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2022 IEEE Creative Communication and Innovative technology, ICCIT 2022

作者： Alwiyah Padeli Yusuf, Maulana Kusumah, Hendra Suwandi Wiraraja Madura University Accounting Study Program Sumenep Indonesia University of Raharja Master of Information Technology Indonesia University of Raharja Department of Information System Indonesia University of Catur Insan Cendikia Department of Information Technology Indonesia

ISBN: (纸本)9781665468763

The increase in the production of municipal solid waste around the world will be expected to continue to increase. Even though developed countries already have recycling technology to convert waste into products that can be reused, such as generating electricity, heat energy, composting fertilizers, and biofuels, there are still many challenges created by waste because in developing countries the countermeasures themselves are still so things are difficult starting from the inadequate collection, transportation, and disposal of waste. This research will solve the problem of evaluate various waste-to-energy technologies that have been developed since the invention that was able to convert recycled waste into renewable energy until now. This research can be divided into four groups. Namely starting from waste treatment thermally, biologically, biorefinery, and utilization of landfill gas. The novelty of this research for waste-to-energy technology with an integrated waste management system, it has been safely understood and tested feasible for energy renewal which can already show several examples from around the world. The method used to solve the unresolved waste problem in this scientific paper is to use WTE and ISWM-S technology which can certainly be a brilliant solution in converting urban solid waste into renewable energy for a clean world from waste to waste and also provides a future. Where people no longer need to worry about the limitations of limited natural resources to be processed into energy. © 2022 IEEE.

关键词： Municipal solid waste

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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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2024 International Conference on Advanced information Scientific Development, ICAISD 2024

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

ISBN: (纸本)9798350392036

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. © 2024 IEEE.

关键词： Contrastive Learning

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Citrus Limon L. Ripeness Identification Using Feature Extraction of Mean RGB, HSV, LBP and K-Nearest Neighbor

Citrus Limon L. Ripeness Identification Using Feature Extrac...

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2023 International Seminar on Application for technology of information and Communication, iSemantic 2023

作者： Priyo Utomo, Ade Cahyo Sari, Christy Atika Rachmawanto, Eko Hari Hadi, Heru Pramono Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%. © 2023 IEEE.

关键词： Citrus fruits

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Decision Support System in Determining the Achievement of Widyaiswara Value Using WASPAS and TOPSIS Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPSDM PROVSU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WASPAS method and the TOPSIS method. Based on the results of tests carried out five times, the results of the WASPAS method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPSIS method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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Optimization of Certainty Factor Algorithm to Overcome Uncertainty in Expert System Identification of Pests and Diseases of Cocoa 2

Optimization of Certainty Factor Algorithm to Overcome Uncer...

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2nd International Conference on Electronic and Electrical Engineering and Intelligent System, ICE3IS 2022

作者： Gunawan, Rakhmat Dedi Ahmad, Imam Parjito Anggono, Harry Vernando, Ego Hengki Jaya, Firman Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Stkip Pgri Information Technology Education Study Program Situbondo Indonesia

ISBN: (纸本)9781665465410

Lampung Province is one of the regions with the highest cocoa production, but many factors can interfere with cocoa production. One of them is the factor of pests and diseases of cocoa that cannot be identified and prevented beforehand. An expert system is a system that adopts expert knowledge or experts in a particular field. However, the diagnosis usually contains uncertainty in the form of answers and statements used. Certainty Factor (CF) algorithm, is one of the algorithms that is able to overcome uncertainty by providing a value for the level of trust from experts and users. However, because the CF value is based on the level of confidence in the symptoms experienced by the user, it creates a problem, namely the consistency of the user's answers. So, it is necessary to make improvements to the CF algorithm, to overcome the inconsistency of user answers through the use of Consistency Ratio (CR). Through the use of CR, inconsistencies are overcome through comparisons between the consistency index and the random index. Based on the results of the accuracy test, the proposed model is able to produce an accuracy rate of 86.67% in the diagnosis of pests and diseases on cocoa plants. © 2022 IEEE.

关键词： Cocoa

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Urgency Detection of Events Through Twitter Post: A Research Overview 4

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

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4th International Conference on Electrical Engineering and Computer Science, ICECOS 2024

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

ISBN: (纸本)9798350368253

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. © 2024 IEEE.

关键词： Tweets

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LED and binaural beats sleeping mask as sleep-wake cycle regulations based on brain wave stimulation

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Journal of International Dental and Medical Research 2018年第2期11卷 745-750页

作者： Karimasari, Azisya Amalia Widiyanti, Prihartini Sofiah, Amila Wardhani, Priyanka Kusuma Dzulfiqar, Andi Achmad Chabib, Choirul Asmaningtias, Novia Dwi Biomedical Engineering Study program Faculty of Science and Technology Universitas Airlangga Indonesia Institute of Tropical Disease Universitas Airlangga Indonesia Otomatization Information System Faculty of Science and Technology Universitas Airlangga Indonesia

