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Clustering spatial on the GSTAR model for replacement new oil well

AIP Conference Proceedings 2013年第1期1554卷 205-209页

作者： Budi Nurani Ruchjana Atje Setiawan Abdullah Toni Toharudin I Gede Nyoman Mindra Jaya Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Informatics Engineering Study Program Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Department of Statistics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Jl Raya Bandung Sumedang Km 21 Jatinangor Sumedang 45363-West Java Indonesia

Space time models such as the Generalized Space Time Autoregressive (GSTAR) is an important theoretical research topics with many applications in large number of areas ranging from the spread of diseases, mining, economic growth, ecology, agriculture and population development. In this paper we introduce a clustering spatial for determining a group of locations for weight matrix of the GSTAR model. We use Ordinary Least Squares method to estimate the parameters of model and apply the result to develop a GSTAR-Kriging model for replacement new oil wells at volcanic field in Jatibarang, West Java-Indonesia.

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User Experience Analysis on Class I LPKA Palembang Filial E-School

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Journal of Physics: Conference Series 2020年第1期1500卷

作者： D. Tri Octafian Febrianty Hendra Hadiwijaya Informatics Engineering Study Program Palembang Palcomtech Polytechnic Indonesia Accounting Study Program Palembang Palcomtech Polytechnic Indonesia Visual Communication Design Study Program Palembang Palcomtech Polytechnic Indonesia

The Class I LPKA Palembang management wishes to present academic services through the provision of systems that can better support education. Therefore, Filial e-school was built and implemented as a learning system in filial schools implemented in LPKA. The e-school system with the link address http://***/, consists of several modules: ***-based learning module, ***-based learning module, ***-based learning module, *** learning media, *** and submission assignment media, *** media. This system facilitates the learning process of LPKA students to be able to learn independently with existing media and make it easier for teachers to deliver learning material. The system development method used in this study was the Rapid Application Development (RAD) method. Testing of user experience on the use of e-school was tested using the User Experience method with the following aspects:Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. Based on the results of UEQ differences between parent schools' teachers and LPKA students on the use of filial e-school, it was found that e-school filial gave slightly higher impressions to parent schools' teachers compared to students. The average results of the UEQ questionnaire for all users of the e-school filial system showed that the stimulation and novelty aspects were felt to be higher than the other four aspects.

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Application for Airport Tenant Selection Using Weighted Product-based Decision Support System

Application for Airport Tenant Selection Using Weighted Prod...

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Electrical and Information Technology (IEIT), International Conference on

作者： Arwin Datumaya Wahyudi Sumari Muhamad Andika Saputra Astika Ayuningtyas Catur Sudarmadi Aerospace Intelligent System and Data Engineering Research Group Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Cognitive Artificial Intelligence Research Group Politeknik Negeri Malang Malang Indonesia Informatics Study Program Faculty of Industrial Technology Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Health Informatics Research Group Faculty of Industrial Technology Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia

This research aims to develop an application for selecting the best new tenant at PT Angkasa Pura II Sultan Thaha Jambi Airport Branch by utilizing Weighted Product (WP) method as the decision support system. Our approach is descriptive research with data analysis technique using four prospective tenants coded A_1 to A_4. The data was collected through observation, interviews, documentation, and literature study. The steps for selecting the best new tenant using the WP method include determining the criteria, sorting the suitability of alternatives and criteria, determining the weight of each criterion and its normalization, calculating the score, S value as an alternative preference, and calculating the ranking, V value as the final alternative preference. Based on the final calculation results, the new tenant coded A_4 is the best alternative based on the data collected from the Financial Management (FHFM) Unit and the Commercial Unit, with a value of V_4 is 0.294.

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Load balancing factor using greedy algorithm in the routing protocol for improving internet access

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IOP Conference Series: Materials Science and engineering 2018年第1期420卷

作者： Ady Satria Poltak Sihombing Sawaluddin Informatics Engineering Study Program Magister Faculty of Computer Science and Information Technology University of Sumatera Utara

Load Balancing is very well applied to the distribution of internet access at any point of the Wi-Fi area so that the use of limited devices can be optimal and on target. The proper use of the Greedy Algorithms when applied to an access point device is very capable in resolving excessive loading in a single resource to take the best choice at every stage in an optimum process. Access point device is also a success factor in running the optimization of the distribution of Wi-Fi access on the Access Point is strongly influenced by the parameters set. In this research, user access factor in one very high Wi-Fi area also influences the possibility of incoming access failure. For the application of the results of this study can be utilized on all access point devices that have limits, but for speed internet access remains at the capacity provided bandwidth.

