Reviewerly/exHarmony huggingface dataset:
Academic Citizenship Behaviour Mediates Between Green Performance Management, Green Training and Development, and Organization Environmental Performance in The Jordanian Government Universities

Authors:
raw_author_name: Yusnita Yusof

Abstract: Purpose: This paper aims to examine the academic citizenship behaviour mediating the effect between Green Performance Management, green training and development, and organization environmental performance in Jordanian government universities. Research methodology: The paper contributes to filling this research gap by examining these effects. A sample of 404 employees in the Jordanian Government universities was analysed using contemporary variance-based structural equation modelling (Amos - SEM) software. Results: Results: The findings revealed a favorable correlation between green training and development and two key variables: academic citizenship behavior and organizational environmental performance. Similarly, a positive relationship was observed between green performance management and both academic citizenship behavior and organizational environmental performance. Additionally, a direct positive association emerged between academic citizenship behavior and organizational environmental performance. Moreover, the results unveiled the mediating role of academic citizenship behavior in the relationship between green training and development, as well as green performance management, and organizational environmental performance. Conclusion: This study offers valuable insights for HRM practitioners, emphasizing the significance of Green HRM practices in augmenting organizational environmental performance.
CREATIVE THINKING PROCESS IN STUDENT‘S SCIENTIFIC WORKS

Authors:
raw_author_name: Dawud Dawud
raw_affiliation_string: Fakultas Sastra, Universitas Negeri Malang
raw_author_name: Heri Suwignyo
raw_affiliation_string: Fakultas Sastra, Universitas Negeri Malang
raw_author_name: Abdul Wahid
raw_affiliation_string: Fakultas Keguruan dan Ilmu Pendidikan, Universitas Muhammadiyah Makassar

Abstract: This study aims to explain the process of creative thinking, including analytic, evaluative, applicative, and interpretative students in scientific work. The scientific works studied were in the form of Student Creativity Program, State University of Malang, Indonesia. This research uses a qualitative approach with a content analysis method. This research data in the form of paragraphs, paragraph clusters, and full text. The data source of this research is the scientific work of students. The research data collection technique was carried out by survey and documentation study. The process of data analysis is grouped into three stages, namely data reduction, data presentation, and drawing conclusions. The findings of this study indicate that the process of creative thinking in writing scientific papers can be done with four stages (1) the analytic stage in scientific work looks at the examination of arguments. (2) Evaluative in scientific work looks at the assessment of arguments in accordance with the topic of study. (3) Applicative in the work appears in arguing according to procedure. (4) Interpretations in scientific work appear in the clarification of meaning, so that the meaning conveyed is clear and directed. The findings of this study contribute to an author's understanding of the importance of using creative thinking processes in scientific writing. However, for further research it is recommended to examine the process of creative thinking with different objects.
SIKAP POSITIF MAHASISWA TERHADAP PENGGUNAAN BAHASA INDONESIA DALAM LINGKUNGAN KAMPUS STKIP PGRI PACITAN

Authors:
raw_author_name: Bakti Sutopo
raw_affiliation_string: Program Studi Pendidikan Bahasa dan Sastra Indonesia STKIP PGRI Pacitan, Indonesia
raw_author_name: Catur Apriyani
raw_affiliation_string: Program Studi Pendidikan Bahasa dan Sastra Indonesia STKIP PGRI Pacitan, Indonesia

Abstract: The purpose of this research was to understand the forms of language attitudes and the factors influencing the language attitudes of students at STKIP PGRI Pacitan towards the Indonesian language. The approach used was descriptive qualitative. Data collection methods in this research included observation, questionnaires, and interviews. The data analysis method used Miles and Huberman's analysis method, which involved data reduction, data presentation, and drawing conclusions. The results of the study showed that the majority of students in the STKIP PGRI Pacitan campus (93%) exhibited loyalty and pride in using the Indonesian language in various aspects, including communication on social media, entertainment, and daily interactions. They were aware of the importance of the Indonesian language in maintaining national unity and considered it attractive and sustainable in the era of globalization. This positive attitude was influenced by factors such as students' knowledge and experiences, a supportive campus environment, emotional aspects as Indonesian citizens, the influence of mass media, and the role of educational institutions. In this increasingly advanced digital era, it is important to continuously enhance understanding, create a supportive environment, and provide resources that promote the use of proper and good Indonesian language to maintain this positive attitude consistently.
Vehicle Speed Detection using Haar Cascade Classifier and Correlation Tracking

