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Precision Rice Vending Machine by Using Multiple Load Cell and IoT Based

Precision Rice Vending Machine by Using Multiple Load Cell a...

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Computer Science, information technology and Engineering (ICCoSITE), International Conference on

作者： Herman Yuliandoko Farisqi Panduardi Nuraini Lusi Sapto Wibowo Information Technology Program Study Politeknik Negeri Banyuwangi Banyuwangi Indonesia Mechanical Engineering Program Study Politeknik Negeri Banyuwangi Banyuwangi Indonesia Electrical Engineering Program Study Politeknik Negeri Malang Malang Indonesia

Indonesia has the world's largest Muslim population, so the potential for Zakat, Infaq, and Sadaqah (ZIS) funding is enormous. The existence of ZIS in the current Covid-19 pandemic is of extreme importance, as issues such as economic crisis, social inequality, and the rise of dhuafa (poor) are becoming more and more visible. However, in the presence of coronavirus, ZIS has become more challenging to manage and distribute. Bans on gatherings, distancing rules, and other restrictions to prevent the spread of the coronavirus make ZIS more challenging to manage. Therefore, we need innovations to build bridges between people in need and supporters. The Internet of Things (IoT) is one system that can bridge this. In this system, IoT enables machine-to-machine communication and reduces human interaction. This research uses IoT to support Rice Vending Machine with high accuracy. The accuracy is achieved using five load cells and a good rice way-out valve mechanism. In previous machines using a single load cell or open the valve according to a certain time. Based on its test results analysis and MAPE values, we found the machine's accuracy facing obtained very well, and the website monitoring was also very effective. This research provides innovation in ZIS management and dramatically benefits society.

关键词： COVID-19 Bridges Technological innovation Machine-to-machine communications Pandemics Sociology Valves

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm 8

Image Processing Implementation to Classify Coffee Fruit Rip...

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8th International Conference on information Management and technology, ICIMTech 2023

作者： Hussaini Dermawan, M. Farhan Witarsyah, Deden Syamsuar, Dedy Fakhrurroja, Hanif Luthfi, Ahmad Herdiansyah, Muhammad Izman Telkom University Faculty of Industrial Engineering Bandung Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Jogjakarta Indonesia Universitas Bina Darma Informatics Study Program Faculty of Science and Technology Palembang Indonesia

ISBN: (纸本)9798350326093

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level. © 2023 IEEE.

关键词： Classification (of information)

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Advancements in Deep Learning Optimization for Post-Earthquake Building Damage Detection A Systematic Review

Advancements in Deep Learning Optimization for Post-Earthqua...

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Advanced information Scientific Development (ICAISD), International Conference on

作者： Sahat Sonang Y Yuhandri Muhammad Tajuddin Information Technology Study Program Universitas Putra Indonesia YPTK Padang Indonesia Department of Computer Science Universitas Bumigora Mataram Indonesia

ISBN: (数字)9798350392036

ISBN: (纸本)9798350392043

This study conducts a systematic literature review (SLR) that focuses on optimizing deep-learning techniques for post-earthquake building damage detection. By employing the PRISMA protocol, this review aimed to collect, analyze, and summarize the findings of various studies published between 2014 and 2024. This research identifies and evaluates optimization methods such as hyperparameter tuning, transfer learning, and data augmentation, highlighting their effectiveness and implementation. Challenges such as data quality, computational costs, and model interpretability were also discussed. The findings indicate that while deep learning techniques significantly enhance the accuracy and efficiency of damage detection, further research is required to address existing challenges and improve model robustness in diverse earthquake scenarios.

关键词： Deep learning Protocols Computational modeling Buildings Transfer learning Earthquakes Optimization methods Robustness Tuning Systematic literature review

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Risk Management of Bank and FinTech Collaboration: A Phenomenological Research

Risk Management of Bank and FinTech Collaboration: A Phenome...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Mercurius Broto Legowo Fangky Antoneus Sorongan Steph Subanidja Study Program of Information System Faculty of Information Technology Institute of Perbanas Jakarta Indonesia Study Program of Accounting Faculty of Economic and Business Institute of Perbanas Jakarta Indonesia Program of Master of Management Post Graduate School Institute of Perbanas Jakarta Indonesia

Banking and Fintech are encouraged to collaborate to fill each other's deficiencies and further grow the digital economy. This collaboration will create benefits for both banks, Fintech, and customers. However, this collaboration also comes with risks. The Financial Services Authority has stated that several risk phenomena can occur in the collaboration of banks and Fintech. First, no law guarantees the protection and exchange of customer personal data. Second, the risk of customer data leakage. Third, the risk of cyberattacks. The fourth is the risk of outsourcing. This research aims to analyze the risk phenomenon of bank and fintech collaboration through the Enterprise Risk Management Framework approach. This study uses a phenomenological research approach, which is a study to study how individuals subjectively experience and give meaning to the phenomenon. Data analysis based on this phenomenon data uses qualitative methods involving banking and fintech practitioners. The results of this study describe the phenomenon of risks that occur in banking-fintech collaboration, as approached by the Enterprise Risk Management framework. Proper risk management will minimize risks when the Bank collaborates with FinTech. This study hopefully contributes to making brief policy recommendations on bank and fintech collaboration risk management for Indonesian financial regulators.

