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International Conference on computer science, information technology, and Electrical Engineering

作者： Ely Mulyadi Kadek Yota Ernanda Aryanto I Made Candiasa Department of Information Technology Politeknik Negeri Jember Department of Computer Science of Postgraduate Program Universitas Pendidikan Ganesha

ISBN: (纸本)9781728134376

The aim purposed of this research is to evaluate clinical management information system called (E-CLINIC) which is integrated with the Primary Care (Pcare) application provided by Indonesia sosial healt insurance organization called BPJS Kesehatan to first level of health cares facility called as FKTP. This evaluation is intended to measure the maturity level on used of two integrated applications using COBIT 4.1 framework. The integration of the Clinic's management information system with PCare is considered to be the main resource that has strategic value to be able to manage information effectively and efficiently for the achievement of organizational goals. The results achieved have been running in accordance with the organization's business objectives, this can be seen from the level of maturity that reaches level 3 (Defined), which is a condition in which the organization has formal and written standard procedures that have been socialized to all levels of management and employees to be obeyed and run in daily activities.

关键词： E-Clinic MIS PCare BPJS COBIT Maturity Management information Systems Maturity maturity level DNA Integration integration health level health clinic Daily Activities

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Analysis of Application of the SAW, WP and TOPSIS Methods in Decision Support System Determining Scholarship Recipients at University

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Journal of Physics: Conference Series 2021年第1期1830卷

作者： Murni Marbun Muhammad Zarlis Zulkifli Nasution Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Teknik Informatika STMIK Pelita Nusantara Medan Indonesia

This research is an analysis of the application of the SAW, WP and TOPSIS methods to the support system for decision making at university. The types of scholarships provided are PPA education scholarships given by the Kementerian Riset, Teknologi dan Pendidikan Tinggi. The research variables are the attributes or criteria specified by the Directorate General of Learning and Student Affairs as contained in the 2018 Academic Achievement Improvement (PPA) guidebook. Decision Support Systems apply the classic FMADM method SAW, WP and TOPSIS. The results of this study are the application of the both methods of SAW and WP produce the same ranking and TOPSIS giving different rankings.

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A Design of Crowd-Based Corruption Prevention System in Indonesia: Indonesia Corruption Map 4

A Design of Crowd-Based Corruption Prevention System in Indo...

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

作者： Nurlina Kristin, Desi Maya Muqsith, Andi Muhammad Mursitama, Tirta Nugraha Sasmoko Makalew, Brilly Andro Information Systems Department Bina Nusantara University Jakarta11480 Indonesia Primary Teacher Education Bina Nusantara University Jakarta11480 Indonesia Mobile Application Technology Program School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Combatting corruption requires not only centralized and institution-based strategy, but must be met with distributive effort supported by abundance of data and technological advancement. This work tackles the issue of decentralized corruption prevention by describing the method of doing heuristic analysis based on multiple data regarding corruption. There are four main data source used for the input of the system in this work, where each data corresponds to a city in a region. All the data are processed into corresponding index, while the indexes will be further used in index interpretation and suggestion mapping process. The output of this system is a decision support system for relevant decision making related to corruption prevention, visualized using Google Map API. This system will be very powerful in the long and tedious war against corruption, when used to its maximum potential. © 2019 IEEE.

关键词： Mapping

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Integrability of Goldilocks quantum cellular automata

arXiv

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arXiv 2024年

作者： Hillberry, Logan E. Piroli, Lorenzo Vernier, Eric Halpern, Nicole Yunger Prosen, Tomaž Carr, Lincoln D. Department of Physics The University of Texas at Austin AustinTX78712 United States Dipartimento di Fisica e Astronomia Università di Bologna INFN Sezione di Bologna via Irnerio 46 BolognaI-40126 Italy Laboratoire de Probabilités Statistique et Modélisation CNRS Université Paris Cité Sorbonne Université Paris France Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 LjubljanaSI-1000 Slovenia Institute of Mathematics Physics and Mechanics Jadranska 19 LjubljanaSI-1000 Slovenia Quantum Engineering Program Colorado School of Mines GoldenCO80401 United States Department of Physics Colorado School of Mines GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO80401 United States

