Reviewerly/exHarmony huggingface dataset:
Development of Biawak Island digital encyclopedia for conservation biology lecture

Conservation Biology is an interdisciplinary science whose purpose is to encourage the development of theory and application in conservation areas. Biawak Island is one of the leading conservation areas in the Indramayu district, therefore conservation biology learning should be done directly on Biawak Island. In practice, studying conservation biology directly on Biawak Island is difficult because of the long distance and expensive access to this place. Based on these problems, a digital encyclopedia of conservation on Biawak Island is needed to solve the problem of needing media that can become a medium for studying conservation in this hard-to-reach area. The method in this research is quantitative, and the research design is development research using the ADDIE development model (Analysis, Design, Development, Implementation, Evaluation), but does not include implementation and evaluation phases. The name given to the encyclopedia is PULBIN PEDIA, which was created using the PHP programming language. The content includes a profile of Biawak Island and conservation on Biawak Island, which contains multimedia narrative text, images, and videos. The digital encyclopedia has a control device that allows users to explore the encyclopedia's contents independently and can be updated at any time by the administrator. The validation expert results show that the PULBIN PEDIA encyclopedia is very valid as a learning medium for students and college students.
Text summarization implementing abstractive and extractive methods

How often do we come across paragraphs which contain important information but are too long to read? Most people tend to overlook humungous paragraphs at the expense of losing out on crucial information. This leads to a gap in topics which otherwise connect other significant concepts to make a meaningful learning experience - something we term as knowledge void. This report aims to highlight the importance of summarization using the two different methods of summarization – abstractive and extractive. We shall discuss the methods in detail including the methodologies, architectures and algorithms involved. This includes the preprocessing of data, the introduction of word embeddings, the application of algorithms like TextRank, building sequence-to-sequence models using LSTMs, applying encoder-decoder architecture and other advanced NLP techniques. We shall also evaluate our work using appropriate evaluation metrics. There has been experimentation using different approaches like unidirectional LSTMs, bidirectional LSTMs, a variety of tokenizers, and incorporation of attention layer to obtain the model with optimal accuracy and consistency.
Hybrid ML Algorithms for Learning Disability Forecast in School Going Children Using Python in Machine Learning Techniques

A learning disability is a neurological illness that impairs a child's ability to read, speak, and do a variety of other skills. The World Health Organization (WHO) estimates that learning disabilities impact 15% of youngsters [14]. The most important challenge for researchers to perform in order to identify learning disabilities early on is efficient prediction and accurate categorization. Our primary goal in this effort is to use soft computing to create a model for the prediction and categorization of learning disabilities. This study proposes a hybrid approach for enabling classification in order to enhance the performance of prediction and classification. This method incorporated classification's primary five techniques. Random Forest, Logistic Regression, Stochastic Gradient Descent, and K-Fold cross validation. In order to implement the system used python. Results analysis reveals the predict of learning disability in effectively
Activity Prediction in Tri Pramana Learning Concept in ResNet-based Virtual Reality Environment

This research aims to visually predict activities in the Tri Pramana Learning Concept in a virtual reality (VR) environment using the ResNet-50 deep learning architecture. The method in this research consists of dataset preparation (data acquisition, frame extraction, data cleaning, image resizing, data subsetting), ResNet-50 model building, and evaluation. The data used in this study comes from learning recordings in a virtual classroom environment of fiber optic splicing practicum. The total number of images in this dataset is 2,163 which is divided into training subset (70%), validation subset (20%), and testing subset (10%). This research focuses on experimenting with epoch variations of 100, 200, 300, and 400 to produce the best model. Through the investigation, it was found that the model with epoch 400 was able to provide the best performance with Accuracy 97.72%, Precision 97.81%, Recall 97.77%, dan F1- Score 97.79%. Future experiments will focus on the variation of learning rate and batch hyperparameters as well as comparisons with other deep learning architectures to predict activities in the Tri Pramana Learning Concept in virtual environments.
Nighttime Traffic Surveillance Using Glare Reduction and Zero-DCE-Based Low-Light Image Enhancement

High-quality image plays a critical role in computer vision tasks such as object detection and scene understanding. However images captured in night traffic conditions usually suffer from low light and glare problems, which increases the difficulty of subsequent computer vision tasks. In this paper we propose a new approach to using Zero-DCE for image enhancement in low light on traffic surveillance cameras at night. We added a glare reduction (Reduce Glare) stage after the image enhancement process was carried out using Zero-DCE. This has been proven to help improve quality and maintain enhanced image structural information. The proof is the increase of the average PSNR from 28.91 to 31.07 and SSIM values from 0.55 to 0.88, for the enhanced images using the proposed approach compared to Zero-DCE alone. Subjective tests also carried out to see the condition of the image before and after processing. The outcomes of the suggested method were able to improve the image's brightness and contrast, visibility of details, and subjective visual quality. The impact can be felt directly by practitioners and parties involved in traffic monitoring, paving the way for more effective and reliable systems. These results not only overcome challenges in low-light conditions, but also open opportunities for the development of better surveillance technologies in the future.
SIBI Syllable Recognition System With LSTM

