Reviewerly/exHarmony huggingface dataset:
Facial expression recognition for a seven-class small and medium-sized dataset based on transfer learning CNNs

As one of the most common biological information for human to express their emotions, facial expression plays an important role in biological research, psychological analysis and even human-computer interaction in the computer field. It is very important to use the efficient computing and processing power of computers to realize automatic facial expression recognition. However, in the research process of this field, most people's technology and model achievements are based on large datasets, which lack the universality of small and medium-sized datasets. Therefore, this project provides an optimization model on a specific seven-class small and medium face image dataset and provides a possible technical optimization reference direction for facial expression recognition models on similar small and medium-sized datasets. During the experiment, the training performance of VGG16 and MobileNet is compared. A comparative experiment is set up to observe the effect of transfer learning mechanism on training results. The results show that transfer learning has a significant effect on the performance of the model, and the accuracy of the optimal test set is more than 90%. Regardless of whether transfer learning mechanism is used, the training performance of VGG16 model structure is better than that of MobileNet structure in the same dataset.
PEMETAAN KONTEN INFORMASI AKUN INSTAGRAM @PERPUSUINYOGYAKARTA

In this study examines an Instagram account @perpusuinyogyakarta. From this account the researcher collected uploads published by @perpusuinyogyakarta during January-December 2021. The purpose of this study was to find out what content was uploaded by the @perpusuinyogyakarta account and how the mapping of the Instagram account @perpusuinyogyakarta during January - December 2021 and what percentage. This study uses a quantitative descriptive method with a sample of 433 posts uploaded during January-December 2021 (1 year). Data collection techniques are observation and documentation study. The results showed that out of 433 posts of informational content and five indicators of library Instagram content, namely event indicators, internal indicators, speech indicators, library information indicators, and knowledge indicators. The most posted indicator is the indicator that shows information related to library information with 161 uploads or 39.07%, the second is information related to events or promoting events/activities with 88 uploads or 21.35%, the third is shows information related to speech with 78 uploads or with a percentage of 18.93%, the fourth is information that contains internal activities with 53 uploads or a total of 12.86%, and there is a low upload, namely information related to general knowledge or certain fields with 47 uploads or a total of 11.40%, and there is a follower response to content that is seen as quite active in the comments column which is communicative with the account manager @perpusuinyogyakarta such as comments that are praise or appreciation.
Analysis of the survey of voice synthesis technology

The original purpose of speech synthesis was to complete the task of converting from text to speech (TTS). With the application of deep learning models in this field of speech synthesis, the results of speech synthesis have gradually reached the level of human voice, which makes it widely used for voice assistant, navigation, reading, intelligent customer service, and many other aspects. In order to help readers expand more research ideas and understand the development process of speech synthesis technology and the ethical choices faced, this article introduces as much as possible in the development process of speech synthesis technology, several frameworks for optimization, as well as interpreting their respective advantages and disadvantages, summarize their approximate results obtained in the MOS test method and analyze the ethical issues that may be brought about by voice cloning technology.
Comparison on machine learning based algorithms for face expression recognition

With the development of machine learning methods, most of tasks has benefited from it. Numerous works have been done to improve the accuracy and robustness of these methods. In this paper, the authors aim to exploit the effectiveness of machine learning algorithms in face expression recognition (FER) task. Three methods, including support vector machine, random forest and convolutional neural network are introduced to test the performance in FER task. Three methods are tested in the public dataset, FER2013. The conclusion is drawn as follow. All these methods can handle the image recognition, which is a 7-class classification task. Furthermore, nerual network achieves the best performance, which achieves 65% accuracy. The paper exploit the potential of machine learning methods and give a brief attempt on applying the popular algorithms into real-world image recognition tasks.
A post-training quantization method applied to the game-environment-based Dueling-DQN model

Reinforcement learning is a common method that focuses on the best behaviors that agents can get the highest rewards for in one particular environment. It was recently combined with deep learning to improve information perception. However, the traditional deep reinforcement model DQN is considered to be as computationally intensive as its layer deplumation. As a result, this paper proposes to include a post-training quantization method in an improved version of DQN to see if it is worthwhile to include. After some experiments, the outputs exactly prove that post-training quantization can deduce the computation with a tiny precision loss.
Exploring hippocampus segmentation on unbalanced data set using U-Net-based models

This paper studies the performance of training the U-Net-based models on an unbalanced data set for hippocampus segmentation. It investigates through a series of ablation studies the effect of the weights in loss function, sampling method, model architecture, and learning rate type, and compare across different trials regarding their dice score and accuracy to identify the best strategy under class imbalance. Lastly, it displays numerical and graphical results before discussing potential implications and future directions.
Optimization of coverage path planning algorithm for robots