Depression rate has reached 17-27% in Indonesia, while about 5-10% of world population have sleep disorder. Unsurprisingly, one of the symptoms of depression is sleep disorder. Sleeping disorder could be treated by sleeping mask. The material of sleeping Mask is PLA (polylactic acid) in 3D printing. There is Arduino Uno as microcontroller to control alarm for sleep-wake cycle. Device works until the first 30 minutes for blue LED and delta binaural beats and the last 30 minutes for yellow LED and gamma binaural beats.. Blue LED and delta wave of binaural beats can stimulate the delta brainwave which related with deep sleep. While yellow LED and gamma binaural beats could stimulate the gamma brain waves and trigger awakening. This research employs causal quantitative method with experimental primary data collection. Additionally, there are two tests in this research, namely sleep and awakening test. A delta wave stimulation is shown in lead C3-C4 during the sleep test. Stimulated delta wave records 23.42 times higher rate than without stimulation. Thus, the system can actually trigger a deep sleep faster. During the awakening test, the stimulation using gamma binaural beats and yellow light shows that delta brainwave amplitude in lead C3-C4 is lower;while alpha brainwave amplitude in lead O1-O2 is higher. Thus, this system is able to stimulate alpha wave faster than without stimulation. The mask could regulate sleep-wake cycle for alarm device and enhance sleep quality. © 2018 University of Dicle.

关键词： Amplitude Brain wave Depression Sleep disorder Stimulation

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Identification of Beef Freshness Using Linear Discriminant Analysis (LDA) Algorithm and Extraction of HSV Values 2

Identification of Beef Freshness Using Linear Discriminant A...

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2nd International Conference on Electronic and Electrical Engineering and Intelligent System, ICE3IS 2022

作者： Napianto, Riduwan Tri Prastowo, Agung Deni Wahyudi, Agung Wajiran Yudoutomo, Yohanes Egi Pratama Suparto, Arico Ayani Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Information Technology Education Study Program Stkip Pgri Situbondo Situbondo Indonesia

ISBN: (纸本)9781665465410

To determine the quality of beef, it is usually seen using a flashlight and matching it with a predetermined color standard. However, this method is time consuming and the results are inconsistent due to human visual limitations. This study aims to identify the freshness of beef based on its color characteristics using feature extraction method with HSV and LDA method for identification. The identification process begins with the transformation process from RGB images to L∗a∗b, then image segmentation serves to separate one object from another and image identification uses the LDA method with feature extraction using HSV. The use of color feature extraction with the HSV algorithm to assist in obtaining information from the colors contained in the image for easy identification. Furthermore, the LDA algorithm has a function to obtain the maximum projection to obtain a smaller dimensional space so that the desired patterns can be separated through the boundary line of a linear equation so as to form a certain class or group. Based on the test results using the confusion matrix, it produces a precision value of 80%, recall of 84%, and accuracy of 82%. © 2022 IEEE.

关键词： Beef

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Mammogram Breast Cancer Classification Based on Deep-Convolutional Neural Network

Mammogram Breast Cancer Classification Based on Deep-Convolu...

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2023 International Seminar on Application for technology of information and Communication, iSemantic 2023

作者： Amadea, Avissa Aurellia Sari, Christy Atika Rachmawanto, Eko Hari Sari, Wellia Shinta Noori, Mohammed S. 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 Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Based on WHO's data, breast cancer is one of the most deadly diseases that has claimed many victims, especially women. This disease begins with the presence of an undetected and eventually turns into malignant (cancer). This happens due to ignorance of the importance of having a medical check-up even though in good health. Doctors and researchers can prevent the development of tumor cells through treatment that begins with radiological examinations to identify the possibility of a person being affected by this disease. One of the most frequently used techniques is Mammography. This technique can detect the presence of tumor cells using advanced technology and several methods in displaying the patient's diagnostic results on low-dose X-rays in the form of mammogram images. The technology is inseparable from the methods used to identify the presence of tumor cells. In this study, we have proposed the CNN method based on the deep-CNN model to identify mammogram images in the detection of breast cancer cells with average evaluation results in terms of accuracy, precision, recall, specificity, and f-measure on mammogram image datasets of 99.52%, 99.72%, 99.31%, 99.72%, and 99.5%. These results showed that this method has a good performance in breast cancer detection. © 2023 IEEE.

关键词： Diseases

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Evaluation of E-government services based on social media using structural equation modeling 4

Evaluation of E-government services based on social media us...

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4th International Conference on information Management and technology, ICIMTech 2019

作者： Nindito, Hendro Madyatmadja, Evaristus Didik Dian Sano, Albert Verasius Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Study Program Bina Nusantara Institute of Creative Technology Malang65126 Indonesia

ISBN: (纸本)9781728133331

Today many local governments have provided aspiration services or social media based complaints about the community to participate in giving aspirations and report problems that occur around the area. To improve the usefulness of this service, we conduct research with the aim of evaluating and identifying the factors that affect the service's application. The impact of this study is that the government can provide services according to the wishes of the community, because the model found can be a reference for the government to increase public trust and satisfaction for users of government services. The influence on the adoption of Aspiration Services is explained by using perceptions of trust, attitudes, and intentions of use that refer to technology acceptance models (TAM). Data processing and analysis in our research using the SEM-PLS method (Structural Equation Model-Partial Least Square). The results in this research will present that services applying technology that gain a positive effect on the awareness of usability and benefit for service users. © 2019 IEEE.

关键词： Least squares approximations

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