bluuebunny/crossref_metadata_2025_split huggingface dataset:
EMPLOYEE PERFORMANCE IMPROVEMENT THROUGH COMPENSATION AND WORK DISCIPLINE AT PT. ICHTIAR GUSTI PUDI IN LANDAK REGENCY
Authors: Pranoto Desmi , Kurniati Dewi , Suharyani Anita 
Published: April 2022

Human resources are central in an institution or company. So that management activities run as desired, the company must have employees who are knowledgeable, qualified skills, and ability to manage their businesses as much as possible so that employee performance will increase. The level of success of a company can be judged based on performance. Employee performance increases if the provision of adequate compensation and good work discipline. Through this research is to analyzes the influence of compensation and discipline on employee performance at PT. Ichtiar Gusti Pudi, Landak Regency. The location of this research at Pagong Hamlet, Amboyo Inti Selatan Village, Ngabang District, Landak Regency. This study is a population study by giving a questionnaire to the entire population of 108 people consisting of maintenance employees in all parts of the company. The data were obtained using a questionnaire with a Likert scale 1-5 scoring technique. The method of analyzing data using SEM is assisted by LISREL 8.80 software. The results show that compensation has an effect on employee performance. It appears that the t-value of the compensation variable is 3.05> 1.96. Work discipline has an effect on employee performance, with the t-value of the variable being 2.28> 1.96.
DETERMINING THE PRIORITY OF THE MARKETING MIX OF THE KUANTAN-II FRIED BANANA AGROINDUSTRY BUSINESS IN THE SUB-DISTRICT OF LIMA PULUH KOTA PEKANBARU USING AHP METHOD
Authors: Maisari Astrie Vita , Nizar Rini , Yasid Hamdan 
Published: April 2022

The purpose of this research is to analyze the priority of the right marketing mix decision in the fan-fried banana agro-industry Kuantan-II. The research method for drawing samples was carried out by using purposive sampling technique. The data analysis method to analyze the priority of the marketing mix uses the AHP (Analytical Hierarchy Process) method manually using Excel software.From the results of the priority research analysis of the Marketing Mix (Marketing Mix) in the Kuantan-II Fan Fried Banana agro-industry, it is known that: Producers or Business Actors of Kipas Kuantan-II Fried Banana must innovate because it produces the highest weight (0,522), the Marketing Mix that must be done Producers prioritize products with the highest weight (0,361), compared to Price with a weight (0,310), Promotion with a weight (0,166), and Distribution with a weight (0,161). The sub-mix on product variables that must be considered by producers or business actors is product quality with the highest weight (0,477). Business actors should innovate on their products, considering the increasingly fierce competition at this time. Innovations such as starting to penetrate into e-commerce will make the reach of consumers wider in the current era of digitalization. In addition, business actors must maintain the quality of their products so that consumers always trust and do not switch to similar competitors. In the promotion variable, business actors should promote their company without always involving other agencies. Although promotion is the third priority in the marketing mix variable, business actors must continue to carry out promotions because with the existence of "promotions" old or new products can be known or known by consumers, especially consumers in the Pekanbaru area.
Peran Orientasi Pasar dan Inovasi dalam Menciptakan Keunggulan Bersaing dan Kinerja Pemasaran Kalangan Konsumen Muslim/ Muslimah pada UKM Batik di Wilayah Jember
Authors: Shodiqin Dimas Herliandis , Rhain Ainur 
Published: April 2022