Abstract. In the era of technology gradually into the home, sweeping robots have become a must for many families. However, due to the lack of algorithms in the robot itself, there are still many problems with sweeping robots. In order to save cost and improve efficiency, it is necessary to improve the algorithm of robot coverage path planning. In this paper, we study the robot to complete full-area coverage path planning using sensors in an unknown environment. In this paper, the wavefront algorithm is combined with the traditional zigzag full-area path planning algorithm. The authors find that the combined algorithm speeds up the sweeping and reduces the repetition rate. Combining several different algorithms together like this can have more different applications in real life.
Predicting Solar Radiation Based on Meteorological Data Using Machine Learning Techniques: A Case Study of Isparta

Solar energy systems which is one of renewable energy sources takes more interest and gains prevalence day by day. As in other many renewable energy sources, a significant problem in solar energy systems is the unstability of the energy that the system will provide. Prediction of the energy to be obtained is very important in this respect. In this study, solar radiation is predicted using meteorological data taken from the General Directorate of Meteorology for Isparta. For predictions, the random forest (RF), KNN (k-Nearest Neighbor), ANN (Artificial Neural Networks) and Deep Learning (DL) methods are used. In addition, the results of dummy variable usage for time data are examined with these different methods. According to the findings obtained, it is seen that the dummy variable usage increases performance for ANN and DL methods but decreases performance for random forest and KNN methods. Best results are obtained for the prediction of the solar radiation with ANN and DL.
MENINGKATKAN KEMAMPUAN CALISTUNG ANAK TUNAGRAHITA DENGAN METODE VAKT (VISUAL, AUDIO, KINESTETIK, DAN TAKTIL)

Education is very important in the life of citizens and includes children with special needs which are also regulated by the state. According to the law, children with special needs have the right to get a quality education. Children with mental retardation, in learning to read, write, and count, of course, face obstacles in their cognition, mastery, use of language, and physical-motor abilities. Therefore they need learning methods to improve their cognitive. The purpose of this article review is to review scientific articles that discuss effective scientific methods for mentally retarded children. The method used is library research with reference sources obtained from Google Scholar. The criteria for articles used as references are journals published in the last 10 years from 2012-2021. The results of the selected review articles state that visual, audio, kinesthetic, and tactile methods can be applied as learning methods for mentally retarded children, by optimizing all sensory functions. The application of this method is considered effective for helping mentally retarded children in the learning process, especially in reading, writing, and arithmetic. With this, it is hoped that it can help improve the learning achievement of mentally retarded children.
PENGEMBANGAN MEDIA PEMBELAJARAN PAKU SARAJA PADA MATERI AKSARA JAWA UNTUK SISWA KELAS IV SD

This research is motivated by the results of observations made on fourth-grade students at SDN 1 Watudandang regarding students' difficulties in understanding and memorizing Javanese script. Some of the obstacles that arise include the limitations of learning tools and media. This research is Research and Development (Research &amp; Development) with the ADDIE research model. The purpose of developing the Paku Saraja learning media (Javanese Script Cube Board) on Javanese Script material is to improve the learning outcomes of fourth-grade students at SDN 1 Watudandang. Data collection techniques used are questionnaires and questionnaires. The data analysis technique is a qualitative data analysis technique. Based on the results of the study, which included material validity tests by material experts obtained an average score of 92 with very good eligibility criteria. Then the media validity test by media experts obtained an average value of 95 with very good eligibility criteria. The teacher's practicality test of the media obtained a score of 97 with very good eligibility criteria. As well as the practicality test of the media by students obtaining a score of 97 with very good eligibility criteria. Based on the product effectiveness test, many student scores increased above the KKM, namely 15 students out of 18 students. So, it can be concluded that the Paku Saraja learning media is feasible and effective for use in learning.
PENERAPAN TEKNIK KAIZEN BERBANTUAN ARENA NUMBERS GAME UNTUK MENINGKATKAN KEMAMPUAN NUMERASI SISWA SD NEGERI BANJARHARJO

Based on the 2021 education report card, the numeracy ability of students at SD Negeri Banjarharjo requires intervention. The application of kaizen-assisted game techniques is an action to solve the problem. It is based on the theory that regular and continuous habituation can foster internal motivation to like that habituation, including playing with numbers and numeracy. This research explores how the application of kaizen techniques assisted by arena numbers games at SD Negeri Banjarharjo and its impact on improving students' numeracy skills. The respondents in this study were 121 students in grades 1-6 of SD Negeri Banjarharjo. This research is qualitative descriptive research that uses observation, interviews, and study documents as data collection instruments. The data obtained were analyzed using data triangulation techniques. The results showed that the kaizen technique assisted by arena numbers games has been implemented well and is able to increase student motivation in processing numbers and can improve students' numeracy skills.
Bantuan Operasional Sekolah (BOS): Antara Aturan VS Implementasi di Sekolah Dasar Negeri 1 Padaherang Kecamatan Padaherang Kabupaten Pangandaran