Goldilocks quantum cellular automata (QCA) have been simulated on quantum hardware and produce emergent small-world correlation networks. In Goldilocks QCA, a single-qubit unitary is applied to each qubit in a one-dimensional chain subject to a balance constraint: a qubit is updated if its neighbors are in opposite basis states. Here, we prove that a subclass of Goldilocks QCA—including the one implemented experimentally—map onto free fermions and therefore can be classically simulated efficiently. We support this claim with two independent proofs, one involving a Jordan–Wigner transformation and one mapping the integrable six-vertex model to QCA. We compute local conserved quantities of these QCA and predict experimentally measurable expectation values. These calculations can be applied to test large digital quantum computers against known solutions. In contrast, typical Goldilocks QCA have equilibration properties and quasienergy-level statistics that suggest nonintegrability. Still, the latter QCA conserve one quantity useful for error mitigation. Our work provides a parametric quantum circuit with tunable integrability properties with which to test quantum hardware. © 2024, CC BY.

关键词： Qubits

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Performance analysis of combination of fuzzy analytic hierarchy process (FAHP) algorithms with preference ranking organization method for enrichment evaluation algorithm (PROMETHEE II) in the ranking process to determine the increase in employee class

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： M. Irfan Ramadhan Muhammad Zarlis Benny Benyamin Nasution Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Information and Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

In this study conducted a Performance Analysis of the Combination of Fuzzy Analytic Hierarchy Process (FAHP) Algorithm with the Preference Ranking Organization Method for Enrichment Evaluation algorithm (PROMETHEE II) in the ranking process to determine the increase in employee groups. From the results of the experiment the Performance Analysis of Fuzzy Analytic Hierarchy Process (FAHP) Algorithm with the Preference Ranking Organization Method for Enrichment Evaluation algorithm (PROMETHEE II) in the ranking process to determine the increase in the employee class obtained by the average employee considered at 62.31%. Seeing the percentage value considered with the Promethee algorithm (45.33%) lower than the Fuzzy AHP algorithm (79.30%), it can be said that the Combination Fuzzy AHP algorithm with Promethee is more selective in the weighting and ranking process.

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Silica nanocone array as a template for fabricating a plasmon induced hot electron photodetector

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Photonics Research 2019年第3期7卷 294-299页

作者： ZHIQIANG YANG KANG DU FANFAN LU YANG PANG SHIJIA HUA XUETAO GAN WENDING ZHANG SOO JIN CHUA TING MEI Key Laboratory of Space Applied Physics and Chemistry Ministry of Education and Shaanxi Key Laboratory of Optical Information TechnologySchool of Science Northwestern Polytechnical University Department of Electrical and Computer Engineering National University of Singapore LEES Program Singapore-MIT Alliance for Research & Technology (SMART)

Plasmon induced hot electrons have attracted a great deal of interest as a novel route for photodetection and lightenergy harvesting. Herein, we report a hot electron photodetector in which a large array of nanocones deposited sequentially with aluminum, titanium dioxide, and gold films can be integrated functionally with nanophotonics and microelectronics. The device exhibits a strong photoelectric response at around 620 nm with a responsivity of 180 μA/W under short-circuit conditions with a significant increase under 1 V reverse bias to 360 μA/W. The increase in responsivity and a red shift in the peak value with increasing bias voltage indicate that the bias causes an increase in the hot electron tunneling effect. Our approach will be advantageous for the implementation of the proposed architecture on a vast variety of integrated optoelectronic devices.

关键词： Silica nanocone array plasmon induced hot electron photodetector

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The Effect of Several Kernel Functions to Financial Transaction Anomaly Detection Performance using One-Class SVM

The Effect of Several Kernel Functions to Financial Transact...

