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7th International Conference on informatics and Computing, ICIC 2022

作者： Henderi Nasrullah, Mumammad Hudzaifah Nudiyah, Laura Belani Sunarya, Po Abas Sofiana, Sofa Setiyadi, Didik University of Raharja Informatics Tangerang Indonesia University of Raharja Management of Retail Study Program Tangerang Indonesia Pamulang University Faculty of Engineering Informatics Engineering Departement Tangerang Indonesia Universitas Indonesia Mandiri Infotmatics Faculty of Technolgy and Design Jakarta Indonesia

ISBN: (纸本)9798350345711

River pollution has become a severe problem in Indonesia. Industrial waste causes water pollution because the waste is not filtered before being discharged into the river. Illegal waste dumping cannot be prosecuted due to insufficient data and unknown disposal times. Therefore, a tool is needed to measure river water waste to measure polluted water waste data. Studies on river water monitoring devices have shown that there are no portable monitoring tools based on the internet of things for river water waste that follows regulatory standards from the Minister of Health. This study aims to produce a portable monitoring tool based on the internet of things for water waste. The system was developed using TDS sensors, turbidity, pH, MQ-135 sensors, and the system is equipped with a GPS module to indicate the location's latitude. The monitoring system is developed through the stages of system design, testing water samples, setting water quality standards and required hardware and components, setting river water quality parameters, and conducting system testing. The test results show that the system can send the data obtained to dashboard things via an internet connection, the TDS sensor error rate is 2.17%, the pH sensor error rate is 1.87%, the turbidity sensor error rate is 1.66%, the MQ135 sensor value is at the quality limit. The internet of things-based portable river waste monitoring system produced through this research helps related parties to identify and handle polluted rivers. Water according to the standards of the Ministry of Health, and the GPS module shows location measurements and information according to the location's latitude on google maps. © 2022 IEEE.

关键词： Internet of things

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Analyzing the use of SEO and Google Analytic on the Website of Vocational High School of Information Technology Annajiyah 3

Analyzing the use of SEO and Google Analytic on the Website ...

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3rd International Conference on Electrical, Electronics, informatics, and Vocational Education, ICE-ELINVO 2020

作者： Supraba, L.D. Jati, H. Electrical and Informatics Engineering Education Study Program Faculty of Engineering Yogyakarta State University Indonesia

The number of Islamic boarding school teaching both Information Technology (IT) Education and Religious Education is still limited. Vocational High School of Information Technology Annajiyah located in Tambakberas, Jombang, East Java is a school having both subjects taught. The existence of Vocational High School of Information Technology Annajiyah has not been widely known by outside and inside society of Jombang Regency. Therefore, Therefore, analysis of the use of SEO is necessary to determine the potential of website visit and school promotion. Previously, Vocational High School of Information Technology Annajiyah promoted school by using brochures only. This method was considered able to introduce the school through traditional way. Analysis result of improving SEO can be seen in Google Analytic recorded a number of site visits amounted 403 in June, where 82.2% of active users are dominated by mobile phone users and fluctuation of the number of visits. This increase is affected by both the implementation of SEO and online PPDB process during the COVID pandemic. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Websites

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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The use of long short-term memory models to estimate soybean pricing: a regional climate data evaluation from Brazil

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IEEE Access 2025年 13卷 101869-101884页

作者： Oliva, Jefferson Tales Martelli, Otavio Pigozzo Barbosa, Marco Antonio De Castro Molin, Viviane Dal Casanova, Dalcimar Teixeira, Marcelo Federal University of Technology-Paraná Graduate Program in Electrical and Computer Engineering Pato Branco Brazil Federal University of Technology-Paraná Department of Academic Informatics Pato Branco Brazil Federal University of Technology-Paraná Graduate Program in Production and Systems Engineering Pato Branco Brazil

This work uses machine learning methods to analyze the influence of the Brazilian climate on international soybean price variability. For this purpose, climatic data, historical series of the extended national consumer price index, dollar price historical series, soybean harvest historical series, and international soybean price historical series are collected from different data sources. The data is then preprocessed and grouped by state. Afterward, data from the five most productive Brazilian states, Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS), which together correspond to 74.9% of total production, are chosen. Then, predictive models were built using the long short-term memory (LSTM) method, which is applied to each state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. These models are evaluated using 10-fold sequential split cross-validation, whose predictive results are used for performance comparison through statistical hypothesis testing. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest average values of root mean squared error (RMSE) and mean absolute error (MAE), which are 20.90 and 16.72, respectively. Regarding predictors trained without climate data, the RS and PR obtained the lowest averaged values of RMSE (20.84) and MAE (16.81), respectively. After performing statistical hypothesis tests, no significant differences were found between the models, stating, with certainty 95%, that the Brazilian climatic data did not influence soybean prices in our study. © 2013 IEEE.

