bluuebunny/crossref_metadata_2025 huggingface dataset:
PENERAPAN POLA ASUH DEMOKRATIS DALAM MENUMBUHKAN MINAT BACA GENERASI ALPHA
Authors: Shaleha Imroatun , Riani Nur
Published: December 2023

The tradition of reading in the family is one of the habituations of parents in fostering interest in reading. The alpha generation is a child born in the digital era which is certainly very close to technology. People's parenting plays a role in growing children's reading standards. So, this study aims to determine the application of democratic parenting in Kecicang Asri Housing, Karangasem, Bali in fostering interest in reading. In addition, it is also to find out the causal factors and efforts of parents in growing interest in reading. The qualitative research with this descriptive approach uses the method of collecting observational data, interviews, and documentation. The results are, (1) the democratic parenting style provided by parents in fostering interest in reading is to provide a variety of reading books, educational games, and put up pictorial posters in the child's room. (2) Factors causing children's difficulty in cultivating interest in reading due to lack of care, habituation, and assistance from parents (internal) as well as from environmental factors (external). (3) The efforts made by parents in fostering interest in reading are by habituating to the bookstore, providing educational children's games, putting up posters and reading in the children's room. 
Abstrak
Tradisi membaca dalam keluarga menjadi salah satu pembiasaan orang tua dalam menumbuhkan minat baca. Generasi alpha merupakan anak yang lahir di era digital yang tentunya sangat dekat dengan teknologi. Pola asuh orang berperan dalam menumbuhkan minabat baca anak. Sehingga penelitian ini bertujuan untuk mengetahui penerapan pola asuh demokratis di Perumahan Kecicang Asri, Karangasem, Bali dalam menumbuhkan minat baca. Selain itu juga untuk mengetahui faktor penyebab serta upaya orang tua dalam penumbuhan minat baca. Adapun penelitian kualitatif dengan pendekatan deksriptif ini menggunakan metode pengumpulan data observasi, wawancara, dan dokumentasi. Hasil dari penelitian ini adalah, (1) pola asuh demokratis yang diberikan orang tua dalam menumbuhkan minat baca adalah menyediakan berbagai buku bacaan, permainan yang mendidik, dan memasang poster bergambar di kamar anak. (2) Faktor penyebab kesulitan anak dalam meumbuhkan minat baca karena kurang mendapatkan pengasuhan, pembiasaan, dan pendampingan dari orang tua (internal) serta dari faktor lingkungan tempat tinggal (eksternal). (3) Upaya yang dilakukan orang tua dalam menumbuhkan minat baca adalah dengan pembiasaan ke toko buku, memberikan permainan anak yang mendidik, memasang poster bergambar dan terdapat bacaan di kamar anak.
Understanding the Perspectives and Usability of Digital games for Children with Intellectual Disabilities
Authors: RP Dhiyaneshwari , C Renuga Devi
Published: December 2023

Typically, the digital games are used as a medium for teaching students having intellectual disabilities, and it helps the student to enhance their learning skills and to understand their surroundings. Intellectual disability is a neurological disease that manifests as a deficit in an individual's mental and adaptive functioning during childhood. Moreover, the computer-assisted training has been shown to be the most effective method of instruction for children with disabilities in terms of conceptual learning, academic accomplishment, and skill-based development. Traditionally, some existing research works are done in this field for analyzing the effectiveness of digital games. Accordingly, the main contribution of this research work is to determine the perception of special educators and usability of digital games in educational settings for children with intellectual disabilities. By identifying the needs for their design and use in those children's classes, this study intends to further illuminate how to employ digital games in education as a contribution to improving educable intellectually impaired children's teaching and learning practices. In addition, a case study is conducted in this work using a closed-ended questionnaire on a sample of 60 special educators, handling Children with Intellectual disabilities. According to this case study analysis, the quantitative analysis suggest that special educators have a strong need to use digital games to optimize learning for children with intellectual disabilities and to promote digital inclusion. Based on the outcomes, it is inferred that the digital game based learning could be more helpful and beneficial for the student with intellectual disabilities in real time.
A Machine Learning Model for Determination of Gender Utilizing Hybrid Classifiers
Authors: Nasien Dewi , Adiya M. Hasmil , Rahayu Yusnita , Dahliyusmanto Dahliyusmanto , Erlin Erlin , Anggara Devi Willieam
Published: December 2023

One part of forensic anthropology involves investigating skeletal remains to identify corpses, and many of these remains were found incomplete, burned, broken, or destroyed, making investigation challenging. This study aims to use the pelvis and femur to identify the gender of skeletal remains. The pelvis and femur have previously been proven to be accurate indicators of a corpse's gender. The identification process is done through the measurement of the subpubic angle of the pelvis and the angle taken straight down from the top of the femur to the patella and then straight up. The two measurements were combined using the principal component analysis (PCA) method into two attributes on the x and y axes. These attributes were later used as data for the machine learning model design. The design process consisted of an Artificial Neutral Network (ANN) design model and Support Vector Machine (SVM) design model combined into a hybrid machine learning system. The ANN and SVM hybrid machine learning were tested with acquired data. The result of the test using the confusion matrix showed 83.33% accuracy, which is categorized as "good classification" based on Area Under the Curve (AUC).
Effectiveness Analysis of Hydraulic Torque Wrench Machine Using Failure Mode and Effect Analysis (FMEA) and Logic Tree Analysis Study Case on Heavy Equipment Manufacturing
Authors: Prihananto Dhadung , Sahroni Taufik Roni
Published: December 2023