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The Scientific Progress and Prospects of Artificial Intelligence for Cancer Detection: A Bibliometric Analysis

The Scientific Progress and Prospects of Artificial Intellig...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Fairuz Iqbal Maulana Puput Dani Prasetyo Adi Dian Lestari Sandy Vikki Ariyanto Agung Purnomo Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta Indonesia Faculty of Medicine Universitas Airlangga Surabaya Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

Using the Scopus database, this study aims to investigate the use of artificial intelligence for cancer detection in the last ten years from 2013 to 2022. The researchers used bibliometric analysis combined with VosViewer and Rstudio software quantification method for literature analysis. The results of the flushed articles show data such as publication year, journal, country, keywords, and authors, to the highest number of citations. Common keywords used by researchers are artificial intelligence, medical, and human. Researchers limited the findings through keywords such as in the last ten years, documents are journals, and English only so that 1868 articles were obtained. The results found that Harvard Medical School affiliation had the highest number of articles, with 101 articles, by subject area, Medicine had a proportion of 41.9% (n=1320). This bibliometric study will be useful for other researchers to examine the development of research on Artificial Intelligence for Cancer Detection in the last ten years.

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Trajectory Analysis of Inter-Island Logistics Transportation for Aggregate Material Using Web-Based Information

Trajectory Analysis of Inter-Island Logistics Transportation...

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Technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Aji Suraji Syarifuddin Ishak Prabowo Prabowo Muhammad Fatkhurrozi Gholiqul Amrodh Alawy Rangga Pahlevi Putra Dept. of Civil Engineering University of Widyagama Malang Malang City Indonesia Study Program of D4 Eng. Tech and Civil Building Maintenance Malang State University Malang City Indonesia Dept. of Ocean Engineering Institut Teknologi Sumatera Lampung Selatan Regency Indonesia Dept. of Informatics Engineering University of Widyagama Malang Malang City Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

Transportation of material aggregates over long distances and between islands requires a long time by changing modes of transportation. Therefore, determining a material aggregate travel trajectory model using a web database is something that can help in logistics movement analysis. This study aims to create a web-based material aggregate transportation trajectory model. The data collection method involves extracting data with Google Maps which shows distance and time indications. Next, validation is carried out in the field with a direct survey at the location. The analytical method uses statistical methods to create modeling using a linear regression model approach and statistical tests using anova. The results of the study show that the linear regression model is simple with an independent variable coefficient of 0.0306 and an R-square of 0.8649. Meanwhile, using the ANOVA test, it was stated that the modeling results were quite significant and the model could be used to make predictions.

关键词： Analytical models Aggregates Linear regression Loading Transportation Predictive models Mathematical models Trajectory Analysis of variance Logistics

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Analysis A parallel combination between the Number Theorists aRe Us, Riverst Shamir Adleman and Triple Data Encryption Standard methods for measuring the speed of document security

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Journal of Physics: Conference Series 2019年第1期1230卷

作者： Luken Candawan Hardiaman Hulu William David Sipayung Muhammad Hafis Christnatalis Informatics Engineering Study Program Deparment of Technology and Computer Science Universitas Prima Indonesia Medan Indonesia

Computer security is a very important thing in an information system. The strength of the NTRU algorithm is the difficulty of finding a short vector of a lattice (a discrete subgroup of a collection of vectors that includes the entire vector environment) of a random polynomial that has a large degree. The strength of the RSA algorithm lies in the level of difficulty in factoring non-prime numbers into the primary factor. As long as no efficient algorithm has been found to find the prime factors of large integers, the RSA algorithm is highly recommended for message encryption. And finally this is the TRIPEL DES algorithm designed using a 56-bit key, and that size is enough to run a secure encryption technique. This algorithm provides a simple solution that is running the DES Algorithm 3 times for data blocks. The results of our study of measuring speed on encryption and decryption using the same file are superior to the RSA algorithm compared to the NTRU and TRIPLE DES algorithms.