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Ann : Predicting of State Retail Sukuk Based on Region in Indonesia 3

Ann : Predicting of State Retail Sukuk Based on Region in In...

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3rd International Conference on Computational Science and information Management, ICoCSIM 2019

作者： Solikhun Pujiastuti, Lise Wahyudi, Mochamad AMIK Tunas Bangsa Pematangsiantar Informatics Management Study Program North Sumatra Indonesia STMIK Antar Bangsa Information System Study Program Banten Indonesia Universitas Bina Sarana Informatika Faculty of Technical and Informatics Information Technology Study Program DKI Jakarta Indonesia

Retail Sukuk is a product of State Sharia Securities (Sukuk) issued by the Government of the Republic of Indonesia in this case the Ministry of Finance and sold to individuals or individuals of Indonesian Citizens through Selling Agents in the domestic Primary Market. This research contributes to the government and the Bank to be able to do the maximum promotion for the next sukuk issuance. The data used is data from the Ministry of Finance. These data are sukuk sales data with series 002-010 based on regional groups. The algorithm used in this study is Artificial Neural Network with Backpropogation method. Variabel masukan yang digunakan adalah kelompok wilayah bagian barat selain Jakarta (X1), kelompok Jakarta (X2), kelompok Indonesia Bagian Tengah(X3), dan kelompok Indonesia Bagian Timur (X4) dengan model arsitektur pelatihan dan pengujian sebanyak 4 arsitektur yakni 4-2-1, 4-3-1, 4-2-3-1 dan 4-3-2-1. The best architectural model is 4-3-1 with epoch 266, MSE 0.009918 and 100% accuracy rate. From this model, predictions of retail country sukuk will be made by region. © Published under licence by IOP Publishing Ltd.

关键词： Sales

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Urgency Detection of Events Through Twitter Post: A Research Overview

Urgency Detection of Events Through Twitter Post: A Research...

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International Conference on Electrical Engineering and Computer Science (ICECOS)

作者： Frederick William Edlim Gregorius Edo Rangga Kurnia Putra Wiratama Riyan Mahmudin Andi Solihin Amelia Devi Putri Ariyanto Diana Purwitasari Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Information Technology and Systems Study Program Widya Husada University Semarang Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

Indonesia is located in volatile Pacific fire ring and stands as one of the most global disaster-prone areas. The government and public are in constant vigilance of the potential threats. Social media generates large amounts of data from its users and is one of the prime candidates to be used as a disaster monitoring and response system. Several studies have demonstrated the effectiveness of using such an approach for developing disaster monitoring systems. but due to the number of messages generated, filtering is needed to extract useful information from the message. Hence, it's needed to detect an urgency from a message. This review, which was carried out following the PRISMA model, focused on the detection of the urgency of Indonesian Twitter during crisis events. From studies selected, several recommendations are suggested for future endeavor in this topic. Future systems are advised to employ three or four class schemes rather than binary class to gain more nuanced insights into tweet urgency. On-Event training and testing approaches are suitable for frequently occurring events, whereas out-of-event approaches offer broader applicability for real-world scenarios. Both machine learning and deep learning methods, including multimodal approaches, have demonstrated efficacy in urgency detection. Addressing pre-processing challenges, such as abbreviations and slang, is critical, and ensuring consistency in manually annotated data is essential. Additionally, the selection of appropriate word embeddings, such as fastText, IndoBERT, or crisis-specific embeddings, is crucial for achieving optimal model performance.

关键词： Training Deep learning Support vector machines Social networking (online) Disasters Blogs Data mining Synchronization Monitoring Testing

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MIKA: An Assistive technology for Communication Learning in the Indonesian Language for Children with Autism Spectrum Disorder 14

MIKA: An Assistive Technology for Communication Learning in ...

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14th International Conference on Education technology and Computers, ICETC 2022

作者： Puspitasari, Ira Margaretha, Margaretha Yuliani, Sri Retno Khamida, Nishrina Wikantono, Vitotamma Emir Muhammad Information System Study Program Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia Psychology Study Program Faculty of Psychology Universitas Airlangga Surabaya Indonesia Special School for Autism River Kids Malang Indonesia Center of Integrated Supports for Children with Special Needs Regency Sidoarjo Indonesia

ISBN: (纸本)9781450397766

In recent years, assistive technologies have been adopted rapidly worldwide to increase quality treatments for individuals with autism spectrum disorder (ASD), including in Indonesia. However, adaption to a local context, e.g., using a local language, is needed to optimize the benefits. This study proposes an Indonesian version of an application technology called the media of visual communication for children with ASD (MIKA). The application development integrates agile scrum and user-centered design methodologies. The design and implementation are tested multiple times in the sprint reviews and usability evaluation to assure that the end product meets the standards of a therapy tool. MIKA offers a communication learning facility based on treatment and education of autistic and communication handicapped children (TEACCH) principles, a progress tracking and reporting feature, and a personalized content management tool based on user history and learning progress. ASD professionals, i.e., therapies and counselors, who participated in the sprint reviews and evaluations, acknowledged the advantages of using a tech-based therapy tool and the willingness to adopt MIKA. The MIKA project is in progress, targeting better facilitation of early childhood special education, and is now focusing on corrective maintenance and perfective improvements based on feedback from users and evaluators. © 2022 ACM.