Production quality in terms of process efficiency and quality in the manufacturing industry must always be improved in order to maintain customer confidence. PT XYZ as a heavy equipment assembly company is one of the companies that depends on process reliability for a smooth production process. Based on this, the problems raised in this study focus on increasing the efficiency of the process of installing bolts on slew bearings. By using Overall Equipment Efficiency (OEE) and Process Capability (CpK) as the main benchmarks for measuring the quality of the production process where the latest data shows the average OEE value is at 18.53%, while the CpK value for the bolt tightening process is at 0 ,67. The OEE and CpK figures obtained show that the process quality is still not optimal and needs to be improved. The purpose of this research is to identify and prevent as many factors as possible that can lead to process failure. The methods used to evaluate processes and to identify where and how a process might fail are Failure Mode and Effect Analysis (FMEA) and Logic Tree Analysis (LTA). Both methods are used to identify and prevent as many factors as possible that can lead to a process failure. The results of research using the FMEA and LTA methods show that in the process of installing slew bearing bolts there is a process that needs to be improved because the RPN value is quite high, namely above 125. Some suggestions for improvement such as the use of a manipulator arm on a torque tool and the implementation of a manufacturing execution system (MES) can reduce the RPN value from above 125 to 28, where the process obtained is better than before.
Performance Evaluation of Logistics Service Provider (LSP) in FMCG Companies Using Physical Distribution Service Quality (PDSQ) Dimension: Case Study
Authors: Yuliawati Evi , Brilliana Clora , Rahmawati Nur , Trihastuti Dian
Published: December 2023

Increasingly fierce business competition requires companies to be able to meet customer desires on time, in the right amount and in the right quality. FMCG XXX Company is a skin care product manufacturing company that focuses on production activities. Therefore, the company transfers product distribution activities to customers (distributors) to Logistics Service Providers (LSP). FMCG XXX hold consumer’s satisfaction in the highest regard. Along with the increasing number of activities being diverted, FMCG XXX companies aim to evaluate LSP performance through appropriate indicators. The indicators evaluated in this study adopt dimensions in Physical Distribution Service Quality (PDSQ) which consist of three dimensions, namely timeliness, availability and condition. Based on the results of the study, 13 indicators were obtained that FMCG XXX Company used to evaluate LSP performance. In general, around 69% of LSP's actual performance has been able to meet the targets set by the company, where two indicators are able to exceed the target and seven indicators are in accordance with the target. However, the company still has to focus on four indicators that have negative deviations because the actual performance value is less than the target set by the company. Negative indicators come from the availability and condition dimensions. The company coordinates with LSP to design improvement projects in order to improve actual performance according to the company's targets.
The Business Digitalization Model to Enhance Family Business Performance
Authors: Gunawan Ricky Adrian , Sundjaja Arta , Pratama Andika
Published: December 2023

Digital transformation is changing how an organization uses technology, enterprise, processes, and people to improve performance and adopt a new business model. Digital transformation drives value through shared industry information and insights. However, several limitations, such as differences in culture and perspective between owners and management, impede the implementation of this digitalization. Harmonization is needed to keep the changes from getting out of hand because the digitization process is affected not only by sales, marketing, and finance processes but also by the culture of digitization. This study investigates the impact of digital organizational culture, digital capabilities, digital technology, and digital transformation strategy on the performance of family businesses. The research design is a quantitative study with structural equation modeling. The population in this study cannot be determined due to limited access to the association. The sample size was calculated using the G-Power calculator with an effect size of 0.15, an alpha level of 0.05, and a power of 0.80. According to the calculation, there are 43 respondents in the study. The sampling technique is convenient sampling. The survey was distributed online using questionnaires sent via email. The data analysis software is Smart PLS 4.0.8.5. The result shows that the organization's culture plays a big part in improving performance. The organization's culture strongly affects business digitization and technology value development. The value of developed technology affects business performance. Therefore, the top management needs to prioritize the IT development that transforms their business and improves business performance
Application of E-Glass Jute Hybrid Laminate Composite with Curved Shape on Compressive Strength of Cylindrical Column Concrete
Authors: Zulfikar Achmad Jusuf , Yaakob Mohd Yuhazri , Syah Rahmad Bayu
Published: December 2023