Authors:
raw_author_name: Ayesha Siddiqua
raw_author_name: Sumera Sumera

Abstract: Objectives: The aim of this study is to develop an efficient and cost-effective solution for predicting vehicle speeds using recorded video data. Methods: The proposed system employs a combination of image processing techniques and computer vision to calibrate cameras for traffic simulation, enabling the extraction of information on average vehicle speeds. It utilizes the Haar Cascade Classifier for object detection, followed by a correlation tracker for vehicle tracking. Speed estimation is achieved through the frame differencing method. The dataset comprises 90 minutes of recorded data from highway cameras, showcasing diverse traffic scenarios with various vehicle types (trucks, trailers, cars, buses, and bikes) at varying speeds. Predicted values are compared with ground truth data obtained from a GPS-equipped car, using Mean Absolute Error (MAE) as the evaluation metric. Findings: The algorithm's performance is evaluated, resulting in an average error rate of 1.72 km/h (2.07%). These findings are compared with state-of-the-art data. Novelty: This study introduces a novel system that combines the Haar Cascade Classifier, correlation tracker, and frame differencing method to track vehicle positions, incorporating bike detection into the analysis, and calculate their moving speeds. A relative analysis underscores the system's performance, emphasizing its effectiveness in real-world applications and demonstrating refinement in accuracy assessment. Keywords: Image processing, Vehicle speed estimation, Haar Cascade Classifier, Correlation tracker, Error rate calculation, Computer vision
Rancang Bangun Sistem Informasi Industri Asphalt Mixing Plant pada PT. Selo Progo Sakti

Authors:
raw_author_name: Hedi Pandowo
raw_affiliation_string: Politeknik Negeri Madiun
raw_author_name: Chanif Kurnia Sari
raw_affiliation_string: STIKES Surya Global Yogyakarta

Abstract: PT. Selo Progo Sakti is a company engaged in the Asphalt Mixing Plant industry. Asphalt Mixing Plant is a production equipment that produces Hotmix in the form of a mixture of asphalt with some aggregate materials used as road pavement materials. This Asphalt Mixing Plant operates for production according to orders from consumers and the character of the production results in the form of hotmix must meet certain temperature criteria for gnats to be spread out on the road media so that it must be avoided so that the product conditions do not occur at low or cold temperatures because it will harden and cannot used for road pavement. Therefore, the accuracy in delivering the product to the location where it will be held will greatly determine the quality of the production after it is held on the road. In addition, product quality is also determined from the job mix or the proportion of the material mixture that has been agreed upon in accordance with the job specifications, so it needs supervision from various parties involved in the implementation of the work. The existence of an information system is a tool for controlling production costs, in this case hotmix products produced from Asphalt Mixing Plant machines are needed to monitor every production process from several departments that have been worked on so that data management can be done quickly and accurately. Therefore, this system was built in order to overcome problems such as calculating the cost of production of hotmix for each product according to jobmix, cost control, inventory control and preparation of financial reports which can be done in one integrated information system. Tools used in making this system is Visual Basic. The application design method uses the ProtoTyping method.
Features of Scientometric Results of a Russian Scientific Journal: the Case of the Scientific Direction “Economic Sciences” of the Bulletin of Chelyabinsk State University

Authors:
raw_author_name: Dmitri A. Pletnev
raw_affiliation_string: Chelyabinsk State University