关键词： Brazilian Climatic Data Long-Short Term Memory Machine Learning Soybean Time Series

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Analysis on Performance of Semi-Real-Time Transcription on Health App

Analysis on Performance of Semi-Real-Time Transcription on H...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Yoenie Indrasary Daniel Nugraha Ary Setijadi Prihatmanto Ivany Sarief Rudy Gunawan Dhema Yunautama Doctoral Program of Electrical Engineering and Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia State Polytechnic of Banjarmasin Banjarmasin Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Dept. of Electrical Engineering Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Dept. of Informatics Engineering Directorate of Vocational Universitas Sangga Buana Bandung Indonesia

ISBN: (数字)9798331527686

ISBN: (纸本)9798331527693

The fragmentation of health information systems has hindered seamless data exchange in healthcare services, posing challenges in achieving efficient, real-time access to patient health data. This study addresses these issues by evaluating the implementation of a semi-real-time transcription system using a distributed architecture with a message broker to enhance the documentation of clinical examination processes in primary health services. The research focuses on assessing the feasibility of this approach by measuring key performance indicators such as latency and word error rate (WER) during clinical conversation transcription. Audio recordings were segmented into shorter fragments to simulate real-time transcription, and data transmission was conducted through the Advanced Message Queuing Protocol (AMQP). The findings demonstrate that the average latencys achieved by semi-real-time transcription system is 7.7s, indicating its potential suitability for clinical documentation applications that do not require strict real-time processing. However, glitches observed in the message broker's forwarding mechanism suggest the need for further optimization to ensure consistent performance. Future work aims to develop strategies to minimize transcription errors, enhance reliability, and improve the overall integration of this system in healthcare settings. This study contributes to the advancement of health information systems by offering architecture into scalable and effective methods for semi-real-time data transcription and interoperability.

关键词： Protocols Speech recognition Medical services Documentation Oral communication Real-time systems Telecommunications Reliability Optimization Information systems

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Multi Task Classification Using Deep Learning Approaches for Big Five Personality Traits Prediction: A Review 11

Multi Task Classification Using Deep Learning Approaches for...

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11th International Conference on Information Technology, Computer and Electrical engineering, ICITACEE 2024

作者： Nudin, Salamun Rohman Gernowo, Rahmat Somantri, Maman Wibowo, Adi Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389289

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the Science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98%), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67%), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36%) and lowest (59%). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG. © 2024 IEEE.

关键词： Contrastive Learning

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Real-time Vehicular Sensing System Design for Integrated Sensing as Service and IoT Platform in Smart Cities 11

Real-time Vehicular Sensing System Design for Integrated Sen...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Eriyadi, Mindit Lubis, Fetty Fitriyanti Supangkat, Suhono Harso Hidayat, Fadhil Doctoral Program of Instiut Teknologi Bandung Indonesia School of Applied Science Universitas Telkom Bandung Indonesia School of Electrical Engineering and Informatics Instiut Teknologi Bandung Indonesia Institut Teknologi Bandung Smart City and Community Innovation Center Bandung Indonesia

ISBN: (纸本)9798350389654

This study focuses on the design and implementation of a Real-time Vehicular Sensing System (RVSS) aimed at enhancing air quality monitoring in smart cities. By integrating advanced sensors into moving vehicles, the system captures real-time environmental data across diverse urban areas. This research addresses the limitations of static monitoring stations, offering broader geographical coverage and greater data collection flexibility. The proposed system includes low-cost components, enhanced sensor calibration, and optimized data processing algorithms to ensure accurate and reliable data. It also features real-time data transmission and a user-friendly dashboard for dynamic monitoring. The primary contribution of this study is to establish a robust foundation for an effective Vehicular Sensing system, providing valuable insights for researchers and policymakers to improve air quality management in smart cities. © 2024 IEEE.

关键词： Air quality

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Energy Planning and Utilization in the North Sulawesi Electricity System

Energy Planning and Utilization in the North Sulawesi Electr...

