Reviewerly/exHarmony huggingface dataset:
Purified Konjac Glucomannan as Thickener for Substituting Gelatin in Making Panna Cotta

Authors:
raw_author_name: Fahmi Fahmi
raw_affiliation_string: Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

Abstract: A thickener such as gelatin is essential in increasing viscosity and forming a gel system. Nowadays, gelatin is one of the most popular thickeners in food, pharmacy, and cosmetic products. Animal skins which lead to halal issues are still common sources of gelatin. Crude konjac flour (CKF) which is sourced from porang tubers and has a high degree of purity of glucomannan (GM) is a potential substitute for animal skins. Moreover, the use of KGM also supports national programs of processing agricultural products into finished products ready to export. This study applies five different CKF variants as panna cotta (PC) thickener: CKF from the fresh bulb of porang (Amorphophallus oncophyllus sp.) (CH-UP), CKF from chips of Porang (CH-CP), a native CKF, as well as laboratory-purified products of CKF (&gt;90%-w of GM content) (DM-CKF-M3X-50, and DM-CKF-M3X-96), and commercially products of porang flour (K-TPO and K-TPM) were applied to make PC; substituting gelatin. Only CKF, DM-CKF-MX-50, and DM-CKF-M3X-96 successfully thickened PC in terms of appearances. Further, organoleptic analysis was applied to CKF, DM-CKF-MX-50, and DM-CKF-M3X-96. According to the organoleptic analysis, PC with CKF, DM-CKF-MX-50, and DM-CKF-M3X-96 was more preferred by the respondents than commercial PC. In overall, CKF application on PC exhibited improved sensory properties and tastes of PC.
Prediction of Palm Oil Production Results PT.KSI South Solok Using Ensemble k-Nearest Neighbor

Authors:
raw_author_name: None Atus Amadi Putra
raw_author_name: None Dony Permana
raw_author_name: None Zilrahmi

Abstract: In 2022 PT. KSI experienced a decline in palm oil production due to replanting steps. In managing palm oil production PT. KSI has problems with palm oil production results not reaching targets so that it can affect the Company's Work Plan and Budget, therefore it is very necessary to predict palm oil production results so that all palm oil production and processing activities can run according to plan. The ensemble technique is a method which has predictive accuracy capabilities and is very efficient to use in the k-NN method, so there is no need to search for the optimal k value. Based on the results of the analysis that has been carried out, it can be seen that by using an ensemble the level of accuracy is 9.36%, which is considered high accuracy compared to just using a single kNN with k = 1 of 10.84%. So it can be concluded that the model has worked well with the data.
Fuzzy K-Nearest Neighbor to Predict Rainfall in Padang Pariaman District

Authors:
raw_author_name: None Nonong Amalita
raw_author_name: None Yenni Kurniawati
raw_author_name: None Zamahsary Martha

Abstract: Rainfall is the amount of water that falls to the ground surface during a certain period which is measured in millimeters. The amount of rainfall can be estimated or predicted. One method used to predict rainfall is Data Mining, namely computer learning to analyze knowledge automatically so that a perfect new model is obtained. One of the best prediction algorithms in data mining is Fuzzy K-Nearest Neighbor (FK-NN) which uses the largest membership degree value from the test data in each class to determine the class. The number of sample classes obtained from rainfall data in Padang Pariaman Regency experienced unbalanced classes. One way to handle imbalance class cases is to use the Synthetic Minority Over-sampling Technique (SMOTE) technique which produces as much minority data as majority data. The results obtained in this study used the FK-NN classification with a total of 343 test data, parameter K=12 and using the Euclidean distance. The accuracy value was quite good, namely 76,38%.
Human Capital for Economic Development: A Study of Education Production Performance (EPP) in Khairpur

