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SSRN 2022年

作者： Bimantara, I. Made Satria Yuhana, Umi Laili Supriana, I. Wayan Pardede, Eric Department of Informatics Institut Teknologi Sepuluh Nopember 60117 Indonesia Informatics Study Program Faculty of Mathematics and Natural Sciences Udayana University Indonesia Department of Computer Science and Information Technology La Trobe University BundooraVIC3086 Australia

University Course Timetabling (UCT) is a common problem in educational institutions. The preparation of the class schedule must pay attention to available resources without violating set constraints. This research applies Evolutionary Algorithm such as Genetic Algorithm into timetabling system, to replace human expertise in generating optimal lecture schedules. Genetic Algorithm (GA) uses chromosomes to represent the solution of the UCT. One chromosome represents a set of schedule solutions that AG generates. Genes and alleles become components of chromosomes that represent the value of each entity to be optimized. We modeled chromosomes into four gene types, each of which has three allele types, namely day, hour, and room alleles which will be optimized with GA. The N-point and cycle crossovers were implemented into the new chromosome encoding scheme and do not take place at the gene level, but at the allele level by grouping similar allele types before the crossover process is carried out. The success rate is measured by the percentage of the optimal number of schedules generated from the trials. The proposed method provides a success rate of 80 - 85% and can produce an optimal schedule with an average computation time of 8 minutes. GA can reduce human resources and save time in the process of preparing lecture schedules. © 2022, The Authors. All rights reserved.

关键词： Genetic algorithms

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The Design of VBee Diary Writing Application

The Design of VBee Diary Writing Application

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International Conference on Education and technology (ICET)

作者： Christiana Sidupa Hermawan Nugroho Yella Dezas Perdani Interior Design Department Digital Language Learning Center Faculty of Humanities Bina Nusantara University Jakarta Indonesia Informatics Engineering Study Program Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Interior Design Department Digital Language Learning Center Faculty of Humanities Bina Nusantara University Bandung Indonesia

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools.

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer Science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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Profile of Students' Technological Content Knowledge in School Mathematics 1

Profile of Students' Technological Content Knowledge in Scho...

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1st International Conference on Computer, Science, Engineering and technology, ICComSET 2018

作者： Mulyanti, Yanti Rahmat, Dadan Darhim Mathematics Education Study Program FKIP UMMI Indonesia Information Technology Education Study Program FKIP UMMI Indonesia

This study aims to find out the technological content knowledge profile of Mathematics Education Students of Teacher Training and Education Faculty, Universitas Muhammadiyah Sukabumi who have completed courses in Mathematics Capita Selecta III. The research method used is descriptive with quantitative approach. Data is collected by survey method, using a questionnaire instrument whose statement is based on the component of technological content knowledge. The results showed that students' technological content knowledge was in a good category with an means 3.52 which means that students of Mathematics Education understood how to integrate technology and material in learning school mathematics. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Students

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Classification Of Aedes Mosquito Larva Using Convolutional Neural Networks And Extreme Learning Machine

Classification Of Aedes Mosquito Larva Using Convolutional N...

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International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM)

作者： Pauzi Ibrahim Nainggolan Syahril Efendi Mohammad Andri Budiman Maya Silvi Lydia Ivan Joshua Dhani Syahputra Bukit Romi Fadillah Rahmat Ledy Afrida Sinaga Edi Subroto Department of Computer Science Universitas Sumatera Utara Medan Indonesia Department of Information Technology Universitas Sumatera Utara Medan Indonesia Department of Public Health Universitas Sumatera Utara Medan Indonesia Environmental health and diseases control Ministry of Health Medan Indonesia Department of midwifery study program STIKes Mitra Husada Medan Sumatera Utara Indonesia

The spread of diseases transmitted by Aedes mosquitoes, such as Dengue fever, Chikungunya (CHIKV), and Zika, poses a severe health problem in many countries. Aedes mosquitoes can be found in tropical and subtropical areas. One method to control the diseases is by controlling the population of Aedes mosquitoes, and one way to control the population of Aedes mosquito is by exterminating Aedes mosquito larvae. Identifying mosquito larvae, however, demands a considerable amount of effort, time, and specialized knowledge about the morphology and anatomy of mosquito larvae to accurately classify the various types. Therefore, a system is needed to classify Aedes and non-Aedes mosquito larvae. In this study, classification was carried out using larvae images taken using a digital microscope. The methods used to classify mosquito larvae images are Convolutional Neural Networks (CNN) to extract features from the larvae image and Extreme Learning Machine (ELM) to classify the larvae image. The result obtained from evaluating the CNN-ELM model is an accuracy of 98%, f1-score of 99% for Aedes larvae, and fl-score of 96% for non-Aedes larvae.