This study provides a better understanding of reinforcing cylindrical concrete columns (CCC) using a hybrid laminated composite material (HLC) composed of jute and e-glass fibers, including the influence of layer quantity on strength and a comparison with previous research. The utilization of these alternative materials may lead to the development of novel and efficient solutions for constructing durable and robust structures. The primary objectives of this research are to assess the effects of employing HLC as a reinforcing layer on CCC compressive strength, optimize the reinforcement process by selecting appropriate layer sequences and types, and analyze the type of fiber damage in relation to the strength of HLC composite material. The materials utilized in this study encompass woven jute fabric sheets, e-glass fiber sheets, and epoxy resin. Compressive strength testing was conducted following ASTM C39 standards. Specimen variations were based on the number and type of reinforcing layers. The results revealed that CCC compressive strength increased by up to 100% with the application of up to three layers of jute compared to an unlayered specimen. Furthermore, CCC compressive strength experienced a remarkable enhancement of up to 150% with the incorporation of HLC composite. Hence, the implementation of HLC demonstrates significant potential for augmenting the strength of concrete structures.
Soft Skills and Hard Skills Needed In Industry 4.0 For Electrical Engineering Students
Authors: Sukardi Sukardi , Jalinus Nizwardi , Islami Syaiful , Sakti Rizki Hadian , Husnuzhan Husnuzhan , Zaus Anggi Agni , Zaus Mahesi Agni
Published: December 2023

This paper investigates industry perceptions regarding the relevance of the courses in the curriculum provided by universities and whether they are in accordance with the demands that exist in the industrial world. This research uses a descriptive survey method. The sample taken from electrical engineering alumni who worked in industry was 242 people. This research uses a stratified random sampling technique. The instrument used is a 4-point scale. The assessment was rated Strongly Agree, Agree, Disagree, and Strongly Disagree with weights of 4, 3, 2, and 1, respectively. Three vocational education experts validated the instrument. Reliability was performed with Aiken-V. The questionnaire contains 34 questions. Research data was analysed by percentage, mean, and standard deviation. The findings show that the soft skills and hard skills achieved in each course in the curriculum are arranged in accordance with industry needs. Soft skills and hard skills in the curriculum can be provided to students so that they can look for related jobs.
Analysis and Identification of Non-Impact Factors on Smart City Readiness Using Technology Acceptance Analysis: A Case Study in Kampar District, Indonesia
Authors: Anam M. Khairul , Yunianta Arda , Alyamani Hasan J. , Erlin Erlin , Zamsuri Ahmad , Firdaus Muhammad Bambang
Published: December 2023

Most countries start to implement Smart Cities as an innovation for urban strategy. However, not all Smart Cities implementations worked and were implemented well, because the community still not ready for the implementation of Smart City. The aim of this research is to investigate community readiness and finding low impact factors for implementing smart cities based on 5 factors, namely AU, PEOU, ATU, BIU, and PU. This research was using a qualitative study with the Technology Acceptance Model approach (TAM) to investigate the relationship between 5 factors. Based on the results of data distribution, there are 2 clusters, namely people who know about public service applications and people who are not aware of any public service applications. Furthermore, there are 3 tests conducted in this research namely T-test, F-test and Coefficient Determination Test to determine the impact and influence of the relationship between each factor. However, from the results of the t-test it was found that there were 2 relationships that had no impact because the t-count was negative and the 2 relationships between these factors were between PU - AU and AU - PU.
Trends in E-Commerce And Social Media Research in Asia: Five Years of Scientometric and Content Analysis
Authors: Aulawi Hilmi , Suseno Novie Susanti , Abdullah Khairul Hafezad
Published: December 2023

This paper aims to provide scientometric and content analysis towards e-commerce and social media research in Asia. The Web of Science (WoS) and Scopus databases were used in searching for articles. There were 884 (433 publications from the Web of Science and 451 articles from Scopus) papers analysed. Based on the analysis of two databases, the number of publications from the Web of Science database showed a significant increase yearly. In comparison, the Scopus database showed fluctuating growth every year. One of the countries that enormously contributed to the research was China, which can be seen from the author’s and country’s analyses. The ACM International Conference Proceeding Series was the most contributing conference proceedings. Based on the keyword results, there are five keywords that appear most often. Referring to the data from the last two years (2021–2022), the keywords “machine learning” and “social media marketing” are the most frequently used. These two keywords are most often associated with e-commerce and social media keywords. These findings are expected to provide a substantial understanding towards e-commerce and social media research, particularly in the Asian region. This paper will assist researchers in understanding new topics, collaborating with other researchers, and determining relevant sources and countries. Analysed keywords can inspire new research. Consequently, researchers can learn about new technology, societal changes, and impending challenges and opportunities by tracking keyword trends.
Improving Text Summarization Quality by Combining T5-Based Models and Convolutional Seq2Seq Models
Authors: Lubis Arif Ridho , Safitri Habibi Ramdani , Irvan Irvan , Lubis Muharman , Al-Khowarizmi Al-Khowarizmi
Published: December 2023

