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International Conference on informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Zaid Romegar Mair Widya Cholil Evi Yulianti Dona Marcelina Theresiawati Ika Nurlaili Isnainiyah Informatics Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Jakarta Indonesia Information System Study Program Computer and Natural Science Faculty Indo Global Mandiri University Indonesia

It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a similar process for achieving a prediction of the final result. The implementation for each of these procedures follows the steps that are summarized into a flow of analysis stages that can help to develop the application of an algorithm. The initial stage is to take the handwriting from the user which is then pre-processed the image, to eliminate existing noise, and sharpen the contrast, so that the image can be seen clearly. Images will be processed and analyzed using the Convolutional Neural Network model, training will be carried out, with an average training of a dataset of 100 epochs or about 7 to 10 minutes, and labeling on the trained dataset. The accuracy of the training reached 98.89%, as a proportion of the different characteristics of the handwriting sample.

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider 6

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Atmaja, Ardian Budi Kusuma Hidayat, Egi Muhammad Idris Riyanto Trilaksono, Bambang Siregar, Simon Habibullah, Natsir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Telkom University Doctoral Program of Electrical Engineering Department Computer Engineering Faculty of Applied Science Indonesia

ISBN: (纸本)9798350358346

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees. © 2023 IEEE.

关键词： Geometry

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Spatial Hotspot Data and Weather for Forest Fire Data Clustering 5

Spatial Hotspot Data and Weather for Forest Fire Data Cluste...

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5th International Conference on Information and Communications Technology, ICOIACT 2022

作者： Mimboro, Prasetyo Kusrini, Kusrini Laksito, Arif Dwi Postgraduate Program Universitas Amikom Yogyakarta Yogyakarta Informatics Engineering Departement Amikom Yogyakarta Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Amikom Yogyakarta Indonesia

ISBN: (数字)9781665451406

ISBN: (纸本)9781665451406

Prediction of fire forest will be needing several parameters that located on the same location and on the same time frame. This is important to have data on the same location and same time periods, since forest fire mostly triggered by weather or temperature condition on certain area on the certain time. Since there are many parameters involved, the preprocessing will need to made the data have standard structure. The clustering process needed to give a label to the data with five class label, very low risk, low risk, medium risk, high risk, very high risk. Based on the data set, we measurement the best cluster number related with DB index, the results shows that 8 cluster is the best number of the data with DB Index score are 0.8856. © 2022 IEEE.

关键词： Fires

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Performance Evaluation of Oversampling Methods on Deep Learning-Based Skin Cancer Classification

Performance Evaluation of Oversampling Methods on Deep Learn...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Supriyanto, Catur Salam, Abu Zeniarja, Junta Wijaya, Adi Universitas Dian Nuswantoro Bachelor Program in Informatics Engineering Faculty of Computer Science Semarang Indonesia Universitas Indonesia Maju Department of Health Information Management Jakarta Indonesia

ISBN: (纸本)9798350339215

The field of dermatology faces considerable challenges when it comes to early detection of skin cancer. Our study focused on using different datasets, including original data, augmented data, and SMOTE oversampled data, to identify skin cancer. Our dataset consisted of images of skin lesions from the MNIST Skin Cancer dataset (HAM 10000), including samples of both cancerous and benign cases in the dataset. We employed data augmentation to expand the dataset's size and increase the diversity of skin lesion features. Furthermore, to tackle class imbalance in the dataset, we applied the SMOTE oversampling technique to generate synthetic samples for the under-represented group. With the original, augmented, and SMOTE oversampled datasets, we trained a Convolutional Neural Network (CNN) model. The performance of the model was evaluated using accuracy, recall, precision, and F1-score. The comparison between the results obtained from the original data, augmented data, and SMOTE oversampling data clearly revealed distinctions in performance. Our findings clearly demonstrate that employing data augmentation and SMOTE oversampling can significantly enhance the efficacy of skin cancer detection. © 2023 IEEE.

关键词： Neural network models

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Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN)

Maternal Health Risk Classification - A Comparison between A...