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Optimization of hyper parameter bandwidth on naïve Bayes kernel density estimation for the breast cancer classification 2

Optimization of hyper parameter bandwidth on naïve Bayes ke...

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2nd International Conference on information and Communications technology, ICOIACT 2019

作者： Sasongko, Theopilus Bayu Arifin, Oki Al Fatta, Hanif Information Technology Department Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Management of Informatics Study Program Economy and Business Departement Politeknik Negeri Lampung Lampung Indonesia

ISBN: (纸本)9781728116556

Cancer is viewed as the most harmful disease in the world. One of the most deadly cancer diseases attacking the women is breast cancer. In this paper, used Naïve Bayes classifier Kernel Density Estimation in breast cancer Wisconsin dataset take from UCI data repository. Naïve Bayes with Kernel Density Estimation was used as it could enable the Naïve Bayes to process the quantitative data. However, the performance of KDE (kernel density estimation) highly depends upon the size of the bandwidth parameter used to control the curve. The problem an accurate choice of parameter bandwidth (h) using trial and error technique requires a long process. A large bandwidth (h) will over-smooth the density and mask the structure in the data, a small bandwidth (h) will yield a density estimate that is spiky and very hard to interpret. The aim of this research is to compare the optimization of grid search parameter with the genetic algorithm to determine the bandwidth parameter (h) on the Naïve Bayes Kernel Density Estimator algorithm. The parameters used to compare the two optimization methods included accuracy, AUC (Area under Curve), and computation time. The experiment results on the test of the significance value on the comparison of grid search and algorithm in determination of the bandwidth parameter (h) naïve Bayes kernel density used Mann-Whitney Test. The result of the significance ranking showed that mean rank of the genetic algorithm accuracy was 489.95 better than the mean value of the rank of grid search accuracy at only 189.05, mean rank of AUC genetic algorithm was 491.82 better than mean rank of AUC grid search only at 187.18. The mean rank of computation time grid search was 243.37 faster than mean rank of computation time genetic algorithm at 435.63. © 2019 IEEE

关键词： Classification (of information)

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Survival analysis of Kasturi tobacco plants in Jember district using the stratified cox and extended cox models.

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MethodsX 2025年 14卷

作者： Angga Iryanto Pratama Dwi Rantini Ratih Ardiati Ningrum Arip Ramadan Fazidah Othman Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Research Group of Data-Driven Decision Support System Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Surabaya 60115 Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Surabaya Campus Surabaya 60231 Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaya Malaysia

In 2022, tobacco was the top export commodity, generating $106.3 million in sales. East Java Province contributes significantly to Indonesia's tobacco production, with an annual output of 188.6 thousand tons. Jember Regency is the area in East Java Province which is a Kasturi tobacco cultivation area. The productivity of Kasturi tobacco continues to decrease due to several factors that can affect the survival of the tobacco. This study aims to analyze the survival of Kasturi tobacco by creating stratified Cox and extended Cox models in order to handle factors that cannot fulfill the proportional hazard assumption. Based on the results of the analysis, the stratified Cox model is the best model with AIC and BIC values of 798.108 and 805.5748 respectively, while the extended Cox has AIC and BIC values of 840.2186 and 850.1732 respectively. Variables that can significantly affect the survival of Kasturi tobacco are the variable concentration of ZA fertilizer, pesticide concentration. The addition of ZA fertilizer must be appropriate, because if excessive it can cause poisoning of tobacco plants. Likewise with pesticides, if excessive it will cause damage to the leaves. This policy can increase the productivity of Kasturi tobacco. Then, Jember Regency contributes greater export capacity. • This paper aims to determine the factors that affect the survival of Kasturi tobacco plants in Jember • By using the extended Cox model, the best one is obtained using the Heaviside function with AIC and BIC values of 840.2186 and 850.1732, respectively • The stratified Cox model is better than the extended Cox model, which has AIC and BIC values of 798.108 and 805.5748, respectively

关键词： Productive agriculture Cox proportional hazard Stratified cox Extended cox Kasturi tobacco Cox Proportional Hazard Model, Stratified Cox Model, and Extended Cox Model

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Multidocument Summarization using GloVe Word Embedding and Agglomerative Cluster Methods

Multidocument Summarization using GloVe Word Embedding and A...