In the natural language processing field, there are several sub-fields that are very closely related to information retrieval, such as the automatic text summarization sub-field. obtained from the convolutional T5 and Seq2Seq models in summarizing text on hugging faces found features that can affect text summary such as upper- and lower-case letters which have an impact on changing the understanding of the text of the document. This study uses a combination of parameters such as layer dimensions, learning rate, batch size, and the use of Dropout to avoid model overfitting. The results can be seen by evaluating metrics using ROUGE. This study produces a value of ROUGE-1 on 4 documents that are tested which produces an average of 0.8 which is the optimal value, for ROUGE-2 on 4 documents that are tested which results in an average of 0.83 which is an optimal value while ROUGE-L on 4 documents conducted tests that produce an average of 0.8 which is the optimal value for the summary model.
Examining the Practicality of Mobile-Based Gamification Assessment in Electrical Machine Course: A Study in Industrial Electrical Engineering
Authors: Yanto Doni Tri Putra , Ganefri Ganefri , Sukardi Sukardi , Kurani Rozalita , Yanto Jelpapo Putra
Published: December 2023

Mobile-based gamification learning is increasingly popular for enhancing student interest and motivation in the learning process, including its application in evaluating learning outcomes. However, the practicality of its use, from the perspective of students as users, needs further evaluation. This study aims to assess the practicality of mobile-based gamification assessment (M-BGA) in evaluating student learning outcomes in the Electrical Machine Course (EMC). M-BGA was developed using Kahoot! application. A survey-based quantitative research design was employed, using the Practicality Assessment Instrument (PAI) as the data collection tool. The practicality of M-BGA was evaluated based on student assessments after its implementation in an EMC. This research involved 83 second-year students from the Industrial Electrical Engineering Study Program, Faculty of Engineering, Universitas Negeri Padang, Indonesia. The results indicate a high level of practicality in several aspects. The Ease of Use aspect scored 92.23% (highly practical), the Reliability aspect scored 89.82% (highly practical), the Student Engagement aspect scored 88.55% (highly practical), and the Learning Impact aspect scored 90.19% (highly useful). Overall, based on student responses, the M-BGA proved to be highly practical in evaluating student learning outcomes in the EMC. M-BGA can serve as an alternative approach for assessing student learning outcomes with an innovative approach.
Comparison Between Face and Gait Human Recognition Using Enhanced Convolutional Neural Network
Authors: Sadeq Fatima Esmail , Al-Ta'i Ziyad Tariq Mustafa
Published: December 2023

Identifying people at distance is an important task in daily life Because of the increase in terrorism. Biometrics is a better solution to overcome personal identity problems, and this applies to soft biometrics also. Soft biometric are features that can be extracted remotely and do not require cooperation with people. This paper introduces a comparison between human face recognition and human gait recognition using soft biometric features. Nine face attributes and nine gait attributes are taken from a dataset built by researchers. The constructed dataset is composed from (66) videos for (33) persons. Features are extracted using Haar and MediaPipe methods. The extracted features are classified using enhanced convolutional neural network. This work achieves an accuracy of 95.832% in human face recognition and an accuracy of 89.583% in human gait recognition. From the above results it turns out that the proposed method achieved promising results with regard to Recognize people remotely
A Conceptual Aquila Merged Arithmetic Optimization (AIAO) Integrated Auto-Encoder Based Long Short Term Memory (AUE-LSTM) For Sentiment Analysis
Authors: J Sangeetha , V Maria Anu
Published: December 2023

Sentiment analysis is a branch of analysis that uses disorganized written language to infer the opinions and emotions of people's critiques and attitudes toward entities and its features. In order to produce acceptable results, the majority of sentiment analysis models that employ supervised learning algorithms require a large amount of labeled information during the training stage. This is typically costly and results in significant labor expenses when used in practical applications. In this study, an intelligent and unique sentiment prediction system is developed for accurately classifying the positive, negative, and neutral comments from the social media dataset. Data preprocessing, which entails noise reduction, tokenization, standardization, normalization, stop word removal, and stemming, is done to ensure that the data is of a high enough quality for efficient sentiment prediction and analysis. The preprocessed data is then used to extract a mix of features, including hash tagging, Bag of Words (BoW), and Parts of Speech (PoS). Consequently, in order to choose the best features and speed up the classifier, a new hybrid optimization method called Aquila merged Arithmetic Optimization (AIAO) is used. Furthermore, an Auto-Encoder based Long Short Term Memory (AuE-LSTM), an innovative and clever ensemble learning technique, is used to precisely anticipate and classify user feelings based on the chosen data. This study uses a variety of open source social media datasets to evaluate the performance of the suggested AIAO integrated AuE-LSTM model.
SQL Injection Detection Using RNN Deep Learning Model
Authors: ALAzzawi Abdulbasit
Published: December 2023

