kebijakan Kominfo atas Pemblokiran Situs non-PSE pada Media Sosial Twitter

Kominfo is a state government agency in the field of communication and information. Some time ago Kominfo issued a policy, namely the blocking of sites that do not register themselves as PSE. This policy has become a hot topic on social media, especially Twitter. Therefore, this research was conducted by collecting public opinion, especially on Twitter for sentiment analysis. The goal is to be able to classify public responses into positive, negative and neutral opinions using the InSet Lexicon. In addition, the classification will compare several classification methods, namely Decision Tree, KNN, Naïve Bayes, Random Forest, Logistic Regression and SVM. The results of this study stated that as many as 1234 tweets that had been pre-processed tended to be negative with a percentage of 82.82%. while positive tweets are worth 10.53% and neutral tweets are 6.65%. The method with high accuracy value in this study is the KNN and Random Forest methods with an accuracy of 85.8%.
Penerapan Metode Harris Benedict Pada Media Informasi Kebutuhan Gizi Harian Berbasis Android

Calculation of nutritional needs is a way to find out a person's nutritional needs, which is usually done by nutritionists before compiling a diet menu. One formula that is often used is the Harris Benedict formula. The problem of this research is how to make an application for calculating nutritional needs with the Harris Benedict formula based on android mobile. This application aims to assist nutritionists and ordinary users in calculating nutritional needs through the results of calculations and dietary advice provided. The methodology in this study uses research and development which includes observation/data collection, interviews and literature study. As for software development using the waterfall model development method (waterfall). The implementation is built with the Java programming language, IDE (Integrated Development Environment) with Eclipse applications, Software Development Kit (SDK) which includes API (Application Programming Interface) tools. Testing is done by black box testing to evaluate the external appearance (Interface) and application functionality. This research has succeeded in implementing the Harris Benedict formula in an Android mobile-based nutritional needs calculation application that provides output for weight categories, ideal body weight, and dietary advice. Other features include a list of food and household sized tools, and an application guide. The purpose of this study is to produce an application that helps users calculate nutritional needs faster than manual calculations with correct results such as manual calculations. From the results of testing the application in black box, the results are in line with expectations.
Kinerja Algoritma Convolutional Neural Network dalam Klasifikasi Covid-19 Varian Omicron Berdasarkan Citra Ct-Scan Thoax

The second wave of the Covid-19 tsunami in India has broken the record for the highest number of additional cases and deaths in the world. Variant mutations are one of the contributing factors. Infection Crown variant Delta (B.1.617.2) is a mutation of the Covid-19 infection that has been endemic (SARS-CoV.2 B.1.617). The problem in this study is that the level of accuracy is still low in determining the covid-19 variant of the omicron resulting in uncertainty in decision makers by experts so that this research is needed to help with excellent accuracy measurements. The purpose of this study is to find a good model by applying the Convolutional Neural Network algorithm so that it can increase high accuracy and can be used in decision making by medical experts. The results of this study provide important information that the image size and the amount of input data greatly affect the level of accuracy in the Convolutional Neural Network method with the stages of data collection, preprocessing, Image Augmentation, Resize, Split Data, Convolutional Neural Network Architecture, Convolution, Pooling, Flattening, Full Connections, and Evaluations. Accuracy results with 400 input data produce training and testing (validation) on a chest x-ray image dataset using the Convolutional Neural Network architecture that has been created, 30 iterations (epochs) and 30 step_per_epochs showing an accuracy value of 0.88 or 88 % and the loss value is 0.3119 and the accuracy results with input data are 800 data, resulting in training and testing (validation) on the chest x-ray image dataset using the Convolutional Neural Network architecture that has been created, iterations (epochs) 30 times, and step_per_epoch as many as 30 shows an accuracy value of 0.93 or 93% and a loss value of 0.2711
Analisis Sentimen Tokopedia Pada Ulasan di Google Playstore Menggunakan Algoritma Naïve Bayes Classifier dan K-Nearest Neighbor

The growth of marketplace users in Indonesia continues to grow with one of the largest marketplaces being Tokopedia with a total download of more than 50 million. This achievement cannot be separated from the role of evaluating application performance by consumers on Google Play, this can affect other consumers' trust in the Tokopedia application. The purpose of this study is to conduct a sentiment analysis on application performance based on application user comments, where the dataset used in this study is 992 comments. The algorithms used in this research are nave Bayes algorithm and k-nearest neighbor. The results showed that the accuracy of the nave Bayes algorithm was 75.30% and the accuracy of the k-nearest neighbor algorithm was 86.09%.
Rancangan Sistem Aplikasi Edukasi Augmented Reality Mengenal Daerah Nusantara Indonesia Berbasis Android Menggunakan Unity

Along with the times, science is growing and increasingly studied. Science is usually summarized in a book which is often called an encyclopedia. The explanation in the book only contains two-dimensional theory and images. By applying Augmented Reality, making cultural recognition applications will be more interesting. Displays 3D images taken from 2D images so that they appear more vivid images. The application of Augmented Reality also encourages children to get to know culture more through interesting learning. It is hoped that students' proficiency in learning will rise with the help of this program. Based on the test results using Augmented Reality, it can be concluded that in order to get good results the user is asked to place the picture book in a flat place. This application does not succeed in displaying objects if the markerless is uneven
Analisis Kepuasan Pengguna Terhadap Sistem E–Raport Menggunakan Metode EUCS dan Model Delone and McLean