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Logistic Regression Model of Relationship between Breast Cancer Pathology Diagnosis with Metastasis

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Journal of Physics: Conference Series 2021年第1期1752卷

作者： M N Bustan B Poerwanto Statistics Study Program Universitas Negeri Makassar Makassar Department of Informatics Engineering Universitas Cokroaminoto Palopo

Management of breast cancer requires a diagnosis of breast cancer, including an accurate pathology diagnosis to direct the provision of appropriate treatment. Part of inseparable diagnosis of breast cancer itself is determining the presence of metastasis. This study aims to determine the relationship model of pathological diagnosis with the possibility of metastasis to other organs of the breast. Pathology diagnosis results include tumor position, topography, behavior, grade, and tumor status. This study used secondary data from the Hospital Information System (SIRS) of the hospital in Makassar, Indonesia. Data obtained from the results of pathology and clinical examinations of breast tumor as many as 204 patients were hospitalized during the year of 2018. Binary regression analysis modeling was performed to see the relationship between types of pathological diagnosis (laterality, topography, behavior, grade, tumor status) of breast cancer with the possibility of metastases to other organs. The results of the analysis found a significant relationship between the position and status of the tumor with the presence of metastasis. The results of the metastatic binary logistic regression model was L(Y) = 1.330 – 0.670lat1 – 0.779lat2 – 0.724status Chi-square analysis between metastasis with surgery and chemotherapy found the significant relationships between metastasis with surgery (X2 = 15.951; p value = 0.001) and metastasis with chemotherapy (X2 = 20,796; p value = 0.001). The results of this analysis indicate that the position and status of the tumor have a relationship with the likelihood of metastasis. In addition, this metastasis further determines the management of treatment whether surgery or chemotherapy or both.

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Traffic sign detection using histogram of oriented gradients and max margin object detection

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Journal of Physics: Conference Series 2019年第1期1230卷

作者： Reinaldo Natanael Manurung Juara immanuel Simbolon Christnatalis Informatics Engineering Study Program Deparment of Technology and Computer Science Universitas Prima Indonesia Medan Indonesia

Traffic signs are important markers in two-wheeled and four-wheeled vehicles. However, there is a change in direction or arrangement on the road that cannot be opened on a map which can cause incorrect information, which can cause traffic jams. In this journal the author uses a camera mounted on a car that provides a solution for drivers who issue problems that occur on the road that show directions or arrangements that are not directly updated using the HOG and MMOD methods. HOGs and MMODs are methods that can refute objects well, and move images and will be recognized immediately. The information received can be sent directly to an electronic map so that it can be accessed automatically by the driver's information and assistance and other information finds the right path, so that it can help the driver and can avoid traffic jams.

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Villages Status Classification Analysis Involving K-Means Algorithm To Support Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi Work programs

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： Paska Marto Hasugian Harvei Desmon Hutahaean Bosker Sinaga Sriadhi Saranom Silaban Informatics Engineering Study Program STMIK Pelita Nusantara Medan Indonesia Computer Science and Informatics Education Study Program Faculty of Engineering Universitas Negeri Medan Medan 20221 Indonesia Departement of chemistry Universitas Negeri Medan Medan 20221 Indonesia

Data mining is a technique of extracting information that has not been known before in a collection of data in the database. Data mining has been applied in various fields that require extracting information, some of the work that can be generated with data mining is classification, prediction, and data grouping. In this study, an analysis of village data collection was carried out to explore the potential or knowledge of the data that has been presented with the main objective of producing a grouping of village status. To support clustering or grouping activities the K-means algorithm used with the general process is to carry out the modeling process without supervision and is one of the methods for grouping data with a system partition, with the principle of allocating each data to the centroid or the closest average, work steps conducted in support of this research is to collect data related to the analysis of data grouping and proceed with the calculation process in accordance with the work steps of the K-means algorithm, the amount of data used as a test of 303 villages scattered in the old Padang regency. The results of calculations by displaying a new group of Cluster 0 is occupied by 120 villages, cluster 1 with a total data of 123 villages, Cluster 2 with a total of 6 villages, cluster 3 with a total of 33 villages while cluster 4 with a total of 21.

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