Tujuan dari penelitian ini adalah untuk menguji pengaruh orientasi pasar terhadap keunggulan bersaing pada UKM Batik di Kabupaten Jember; untuk menguji pengaruh Inovasi produk terhadap keunggulan bersaing pada UKM Batik di Kabupaten Jember; untuk menguji pengaruh orientasi pasar terhadap kinerja pemasaran pada UKM Batik di Kabupaten Jember; untuk menguji pengaruh Inovasi produk terhadap kinerja pemasaran pada UKM Batik di Kabupaten Jember; untuk menguji pengaruh keunggulan bersaing terhadap kinerja pemasaran pada UKM Batik di Kabupaten Jember.Penelitian ini menggunakan pendekatan kuantitatif. Jenis penelitian yang dipakai adalah penelitian explanatory. Populasi penelitian adalah Konsumen Batik Asli Jember Seperti Batik Rolas, Notohadinegoro Dan Batiak Sumber Jamber di Kabupaten Jember. Sampel penelitian sebanyak 100 orang. Metode analissi data menggunakan Structural Equations Model (SEM) dengan uji validitas dan reabilitas konstruk, uji asumsi SEM dan pengujian hipotesis. Haisl penelitian ini menunjukkan bahwa orientasi pasar dan inovasi produk terhadap keunggulan bersaing dan kinerja pada UKM Batik di Kabupaten Jember;
Garda Pangan; Inovasi Gerakan Filantropi Islam Berbasis Lingkungan
Authors: Nur Khayyis , Bakir Abdul Hamid 
Published: April 2022

Indonesia merupakan salah satu Negara pembuang sampah makanan terbesar kedua di dunia. Limbah makanan (food waste) yang tidak terkontrol dengan baik akan menjadi timbulan limbah yang tentu sangat membahayakan lingkungan. Surabaya sebagai salah satu kota terbesar tidak mampu mengatasi permasalahan limbah makanan (food waste) . Maka dari itu, Garda Pangan hadir sebagai salah satu Startup sosial guna menyelamatkan makanan yang masih layak dan disalurkan kepada warga yang membutuhkan.Adapun tujuan dari penelitian ini adalah (1) mendeskrispsikan potensi dan asset komunitas Garda Pangan. (2) mendiskripsikan upaya garda pangan dalam menjaga lingkungan (3) Melihat peran Garda Pangan sebagai gerakan filantropi islam berbasis lingkungan. Hasil pengumpulan data dianalisis menggunakan pendekatan ABCD (Asset Based Community Development) dan Analisis Deskriptif. Hasil penelitian ini menjelaskan bahwa Garda Pangan sebagai salah satu Food Bank (bank makanan) maka kegiatan Garda Pangan berpusat pada 3 hal, yaitu : (1) penyelamatan limbah makanan (food waste),(2) pembelian atas hasil panen yang berlimpah (gleaning up) hasil pertanian yang melimpah, dan (3) mengemas, atau memproduksi kembali makanan yang memiliki tampilan buruk (ugly produce) namun terjamin kualitasnya. Potensi komunitas garda pangan dalam pendekatan ABCD meliputi aset manusia, aset fisik, aset sosial, aset finansial, dan aset alam. Selain itu, Sebagai salah satu gerakan filantropi islam, komunitas Garda Pangan berupaya untuk memberikan sumbangsih sosial bagi masyarakat dan tentunya bertujuan untuk menyelamatkan lingkungan dari bahayanya limbah makanan.
Heuristic self-organization of knowledge representation and development: analysis in the context of explainable artificial intelligence
Authors: Dotsenko Sergiy , Kharchenko Vyacheslav , Morozova Olga , Rucinski Andrzej , Dotsenko Svitlana 
Published: April 2022