The problem discussed in this study is the E-Raport System used by SMK Muhammadiyah Lubuklinggau City, since the beginning of 2017 the use has never been evaluated, measuring the performance of the satisfaction of using the application. So that it is not yet known how effectively the application can help its users, so from this problem researchers Measure User Satisfaction from the success of the E - Report System in SMK Muhammadiyah Lubuklinggau City using the EUCS method and the McLean Model. This study is about analyzing the level of satisfaction of E-Raport users at SMK Muhammadiyah Lubuklinggau. This study aims to determine the application of the system that has been used and to determine the level of satisfaction of users of the E-Raport system at SMK Muhammadiyah Lubuklinggau. This study uses 2 methods of End User Computing Satisfaction (EUCS). ) and the Delone and McLean models. The EUCS method emphasizes user satisfaction, by analyzing the system based on content, accuracy, appearance, convenience and timeliness, while the Delone and McLean Model method analyzes system user satisfaction based on System Quality, Information Quality, Service Quality. This type of research is a descriptive type using research instruments in the form of a questionnaire. With 40 respondents, the results are valid and mutually influence user satisfaction. (This study uses a measuring instrument in the form of a questionnaire distributed to 40 respondents who are teachers of SMK Muhammadiyah Lubuklinggau). From the results of the analysis that has been carried out, the following results are obtained for the validity test using the EUCS method that is valid to use, and for the validity test the Delone and Mclean model method is valid to use, for the reliability test of the two reliable methods to be used, and for the results of the T test and test F stated that the two methods mutually influence user satisfaction
Rancangan Sistem Informasi Layanan Administrasi Desa Berbasis Web

Sukasih Village is a government agency at the sub-district level, until now it still has several problems in data management, one of which is the process of submitting correspondence for the benefit of the residents is still manual and has the impact of requiring a long processing time until the letter is completed, because residents have to come to the village office repeatedly. times, namely at the time of delivery and at the time of collection of the letter. Another problem is when storing citizen data is still manual and can cause documents to be damaged, lost and the risk of data not being updated. For this reason, it is necessary to have a letter submission information system that can be accessed by interested parties, both within the village and outside the village environment. The design of this system aims to implement and develop a technology information system as a forum for digitizing document submission in Sukaasih Village, in order to overcome or minimize errors in the local community document recording process and can shorten the time associated with administrative services to be easier, faster and more efficient. In designing this website-based document management information system, the system development method used is Rapid Application Development, and the PHP programming language. From the results of the validity test with an r table value of 0.433, the calculated r value for each question is as follows: P1 r count n is 0.4389, P2 r counts N is 0.8568, P3 r counts n is 0.8029 , P4 r count N is 0.8568, P5 r calculates N is 0.8857, P6 r calculates N is 0.8857, P7 r counts N is 0.8029, P8 r counts N is 0.8568, P9 r calculates N is 0.8857, P10 r calculates N is 0.8029, P11 r calculates N is 0.8029, and P12 r calculate the N is 0.4563
Prediksi Hasil Belajar Hybrid Menggunakan Artificial Neural Network Dengan Multilayer Perceptron

The implementation of online distance learning affects the psychosocial aspects of students so that a combination of offline and face-to-face learning is carried out using Hybrid Learning. The problem in this research is the analysis of the competencies that will be generated, student characteristics, face-to-face interactions, online learning strategies, and lecturers by calculating the data from the Hybrid Learning evaluation to get the best level of accuracy using the Machine Learning technique method. The purpose of this study is to evaluate the results of Hybrid learning using the Artificial Neural Network (ANN) method which is expected to have the right level of accuracy and prediction and tolerate errors so that it can produce good predictions and can be used to model good relationships in finding patterns in the data. . Prediction of Hybrid Learning learning outcomes during the Covid 19 pandemic using Machine Learning techniques consisting of 12 attributes with a total of 1,231 datasets of Hybrid Learning learning outcomes in 2022. The Artificial Neural Network algorithm model uses Retrive operators, Set Roles, optimization parameters, Cross Validation, Apply Models, Performance and Logs. Accuracy results show 99.35% meaning that the results of the learning evaluation using Hybrid Learning with predictions that match and turn out to be appropriate are 1039, then those that do not match are 8. The predictions are very suitable and turn out to be very suitable in 104. Artificial Neural Network with Multilayer Perceptron, with two hidden layer and the format of the first hidden layer is 2 nodes, then the second hidden layer is 5 nodes with an output of 3 nodes
Komparasi Metode Simple Addtive Weighting dan Weight Product Menggunakan Sistem Pendukung Keputusan pada Penerimaan BLT

Direct cash assistance is a program of local government efforts to deal with problems that occur in underprivileged families. This program is sought so that the community has less impact on economic growth and welfare. The methode used this system is.the.Simple Addtive Weighting (SAW) and Weight Product (WP) methods. Simple Additive Weighting (SAW) is a decision making process which in the process adds up the weights of the performance appraisal on all alternative attributes. While the Weight Product (WP) method is an analyst decision.methode for a multi-criteria decision making (MCDM) or multi - criteria decision making (MCDM). The existence of a comparison between the two methods is expected to help better select residents in receiving BLT so that they are more targeted. In this study resulted in a system to determine the citizens who are entitled to receive BLT, based on the result the study. Comparison of the SAW and WP methods using 20 alternative data, shows that the second method gets accurate data and is suitable if applied as a ranking of citizens in BLT receipts. In the ranking occupied by Burhan by getting the highest score on the 2 methods, there is an equal ranking of the 2 methods caused by the alternative performance scores, and the weight value of the first criterion in each method. Results Based on the research, is it recommended to use the SAW method to determine the ranking, cause the Ievel of suitability of.the.data in the field is higher than the WP found 99.40 WP found 99.20%.