Abstract: The article presents the results of the use in the academic community of articles of the scientific journal Bulletin of Chelyabinsk State University in the direction of “Economic Sciences”. The study is based on data from the RSCI information system for 2018–2022. The total number of citations for each issue, individual articles, and the H‑index for issues and by year were calculated. The main trends and patterns in citing articles have been identified, including a three-year delay, passion for the topic of digitalization, inattention to articles by young authors and to international topics. The results of the study may be useful to editors of scientific journals for comparing the indicators of their journals with the one studied in this article, as well as for improving editorial policies.
Peningkatan Kompetensi Komunikasi Bahasa Inggris Pramuwisata Lokal Desa Tista Melalui Pelatihan Merancang Tour Itinerary

Authors:
raw_author_name: Ni Nyoman Deni Ariyaningsih
raw_affiliation_string: Program Studi Sastra Inggris, Universitas Mahasaraswati Denpasar
raw_author_name: Ida Ayu Putri Gita Ardiantari
raw_affiliation_string: Program Studi Sastra Inggris, Universitas Mahasaraswati Denpasar

Abstract: The importance of a tour guide competence and professionalism is the rational of this community service program.The focus of this program is to increase the competence of local tour guides in English by being able to design tour itinerary. This activity was done in Tista Village that is located in Kerambitan District, Tabanan Regency, Bali. The purpose of the activity is to help tourism actors especially local tour guides in Tista Village to enhance their English as one of the competency demands. Community Based Research (CBR) approach was implemented that prioritizes community needs and allows space for local wisdom as knowledge and solutions for the community. The service program was carried out using several methods, namely the lecturing method, question and answer method as well as discussion, as well as demonstration and simulation methods. Providing added value for local tour guides, the activities also include designing tour packages and practicing explaining them in English. The application of role play activities creates a more active and attractive learning atmosphere and has succeeded in increasing the participants' self-confidence as local tour guides. Through training activities in the community service program, the participants are able to understand and practice the English language used in explaining tour itinerary and packages.
Pengembangan bisnis jasa “kaluna badminton club” menggunakan business model canvas

Authors:
raw_author_name: Reza Widhar Pahlevi
raw_affiliation_string: Universitas Amikom Yogyakarta

Abstract: Kaluna Badminton Club is a service business that provides a platform for young children to teenagers to become talented and accomplished athletes by practicing using the correct basic badminton techniques. The purpose of establishing this business is because there is not yet a single club that accommodates children from young age to adults to become proficient at playing badminton with the correct basic techniques in Imogiri District. This research was conducted to find out how to manage and develop business strategies at the Kaluna Badminton Club using the Business Model Canvas concept. The Business Model Canvas framework is used as a tool to achieve business targets in a detailed and structured manner. By using this study, it becomes easier for business processes to achieve their goals. The research results from this Business Model Canvas identification can provide the right business strategy choices for the Kaluna Badminton Club in each block. The blocks on the Business Model Canvas include customer segments, value propositions, channels, customer relationships, key resources, key activities, key partners, cost structure, revenue streams. Each of these blocks has its own role which is very important for achieving the business model.
CLASSIFICATION OF SMS SPAM WITH N-GRAM AND PEARSON CORRELATION BASED USING MACHINE LEARNING TECHNIQUES

Authors:
raw_author_name: Nova Tri Romadloni
raw_affiliation_string: Universitas Muhammadiyah Karanganyar
raw_author_name: Nisa Dwi Septiyanti
raw_affiliation_string: Universitas Muhammadiyah Karanganyar
raw_author_name: Cucut Hariz Pratomo
raw_affiliation_string: Universitas Muhammadiyah Karanganyar
raw_author_name: Wakhid Kurniawan
raw_affiliation_string: Universitas Muhammadiyah Karanganyar
raw_author_name: Rauhulloh Ayatulloh Khomeini Noor Bintang
raw_affiliation_string: Universitas Muhammadiyah Karanganyar