Authors:
raw_author_name: Safiullah Junejo

Abstract: The analysis of education production performance involves evaluating the inputs of faculty, teachers, and students to determine the academic achievement of students. This study aims to estimate the education production performance of both state and private higher secondary schools in Khairpur and identify the factors that affect instructional outcomes in the region. Education is crucial for development, as a high-quality education system is essential for increasing people's skills, knowledge, and abilities, ultimately contributing to the growth of human capital. In a developing country like Pakistan, where policymakers face challenges such as a rapidly growing population, low levels of education, and limited resources, improving educational efficiency is critical to achieving progress. A thorough understanding of the factors that contribute to instructional success is essential in this regard. To construct the model, a cross-sectional dataset was used, and a standard least squares method was employed with annual examination results as the output variable and school inputs, student characteristics, family background, and teacher characteristics as the input variables for both private and public schools. The results of the study indicate that student characteristics, teacher qualities, and family background, except for the mother's education, career, and income, have a statistically significant impact on students' academic performance. The findings of this study have significant policy implications for Khairpur and Pakistan as a whole. Improving educational outcomes will be critical in enhancing the human capital stock, which, in turn, is essential for economic growth and improving living standards. By understanding the factors that contribute to instructional success, policymakers can devise effective strategies to address the challenges faced by the education sector and improve overall educational efficiency.
Student Motivation In Class VII Educational Learning At Smp Negeri 10 Pekanbaru

Authors:
raw_author_name: None Ridwan Nasution
raw_affiliation_string: Riau Islamic University
raw_author_name: None Oki Candra
raw_affiliation_string: Riau Islamic University

Abstract: This research aims to determine the level of student motivation in Physical Education Class VII learning at State Junior High School 10 Pekanbaru. This research is quantitative research, the method used is a descriptive method with a survey type. The population in this study was class VII students at Pekanbaru 10 State Middle School, totaling 279 students. The sampling technique uses total sampling technique. The instrument used in this research used a Likert scale or questionnaire method which was distributed to respondents. Based on research results, Student Motivation in Class VII Physical Education Learning is classified as Very High, this can be seen in the percentage results of 83% which are in the assessment range of 81%-100% with Very High criteria .
Increasing Awareness of the Village Disaster Risk Reduction Forum in Magetan Regency in Realizing Disaster Preparedness

Authors:
raw_author_name: Sunarto Sunarto
raw_affiliation_string: Politeknik Kesehatan Surabaya
raw_author_name: Heru Santoso Wahito Nugroho
raw_affiliation_string: Politeknik Kesehatan Surabaya
raw_author_name: Suparji Suparji
raw_affiliation_string: Politeknik Kesehatan Surabaya

Abstract: Disaster risk reduction forums as a capacity in disaster resilient villages often experience difficulties in realizing disaster preparedness. It is necessary to prioritize any element that is immediately realized, so that what is done truly makes society have resilience and toughness. five disaster preparedness parameters that must be prepared by the forum. These five parameters have 25 elements as constructs. Elements as a construct of disaster preparedness parameters become an instrument called Difficulty and Usefulness of Elements in Disaster Preparedness (DUEDP-Questionnaire). This DUEDP questionnaire serves as a guide enumerator for interviewing forum administrators and communities in 23 disaster-resilient villages in the Magetan district. Data was collected for three months starting May-July 2023. The element prioritization technique uses the Quadrant of Difficulty and Usefulness (QoDU) method. This method focuses on elements in the upper left quadrant, namely elements that are very useful but how to make it happen is very difficult. The research results place the elements of involving vulnerable groups in socializing about disasters, providing village funds for disaster management, preparing contingency plan documents, providing early warning system tools, and training families to provide disaster preparedness bags as the main priorities that must be immediately realized by the forum.
Unveiling the Catalysts of Digital Transformation Acceptance: Insights from Employees in Online Distance Learning Higher Education Institutions