SQL injection attacks are a common type of cyber-attack that exploit vulnerabilities in web applications to access databases through malicious SQL queries. These attacks pose a serious threat to the security and integrity of web applications and their data. The existing methods for detecting SQL injection attacks are based on predefined rules that can be easily circumvented by sophisticated attackers. Therefore, there is a need for a more robust and effective method for detecting SQL injection attacks. In this research, we propose a novel method for detecting SQL injection attacks using recurrent neural networks (RNN), which are a type of deep learning model that can capture the syntax and semantic features of SQL queries. We train an RNN model on a dataset of benign and malicious SQL queries, and use it to classify queries as either benign or malicious. We evaluate our method on a benchmark dataset and compare it with the existing rule-based methods. Our experimental results show that our method achieved high accuracy and outperformed the rule-based methods for detecting SQL injection attacks. Our research contributes to the field of web application security by providing a new and effective solution for protecting web applications from SQL injection attacks using deep learning. Our method has both practical and theoretical implications, as it can be easily integrated into existing web application security frameworks to provide an additional layer of protection against SQL injection attacks, and it can also advance the understanding of how deep learning models can be applied to natural language processing tasks such as SQL query analysis.
Intensive Malware Detection Approach based on Data Mining
Authors: Salem Israa Ezzat , Al-Saedi Karim Hashim
Published: December 2023

Malicious software, sometimes known as malware, is software designed to harm a computer, network, or any of the connected resources. Without the user's knowledge, malware can spread throughout their computer system. Malware is typically disseminated via online connections and mobile devices. While malware has always been a problem in the digital age, its effects have gotten increasingly serious. Traditional malware detection methods seek to locate specific malware samples and families to recognize harmful codes and can be located using traditional signature- and rule-based detection methods. The research focuses on developing malware detectors using data mining techniques. The proposed method outlined below sets itself apart by emphasizing the processing of malware behaviors significantly dependent on aspects. Finding more dependable intelligent detecting techniques is a crucial component of this paper. In order to identify the cluster of the most essential malware features and use decision tree classifiers for malware detection, the study, a common methodology for creating malware detectors based on data mining, is implemented and investigated. Our approach can identify the most significant features of malware that can significantly determine and detect a malware code.
Fuzzy Genetic Particle Swarm Optimization Convolution Neural Network Based On Oral Cancer Identification System
Authors: Dharani R , Revathy S. , Danesh K.
Published: December 2023

Oral cancer is the eighth most common type of cancer in the world. Every year, 130,000 people in India die from mouth cancer. Getting a diagnosis from a clinical exam by skilled doctors and a biopsy takes time. When a problem is found early, it is always easier to treat. The primary goal of this work is to recognise disease-affected oral regions in a given oral image and classify the oral cancer disorder. This study employs unique Deep Learning algorithms to detect the location of disease-affected oral areas. This work employs the most effective feature extraction techniques, including appearance and patter-based features. Following feature extraction, the Bee Pulse Couple Neural Network (BeePCNN) algorithm is used to choose the best feature. Finally, Deep Learning is used to classify these attributes. An innovative FGPSOCNN reduces the computational complexity of CNN. On an additional real-time data set from Arthi Scan Hospital, a secondary evaluation is conducted. The experimental results indicate that the innovative FGPSOCNN performs better than existing methods.
Student Acceptance Study of PhET Simulation with an Expanded Technology Acceptance Model Approach
Authors: Faizah Silviana Nur , Dina Lia Nur Atiqoh Bela , Kartiko Ari , Ma`arif Muhammad Anas , Hasan Moch. Sya'roni
Published: December 2023

Phet simulation is a computer-based practicum simulation medium that helps to increase students’ engagement and understanding through concept visualization. Even though there have been numerous studies on the Technology Acceptance Model (TAM) related to Phet simulation, the TAM study of Phet simulation combined with certain learning methods is rarely observed. We propose an advanced version of TAM by including the external variables of system quality, user characteristics, and instructor. This study is a quantitative design with a descriptive, explanatory type. This model was tested using an online questionnaire disseminated to 49 students that finished taking basic natural sciences subjects using Phet simulation based on problem-based learning. The result showed that system quality has an effect on perceived usefulness, perceived ease of use has an effect on behavioral intention of use, behavioral intention of use has an effect on actual usage, and there is no relationship between instructor quality on perceived usefulness. Grit on perceived ease of use, learner anxiety, and perceived usefulness on the behavioral intention of use. These findings have implications regarding user acceptance of Phet simulation combined with certain learning methods, specifically problem-based learning.
Enhancing Support For Senior Citizens: Development And Evaluation of The OSCA Information Management System With Agile Methodology and ISO/IEC 25010 Compliance
Authors: Velasquez Johannah Mae C. , Cochanco Alexander S. , Luciano Ruth G.
Published: December 2023

