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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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What does functional connectivity tell us about the behaviorally-functional connectivity of a multifunctional neural circuit?

What does functional connectivity tell us about the behavior...

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2022 Conference on Artificial Life, ALIFE 2022

作者： Izquierdo, Eduardo J. Candadai, Madhavun Cognitive Science Program Indiana University Luddy School of Informatics Computing and Engineering Indiana University United States

What insights can statistical analysis of the time series recordings of neurons and brain regions during behavior give about the neural basis of behavior? With the increasing amount of whole-brain imaging data becoming available, the importance of addressing this unanswered theoretical challenge has become increasingly urgent. We propose a computational neuroethology approach to begin to address this challenge. We evolve dynamical recurrent neural networks to be capable of performing multiple tasks. We then analyze the neural activity using popular network neuroscience tools, specifically functional connectivity using Pearson’s correlation, mutual information, and transfer entropy. We compare the results from these tools against a series of informational lesions, as a way to reveal their degree of approximation to the ground-truth. Our initial analysis reveals an overwhelming large gap between the insights gained from statistical inference of the functionality of the circuits based on neural activity and the actual functionality of the circuits as revealed by mechanistic interventions. © Artificial Life Conference Proceedings 2022.

关键词： Recurrent neural networks

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Determination of bulog regional sub-division in east java using connected domination number theory 5

Determination of bulog regional sub-division in east java us...

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5th International Conference on Combinatorics, Graph Theory, and Network Topology, ICCGANT 2021

作者： Umilasari, Reni Saifudin, Ilham Study Program of Informatics Engineering Universitas Muhammadiyah Jember Jl. Karimata 49 Jember68121 Indonesia

Bulog is a state-owned public company engaged in food logistics. There are about 18 Bulog warehouses in East Java Province with an uneven distribution. Because the scope of Bulog's business includes logistics or warehousing, surveys and pest eradication, provision of plastic bags, transportation business, food commodity trading and retail business, there must be good coordination between regional sub-divisions and warehouse complexes. In this study, the minimum regional sub-division recommendations in the East Java region were determined using the theory of connected domination number in graphs. The location of the warehouse complex is described as the vertex and adjacent warehouse complexes are connected by edges. In this research, we also determine the connected domination number of unicyclic graph and vertex amalgamation operations for several classes of graphs. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Metals

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The Improvement of Personal Service in the MSMEs Marketplace Using a Rank-Based Collaborative Filtering Approach

The Improvement of Personal Service in the MSMEs Marketplace...

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2022 International Conference on Electrical and Information Technology, IEIT 2022

作者： Lestari, Sri Yulmaini Aswin Sulyono Nul Fikri, Ruki Rizal Pratama, Yan Aditiya Informatics Engineering Study Program Faculty of Computer Science Lampung Bandar Indonesia Management Study Program Faculty of Business Economics Lampung Bandar Indonesia

ISBN: (数字)9781665453035

ISBN: (纸本)9781665453035

Indonesian MSMEs in 2022 will begin to enter the transformational recovery phase. Various preparations must be made in order to adapt. One that has been done is to increase the number of MSMEs entering the digital ecosystem, such as the MSME marketplace. The MSME Marketplace is used for marketing various MSME products online. The MSME Marketplace must be supported by methods that are able to provide good and fast personal services, considering the types and variety of products offered are increasing in number and varying from time to time. Therefore, this study proposes the Porat_Rank method to produce product recommendations that match user interests quickly so that users are served well. The experimental results show that the Porat_Rank method is superior to the Copelan Score method both in producing recommendations and in processing speed. © 2022 IEEE.

关键词： Collaborative filtering

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Sasirangan Cloth Recognition and Shopping Experience Simulation Based on Virtual Reality Game with Non-Player Character Integration 8

Sasirangan Cloth Recognition and Shopping Experience Simulat...

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8th International HCI and UX Conference in Indonesia, CHIuXiD 2022

作者： Subandi, Subandi Syahidi, Aulia Akhrian Zakiah, Siti Kiyokawa, Kiyoshi Riyadi, Ahmad Noor, M. Helmy Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin Indonesia Universitas Brawijaya Informatics Engineering Undergraduate Program Faculty of Computer Science Malang Indonesia Nara Institute of Science and Technology Cybernetics and Reality Engineering Laboratory Ikoma Japan Politeknik Negeri Banjarmasin Informatics Engineering Diploma Program Banjarmasin Indonesia

ISBN: (纸本)9781665476645

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91. © 2022 IEEE.

关键词： Virtual reality

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IoT: Monitoring Temperature, Water pH, and Automatic Water Drainage Systems for Gurami Cultivation

IoT: Monitoring Temperature, Water pH, and Automatic Water D...