Deaf people are people who are unable to communicate with spoken language. Deaf people communicate with the Indonesian Sign System or commonly known as SIBI. In fact, deaf people often communicate and socialize with normal people, but not all normal people understand and understand SIBI. We as researchers want to provide a way out so that deaf people can convey information to normal people, who do not understand SIBI. The input of this research is SIBI movement which is saved in Video format, then the video is processed with the LSTM algorithm. Video The results of the processing are in the form of classified words, the output of this research is in the form of text. The word data set in this study consisted of 3 words, each word contained 30 data sets. The level of accuracy of this study when recognizing words in SIBI that do not hit the face is 100%.
EOCENE-OLIGOCENE CLIMATE BASED ON PALYNOLOGICAL RECORDS

This study is a part of the investigation on Tertiary paleoclimate conducted by LEMIGAS Stratigraphy Group. The paleoclimate reconstruction covers most area of western Indonesia including South Sumatra Basin, Sunda-Asri Basin, Northeast Java Basin South Kalimantan and Northeast Java Basin, West Natuna and South Sulawesi (Figure 1). This paper is aimed to figure out the regional paleoclimate of western Indonesia which occurred during Eocene-Oligocene. In fact, the knowledge of paleoclimate is useful to define sea level changes which are believed to have relationship with stratigraphy and sedimentology of these areas. The paleoclimate interpretation can be approached using different tools such as biostratigraphy and geochemistry. In this study, paleoclimate is interpretated based on biostratigraphy (microfossil evidences) including palynomorph and foraminifer. Palynomorphs were mainly applied on the non-marine to transitional sections, whilst foraminifers were used in interpreting shallow to deep marine sediments. In fact, most interpretations rely on palynological evidences as these simply provide suitable data for paleoclimate analysis. In case of both microfossils appear in the same section, the paleoclimate interpretation based on palynomorph can be placed in a certain stratigraphic level which is defined based on the occurrence of the age-restricted foraminifer. The paleoclimate interpretation of certain strati- graphic level is based on the compilation of palynological and foraminiferal data deriving from different areas. This method is used to obtain representative picture of paleoclimate which occurs in the selected stratigraphic range of the western Indonesia
A Seamless Motion Planning Integrating Maneuver Decision Based on Hybrid Model Predictive Control

Motion planning in autonomous driving is a major challenge, as it needs to consider the continuity between the actions output by internal modules and the need for consistency in optimizing driving behavior. Otherwise, it may lead to overly conservative or irrational driving behavior in complex scenarios. To address these issues, we propose a hybrid model predictive motion planner (HMPC) that integrates logical decision-making and motion planning, enabling seamless planning of vehicle motion without semantic decisions or predefined trajectories while extending functionality for external decisions. Testing results reveal that HMPC surpasses the conventional hierarchical MPC motion planner, ensuring better maintenance of the desired speed and greater adaptability to external behavior decision-making modules.
Recommender Systems based on Parallel and Distributed Deep Learning

As individuals have become overloaded with information, Recommender Systems (RS) were created to provide machine generated recommendations. Significant advancements in RS have been made thanks to Machine Learning methods; Deep Learning (DL) in particular has become extremely popular. Despite the fact that Deep neural networks (DNNs) upgrade notably the performance of RS, they make them larger and more memory-intensive systems. To that end, the solution is adding (data or model) parallel and distributed algorithms to DL RS. In this paper, we present our large-scale, multi-staged, hybrid RS that processes a million-scale dataset, as well as the most noteworthy parallel or/and distributed DL systems. Finally, we outline directions regarding the future evolution of our RS by adding some features and ideas from such systems.
Correlation Between Obesity, Emotional, Social Well-being, and Behavioral Problems among Adolescents