Abstract: The Short Message Service (SMS) has garnered widespread popularity due to its simplicity, reliability, and ubiquitous accessibility.This study aims to enhance the efficacy of SMS classification by refining the classification process itself. Specifically, it strives to streamline the process by diminishing feature dimensions and eliminating inconsequential attributes. The textual data undergoes preprocessing, which involves employing the N-Gram technique for feature representation, followed by meticulous feature selection utilizing Pearson Correlation. The study employs 5 of classification algorithms. Notably, the findings underscore that the optimal outcomes emerge from the fusion of the N-Gram methodology with feature selection through Pearson Correlation. Among these, the Support Vector Machine methodology stands out, exhibiting a remarkable 91.41% enhancement in accuracy without feature selection, a further improvement to 91.96% through N-Gram utilization, and a final performance of 70.80% following the inclusion of weighted correlation. However, it is imperative to acknowledge the limitations inherent in the model's generalizability, primarily stemming from the utilization of a relatively modest dataset. Despite the efficacy of Pearson correlation and N-gram-based feature selection in curbing data dimensionality and enhancing processing efficiency, certain pertinent features may have been overlooked, or the chosen attributes might not be optimally suited for specific classifications.
Course Construction and Practice of Embedded Computing for New Engineering Education

Authors:
raw_author_name: Dongxin Wen
raw_author_name: Hongwei Liu
raw_author_name: Yanjun Shu
raw_author_name: Danyan Luo

Abstract: Facing the reform and development of the New Engineering Education, the paper combines the Embedded Computing course construction and practice. The course of Embedded Computing is an elective course for postgraduates majoring in Computer Science in Harbin University of technology. Under the guidance of the education direction for Emerging Engineering Education, it must be strengthened the construction and practice of the course. This paper combines the traditional teaching mode with the online teaching mode, the theoretical content driven by problems with DIY practice, and adopts a diversified evaluation system. Through the curriculum reforms, the students' learning enthusiasm has been actively mobilized, and the teaching quality has been significantly improved. This paper can provide reference for reform of talent training in our teaching courses.
Peningkatan Keterampilan Berbicara Melalui Metode Time Token Arends Pada Siswa Kelas V SDN 132 Babalohe Kabupaten Bulukumba

Authors:
raw_author_name: None Aliem Bahri

Abstract: The aim of this research is to improve speaking skills through the Time token areinds method in class V Indonesian language subjects at SDN 132 Babalohe. The type of research used is pre-experimental research with the aim of. The research design used was a one-shot case study, namely an experimental research carried out to show the strength of measurement and scientific value of a research design and the experimental units in this research were 19 students in class V at SDN 132 Babalohe as a trial class for implementing the use of Time. Arends Token. The data collection technique in this research was carried out using a student interest in learning questionnaire sheet technique (student responses). The research results show that analysis of student interest in learning questionnaire data shows that the ideal score of 92.89% is in the very good category, because it is in the range of 75% - 100%,Keywords: Effectiveness of Bolding Media (Rolling Ball), Short Story Writing Skills
A Hybrid Visionary for Unveiling Human Motion in the Face of Occlusion with Mask R-CNN, RNN, and MHT

Authors:
raw_author_name: Chirag Sharma

Abstract: Addressing the intricate challenges of Human Motion Detection (HMD), this research presents a pioneering hybrid methodology integrating advanced computer vision and deep learning techniques. Focused primarily on mitigating the impact of occlusion in visual data, the proposed approach employs a Mask Region-based Convolutional Neural Network (Mask R-CNN) for precise motion segmentation. The dual challenges of self-occlusion and partial-occlusion are specifically targeted. The three-fold strategy encompasses motion segmentation, object classification, and tracking algorithms to discern and identify human motion accurately. Motion segmentation involves isolating the moving object within video frames, followed by object classification utilizing a Recurrent Neural Network (RNN) to determine the human presence and to tune the parameter of RNN; this work introduced a novel hybrid Whale Optimization Algorithm and Red Deer Algorithm (WOA-RDA), which gives better convergence speed with high accuracy. To tackle the persistence of occlusion, particularly self-occlusion, Multiple Hypothesis Tracking (MHT) is introduced for robustly tracking human gestures. An innovative aspect of the proposed approach lies in the integration of an RNN trained with 2D representations of 3D skeletal motion, enhancing the model’s understanding of complex human movements. The proposed methodology is rigorously evaluated on diverse datasets, incorporating scenarios with and without occlusion. Experimental results underscore the effectiveness of the hybrid approach, showcasing its ability to accurately identify human motion under varying conditions, thereby advancing the field of human motion detection.
Optimized Fuzzy Model in Piecewise Interval for Function Approximation