From the analysis of the main theoretical provisions of heuristic self-organization systems and logical models, it follows that according to O. G. Ivakhnenko's systems of heuristic self-organization, the first task is to determine the factors content “that determine the essence of different images”. These are the images that characterize the objects of a particular subject area. After determining the composition and content of these images, the next problem is solved, namely, the problem of “generating the new successful heuristic”, which in content is a solution that leads to increased accuracy. Note that we are talking about improving the accuracy of solving the problem of data processing. It follows from the above mentioned that heuristic self-organization systems are data processing systems. This allows the multiplicity of heuristics. Heuristics in content correspond to the logical rules applied in heuristic self-organization systems. The main provisions of the heuristic self-organization system theory were developed by O. G. Ivakhnenko in the eighties of the last century, but they remain unnoticed to this day. At this time, the task is to explain why the neural network makes such a decision and not another. Based on this, the concept of “explainability of artificial intelligence” was introduced for artificial intelligence. It is the content of heuristics that forms the structure of the neural network in the form of logical rules and determines the logic of the decision made. It is established that the derivation rule, which is the basis for constructing artificial neural networks, is an abductive rule, which, unfortunately, does not meet the fourth heuristic and does not meet the definition of intelligence: intelligence is the ability to measure things. Unfortunately, none of the neural networks can measure things. From the analysis of the basic rules content of inference, it follows that the dialectical method of inference is general (generating) for the basic logical methods of inference. The difference lies in the composition and content of the middle member of the triangular relationship, namely, in the form of the element combination of the relationship: the transition from one concept to another. The explainability of artificial intelligence refers to the laws of the structure and activity of artificial neural networks. But modern theories of artificial neural networks ignore the existence of logical rules (heuristics), which were established by O. G. Ivakhnenko. After all, only knowing the rules based on which problems are solved, it is possible to check the correctness of the decision, but not by searching for such rules. The three hypotheses about the explainability of artificial intelligence and the theory of machine identification can be further defined as statements or theorems and strictly proved.
Convolutional neural network hyperparameter optimization applied to land cover classification
Authors: Yaloveha Vladyslav , Podorozhniak Andrii , Kuchuk Heorhii 
Published: April 2022

In recent times, machine learning algorithms have shown great performance in solving problems in different fields of study, including the analysis of remote sensing images, computer vision, natural language processing, medical issues, etc. A well-prepared input dataset can have a huge impact on the result metrics. However, a correctly selected hyperparameter combined with neural network architecture could highly increase the final metrics. Therefore, the hyperparameters optimization problem becomes a key issue in a deep learning algorithm. The process of finding a suitable hyperparameter combination could be performed manually or automatically. Manual search is based on previous research and requires enormous human efforts. However, there are many automated hyperparameter optimization methods have been successfully applied in practice. The automated hyperparameter tuning techniques are divided into two groups: black-box optimization techniques (such as Grid Search, Random Search) and multi-fidelity optimization techniques (HyperBand, BOHB). The most recent and promising among all approaches is BOHB which, which combines both Bayesian optimization and bandit-based methods, outperforms classical approaches, and can run asynchronously with given GPU resources and time budget that plays a vital role in the hyperparameter optimization process. The previous study proposed a convolutional deep learning neural network for solving land cover classification problems in the EuroSAT dataset. It was found that adding spectral indexes NDVI, NDWI, and GNDVI with RGB channels increased the result accuracy (from 64.72% to 84.19%) and F1 (from 63.89 % to 84.05%) score. However, the convolutional neural network architecture and hyperparameter combination were selected manually. The research optimizes convolutional neural network architecture and finds suitable hyperparameter combinations applied to land cover classification problems using multispectral images. The obtained results must increase result performance compared with the previous study and given budget constraints.
Technique for IoT malware detection based on control flow graph analysis
Authors: Bobrovnikova Kira , Lysenko Sergii , Savenko Bohdan , Gaj Piotr , Savenko Oleg 
Published: April 2022

The Internet of Things (IoT) refers to the millions of devices around the world that are connected to the Internet. Insecure IoT devices designed without proper security features are the targets of many Internet threats. The rapid integration of the Internet into the IoT infrastructure in various areas of human activity, including vulnerable critical infrastructure, makes the detection of malware in the Internet of Things increasingly important. Annual reports from IoT infrastructure cybersecurity companies and antivirus software vendors show an increase in malware attacks targeting IoT infrastructure. This demonstrates the failure of modern methods for detecting malware on the Internet of things. This is why there is an urgent need for new approaches to IoT malware detection and to protect IoT devices from IoT malware attacks. The subject of the research is the malware detection process on the Internet of Things. This study aims to develop a technique for malware detection based on the control flow graph analysis. Results. This paper presents a new approach for IoT malware detection based on control flow graph analysis. Control flow graphs were built for suspicious IoT applications. The control flow graph is represented as a directed graph, which contains information about the components of the suspicious program and the transitions between them. Based on the control flow graph, metrics can be extracted that describe the structure of the program. Considering that IoT applications are small due to the simplicity and limitations of the IoT operating system environment, malware detection based on control flow graph analysis seems to be possible in the IoT environment. To analyze the behavior of the IoT application for each control flow graph, the action graph is to be built. It shows an abstract graph and a description of the program. Based on the action graph for each IoT application, a sequence is formed. This allows for defining the program’s behavior. Thus, with the aim of IoT malware detection, two malware detection models based on control flow graph metrics and the action sequences are used. Since the approach allows you to analyze both the overall structure and behavior of each application, it allows you to achieve high malware detection accuracy. The proposed approach allows the detection of unknown IoT malware, which are the modified versions of known IoT malware. As the mean of conclusion-making concerning the malware presence, the set of machine learning classifiers was employed. The experimental results demonstrated the high accuracy of IoT malware detection. Conclusions. A new technique for IoT malware detection based on control flow graph analysis has been developed. It can detect IoT malware with high efficiency.
Methods and algorithms for protecting information in optical text recognition systems
Authors: Dergachov Konstantin , Krasnov Leonid , Bilozerskyi Vladislav , Zymovin Anatoly 
Published: April 2022