Authors:
raw_author_name: Zahir Osman

Abstract: Online distance learning in higher education institutions is experiencing significant growth and is increasingly adopting digital transformation. However, employee acceptance and adoption of these changes present a major challenge. This study investigates the factors influencing employee acceptance of digital transformation in online distance learning institutions. It examines the influence of latent variables, such as effort expectancy, performance expectancy, self-efficacy, and intention, on the acceptance of digital transformation. It also expands on existing theoretical frameworks and provides empirical evidence of their importance. Data was collected from 387 employees using a structured questionnaire, and statistical analysis, including regression and PLS structural equation modelling, was used to assess the relationships between variables. The findings revealed that effort expectancy, performance expectancy, self-efficacy, and intention significantly influenced employee acceptance of digital transformation. The indirect relationship hypotheses are also supported. Several practical implications and strategies such as user-friendly technologies, effective communications, professional development opportunities and involvement in decision-making processes are identified as key strategies to enhance employee acceptance. The study contributes to the existing knowledge of acceptance theories and suggests avenues for future research including exploring additional variables such as culture and contextual factors and conducting longitudinal studies to understand the long-term effects of digital transformation.
Access to Digital Justice

Authors:
raw_author_name: Arabella Kyprianides
raw_author_name: Ben Bradford
raw_author_name: Jonathan Jackson

Abstract: Chapter 7, Access to Digital Justice, asks the central question: how accessible is online justice? This chapter explores how those who administer justice, those who provide advice and those who use the online justice system experience it. In doing so, we explore how the use of technology in the justice system is shaped by, and may reshape, people’s orientations and sensibilities towards law and technology. We use our data, in this chapter, to explore how consciousness of how people think and feel about the law relates to their capability of acting upon it.
Instagram Features as Media for Learning English Listening Comprehension

Authors:
raw_author_name: Ridha Mardiani
raw_affiliation_string: Sekolah Tinggi Keguruan dan Ilmu Pendidikan Pasundan

Abstract: This study aimed to investigate what Instagram features that help students in learning English listening comprehension, and to find out the students’ perceptions towards Instagram as a media to learn the subject. Mixed method was used for this study, specifically in the form of a case study in one secondary school in Cimahi, West Java, Indonesia. Ten secondary school students aged between 15 and 18 years were chosen as participants of this study. The researchers tried to create Instagram content that would help the students learn the subject, combined with the use of questionnaires, classroom observation, and students’ interview to obtain data. Data from questionnaires were analyzed using percentage calculation, data from classroom observation were analyzed based on the activities in the classroom and displayed in the form of table, while students’ interview were analyzed based on deductive thematic data analysis. The result shows that the students are familiar with Instagram Story, Post, Reel, and Live. These Instagram features were used as tools for learning English Listening comprehension. The students perceived that the use of Instagram features for listening English comprehension could help them develop their potencies, make the learning materials more interested, assist them to learn and be more creative.
Analysis of Credit Card Fraud Detection Performance Using Random Forest Classifier &amp; Neural Networks Model

Authors:
raw_author_name: Abdi Dharma
raw_affiliation_string: Informatics Engineering Study Program, Faculty of Science and Technology, Universitas Prima Indonesia, Jl. Sampul No. 3, Medan, North Sumatra, Indonesia

Abstract: Credit card fraud is one example of data manipulation in the e-commerce industry. Because credit card fraud is so common, preventing it can be difficult. Therefore, it is important to identify credit card fraud as soon as it occurs. Determining the validity of a transaction is a fraud detection process. Credit/ Debit cards/ any financial services are small plastic cards given to members of certain financial organizations with proper identity and verification. This research is quantitative research that uses a dataset that has been verified and classified as fraudulent or non-fraudulent transactions. This research will limit itself to credit card fraud detection methods that use Neural Networks and Random Forest Classifier algorithms. Using publicly available credit card transaction data as a starting point, this study will examine how well machine learning algorithms do overall in identifying credit card fraud. First of all, we check for the presence of duplicate values in the data set. The result of this check shows that there are no duplicate values in the set, marked with the value ‘False’. Next, we focus on class in the target variable ‘Class’. The output of this check shows the wide variety of samples for each class in the goal variable ‘Class’. In this example, class 0 has 284.315 samples and class 1 has 284.315 samples. Based totally on the studies performed, it is possible to conclude that the usage of machine learning algorithms, together with Random Forest Classifier and Neural Networks, can be effective in detecting credit card fraud. The results of the algorithm performance analysis show that the model developed can identify fraudulent transactions accurately. In addition, the data preparation stages, correlation analysis, and model performance evaluation also contribute to understanding potentially fraudulent credit card transaction patterns.
A New Hybrid Algorithm Based on the Firefly Algorithm and Cuckoo Search to Estimate Survival Analysis of Truncated Inverse Gompertz Distribution

