1,720,973 research outputs found
CLASSIFICATION OF MISSING VALUES HANDLING METHOD DURING DATA MINING: REVIEW
Full text linkCLASSIFICATION OF MISSING VALUES HANDLING METHOD DURING DATA MINING: REVIEW. Missing data often occurs in researchs or surveys. Many real datasets or data mining have missing data, thus affecting the quality of the data. There are various causes resulting in incomplete data, such as: manual data entry procedure, incorrect measurement, equipment error, and many others. Any errors causing data missing make it difficult in a data analysis. This is due to the algorithms of data analysis that only work if the data is complete. Missing data analysis may help resolving missing data. Missing data can be replaced with a value based on the possibility of other information available, so that the data set can be analyzed. Many specialists have been working on this issue to present more modern techniques. Many strategies are available for handling the missing data, however investigator has difficulty in finding the right technique in the absence of information about strategy and implementation. The purpose of this research paper is to classify methods of miss- ing data handling based on statistical method and machine learning. Results from this study are clas- sification methods of missing data handling by ignoring technique, model base technique and impu- tation technique , which are complemented with the advantages and disadvantages of each method. Keywords: missing value, statistic, machine learning, classification, method
Strategi Pemeliharaan Komponen pada Sistem Pendingin RSG-GAS Berdasarkan Estimasi Interval Waktu Perawatan
Full text linkSTRATEGI PEMELIHARAAN KOMPONEN PADA SISTEM PENDINGIN RSG-GAS BERDASARKAN ESTIMASI INTERVAL WAKTU PERAWATAN. Proses penuaan akan menyebabkan penurunan keandalan dan kinerja reaktor, oleh karena itu diperlukan pemeliharaan sistem/komponen reaktor yang optimal. Pemeliharaan korektif terhadap sistem/komponen berdampak pada frekuensi kerusakan dan biaya perawatan yang tinggi. Tujuan dari penelitian ini adalah melakukan proses pendekatan manajemen keandalan dengan melakukan perencanaan interval pemeliharaan. Skenario pemeliharaan dapat dilakukan berdasarkan penggantian komponen sesuai dengan mean time to failure (MTTF) dan ketika keandalan komponen memenuhi presentase yang ditargetkan. Metodologi yang digunakan adalah uji distribusi data dan estimasi parameter untuk menetukan interval waktu perawatan dan keandalan komponen. Data yang dievaluasi adalah data perawatan komponen dari sistem pendingin RSG-GAS teras 81 sampai 94 tahun 2013-2017. Hasil pengolahan data menunjukkan bahwa untuk meminimalkan jumlah downtime berdasarkan interval waktu perawatan dan nilai keandalan komponen, maka strategi perawatan yang dapat dilakukan adalah untuk komponen Pompa Primer (JE-01 (AP01-02)) interval perawatan 245,27 hari dengan peluang keandalan komponen (R(t)) = 35,2%. Untuk komponen Instrumentasi Pengukuran Aktivitas γ (PA01-02/CR001) interval perawatan 203,57 hari dengan peluang keandalan komponen (R(t)) = 51,1%. Sedangkan jika diinginkan keandalan komponen sebesar 60% maka dapat dilakukan interval waktu perawatan 144,23 hari untuk komponen JE-01 (AP01-02) dan 160,35 hari untuk komponen PA01-02/CR001.Kata kunci: keandalan, perawatan, sistem pendingin, RSG-GA
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
IMPLEMENTATION OF MISSING VALUES HANDLING METHOD FOR EVALUATING THE SYSTEM/COMPONENT MAINTENANCE HISTORICAL DATA
Full text linkMissing values are problems in data evaluation. Missing values analysis can resolve the problem of incomplete data that is not stored properly. The missing data can reduce the precision of calculation, since the amount of information is incomplete. The purpose of this study is to implement missing values handling method for systems/components maintenance historical data evaluation in RSG GAS. Statistical methods, such as listwise deletion and mean substitution, and machine learning (KNNI), were used to determine the missing data that correspond to the systems/components maintenance historical data. Mean substitution and KNNI methods were chosen since those methods do not require the formation of predictive models for each item which is experiencing missing data. Implementation of missing data analysis on systems/components maintenance data using KNNI method results in the smallest RMSE value. The result shows that KNNI method is the best method to handle missing value compared with listwise deletion or mean substitution.Keywords: missing value, data evaluation, alghorithm, implementation IMPLEMENTASI METODE PENANGANAN DATA HILANG UNTUK MENGEVALUASI DATA SEJARAH PERAWATAN SISTEM/KOMPONEN. Data hilang merupakan masalah dalam melakukan evaluasi data. Analisis data hilang dapat menyelesaikan permasalahan ketidaklengkapan data yang tidak tersimpan dengan baik. Data yang hilang akan memperkecil presisi dari perhitungan, dikarenakan jumlah informasi yang tidak lengkap. Tujuan dari penelitian ini adalah implementasi metode penanganan data hilang untuk evaluasi data sejarah perawatan sistem/komponen RSG GAS. Metodologi yang digunakan untuk menentukan data hilang yang berhubungan dengan data sejarah perawatan sistem/komponen adalah statistics, listwise deletion dan mean substitution, dan machine learning (KNNI). Metode mean substitution dan KNNI dipilih karena metode ini tidak memerlukan informasi untuk pembentukan model prediksi untuk setiap item yang mengandung data hilang. Implementasi analisis data hilang pada data perawatan sistem/komponen menggunakan metode KNNI menghasilkan nilai RMSE terkecil. Hasil ini menunjukan bahwa metode KNNI merupakan metode terbaik untuk menangani data hilang dibanding dengan listwise deletion atau mean substitution.Kata kunci: data hilang, evaluasi data, algoritma, implementasi</jats:p
PENGEMBANGAN KODE UNTUK ANALISIS KETIDAKPASTIAN INPUT PARAMETER FUEL TEMPERATURE PADA KODE MONTE CARLO N-PARTIKEL TRANSPORT
Full text linkPada penelitian ini dilakukan pengembangan kode untuk analisis ketidakpastian parameter fuel temperature selama history iradiasi dalam perhitungan burn-up bahan bakar menggunakan kode Monte Carlo (MCNPX). Ketidakpastian parameter input fuel temperature diperhitungan dengan mengambil sekitar ±1% dan ± 5% dari nilai nominal 900K. Sehingga dibutuhkan data nuklir pada suhu tertentu. MCNPX memerlukan data nuklir dalam bentuk ACE format. Data nuklir format ACE ini bisa diperoleh melalui ENDF (Evaluated Nuclear Data File) yang telah diproses oleh aplikasi NJOY. Antarmuka dibuat untuk memperoleh data nuklir dalam bentuk ACE format dari ENDF melalui proses perhitungan NJOY khusus untuk perubahan temperatur pada rentang tertentu. Pengembangan kode dibuat dalam script phyton dan dilakukan kopling dengan MCNPX.
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