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2023 International Conference on Networking, Electrical engineering, Computer Science, and Technology, IConNECT 2023

作者： Sulistiani, Heni Saputra, Wijaya Darwis, Dedi Isnain, Auliya Rahman Rimanda Putra, Ardy Khairunisa, Yosi Universitas Teknokrat Indonesia Study Program of Accounting Information System Lampung Indonesia Universitas Teknokrat Indonesia Study Program of Computer Engineering Lampung Indonesia Universitas Teknokrat Indonesia Study Program of Informatics Lampung Indonesia Regional Research and Development Agency Lampung Indonesia

ISBN: (纸本)9798350331172

Gurami is a native fish from Indonesian waters that is much-loved by Indonesian people for daily food consumption. The gurami inhabits still waters such as swamps, lakes, and ponds. Besides that, carp cannot live in a water content that is too alkaline or acidic, the oxygen content in the water must be stable. Water quality is a very important factor and can affect the survival of cultivated fish. Several parameters must be considered in improving the development of carp, one of which is the temperature and pH of the water and automatic drainage of water. In this paper, we conduct IoT-based research that focuses on controlling water temperature and pH and automatically draining pool water. Water temperature and pH control such as a pH sensor temperature sensor and a water turbidity sensor will later be connected to the ESP 32 microcontroller which already has a wi-fi module. A system that is linked to electrical power and the internet then the sensor will read the water quality including the pH temperature value and water turbidity from inside the fish pond, after getting the data, the data will go to ESP 32. This research can help gurami cultivating farmers to make it easy to control the pH temperature and perform automatic pool water draining. The results of sensor testing with actual data are pretty accurate with the average error value of the ds18b20 sensor being 0.05% while the value of the pH sensor itself is 0.07%. © 2023 IEEE.

关键词： Temperature sensors

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Fine-Tuned Attribute Weighted Naïve Bayes with Modified Partial Instances Reduction for Gaming Disorder Classification

HighTech and Innovation Journal

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HighTech and Innovation Journal 2025年第1期6卷 67-80页

作者： Latubessy, Anastasya Wardoyo, Retantyo Musdholifah, Aina Kusrohmaniah, Sri Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Informatics Engineering Faculty of Engineering Universitas Muria Kudus Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta55281 Indonesia Department of Psychology Faculty of Psychology Universitas Gadjah Mada Yogyakarta55281 Indonesia

Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. © 2025, Ital Publication. All rights reserved.

关键词： Attribute Weighted Classification Fine-Tune Gaming Disorder Instances Reduction Naïve Bayes

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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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Supervised Machine Learning Approach for Predicting Cardiovascular Complications Risk in Patients with Diabetes Mellitus

Supervised Machine Learning Approach for Predicting Cardiova...

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International Conference on Electrical engineering and informatics, ICEEI

作者： Arief Purnama Muharram Fahmi Sajid Master Program of Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

Diabetes mellitus, particularly type-2 diabetes, remains a prevalent health issue, raising concerns due to its associated risk of complications. Among these, cardiovascular complications pose a significant threat, exhibiting high morbidity and mortality rates. Health screening plays a pivotal role in stratifying the risk levels of diabetes patients, facilitating proactive measures to prevent the progression of complications. As such, the primary objective of this study is to develop a predictive model system for assessing cardiovascular risk in diabetes patients. Our study used the Cardiovascular Disease dataset and conducts experiments with various supervised machine learning algorithms, such as Naive Bayes, decision tree, random forest, AdaBoost, and XG- Boost. The results reveal that ensemble learning algorithms based on boosting, particularly AdaBoost and XGBoost, outperform other supervised machine learning methods. However, even with the best performance achieved using the dataset, the accuracy stands at 0.71, and the F -1 score is 0.69, which is still acceptable for screening purposes. Although these results provide valuable insights, indicating individuals at higher risk for cardiovascular complications in diabetes, further improvements are needed to enhance early prevention strategies.

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Spatial Distances and Knowledge Acquisition Strategy for Patenting by Indonesian Academic Inventors 5

Spatial Distances and Knowledge Acquisition Strategy for Pat...

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5th International Conference on Advancement in Data Science, E-Learning and Information Systems, ICADEIS 2023

作者： Arimbawa, I Wayan Agus Wedashwara, Wirarama Gelana, Kassahun Fauzi, Rahmat Iskandar, Ade Rahhmat University of Mataram Dept. of Informatics Engineering Mataram Indonesia Seoul National University Technology Management Economics and Policy Program Seoul Korea Republic of Telkom University School of Industrial and Systems Engineering Indonesia

ISBN: (纸本)9798350303414

Knowledge acquisition is important for innovation and adaptation of organizations including universities. New knowledge and capabilities can be acquired from inside or outside of the institution. There are large body of literature discuss the interaction of universities and the other Triple-helix model's agents, but rarely found and discuss intra helices interactions. This research explores the characteristics of Indonesian academic inventors' knowledge acquisition strategy for patenting in Indonesia. There are two points of view of this research: firstly, the study discusses the knowledge acquisition strategy of Indonesian universities in regard of the knowledge diversity among two collaborating universities and secondly, how is the magnitude of knowledge gaps between two entities influencing the decision for inhouse or out of university *** the data from Sinta, knowledge diversity index is measured using Shannon entropy index of the academic inventor' expertise, university's department, and university's division. The research recognition's gap between two collaborating inventors is measured using the difference of their Scopus' h-indices. The findings show some interesting facts of how academic inventors strategize their collaboration patterns. First, interuniversity collaborations for patenting reveal more diversity on the academic inventors' knowledge than those are in intra-university collaborations. Second, collaborations for patenting with different universities expect better knowledge spill-overs than collaborations within a university. But, this knowledge spill-over only significant at individual level but not at institutional level. It seems that individual recognition is more important than institutional recognition when choosing a collaboration partner. © 2023 IEEE.

关键词： Knowledge acquisition

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