Obesity is considered a multivariate syndrome, which negatively affects the whole body's functioning. Poor health conditions resulting from obesity may act as a barrier to developing a sound mind, thus paving the way for poor learning behavior and outcome. This study explored the correlation between obesity, emotional and social well-being, and adolescent behavioral problems. A quantitative approach using descriptive-correlational design was employed. The 120 students served as respondents to the study. The following research instruments were used: Respondents’ Profile Questionnaire, Respondents’ Emotional Well-being Questionnaire, Respondents’ Social Well-being Questionnaire, and Respondents' Behavioral Problems Questionnaire. Mean and standard deviation and Pearson Product-Moment Correlation Coefficient were used to analyze the data gathered. There were more overweight than obese among the respondents of the study. Results showed that respondents' well-being is high as they manifest a low level of stress and emotional eating. In addition, they manifest a high level of social interaction and a low level of behavioral problems. The respondents' social well-being as social contact was greatly influenced by the respondents' level of obesity. Other variables and constructs were not affected by their level of obesity. It is recommended that stakeholders in education, sports, and health put a mechanism to guide all school learners to participate in physical activities. Keywords : learning behavior, level of stress, multivariate syndrome, poor health condition, social interaction
Electronic Voting System. History, Problems, and Perspectives

This paper presents a theoretical analysis of the development and application of electronic elections (e-elections) in the context of cyber security management. Components and tools of e-elections were presented and discussed in the organizational framework. The implementation of e-elections was analysed on the example of Estonia and Switzerland.
Learning Elementary Science through Technology: Conceptualization of Usage of Videos By Students

Video Based Learning (VBL) is one of the most unique ways of making learning as a fun. Effective and attractive. Video-based learning is considered an effective way and strategy for teaching science as this subject is being taught traditionally through the chalk and talk and lecture method. The main focus of the study were to find out the effectiveness of the practice of Video-based learning in the elementary science classrooms. This study was carried out at one of the elementary schools of the Sukkur Sindh. The design was qualitative in nature. The population of the study was all students of grade 8 who are 27. Unstructured interviews were used as a research tool. By adopting convenience sampling ten elementary-level students were selected. Thematic analysis was used as data analysis technique. The findings of the study revealed that Video-based learning in science makes learning easy, effective, retentive. It creates an active classroom environment, which is needed in this modern era. This study concluded that teachers do not use videos in their classroom practices, resulting in students and teachers taking this subject a little bit more difficult. It was concluded that video-based learning is an effective way of learning.
Kajian Perencanaan dan Pembangunan Sistem Informasi Berbasis WebGIS Kota Palu

Palu is located in the Sulawesi most active fault, with an annual movement of about 7 cm. The epicenter was located near Donggala, with tremors felt in various regions, including North and East Kalimantan. The earthquake had an energy release of approximately 2.5 × 10^20 Nm, equivalent to 200 times the power of the Hiroshima bombing. This presents an interesting subject for studying how to develop a good and accessible disaster mitigation system by utilizing the available information technology today, where disaster information can be easily accessed and synchronized with existing disaster management systems to reduce the impact of earthquake disasters. This research aims to analyze earthquake disaster risks and develop a mitigation model through a spatial analysis approach using Geographic Information System (GIS). The methods employed include analyzing disaster risks by utilizing Digital Elevation Model (DEM) data, road data, and overlaying images with earthquake damage distribution. Additionally, qualitative analysis in the form of disaster management and mitigation analysis is conducted. The data obtained is used to design evacuation routes and determine post-earthquake shelter locations. The results of this research provide a better understanding of disaster vulnerability in the studied areas. Through the developed mitigation model, this research contributes to identifying effective mitigation strategies. The designed evacuation routes and post-earthquake shelter locations provide crucial information for emergency response planning. Furthermore, the analysis results are presented in the form of a WebGIS accessible through a website, enabling easy access to information by the general public
A multiple linear regression model of students’ performance in calculus in the new normal

The Philippines launched an educational reform in 2012, adding two years of senior high schools (SHS) with strands that aim to prepare students for work or pursue college degrees. The STEM strand was designed for those wishing to enroll in Science, Technology, Engineering, and Mathematics-related degree programs. This study investigates the performance in Calculus and the University admission examination of a random sample of 234 enrolled students for the First Semester of 2021-2022 at Caraga State University taking Differential Calculus. It tries to identify the socio-economic predictors of students' performance in Calculus. Results revealed that age, gender, SHS strand, enhancement program, and admission scores in English, Mathematics, and Abstract Reasoning correlate with students' Calculus performance. Also, the students who graduated from the SHS strand performed better in Calculus than those who did not. Nonetheless, Calculus student performance is regardless of the type of community, SHS type, and family monthly income. Among the socio-economic correlates, the SHS strand and calculus enhancement program are the main predictors of student performance in Calculus using multiple linear regression. Other significant predictors of Calculus student performance are the students' admission scores in Mathematics and Abstract Reasoning. This means that students who performed well in the Mathematics and Abstract Reasoning admission scores, along with SHS STEM strand enrolment and provision of the Calculus enhancement program, are indicators of students' performance in Calculus, implying the importance of mathematics interventions for the students' performance. Furthermore, an appropriate senior high school strand for college degree program preference is a necessary pre-requisite.
Articulation and implementation of professional standards for teachers in teacher education institutions