The subject of the study. A concept of OCR systems performance improvement is proposed, which is achieved through the integrated use of special algorithms for preliminary processing of documents picture, an extended set of service functions, and advanced techniques for information protection. Study objectives: development of algorithms that compensate for the influence of the unfavorable points like imperfect lighting conditions overshooting, images geometric deformation, noises, etc., which corrupt the pictured text, on the efficiency of that text recognition. It is needed to provide for a series of service procedures that would ensure adequate data handling while viewing, converting, and storing in standard formats the results, and ensuring the possibility to exchange data in open communication networks. Additionally, it is necessary to ensure the information protection against unauthorized use at the stage of data processing and provide secretiveness of their transmission through the communication channels. Investigation methods and research results: developed and tested algorithms for preliminary picture data processing, namely, for the captured image geometry transformation, picture noise correction with different filters, image binarization when using the adaptive thresholds reduced the negative influence of irregular image portions illumination; in the software, the special services ensure the data processing ease and information protection are affected. In particular, the interactive procedure for text segmentation is proposed, which implies the possibility of anonymizing its fragments and contributes to collecting confidentiality for documents treated. The package for processing document shots contains the face detection algorithm bringing the identification of such information features; it can be used further in the task of face recognition. After the textual doc is recognized, the received data encryption is provided by generating a QR-code and the steganography methods can deliver the privacy of this information transmission. The algorithms' structures are described in detail and the stability of their work under various conditions is investigated. Focused on the case study, docs' text recognition software was developed with the usage of Tesseract version 4.0 optical character recognition program. The program named "HQ Scanner" is written in Python using the present resources of the OpenCV library. An original technique for evaluating the efficiency of algorithms using the criterion of the maximum probability of correct text recognition is implemented in the software. Conclusions. The study results can constitute the basis for developing advanced specialized software for easy-to-use commercial OCR systems.
Adaptive two-step method for providing the desired visual quality for SPIHT
Authors: Li Fangfang 
Published: April 2022

Lossy compression has been widely used in various applications due to its variable compression ratio. However, distortions are introduced unavoidably, and this decreases the image quality. Therefore, it is often required to control the quality of the compressed images. A two-step method has been proposed recently to provide the desired visual quality. The average rate-distortion curve was used to determine the proper parameter value that controls compression. However, its performance for the wavelet-based coder Set Partitioning in Hierarchical Trees (SPIHT) is insufficient because there are very wide limits of visual quality variation for different images for a given value of the compression control parameter (CCP). Additionally, previous work has demonstrated that the level of errors, which is the subject of our study relates to texture features of an image to be compressed, where texture presence is an inherent property of remote sensing images. In this paper, our goal is to develop an adaptive two-step method for SPIHT to improve accuracy. The following tasks were solved. First, a prediction of visual quality for a particular parameter value is conducted. The prediction scheme is based on the information extraction from a certain number of image blocks to perform a visual quality calculation of the image compressed for a given CCP value. A threshold is adopted as the complexity grouping; in this paper, images are divided into two groups: simple and complex images. Second, the results of the grouping determine the adaptive curve model adopted. Finally, a two-step compression method is applied according to this curve. The classical metric Peak signal-to-noise ratio (PSNR) is employed to evaluate the image quality. The research method is based on a validation experiment that is conducted for an image set covering different image complexity and texture features. The comparison results of four typical desired values prove that the accuracy has been generally improved, the variances of both the first and second steps have been reduced sufficiently, and the mean absolute error has also been improved. Conclusion: the improvement effects are significant, particularly in the low desired visual quality. A remote sensing image is taken as an example to analyze in detail; the quality of the decompressed images meets the user’s visual requirement, and the errors are acceptable.
Utilization of Scallop Shells (Placuna placenta) for Potential Water Filter Prototype in Jaring Halus Village, Jaring Halus-Langkat District and the Characterization Test
Authors: Sihotang Muhammad Sontang 
Published: April 2022