关键词： Visual communication

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Determination of Planck's Constant Using the Photoelectric Effect Experiment 11

Determination of Planck's Constant Using the Photoelectric E...

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11th National Physics Seminar, SNF 2022

作者： Fitri, U.R. Ziveria, M. Muhara, I. Department of Physics Education Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta13220 Indonesia Information Systems Study Program Kalbis Institute of Technology and Business Jl. Pulomas Selatan No.22 Jakarta Indonesia Chemical Engineering Study Program Faculty of Industrial Technology Institut Teknologi Bandung West Java Bandung Indonesia

Planck's constant experiment has been carried out to determine the value of Planck's constant using the regression analysis method. The steps are carried out using the scientific process outlined in the practical work steps. The specification of the experimental equipment uses the Planck constant experimental set with 12v/35w tungsten halogen light, 15v output, +-0.2% accuracy, 220V power requirement, 0.5A fuse rating and red, yellow 1, yellow 2, and red color filters, green and blue. Experiments using the concept of the photoelectric effect phenomenon began by irradiating metallic materials with light using a filter. The wavelength (635, 570, 540, 500, 460) nm is the light filter variation. The wavelength that hits the metal material is selected by placing a light filter on the light propagation path toward the metal material. So the light that passes through the filter is only light with a certain wavelength. After the metal material is irradiated by light with a certain wavelength, then the stopping potential voltage measurement is carried out on the metal material irradiated by light. From the variation of the light filter used, it is possible to calculate Planck's constant using the regression method with the value obtained 6.26x1034. This value is very close to the actual Planck's constant value which is 6.62x1034 so an error value is obtained 4.23%. With 95.77% accuracy, Planck's constant value obtained from the calculation using the linear regression method can be said to be very close to the actual Planck's constant value. © Published under licence by IOP Publishing Ltd.

关键词： Photoelectricity

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Web Browser Extension Development of Structured Query Language Injection Vulnerability Detection Using Long Short-Term Memory Algorithm

Web Browser Extension Development of Structured Query Langua...

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International Conference of Computer Science and information technology

作者： Togu Novriansyah Turnip Hotma Aruan Anita Lasmaria Siagian Leonardo Siagian Information Technology Study Program Institut Teknologi Del Toba Indonesia

ISBN: (纸本)9798350399080

Structured Query Language Injection (SQLi) is a client-side application vulnerability that allows attackers to inject malicious SQL queries with harmful intents, including stealing sensitive information, bypassing authentication, and even executing illegal operations to cause more catastrophic damage to users on the web application. According to OWASP, the top 10 harmful attacks against web applications are SQL Injection attacks. Moreover, based on data reports from the UK's National Fraud Authority, SQL Injection is responsible for 97% of data exposures. Therefore, in order to prevent the SQL Injection attack, detection SQLi system is essential. The contribution of this research is securing web applications by developing a browser extension for Google Chrome using Long Short-Term Memory (LSTM), which is a unique kind of RNN algorithm capable of learning long-term dependencies like SQL Injection attacks. The results of the model will be deployed in static analysis in a browser extension, and the LSTM algorithm will learn to identify the URL that has to be injected into Damn Vulnerable Web Application (DVWA) as a sample-tested web application. Experimental results show that the proposed SQLi detection model based on the LSTM algorithm achieves an accuracy rate of 99.97%, which means that a reliable client-side can effectively detect whether the URL being accessed contains a SQLi attack or not.

关键词： Uniform resource locators Structured Query Language Web pages Static analysis SQL injection Browsers Classification algorithms

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A Fractal Characterization of Cough Signals for Covid-19 Pre-Screening Applications 8

A Fractal Characterization of Cough Signals for Covid-19 Pre...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Bandung, Yoanes Langi, Marco William Mutijarsa, Kusprasapta Langi, Armein Z. R. Bandung Institute of Technology Information Technology RG SEEI Bandung Indonesia Bandung Institute of Technology Physics Study Program FMIPA Bandung Indonesia

ISBN: (纸本)9781665416979

This paper presents a correlation fractal dimension characterization as applied to auditory cough signals. We have obtained cough samples from person with and without Covid-19 disease. Our hypothesis is coughs coming from Covid-19 disease exhibit fractal behavior. To show this, we apply fractal-size measurements on both samples. Preliminary results confirm fractality on Covid-19 cough signals. This result can improve performance of pre-screening for identification the presence respiratory diseases, such as Covid-19. © 2021 IEEE.

关键词： Fractal dimension

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