There are still problems with the use of school operational funds, both in terms of coverage and use. This study aims to identify several problems, namely: How is the implementation, limitations and efforts to provide BOS financing for educational equity in SD Negeri 1 Padaherang in 2022. In this study the technique used was qualitative data analysis techniques using observation, interview and study techniques data. Based on the findings and discussion results regarding the use of School Operational Assistance funds, SDN 1 Padaherang in the implementation of the allocation of BOS funds has achieved success and is running on target in a directed manner. starting with the planning, implementation, monitoring and evaluation stages of implementation. BOS funds are used to pay for natural benefits, such as finding library reference works, paying for non-teaching activities, tests and exams. Implementation was constrained by delays in BOS funds at each payment stage and a lack of human resources such as the BOS Treasurer to use ARKAS (School Activity Plan and Budget Application). This causes difficulty in generating usage reports. Efforts to overcome obstacles in managing BOS funds are to first seek recovery funds, meanwhile schools provide technical guidance and ARKAS reporting training through the Cluster KKG group to fill gaps in ARKAS understanding that must be overcome.
Implementasi Algoritma C.45 Dalam Memprediksi Kualitas Aset Kendaraan Kantor

Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency is an institution under a government position consisting of several sub-sectors, one of which is the Assets Sub-sector. The BKAD Regional Asset Sub-sector in Banyumas Regency has a type of Goods Inventory Card (KIB) that has not been managed properly, including KIB for office vehicles making it difficult to make a proposal for office vehicle maintenance. Maintenance of office vehicles is the initial stage of replacing vehicles according to employee needs so that employee performance can be maximized. Forecasts for office vehicle maintenance are presented to facilitate the implementation of duties in carrying out business trips. The methods used in data collection are survey methods, literature, and interviews. The data collection method used in this report uses a quantitative method with the C.45 algorithm. Predicting the quality of office vehicles can carry out several stages such as reviewing office vehicles, classifying the condition of office vehicles, after that a decision is made on which vehicles are suitable for use or not suitable for use. Analysis of predicting the quality of office vehicles using the C.45 algorithm with the rapidminer application can produce results in the form of a decision tree that is used by the asset sub-sector in order to make a decision. Based on the prediction results of office vehicle quality, it can be concluded that office vehicles will be suitable for use if the year of purchase or procurement is more than 2000 and office vehicles will not be suitable for use if the year of purchase or procurement is less than or equal to 2000. If you want to compare the results obtained it is advisable to use other tools or algorithms to make the next report.
Implementasi Triple Exponential Smoothing dan Double Moving Average Untuk Peramalan Produksi Kernel Kelapa Sawit

The production of palm kernel is a significant product for the company and plays a crucial role. Nevertheless, the stability of kernel production is not always consistent, and the quality of the kernel can be detrimental to the company. As consumer demands change over time, companies must anticipate every fluctuation in palm kernel production. Hence it is vital to figure the long run with a settlement prepare utilizing information mining utilizing information within the past. The Triple Exponential Smoothing and Double Moving Average methods, which are data mining methods for future forecasting, were used in this study. The aim of this research is to predict the yield of future oil palm kernel production using the Triple Exponential Smoothing and Double Moving Average methods and to determine the level of forecasting errors using the Mean Absolute Percentage Error (MAPE) method. The data for the last ten years, from January 2013 to December 2022, were used in this study. After testing the Triple Exponential Smoothing method with parameters α=0.2,β=0.γ=0.2, the error rate using MAPE was 9.48%, and the Double Moving Average method had an error rate of 11.2%. The MAPE results of the Triple Exponential Smoothing method are considered very good, while the MAPE results of the Double Moving Average method are categorized as good based on the range of MAPE values. This research is expected to provide information to related companies as a supporting reference in anticipating palm oil kernel production. The conclusion of the research is that the Triple Exponential Smoothing method with the test parameters is the best method for forecasting.
Analisa Sentimen Ulasan Aplikasi Wetv Untuk Peningkatan Layanan Menggunakan Metode Naïve Bayes