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International Conference on Sustainable Engineering and Creative Computing (ICSECC)

作者： Rosalina Rosalina Rafiqul Huda Genta Sahuri Faculty of Computing Information Technology Study Program President University Bekasi Indonesia

ISBN: (纸本)9781728175898

This paper explores the method of extracting multi-document summary terminology that enhances single document summary methods using the information related to the document and perhaps even the relation between the documents. In the problems of fragmentation, density, duplication and selection of passages, the summarization of several documents ranges from the summarization of single documents to the creation of efficient summaries. Our approach addresses these issues by using Agglomerative cluster sentence, GloVe, TextRank, Cosine Similarity. In addition, this research also use NLTK as library filter word such as stopwords, numeric, punctuation, multiple_whitespaces, short_words in order Vectorizing the sentence when using GloVe. The result of this paper was evaluated using ROUGE; 41% for unigram, 17% for bigram, 57% for trigram.

关键词： Terminology Conferences Libraries Generators Filtering theory Internet Object recognition

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Development of Ikigai instructional method to cultivate computational thinking of millennial generations

Development of Ikigai instructional method to cultivate comp...

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Seminar on Advances in Mathematics, Science and Engineering for Elementary School, SAMSES 2018

作者： Hikmawan, R. Sari, D.P. Majid, N.A. Ridwan, T. Nuriyah, W. Aprilia, L. Diani, D. Study Program of System and Information Technology Education Universitas Pendidikan Indonesia Indonesia

Digitalization in industrial revolution 4.0 era has many impacts towards all aspects of life. Massive technology advancement shifts industrial demands in Indonesia from quantitative to qualitative demands. These qualitative demands can be interpreted that today's industry workforce not only need technique competencies but also must have good Computational Thinking (CT) which is the pillar of collaboration, communication, creativity, and problem-solving skills. This issue did not balance with the enhancement of cognitive skills of Indonesians, especially youth or millennial generation. Millennial generation required to overcome multilevel challenges to improve thinking skills particularly on individual level. The low level of intrinsic motivation in using computational thinking to solve its problem became one of millennial culture characteristics. One of the solutions is cultivate student's intrinsic motivation to use CT by utilize Ikigai concept on teaching and learning activities from early grade. The Ikigai role as motivation template has been endure for millennia and proven, if used properly, to be most important factor that help eastern culture people achieve self-actualization. This study aims to develop instructional design that include Ikigai concept to support the achievement of intellectual competencies. Product development is done by Research and Development (R&D) Method with Akker procedure scheme. Product expected to improve students CT in accordance to standard needed in industrial 4.0 era. At this point, we currently at Empirical Testing phase. As expected, we got good response from teacher for product's ease of use and provide clear assessment of students CT Skills. Student that can be described as skilled programmer often have poor communication or collaboration skills with societies. However, when the students have clear life-goal, those lack of social skills are gradually improved. Otherwise, student with good social skills but has poor technique (

关键词： Students

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Visualization of corona virus disease 2019 deoxyribonucleic acid data analysis

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AIP Conference Proceedings 2022年第1期2659卷

作者： H. A. Wijaya Syaifudin Teddy Siswanto Information System Study Program Faculty of Industrial Technology Universitas Trisakti Jakarta Indonesia

Deoxyribonucleic acid (DNA) is a biomolecular genetic code that present in every population that stores and encodes genetic instructions. With increasing technological advances and a lot of research of decoding DNA from various cultures, one of which is a virus. DNA sequence from coronavirus disease 2019 (COVID-19 DNA) virus data that has become a pandemic around the world now has genetic mutations. This research tries to analyze DNA. The sequence of COVID-19 DNA data is then extracted to obtain biological information on genetic makeup variables. Data-analysis-can be arranged as-a process that consists of-several steps where raw data is -and created to produce information and visualization of data needed to acquire knowledge assets. The process of reading data is then analyzed and visualized using biopython which is a special library for bioinformatics computing. Using the method of Data Analysis Process which covers Data Extraction, Data Preparation, Data Exploration & Visualization, Predictive Modelling, Model Validation, and Dissemination. The results of this research display the visualization of data extraction into information on COVID-19 DNA analysis based on the sequence of DNA formers, as well as showing similarities of COVID-19 DNA so that it can be identified using genetic mutations that occur.

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