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Fatmawati, Maylia Novita, Mega Saputro, Nugroho Dwi Chauhan, Alok Singh Nada, Noora Qotrun Sinha, Amit Herlambang, Bambang Agus Gupta, Shruti Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Informatics Semarang Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Semarang Indonesia School of Computing Science & Engineering Galgotias University Greater Noida India ABES Engineering College Department of Computer Science & Engineering Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

Maternal health is a critical concern, particularly for individuals who are pregnant and will shape the future generations. However, not all expectant mothers receive tailored attention and care for their unique health needs. Consequently, many mothers face high levels of health risks during pregnancy, highlighting the importance of classifying maternal health risks. Classification can help identify influential factors affecting maternal health and predict risk levels for individual mothers. In the field of data mining, various classification methods exist for analyzing complex datasets. This study focuses on two widely used algorithms: decision tree and k-Nearest Neighbor (kNN). By employing these algorithms, we aim to classify a dataset comprising 1,014 records of maternal health risk levels. Through cross-validation and T-tests, we rigorously evaluate the performance of the decision tree and kNN algorithms in this context. Our findings indicate that the kNN algorithm is more suitable for classifying maternal health risks, achieving a significantly higher accuracy of 71.50% compared to the decision tree algorithm's accuracy of 70.71%. This result establishes the superiority of the kNN algorithm in accurately classifying maternal health risks. These findings have implications for developing targeted interventions and tailored healthcare strategies to mitigate identified risks. © 2023 IEEE.

关键词： Health risks

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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Blockchain-based Smart Contract in Service-Oriented Business Processes 7

Blockchain-based Smart Contract in Service-Oriented Business...

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7th International Conference on Information Technology Systems and Innovation, ICITSI 2022

作者： Parjuangan, Sabam Suhardi Nughara, I Gusti Bagus Baskara Khoirunnisa, Elvin Doctoral Program of School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung40132 Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung40132 Indonesia University of Twente Faculty of Electrical Engineering Mathematics Computer Science Enschede Netherlands

ISBN: (数字)9781665465557

ISBN: (纸本)9781665465557

Service systems' business processes show the existence of mutual interaction between users. Running a particular business subdomain requires the role of each user. This role is in line with the concept contained in blockchain-based smart contracts. However, determining the subdomains that require smart contract coding is challenging in developing business processes that will run on the blockchain. We aim to determine the service-oriented business process (in the case of marketplace service) and the subdomain of the business process that requires smart contract coding. This article is essential because it shows how developing IT services without a smart contract differs from developing IT services with a smart contract. The main differences between developing services that need smart contracts and those that do not are that certain process can be run automatically and the record of activity in blockchain cannot be changed by anyone (tamper-proof). We outlined methods for designing marketplace business processes and defined subdomains to be encoded into smart contract code. After reviewing the three marketplace platforms, we determined eight subdomains of the marketplace business process. Two subdomains require smart contract coding from eight, namely the payment and complaint subdomains. © 2022 IEEE.

关键词： Smart contract

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Decision Support System for Employee Performance Assessment for Administration Promotion Using Analytic Hierarchy Process 7

Decision Support System for Employee Performance Assessment ...

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7th IEEE International Conference on Smart Instrumentation, Measurement and Applications, ICSIMA 2021

作者： Kurniawan, Helmi Tanjung, Muhammad Rusdi Swondo, Ashari P Sari, Eka Purnama Negoro, Wahyu Saptha Yusfrizal Universitas Potensi Utama Faculty of Engineering and Computer Science Medan Indonesia Universitas Potensi Utama Visual Communication Design Study Program Medan Indonesia Universitas Potensi Utama English Education Study Program Medan Indonesia Universitas Potensi Utama Faculty of Economy and Business Medan Indonesia

ISBN: (纸本)9781728175225

Companies that are ready to compete must have effective management. To improve employee performance in effective management, it is necessary to support competent and competent employees in their fields. Employees who have an attitude of struggle, dedication, discipline, and professional ability are very likely to have work performance in carrying out their duties so that they are more efficient and effective. To increase employee morale, the Company will reward the best employees and be loyal to the company. This is done as an appreciation for what the employee has done for the company in achieving the company's targets. Decision making to determine the best employees can be done by the company by assessing the performance that has been done by its employees within a certain period of time. Employee performance appraisal is influenced by several criteria, namely attitude, attendance, performance and Service Period. The decision support system for selecting the best employees uses the Analytical Hierarchy Process (AHP) method, where the decision-making process is carried out by assessing alternative choices based on predetermined criteria and can also help the Company to make the best employee decisions. The alternative matrix calculation yields a score of 25.1% for Safrizal, 25.8% for Dedek Rizky, 25.1% for Amira Syakira and 24.0% for Reni Kumala, and the employee who is recommended as the best employee is the employee with the highest score, namely Dedek Rizky with a score of 25.8%. © 2021 IEEE.