This study determined the constructions of administrators and teachers in the articulation and implementation of the Philippine Professional Standards for Teachers (PPST) in teacher education institutions. A qualitative descriptive approach was employed to explore the narratives of the 20 purposively selected participants from the five higher education institutions in Cebu. Coding and categorization of participants' vignettes, following Clarke and Braun's (2014) thematic analysis model, resulted in five indexed themes: neediness not readiness, tenacity, and supportability, challenged but not frustrated, receptivity and positivity, and responsibility and accountability. Points of convergence and divergence were also identified from the TEIs articulation and implementation of PPST. The rationalization attached to integrating the beginning teacher indicators in the teacher education curriculum provides input on establishing contextualized, professional development initiatives for teacher quality. As such, forging partnerships between and among teacher education institutions through curriculum quality audits may be considered.
The Impact of Social Media on Tourism in Qatar

Social media has been at the forefront of technological information dissemination, and it is not showing any signs of slowing down anytime soon. The internet age has increased the prevalence and dependence on technological platforms and social media platforms have been playing a pivotal role in this digital evolution. The tourism sector has been one of the most impacted by this growth and continues to transform into different directions and boundaries and project new paths in terms of growth prospects. For tourism service providers and importantly so, tourism destinations, perhaps the biggest concerns for them to deal with at present are interactions that take place consistently and constantly on these social media platforms. One such destination is Qatar. The Gulf country has suffered some damage to its reputation and image largely due to social media bashing. It is, however, through the same mode of negative chatter that the country could make a strong come back through its tourism sector. This research is therefore carried out to ascertain what the impacts of social media interactions are on the tourism industry in general and how these trends may be utilised for the positive gains that Qatar may experience. The results showed a promising prospect for Qatar to gain its glorious image as a world leading Middle Eastern destination.
Factor Analysis of Student Learning Difficulties Using Powerpoint Media

This learning media is useful for teachers because using media as a tool can help teachers explain the material being conveyed to students. Public Vocational Secondary School-2 Kasongan has sufficient facilities such as LCDs, laptops, and computers, but teachers do not utilize the existing facilities. Therefore, teachers must be able to create interesting learning using PowerPoint media so that students are interested in following the learning provided by the teacher. This research aims to determine the factors influencing students' difficulties using Microsoft PowerPoint. This research was conducted at Public Vocational Secondary School -2 Kasongan. The research object was the class data analysis process, checking data validity. The results of this research show that the factors that influence the difficulty in using Microsoft PowerPoint at Public Vocational Secondary School-2 Kasongan are: 1) several students are technologically clueless and have knowledge of the basics of PowerPoint. 2) Students do not understand the function of using PowerPoint features. 3) Lack of creative ideas and creativity in creating attractive PowerPoint designs.
Achievement of Student Learning Competencies Using Problem Based E-Book in Primary School

Background: This research is motivated by the use teaching materials that are less varied. Aim: The purpose of this study to produce teaching materials in the form of E-Book assisted by Kvisoft Flipbook Maker Pro aplication on natural and social science learning in class IV primary school that are valid, practical, and effective. Results and Dıscussion: This research is a development research (R&amp;D) with the ADDIE model. The ADDIE model consists of analysis, design, development, implementation, and evaluation. The results of validity test of the developed E-Book are 96% for material experts, 96% for media experts, and 94% for linguist with highly valid categoris. The results of the practicality test in the trial school were 94% for teacher responses and 93.21% for student responses. The results of the practicality test in the research school obtained 96% for teacher responses and 96.08% for student responses with very practical categories. The results of the effectiveness test are seen from the N-Gain value, which is 0.72 with a high category. Conclusion: Thus, the use of e-books assisted by the Kvisoft Flipbook Maker Pro application in natural and social science learning in class IV primary schools is declared valid, practical, and effective in learning.
PENERAPAN MOORA PADA PEMBERIAN KEPUTUSAN PREDIKAT SANTRI TELADAN

Darul Hikma Islamic Boarding School is one of the Islamic boarding schools in Asahan Regency. The teaching and learning process at this Islamic boarding school is based on an established curriculum and religious knowledge. However, determining the achievements of exemplary students experiences difficulties. This is because the process carried out is still carried out using formula calculations. Apart from that, there are many data errors due to the large number of criteria being assessed. The aim of this research is to help Islamic boarding school managers determine exemplary students by building a decision support system using the MOORA method. So with this system, managers only input every value obtained by students is entered directly into the system. The input value will be processed automatically by the system so that you can get results quickly, precisely and accurately