The elderly were a member of the vulnerable group which the government supported and assisted in every way possible. To contribute to the support and assistance needed by the elderly who are called senior citizens, this study was conducted. This aims to develop and design a usable, performance-efficient, and functional suitable to the operation and service of the Office of the Senior Citizen Affairs (OSCA), Cabanatuan City office. The System Application Office of the Senior Citizen Affairs Information Management System with Analytics (OSCA-IMSA) was developed using the Agile System Development Life Cycle (SDLC) Model. The agile model has different phases and sub-phases that guarantee the quality and efficient development of the system. Every phase and sub-phases lead to a well-organized, and systematic process of system development. The proponents adopted the ISO/IEC 25010 criteria as an evaluation tool to assess the system's usability, reliability, performance efficiency, functional suitability, security, portability, maintainability, and compatibility. The self-made survey questionnaire was used as the main tool to collect the data from the respondents. Purposive sampling was used to determine the right respondents for the study. The study was composed of two different sets of respondents, the first set was the System Users and the second set was composed of IT Experts. The Office of the Senior Citizen Affairs Information Management System with Analytics (OSCA-IMSA) was evaluated and assessed by the respondents with a result of being highly functional, highly efficient, highly portable, highly maintainable, highly compatible, highly secured, highly reliable, and highly usable. This result indicates that the system passed and conformed to the ISO/IEC 25010 Software Product Quality Standard, hence, is recommended to be deployed at the research locale.
Standardscaler's Potential in Enhancing Breast Cancer Accuracy Using Machine Learning
Authors: Aldi Febri , Hadi Febri , Rahmi Nadya Alinda , Defit Sarjon
Published: December 2023

The major consequence of breast cancer is death. It has been proven in many studies that machine learning techniques are more efficient in diagnosing breast cancer. These algorithms have also been used to estimate a person's likelihood of surviving breast cancer. In this study, we employed machine learning algorithms to predict breast cancer. A total of 569 breast cancer datasets were obtained from kaggle sites. Some of the machine learning algorithms that we use are K-Nearest Neighbor (KNN), besides Random Forest (RF), there is also Gradient Boosting (GB), then Gaussian Naive Bayes (GNB), Vector Support Machine (SVM), and then Logistic Regression (LR). Before algorithms were used to train and test breast cancer datasets, StandardScaler was leveraged to transform training datasets and test datasets for improved algorithm performance. As a result of this utilization, the performance measurement carried out succeeded in producing high accuracy. The highest results were obtained from the Logistic Regression algorithm with an accuracy value of 99%. The value of precison is 99% benign, and 100% malignant. The recall results are 100% benign, and 98% malignant. The F1-Score results show 99% benign, and 99% malignant. It is hoped that this research can help the medical party to determine the next step in dealing with breast cancer.
Optimizing Cloud-Fog-Edge Job Scheduling Using Catastrophic Genetic Algorithm and Block Chain-Based Trust: A Collaborative Approach
Authors: Mohammed Ali Nibras A. , Mohammed Ali Firas A.
Published: December 2023

Collaborative edge-cloud features improve job scheduling. Cloud job scheduling is crucial. Pending delay completion. A cloud-edge mixed system replaced centralized cloud computing. Combining resource levels reduces terminal user service call latency. Decentralization, regionalization, and node dispersal autonomy increase ambiguity, unreliability, and instability. This paper will plan cloud-migrating tasks on edge devices or the cloud to achieve a global optimum. The objective of this research is to enhance the efficiency of job scheduling in cloud-fog edge environments through the integration of the Catastrophic Genetic Algorithm (CGA), a genetic algorithm inspired by natural evolution. Additionally, Berger's theory will be employed to develop a trust-enabled interaction framework based on blockchain technology. The CGA fitness function incorporates load balancing and reasonability in the coordination of services and scheduling of tasks, with the goal of maximizing performance. This article presents proposed improvements to the CGA, which involve the incorporation of mutation and crossover operators, roulette selection, and cataclysm. These changes aim to expand the search area and potentially discover schedules that are more optimal. The approach also effectively deals with the problem of premature convergence, guaranteeing ample time for the algorithm to comprehensively explore the solution space prior to reaching a final solution. The experimental findings indicate that the strategy put forward in this study yields a substantial reduction in task completion time, surpassing 97%. Furthermore, it effectively addresses the best local problem, hence showcasing competing options.
Triglycerides of Crude Palm Oil to Biokerosene: Studies on Electrolysis and Electromagnetic Effect
Authors: Primandari Sri Rizki Putri , Krismadinata Krismadinata , Yuvenda Dori , Lapisa Remon , Kurniawan Andre , Mulianti Mulianti , Bustan Muhammad Djoni , Haryati Sri , Sushanti Gusni , Elshaarani Tarig , Chaniago Yus Donald
Published: December 2023

Crude Palm Oil (CPO) is a potential feedstock for biokerosene. However, it is problematic when used directly because it is gummy, has a high viscosity and is degradable. Various conversion processes have been conducted that directly convert CPO into biokerosene, but it requires high temperature and pressure. Therefore, as a novelty, this study aims to develop the technology for converting triglycerides into biokerosene under relatively low operating conditions and producing similar petroleum kerosene by electrolysis-assisted and electromagnetic induction. In this study, the conversion technology process was conducted in three steps (i) converting triglycerides to Free Fatty Acids (FFA), (ii) converting FFA to alkanes, and (iii) converting alkanes to biokerosene. Step (ii) is assisted by the electrolysis process, meanwhile, step (iii) is assisted by electromagnetic irradiation. The finding showed that electrolysis obtained 73.47% yield of alkanes and electromagnetic irradiation obtained 78.02% yield of biokerosene.  Biokerosene is almost close to kerosene-based petroleum in terms of colour Saybolt, flash point and Net Heating Value. The findings of this study may provide an alternate technology approach for biokerosene synthesis and solution kerosene scarcity.
Multi-Object Detection Using YOLOv7 Object Detection Algorithm on Mobile Device
Authors: Kusuma Patricia Citranegara , Soewito Benfano
Published: December 2023