关键词： Decision support systems

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Analysis and Comparative between Profile Matching and SAW Method in Decision Support 8

Analysis and Comparative between Profile Matching and SAW Me...

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8th International Conference on Cyber and IT Service Management, CITSM 2020

作者： Kurniawan, Helmi P Swondo, Ashari Purnama Sari, Eka Ummi, Khairul Rusdi Tanjung, Muhammad Yusfrizal Universitas Potensi Utama Faculty of Engineering and Computer Science Medan Indonesia English Education Study Program Universitas Potensi Utama Medan Indonesia Universitas Potensi Utama Faculty of Economy and Business Medan Indonesia Visual Communication Design Study Program Universitas Potensi Utama Medan Indonesia

ISBN: (纸本)9781728177014

A decision support system is a solution to help provide decision recommendations in determining which options to choose as a solution, in this decision support system research, namely analyzing and comparing the Matching Profile method and the SAW (Simple Additive Weighting) method in providing the best choice solution in the case of determining teaching staff acceptance. Determination of Admission, The selected teaching staff, are teaching staff who are in accordance with the criteria and quality. In an educational institution, namely TPQ Anbata, it is a very important issue to get elected teaching staff. One way to get teaching staff who is in accordance with the cafeteria is determined by selecting or determining prospective teaching staff by paying attention to various assessment criteria so that the selected teaching staff is feasible. From the tests that have been carried out, the results obtained include all test cases, and the testing is appropriate. The results of the system calculation accuracy test show that the calculation of Matching Profile and SAW (Simple Additive Weighting Method carried out by the system with manual calculations is correct and the feasibility test. Appropriate to use in making decisions determining the recruitment of teachers than the profile matching method in Anbata TPQ. The difference is in the highest value in each method. In the profile matching method, the highest value is Salman Al Fariz with a value of 4.70 while in the SAW method the highest value is Ali Gufron with a value of 8,778., it can be concluded that the most appropriate method in determining the recruitment of teaching staff at TPQ Anbata is the Profile Matching Method. © 2020 IEEE.

关键词： Decision support systems

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Design and fabrication of photovoltaics based on MFS (Ag/BaTiO3/silicon p-type) structure

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Materials science for Energy Technologies 2024年第1期7卷 29-34页

作者： Irzaman Dahrul, M. Rahmani, M. Rukyati, A.M. Samsidar Nurhidayah Deswardani, F. Peslinof, M. Jenie, R.P. Iskandar, J. Wahyuni, Y. Priandana, K. Siskandar, R. Department of Physics Faculty of Mathematics and Natural Sciences IPB University Bogor16680 Indonesia Department of Physics Faculty of Sciences and Technology Jambi University Jambi36361 Indonesia Department of Nutrition Faculty of Health Science and Technology Binawan University East Jakarta13630 Indonesia Department of Computer Engineering Pakuan University Bogor16142 Indonesia Department of Computer Science IPB University Bogor16680 Indonesia Computer Engineering Technology Study Program College of Vocational Studies IPB University West Java Bogor16151 Indonesia

The experiment was carried out by growing BaTiO3 (Undoped or Li-doped) on p-type Si(1 0 0) substrates using the Chemical Solution Deposition (CSD) method and spin coating at a rotational speed of 3000 rpm for 60 s, followed by heating at 850 °C. The characterization results show that the bandgap energy value of the thin film due to lithium doping reduces the bandgap energy value. This is presumably because the donor atom added to a semiconductor causes the allowable energy level to be slightly below the conduction band. The presence of this new band causes the thin film bandgap energy to decrease with a five-valent tantalum dip. The morphological properties showed that the BaTiO3/Si(1 0 0) thin film particles in the deposited lithium had a fairly homogeneous grain. With the addition of lithium acetate as a binder into barium titanate, the grain size is getting smaller because it is suspected that the lithium-ion radius is smaller than the barium-ion radius. Measurement of I-V on the thin film shows that the output voltage value increases with more light intensity hitting the surface of the thin film. The greater the light intensity, the greater the energy of the photons, so the electrons are easier to jump. The three things above (both electrical and morphological properties) conclude that the thin films grown have the potential for photovoltaics. © 2023

关键词： Thin films

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