Authors:
raw_author_name: Dr.Bayda Atiya Kalaf
raw_affiliation_string: University of Baghdad

Abstract: This paper introduces the Right Truncated Inverse Gompertz Distribution (RTIGD) with two parameters δ and ϑ with some of its properties as; (Survival-Function, Hazard-Function, cumulative distribution function, probability density function, ‎r-th moment, mean, variance, Moment Generating Function, Median, and Mode. In addition, we propose a new hybrid algorithm, namely the firefly Algorithm with Cuckoo Search Algorithm (FA_CSA) to estimate the parameters based on the survival functions of RTIGD. Simulation is utilized to compare the proposed algorithm with traditional methods, for example, the Maximum Likelihood Estimator and moment method and the standard algorithms Firefly Algorithm and Cuckoo Search. In most cases, the results demonstrate that the proposed algorithm (FA_CSA) provides an accurate estimation for the survival function since it has less mean squared error than the other estimation methods.
Task Scheduling in a Cloud Environment Based on Meta-Heuristic Approaches: A Survey

Authors:
raw_author_name: Dina Riadh Abdulrazzaq
raw_affiliation_string: Department of Computer Science, College of Science, Mustannsiriyah University, Baghdad, Iraq
raw_author_name: Narjis Mezaal Shati
raw_affiliation_string: Department of Computer Science, College of Science, Mustannsiriyah University, Baghdad, Iraq
raw_author_name: Haider K. Hoomod
raw_affiliation_string: Department of Computer Science Department, College of Education, Mustannsiriyah University, Baghdad, Iraq

Abstract: Cloud computing is one of the emerging technologies that expands the boundaries of the internet by using centralized servers to maintain data and resources. It allows users and consumers to use various applications provided by the cloud provider, but one of the major issues is task scheduling. Task scheduling is employed for the purpose of mapping the requests of users to the appropriate resources available. This paper provides a detailed survey of the available scheduling techniques for cloud environments based on six common metaheuristic algorithms. Those algorithms are the Cuckoo Search Algorithm (CSA), Chicken Swarm Optimization (CSO), Genetic Algorithm (GA), Bat Algorithm (BA), Whale Optimization Algorithm (WOA), and Grey Wolf Optimization (GWO). The literature is analyzed from three perspectives: task type, objectives to be optimized, simulation environment, and quality of service performance metrics. In addition, the research gaps and future directions for future investigation are presented.
PEMANFAATAN FANPAGE FACEEBOOK: PENJAHIT KEBAYA DAN SALON DI DESA SIOPAT SOSOR KABUPATEN SAMOSIR

Authors:
raw_author_name: Juara Simanjuntak
raw_affiliation_string: Universitas HKBP Nommensen
raw_author_name: Juliansen Purba
raw_affiliation_string: Universitas HKBP Nommensen

Abstract: The kebaya sewing service industry and beauty salons are industries that are always in demand by Indonesian people both in cities and in regions. Kebaya is a traditional Indonesian dress. Every religious event and custom almost always uses kebaya cloth. In using kebaya cloth at every event, Indonesian women always make up themselves so that the kebaya cloth used looks more beautiful and beautiful when worn. Therefore, the kebaya cloth sewing industry and beauty salons are one of the service industries that are in great demand by the public in starting a business. The purpose of this community service activity is so that people who start kebaya sewing and beauty salon businesses can reach a wider market by utilizing social media accounts such as Facebook in promoting their business. Facebook social media accounts can be turned into business accounts by adding a fanpage or business page feature. Facebook fanpage is a special page like a blog that contains various kinds of content according to the wishes of its users. The results of this activity are kebaya sewing and beauty salon business actors who have changed their personal Facebook account to a business Facebook account by adding a fan page feature. So that business actors in kebaya sewing and beauty salons can expand their market share through promotions on social media.
Pengaruh Media Papan Perkalian Terhadap Hasil Belajar Matematika Siswa Kelas III SD YPK Elim Kota Sorong