This research discusses the importance of enhancing real-time object detection on mobile devices by introducing a new multi-object detection system that uses the quantified YOLOv7 model. Focusing on the complexities of food item detection, particularly in diverse and intricate contexts, our study uses a dataset that includes five food classes. By investigating the influence of data quantity on the detection model, we demonstrate the superiority of larger datasets in both YOLOv5 and YOLOv7. In addition, our comparison shows that YOLOv7 has better precision, recall, and F1-score values compared to YOLOv5. The crucial methodological contribution lies in the successful quantification of the YOLOv7 model, reducing the model size from 28.6 KB to 14.3 KB and enabling seamless mobile application development. This high-performance mobile application displays a real-time interface response time of 235ms, with precision, recall, and F1-score values of 0.923, 0.9, and 0.911, respectively. Beyond the practical implications for informed dietary choices and improved health outcomes, our study develops object detection techniques theoretically, offering valuable insights that can be applied across various domains and emphasizing the potential impact of our approach on both theory and practice
The Readiness of Minang Weaving Towards Halal Fashion Adoption: A Clustering Analysis of Toe Framework
Authors: Lita Ratni Prima , Putri Nilda Tri , Meuthia Meuthia , Rahmi Devi Yulia
Published: December 2023

This research focuses on clustering the readiness of halal practice implementation in Minang weaving businesses, then based on the clusters that are very ready, it is then carried out the identification of the determinant factors of the readiness to implement the Halal Assurance System in Minang weaving businesses. Sampling was conducted using the non-probability sampling technique through purposive sampling from 103MSMEs of weaving in West Sumatra. The results of this research through K-means cluster analysis show that the grouping of Technology, Organization, Environment (TOE ) halal adoption in weaving MSMEs consists of 6 readiness groups, namely termination (15 MSMEs), maintenance (43 MSMEs), action (23 MSMEs), preparation (13 MSMEs), contemplation ( 2 MSMEs), pre-contemplation (7 MSMEs) spread across five cities/regencies in West Sumatra (Sawahlunto City and 50 Cities Regency which consists of 34 MSMEs respectively, 30 MSMEs from Tanah Datar Regency, 3 MSMEs from Sijunjung Regency, and 2 MSMEs from Payakumbuh City). Of the three determinants of TOE adoption tested, MSMEs' perceptions of technology readiness through the dimensions of compatibility and perceived benefits are higher than organizational and environmental factors. This research has theoretical and practical implications through exploration of the TOE model so that the results of this study can become a further research agenda in encouraging halal certification through developing a halal adoption strategy based on HAS 23000 in weaving MSMEs in West Sumatra.
Optimized Deep Convolutional Neural Network for the Prediction of Breast Cancer Recurrence
Authors: I Arathi Chandran R , Bai V Mary Amala
Published: December 2023

With more than 2.1 million new cases of diagnosis each year, breast cancer is considered to be the most prevalent women disease. Within 10 years, nearly 30% patients who got cured at early-stages experienced cancer recurrence. Recurrence is a crucial aspect of breast cancer behaviour that is inseparably linked to mortality. Despite its importance, the significant proportion of breast cancer datasets rarely include it, which makes research into its prediction more challenging. It is still difficult to predict who will experience a recurrence and who won't, which has implications for the treatment that goes along with it. Clinicians treating breast cancer may be able to avoid ineffective overtreatment if Artificial Intelligence (AI) methods are developed that can forecast the likelihood of breast cancer recurrence. This work proposes a novel automatic breast cancer recurrence classification and prediction system incorporating novel Deep Convolutional Neural Network (DCNN) algorithm. The proposed DCNN model is deployed on Wisconsin Breast Cancer dataset for further evaluation. The role of AI in forecasting recurrence is examined in this work. The experimental results were analysed for various combination of train and validation dataset. The accuracy, precision, recall and F1-score for the proposed DCNN was calculated as 97.63 %, 98.57 %, 96.84 %, 97.89 % respectively.
The Effect of Marketing Pattern and User Perceived Value of Fitness Application on Consumption Behavior
Authors:   Korean Society for Leisure Scie, Chen Qiuru , Kim Sangyoo
Published: December 2023

The purpose of this study was to examine the relationship between marketing pattern and user perceived value of fitness applications on user consumption behavior. Therefore, 480 residents in Anhui province were randomly given questionnaires, and 447 valid questionnaires were collected and sorted out for practical study. SPSS 26.0 was used to analyze the data and verify the hypotheses proposed in this study, using correlation analysis, multiple regression analysis. The main conclusions of this study are as following: First, application marketing pattern all have positive effects on information collection, purchase and post-purchase evaluation. Second, perceived value all have positive effects on user information collection, purchase and post-purchase evaluation.
The Mediating Effects of Sports Confidence in the Relationship between the Fun Factors and Self-Realization in Liberal Arts Physical Education Class
Authors:   Korean Society for Leisure Scie, Seol Su-Hwang , Lee Seung-Bum
Published: December 2023