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International Congress on Applied information technology

作者： Yaya Heryadi Dandalina Doctor of Computer Science Program Bina Nusantara University Jakarta Indonesia Master of Information and Technology Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Anomalies in data become ubiquitous and often unavoidable. Despite it might be caused by various errors during the data collection or transportation, some anomalies potentially give important information such as indication of a new underlying process. The aim of anomaly detection task is to determine all such instances in the input dataset in a data-driven fashion. In the past decade, the proliferation of anomaly data in many domains have raised research interest resulted in a plethora of anomaly detection methods A vast number of previous study reports suggested that there is no single model will achieve the best performance for every dataset. This paper presents empiric results on the effect of several kernel functions to performance of One-Class Support Vector Machine (OC-SVM) as an anomaly detector model. The proposed model is tested using financial transactions of microfinance service dataset from an Indonesian Bank. The empiric results showed that OC-SVM model with Sigmoid and RBF kernels achieve the best statistically significant value of training, validation, and testing accuracies than the OC-SVM model with no-kernel, linear kernel and polynomial (degree 3,4,5,6) kernels.

关键词： Kernel Anomaly detection Training Testing Support vector machines Task analysis Feature extraction

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An intelligent applied Fuzzy Logic to prediction the Parts per Million (PPM) as hydroponic nutrition on the based Internet of Things (IoT)

An intelligent applied Fuzzy Logic to prediction the Parts p...

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International Conference on Informatics and Computing (ICIC)

作者： Purnawarman Musa Herik Sugeru Haya Fadhila Mufza Faculty of Computer Science and Information Technology Universitas Gunadarma Indonesia Faculty of Industrial Technology Study Program of Agrotechnology Universitas Gunadarma Indonesia

Hydroponic plants require regular monitoring of plants that grow well and can even cause plants to die. Because too late in providing nutrition or getting too little or too little food or routine monitoring in the hydroponic system. The innovation proposed in the agricultural sector that we suggest is the process of monitoring hydroponic plants in real-time. This study aims to predict the excess or lack of nutrient content based on the results of routine monitoring and has the analytical ability to determine the prediction of the value of Parts per Million (PPM) to find the nutritional value of plant media. Measurement of nutritional value using Electrical Conductivity (EC) and the potential of Hydrogen (pH) in hydroponic plant media. In this research, using the NFT hydroponic system as the application of fuzzy logic with the Mamdani method to determine the predictions of PPM values in providing nutrients at plants to adjusting the nutritional at each plant (e.g., for water spinach plants are need 1050 until 1400 PPM). The implemented is method Internet of Things (IoT) to remote sensing on measure using a smartphone as the representation of the measurement results on the hydroponic system.

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Analysis of classification and Naïve Bayes algorithm k-nearest neighbor in data mining

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： Lotar Mateus Sinaga Sawaluddin Saib Suwilo Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Naïve Bayes is a prediction method that contains a simple probabilistic that is based on the application of the Bayes theorem (Bayes rule) with the assumption that the dependence is strong. K-Nearest Neighbor (K-NN) is a group of instance-based learning, K-NN is also a lazy learning technique by searching groups of k objects in training data that are closest (similar) to objects on new data or testing data. Classification is a technique in Data mining to form a model from a predetermined data set. Data mining techniques are the choices that can be overcome in solving this problem. The results of the two different classification algorithms result in the discovery of better and more efficient algorithms for future use. It is recommended to use different datasets to analyze comparisons of naïve bayes and K-NN algorithms. the writer formulates the problem so that the research becomes more directed. The formulation of the problem in this study is to find the value of accuracy in the Naïve Bayes and KNN algorithms in classifying data.

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Improving the accuracy of old and young face detection in the template matching method with Fuzzy Associative Memory (FAM)

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： Rafika Sari Sembiring Syahril Efendi Saib Suwilo Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Every human has a face pattern and certain characteristics even though identical twins, but the human face pattern still has its own distinctiveness as well as old face patterns and young face patterns even though the human face pattern is very diverse but for young and old face patterns will be a difference between one face and the other face. Face detection (face detection) is one of the initial stages that very important in face recognition that is used in biometric identification. Face detection can also be used to search or index face data from images or videos that contain faces of various sizes, positions, and backgrounds. Face detection (face detection) automatically with the help of a computer is a problem that is not easy because the human face has a high level of variability both intra-personal and extra-personal variability. This study shows that systems with template matching methods combined with FAM can successfully detect differences in human faces, 80% accuracy, 10% better by using ordinary template matching.

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