Authors:
raw_author_name: None Ahmad Yulianto

Abstract: The purpose of this study was to determine the Influence of Multiplication Board Media on Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Sorong City. This type of research uses Quantitative Research with the research design used is a pre-experimental design with the type One-Group Pretest-posttest. The population is class III A students with a total of 19 students with a sampling technique carried out by nonprobability sampling, namely purporsive sampling. The instruments used are observation sheets and essay tests to measure student learning outcomes, while the results of the analysis of student learning completeness on the average posttest score are 83.84. The reliability test results obtained by Cronbachs Alpha for student responses amounted to 0.852 which means it has a high level of reliability with the normality test of student posttest learning outcomes having a significance level of 0.028 &gt; 0.05. The hypothesis test obtained tcount of 7.001 with df = n – 1 (19-1=18) obtained ttable of 1.729. Based on the results of the analysis of value data, namely tcalculate &gt; ttable (-7.001&gt; 1.729), with a magnitude of significance level of 0.05, the hypothesis is accepted. Thus, it can be concluded that there is an influence of Multiplication Board Media on the Mathematics Learning Outcomes of Grade III Students of SD YPK Elim Malanu in Sorong City.
PENGARUH PENGUASAAN KOSAKATA DAN TATA BAHASA INDONESIA TERHADAP KEMAMPUAN MENULIS EKSPOSISI SISWA KELAS X SMA NEGERI SE KOTA YOGYAKARTA

Authors:
raw_author_name: Mardiansyah Mardiansyah
raw_affiliation_string: Program Studi Pendidikan Bahasa Indonesia, Universitas Sultan Ageng Tirtayasa, Indonesia
raw_author_name: Tatu Hilaliyah
raw_affiliation_string: Program Studi Pendidikan Bahasa Indonesia, Universitas Sultan Ageng Tirtayasa, Indonesia

Abstract: This research aims to: (1) determine whether or not there is an influence of vocabulary mastery on the exposition writing ability of class X SMA Negeri Se-Kota Yogyakarta (2) determine whether or not there is an influence of mastery of Indonesian grammar on the ability to write expositions of class X SMA Negeri Se-Kota Yogyakarta, and (3) determine whether or not there is an influence of mastery of Indonesian vocabulary and grammar on the ability to write expositions of class This research is ex-post facto research. The research subjects were students class X SMA Negeri Se-Kota Yogyakarta. Sampling used a stratified random sampling technique with a total of 345 students taken. Data collection was carried out using ability tests including vocabulary, grammar and expository writing. Data analysis uses product moment correlation analysis techniques and multiple linear regression analysis. The level of error in the analysis results is determined at 5%. The results of the research show that: (1) there is a positive and significant influence of vocabulary mastery on expository writing ability class X student of SMA Negeri se-Kota Yogyakarta with a calculated r value of 0.164, r table of 0.098, relative contribution of 30.29% and effective contribution of 1.82%; (2) there is a positive and significant influence of mastery of Indonesian grammar on the exposition writing ability of class X student SMA Negeri se-Kota Yogyakarta which is indicated by the calculated r value of 0.221, r table of 0.098, relative contribution of 69.71% and effective contribution of 4.18%; (3) there is a positive and significant influence simultaneously on the mastery of Indonesian vocabulary and grammar on the exposition writing ability of class X student SMA Negeri se-Kota Yogyakarta indicated by an F value of 10.950, a regression coefficient (R) of 0.245, and a coefficient of determination (R2) of 0.060. This means that 6% of expository writing ability is influenced by mastery of vocabulary and grammar, while the remaining 94% is influenced by other factors not examined in this research.