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2023 International Conference on Electrical engineering and informatics, ICEEI 2023

作者： Pratama, Arif Majiid Nusa Sutardi, Bagas Maulana Zidny, Irfan Lewi, Irvan Hasanuddin Hidayat, Syarif Hadi, Pradita Octaviandiningrum Pln Corporate University Graduate Program PLN-ITB Jakarta Indonesia Pln UIP3B Sulawesi Makassar Indonesia Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung Indonesia

ISBN: (纸本)9798350381290

Energy sector is one of the contributors to climate change besides forestry, environment, and transportation sectors. Then, the results of the COP 26 in Glasgow meeting states that Indonesia have a target to achieve Net Zero Emission (NZE) by 2060 if there is international support for funding and technology with some note that this project does not interfere with availability and affordability. In achieving the zero-emission target, the government is implementing five main principles, which include increasing the use of new renewable energy (NRE), reducing fossil energy, explore the use of electric vehicles in the transportation sector, increasing the use of electricity in households and industries, and utilizing Carbon Capture and Storage (CCS). In this paper several proposals can be made to further reduce production costs and reduce greenhouse gas emissions in the North Sulawesi system compared to Electricity Supply Business Plan by PLN which is called RUPTL. Two additional scenarios can be used for the proposal, which are addition of geothermal, solar and pump hydro to replace coal power plant and construction of North Sulawesi interconnection with Central Sulawesi. From the simulation results of the cost and carbon emission analysis between three scenarios, the scenario from RUPTL is the cheapest in terms of cost at 3.295 billion USD and the interconnection scenario is the smallest in terms of emissions, with CO2 emissions reaching 0 Mt. © 2023 IEEE.

关键词： Climate change

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Reversible data hiding based on pixel segmentation and prediction for improving hiding capacity

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Signal, Image and Video Processing 2024年第6-7期18卷 5043-5059页

作者： Huang, Cheng-Ta Weng, Chi-Yao Zheng, Guo-Ting Weng, Hao-Yu International Bachelor Program in Informatics Yuan Ze University Taoyuan320315 Taiwan Department of Information Management Yuan Ze University Taoyuan320315 Taiwan Department of Computer Science and Information Engineering National Chiayi University Chiayi City600355 Taiwan Department of Computer Science and Artificial Intelligence National Pingtung University Pingtung900391 Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan City320317 Taiwan

The idea of the traditional histogram shifting technique is to hide a message within the cover-image pixel distribution. However, the embedding capacity is limited by the peak point occurrences. To solve this problem, many reversible data hiding (RDH) techniques are developed to combine pixel prediction and histogram shifting to increase the embedding payload. In this paper, a RDH scheme based on chessboard prediction and pixel partitioning is proposed for enhancing the hiding payload. Pixel partitioning is used to separate a pixel into two parts: most significant bit and least significant bit. Then, the chessboard predictor is adopted to generate prediction errors and separate the pixels. Thereafter, histogram shifting is applied to embed the secret messages into prediction errors. Due to the high similarity of adjacent pixels in an image, the generated prediction errors are highly close to zero, resulting in a large embedding space. The experimental results indicate that the proposed method has superior performance in embedding capacity with acceptable image visual quality compared to existing schemes since it adopts the adaptive adjustment strategy to achieve this improved balance. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Pixels

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Analysis of Digital Population Services for the Poor in Palembang City Using the Information Technology Infrastructure Library (ITIL) Framework 4

Analysis of Digital Population Services for the Poor in Pale...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Antoni, Darius Septiyanti, Reni Akbar, Muhamad Herdiansyah, Muhammad Izman Department of Informatics Engineering Graduate Program Bina Darma University Palembang Indonesia

ISBN: (纸本)9781665433945

As it is known that the city government of Palembang has implemented e-government, but how much e-government can help the Palembang city government to interact between the government and all levels of society including the poor in Palembang city. In its application, the condition of e-government services is still insufficient for the infrastructure to support e-government services for the poor in Palembang city. To design e-government services such as good digital population services, it is necessary to design IS / IT services for people in Palembang City with the Service Design stage in the 2011 Version of the Information Technology Infrastructure Library (ITIL) Framework so that they can be accepted by all levels of society including the poor in Palembang city. This study uses a qualitative approach. The results of this research are in the form of a digital population service information system design such as administrative and population services, Family Hope program (PKH) services and digital archive storage services based on the Service Design stages in ITIL Version 2011 that have been carried out, namely the Service Catalog Management process and Service Level Management in the form of documents. Service Level Requirements, Service Level Agreement and Operational Level Agreement. © 2021 IEEE

关键词： Information management

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