The purpose of this study is to investigate the mediating effect of self-realization on the relationship between fun and sports confidence commitment of liberal arts physical education class. To achieve the goal of this study, a total 230 surveys collected were utilized for analyzing. Data were analyzed frequency analysis and internal consistency analysis to determine demographic characteristics. After that, confirmatory factor analysis, correlation analysis, and structural equation modeling were used. Main findings were as follows: First, fun of liberal arts physical education class had a positive effect on sports confidence. Second, sports confidence of liberal arts physical education class had a positive effect on self-realization. Third, fun of liberal arts physical education class had not effect on self-realization. Fourth, sports confidence mediated the relationship between fun and self-realization. Therefore, it is necessary to increase positive psychological capital through the fun of liberal arts and physical education classes as a way for college students to achieve self-realization.
Peningkatan Kemampuan Membaca Al-Qur’an melalui Penerapan Metode Ummi Bagi Santri Pondok Pesantren Al-Waridin Kabupaten Madiun
Authors: Prayitno Mustofa Aji , Albab Muhammad Ulil , Fadly Wirawan
Published: December 2023

One method that can be used in the education of reading and writing the Qur'an is the Ummi Method. The Ummi method is a method of reading the Qur'an with tartil. Although it is classified as a new method, it has been used by more than 1000 institutions in 24 provinces in Indonesia in 2018. The objectives to be achieved in this community service research are: 1) Introducing the Ummi method to the students of the Al-Waridin Islamic boarding school; 2) Improve the ability to read the Qur'an properly and correctly according to the law of reading (tajwid) and makhorijul letters for students of Al-Waridin Islamic boarding school; 3) Improve the ability to read the Koran with mujawas (tone). The method used is the ABCD (Asset Based Community Driven) method which focuses on improving the ability to read the Qur'an through the application of the Ummi method for the students of the al-Waridin Islamic boarding school. The ABCD method is considered appropriate to be applied because it is asset-based which is in line with the potential possessed by Islamic boarding schools in particular and Pagotan Village in general. The ABCD method has six stages, namely 1) discovery, 2) dream, 3) design, 4) define, 5) destiny, and 6) reflection. The results of the community service research show that the training to read the Qur'an using the ummi method for students at the al-Waridin Islamic boarding school can be declared successful. Participants who previously did not know the makhorijul letters, now have begun to understand and are able to apply the correct pronunciation of makhorijul letters, participants who previously did not know the Ummi method became aware of the methods and styles used in the Ummi method. It is hoped that through training to improve the ability to read the Qur'an through the application of the Ummi method for the students of the Al-Waridin Islamic Boarding School, it can increase the interest of the Al-Waridin Islamic boarding school students to explore the sciences in reading and writing the Qur'an and can increase students' interest in learning Arabic properly and correctly.
Pengenalan Game Edukasi untuk Meningkatkan Perbendaharaan Kosa Kata Benda dalam Bahasa Inggris
Authors: Hariadi Fajar , Jumalia Jumalia , Talakua Alfrian Carmen
Published: December 2023

English is one of the subjects in the school curriculum in Indonesia. One of the English learning materials in class 3 of East Sumba 1 State Madrasah Ibtidaiyah (MIN) is the introduction to objects in English. The current learning process combined with educational game learning media shows an increase in the ability of 28 children to vocabulary nouns in English by 14.54% from the pre-test average result of 78 to 90 on the post-test results. The results of community service show that guidance and empowerment in learning English using educational games have a positive impact and get a good response from students. Empowerment has an important role in encouraging student motivation and increasing student achievement. It is hoped that this community service activity can be sustainable and become one of the collaborations between institutions so that these institutions help form an intelligent, wise and prosperous society.
Inovasi Produk Olahan Susu Aneka Rasa dan Warna di Desa Pagersari Kecamatan Ngantang Kabupaten Malang
Authors: Faizin Nur , Irawati Santi , Soseco Thomas , Nurjanah Nunung
Published: December 2023

This paper presents the results of a community engagement project conducted in Pagersari village, Ngantang district. The project aimed to address issues related to milk processing, packaging, and marketing in the community. The proposed solution involved the development of flavoured and coloured milk beverages that could be produced at home using simple cooking utensils. The community learned how to transform milk into products with various appealing flavours and colours through training and mentoring. Additionally, packaging and labelling training was provided to enhance the products' visual appeal. Marketing efforts included the provision of attractive stands and carts with character designs for selling milk products. Collaboration with the State University of Malang was established to optimize processing and marketing as the project expanded. Ongoing monitoring and evaluation, broadening offline and online marketing channels, and strengthening collaborations with relevant stakeholders were recommended for further improvement. This project is expected to sustainably impact the Pagersari community and serve as an inspiring model for home-based industry development in other regions