Indonesia is a maritime country that has abundant marine wealth. Unfortunately, most fishers still live in poor conditions, including Jaring Halus Village, Secanggang District, Langkat Regency, North Sumatra Province. Previous research has shown that there is much coastal waste, such as Scallop Shells (Placuna placenta), that are not treated, even though it has the potential to help people who are experiencing water crises to get clean water sources. This study aimed to characterize the shells of Scallops and produce calcium carbonate as an activated carbon product to produce clean water. The method used to characterize the mashed scallop shells is X-Ray Diffraction (XRD). In this study, three different sizes, namely 25 μm, 90 μm, and 150 μm, will be compared, and the size and quality selected to produce the best calcium carbonate were tested at different temperatures, namely 800°C, 900°C, 1000°C, and 1100°C. In the x-ray diffraction analysis test, the smallest particle is 25 μm, which has the highest intensity compared to other sizes. The best particle size, which is heated/calcined at a temperature of 1100, has the highest intensity, which can remove all impurities and produce natural calcium carbonate, which is more stable. Based on the study results, it can be concluded that the best calcium carbonate is produced from particles with a size of 25 μm which are calcined at the highest temperature of 1100°C.
Waktu-waktu efektif belajar menurut para ulama dan santri
Authors: Rachmat Rachmat , Mujahidin Endin , Tamam Abas Mansur , Alim Akhmad 
Published: April 2022

<p><em>The purpose of this study was to determine the effective times in the learning process. Through this study, researchers have come to a conclusion that in general there are certain times that are very suitable and primarily used in learning time. Saw., Then refined with field research by examining the use of study time in Islamic boarding schools. From the results of this study showing that in general, the most effective time to study is in the morning, because in general it is a fresh time, so morning is the most productive time to do anything, including learning process. This conclusion is in line with the opinion of the scholars. Furthermore, in detail each time has the most suitable activity from each learning process; Sahur time and evening time are more suitable for memorizing; while the night time is more suitable for repeating and analyzing; and the time of day is more suitable for writing and copying knowledge.</em></p><p align="center"><strong> </strong></p><p align="center"><strong>Abstrak</strong></p><p>Tujuan penelitian ini adalah untuk mengetahui waktu-waktu efektif dalam proses belajar. Melalui kajian ini peneliti telah sampai pada sebuah kesimpulan bahwa secara umum ada waktu-waktu tertentu yang sangat cocok dan utama digunakan dalam waktu belajar. Saw.. Kemudian dilengkapi dengan penelitian lapangan dengan meneliti penggunaan waktu belajar di Pondok Pesantren. Dari hasil penelitian ini menunjukkan bahwa secara umum, waktu yang paling efektif untuk belajar adalah waktu pagi, karena memang secara umum ia merupakan waktu segar, maka pagi merupakan waktu paling produktif untuk mengerjakan apa saja, termasuk proses belajar. Kesimpulan ini sejalan dengan pendapat para ulama. Selanjutnya, secara rinci setiap waktu mempunyai aktivitas yang paling cocok dari masing-masing proses belajar; waktu Sahur dan waktu sore lebih cocok untuk menghafal; sedangkan waktu malam lebih cocok untuk mengulang dan menganalisis; dan waktu siang lebih cocok untuk menulis dan menyalin ilmu.</p>