Authors:
raw_author_name: Anup Kumar Mallick
raw_author_name: Angsuman Sarkar

Abstract: Function approximation is a technique for estimating an unknown underlying function from input-output instances or examples. Researchers have proposed different methods of function approximations, such as the neural network method, the support vector regression method, the reinforced learning method, the clustering method, the neuro-fuzzy method, etc. This paper introduces a novel data-driven function approximation scheme where the input-output data set is first segmented into multiple pieces. A Mamdani-type fuzzy submodel is constructed for each piece or portion, and the membership functions’ parameters for antecedent and consequent are optimally selected through the differential evolution algorithm. The efficacy of the suggested model is verified on three nonlinear functions, viz., a piecewise polynomial function, an exponentially decreasing sinusoidal function, and an exponentially increasing sinusoidal function. A comparative analysis is done based on the simulation results from the proposed model and the results obtained through the two state-of-the-art function approximation techniques, viz., the support vector regression model and the radial basis function network. The simulation results show that the proposed function approximator has satisfactorily approximated the three functions examined here, surpasses the two state-of-the-art techniques in approximating the two sinusoidal functions, and performs the near-best performance for the piecewise polynomial function. The proposed function approximator is expected to be applied as a new state-of-the-art method for function approximation.
Dynamic Indian Sign Language Recognition Based on Enhanced LSTM with Custom Attention Mechanism

Authors:
raw_author_name: Jay M. Joshi
raw_author_name: Dhaval U. Patel

Abstract: In this paper, the author developed a system with an enhanced Long-Short-Term Memory (LSTM) model using a custom Attention Mechanism specifically designed for real-time dynamic Indian Sign Language (ISL) recognition. A large custom dataset of 59 signs was employed. For feature extraction, the MediaPipe framework was used. On this dataset, three different models were trained, the Long Short-Term Memory (LSTM) Dense model with Customed Attention, the LSTM-Dense model with a traditional Attention Mechanism, and the LSTM-Dense model without Attention Mechanism. The proposed Long Short-Term Memory (LSTM) dense model with a customed Attention Mechanism (AM) outperformed the other two models. The proposed LSTM-Dense model with a customed Attention Mechanism achieved a maximum accuracy of 96.08% in predicting the sign. When compared with existing Indian Sign Language recognition methods, our proposed model surpassed all others in accuracy, even with a large number of signs. In addition, 5-fold cross-validation of the proposed model confirmed the durability of our results, with a 93% accuracy. The results show that the proposed recognition system can effectively and robustly recognize ISL gestures.
Analysis of Copy Move Forgery Detection Process by Applying Fuzzy C Means Algorithm Based on Deep Learning in Digital Image Processing

Authors:
raw_author_name: Sugitha N

Abstract: The popularity of digital photos has developed due to technological advancements in the digital environment. Image alteration has become more manageable thanks to powerful and user-friendly photo editing software programs. Therefore, there was a prerequisite to detect the forged part of the image efficiently. Hence, this work emphasizes passive forgery recognition on images tampered by the copy move method, better called Copy Move Forgery Detection (CMFD). Copy Move Forgery (CMF) was fundamentally concerned with covering or repeating one area in a picture by pasting certain regions of a similar picture. Initially, the input digital images were preprocessed through a Gaussian filter to blur the picture to decrease noise. After preprocessing, Multi-Kernel Fuzzy C-Means clustering (MKFCM) was performed to divide the images into numerous clusters to extract the features based on distinctive attributes using the SIFT method. Lastly, with the deep learning technique, the forged parts of the images were detected. The experimental analysis demonstrates that the method was efficient and robust in identifying the forged part of the digital picture, and the performance of the proposed strategy was established on numerous forged pictures.