The most popular online streaming application is WeTV. WeTV is an internet-based streaming service that is used by the public as an entertainment medium. The WeTV application has been downloaded by up to 50,000 users. Application user ratings may affect the image of the application depending on the services provided by the application developer. Many positive, neutral and negative reactions have had a big impact on WeTV. Categorizing user ratings cannot be done manually because it is not easy with very large amounts of data. Therefore, the purpose of this research is to analyze the user rating of the WeTV application on the Goggle Playstore. In this study the processing steps consisted of cleaning, case convolution, tokenization, normalization, stopword and vape removal, after which it was continued with the TF-IDF step and the final result was a confused matrix using the Python programming language with Naive Bayes classifier. method in this research. Using 12,000 reviews found on Google Playstore. to generate positive, negative and neutral sentiments from Wetv application user comments in the play store. The test with the highest precision value of 0.64% with a -1 precision value of 0.58% in Class Recall gives a value of 0.89% in the 90%:10 balance model.
Analisis Kesiapan Pemerintahan Kota Prabumulih Dalam Implementasi E-Government Menggunakan Metode Technology Readiness Index (TRI)

E-government s an nformation technology system developed by the government to mprove public services by providing choices to the public to get easy access to public nformation. For this reason, socialization of e-government needs to be carried out consistently, continuously and with ncentives to the community because the community does not yet understand what and how e-government applications are and the benefits they can get. The problem that occurs at this time s that t s not known how far the level of readiness of the Prabumulih City Government s n the use and application of nformation technology, especially E-Government. Because of this, t s necessary to carry out an analysis or assessment of the readiness to apply nformation technology, n this case the Government of Prabumulih City. The solution offered s to carry out a readiness analysis using the TR method or Technology Readiness (TR) which s a person's tendency to want to use a new technology that aims to achieve everyday life or n the workplace. Meanwhile, the Technology Readiness ndex s an ndex used to measure the readiness of new technology users to achieve goals n everyday life and work. n order to support the Government of Prabumulih City to carry out eGovernment mplementation with the help of nformation and communication technology, t opens new opportunities to further explore nformation so that t can be utilized optimally. E-Government users cover a wide population, both for government, citizens and business people, so that n the end a mutually beneficial relationship s created. The results obtained from this study are Optimism has a value of 1.51, nnovativeness has a value of 1.24, Discomfort has a value of 0.69 and nsecurity has a value of 0.64. The total results show that the relevant agencies are ready to mplement technology.
Penerapan Metode Design Thinking dan Agile dalam Rancang Bangun Aplikasi Penjualanku

Design thinking is a method that concentrates on generating ideas and solutions that begin with a process of empathy for a need that focuses on a human or user perspective. The stages of design thinking can be done repeatedly to improvise ideas and solutions so that they are responsive and adaptive to change. Agile is a software development method in which the stages can be repeated to form a cycle, this is done because the agile method is very concerned about the value of a product. The Anindya Collection is UMK of men's batik clothing that they produce themselves and sell under their own business brand name, Anindya Collection. Problems often occur in managing sales data and recapitulating sales data which is still done manually, namely handwriting in a book, making it less effective and efficient. UMK has a role in boosting the Indonesian economy, so limitations should not prevent UMK from innovating. In this study the authors implemented the Design thinking and Agile Methods in Designing the My Sales Application at Anindya Collection). In this study, the authors concluded that the design thinking method helps improvise ideas and solutions to changes prior to the development stage using agile methods. Meanwhile, agile methods help implement ideas and solutions generated from the design thinking stage.
Data Mining Untuk Melihat Minat Belajar Siswa Menerapkan Metode K-Means

Due to the lack of motivation to learn and learning method using the old method which is very boring, learning planning is currently a burden for educators and educthe ation of children at the junior high level. As a result, the purpose of this study aims at a learning system to create a learning plan for children using ICT. This educational institution known as Al-Furqon can be found in Kadudampit District, Sukabumi Regency. Outdated lecture methods are still used in teaching and learning activities in this school. Because it was previously used as a means of oral communication between teachers and students during the teaching and learning process, this method affects learning in MTs because it cannot be left behind in teaching activities even though it requires more teacher activities than students. Al-Furqon. There was no interesting interaction between students and teachers, and as a result, they became increasingly dissatisfied with traditional teaching approaches, K-Means algorithms and Data Mining techniques were used in the study. Clustering is also used. Data on Teaching Method Value, Learning Facility Value, Grade Condition Value, Environmental Influence Value, and Teacher Professionalism Value were used for testing in this study. to find out students' interests in school by grouping their data and applying K-Means Clustering analysis. It is hoped that after the number of students who are lacking or not interested in learning is identified, it will become the basis for this website design system to be a solution to the problem.