1,720,964 research outputs found
PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN SUPPORT VECTOR REGRESSION DENGAN ALGORITMA GRID SEARCH
Full text linkThe existence of capital market Indonesia is one of the important factors in the development of the national economy, proved to have many industries and companies that use these institutions as a medium to absorb investment and media to strengthen its financial position. Capital market Indonesia is an emerging market development is very vulnerable to global economic conditions and capital markets of the world. Prediction JCI (Jakarta Composite Index) is necessary to know the great value that will occur in the future so as investors can take the right policy. To predict in this study used a Support Vector Regression (SVR) method to find the hyperplane in the best regression function to predict the closing price of the JCI using a linear kernel function with output in the form of continuous data. Parameter selection cost and epsilon using a grid search algorithm combined with cross validation and obtained best cost 1 and best epsilon 0.1. While the criteria to measure the goodness of the model is MAPE (Mean Absolute Percentage Error) and R2 (Coefficient Determination). The results of this study showed that SVR with linear kernel function provides excellent accuracy in the prediction of JCI with R2 results on training data 98.4% with a MAPE 0.873% while the testing of data R2 90.9% with a MAPE 0.613%.
Keywords: JCI, Support Vector Regression (SVR), Hyperplane, Kernel Linear, Grid Search Algorithm, Cross Validation, Accurac
Estimator Matriks Variance-Covariance Spline Truncated Pada Regresi Nonparametrik Birespon
Full text linkRegresi nonparametrik birespon berbeda dengan regresi nonparametrik respon tunggal, dimana model birespon terdiri dari dua variabel respon dengan asumsi terdapat korelasi antar respon. Untuk mengakomodir korelasi antar respon, maka estimasi fungsi regresi memuat matriks bobot berupa matriks variance covariance error. Berdasarkan penelitian sebelumnya, matriks variance covariance diasumsikan sebagai fixed value. Sedangkan dalam kasus riil tidak diketahui nilainya, maka matriks variance covariance tersebut harus diestimasi dari data. Sehingga, tujuan penelitian ini adalah mengestimasi matriks variance covariance untuk mendapatkan model regresi nonparametrik birespon menggunakan spline truncated. Terdapat dua tahap untuk mengestimasi matriks variance covariance. Tahap pertama adalah melakukan estimasi terhadap koefisien regresi nonparametrik birespon menggunakan metode Weighted Least Square (WLS). Tahap kedua adalah mengestimasi matriks variance covariance menggunakan metode MLE dengan mengasumsikan error berdistribusi normal bivariat dengan mean 0 dan variance covariance W. Selanjutnya dilakukan penerapan terhadap data riil yaitu pada data Indeks Pembangunan Manusia (IPM) dan Indeks Pembangunan Gender (IPG). Variabel prediktor yang digunakan adalah angka kesakitan, angka partisipasi kasar SMA dan PDRB Perkapita. Kriteria pemilihan model terbaik berdasarkan titik knot optimum menggunakan nilai Generalized Cross Validation (GCV). Diperoleh model terbaik pada satu titik knot spline linier dengan GCV 14,183. Model hasil estimasi parameter menggunakan matriks variance covariance lebih baik dalam memodelkan data IPM dan IPG Kabupaten/Kota di Pulau Jawa karena mempunyai RMSE sebesar 3,597 lebih kecil dibandingkan model hasil estimasi parameter dengan matriks variance covariance diketahui mempunyai RMSE sebesar 5,019.
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Bi-response nonparametric regression is different from uniresponse nonparametric regression, where bi-response model consists of two response variables with the assumption of dependency. To accommodate the correlation between responses, the estimation of regression function should be consisted of weight in the form of variance covariance matrix of residuals. It can be estimated using variance covariance error matrix. Based on previous research, the variance covariance matrix is assumed to be a fixed value. Whereas in the real case the value is unknown so that the variance covariance matrix must be estimated from the data. The purpose of this study is to estimate the variance covariance matrix of spline truncated on bi-response nonparametric regression models. There are two steps to estimate the variance covariance matrix. The first step is to estimate the Bi-response nonparametric regression coefficient using the Weighted Least Square (WLS) method and the second step is estimated the variance covariance matrix using the MLE method by assuming a bivariate normal distribution error with mean 0 and variance covariance W. Then, the result of the estimation is applied to the Human Development Index (HDI) and Gender Development Index (IPG) data. The predictor variables used were morbidity, gross participation rates of SMA and GDP per capita. Criteria for selecting the best model based on the optimum knot point uses the Generalized Cross Validation (GCV) value. The best model found was spline truncated use one knot with GCV 14.183. The estimation parameter model by using the variance covariance matrix is fit in modeling the HDI and GDI data since the RMSE is smaller than that of fixed variance covariance matrix
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
EVALUASI KESUKSESAN IMPLEMENTASI SAP DI MASA PANDEMI COVID-19 MENGGUNAKAN MODEL UTAUT 3 PADA PT. KAI
Full text linkPenyedia layanan transportasi, PT KAI merupakan bagian dari Badan Usaha Milik Negara (BUMN) pada sektor transportasi darat. Proses bisnis PT KAI didukung oleh integrasi sistem SAP sejak tahun 2012 hingga keadaan pandemi saat ini, ditemukan beberapa permasalahan dalam implementasi yaitu terjadinya penurunan nilai kinerja karyawan pengguna SAP pada PT KAI selama penerapan metode kerja hybrid yang merupakan imbas dari pandemi COVID-19. Perlu diketahui faktor-faktor yang mempengaruhi penurunan kinerja dalam implementasi sehingga dapat disimpulkan implementasi yang dijalankan ini termasuk dalam kategori berhasil atau gagal. Berdasarkan dari permasalahan tersebut penelitian ini berfokus pada analisa kesuksesan implementasi SAP yang dilihat dari sikap pengguna dalam menerima implementasi SAP dimasa pandemi COVID-19 melalui model Unified Theory of Acceptance and Use of Technology (UTAUT-3) dengan variabel Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Habit, Price Value, Behavioral Intention, Use Behaviour, dan Innovation. Hubungan antar variabel perlu diketahui untuk melihat persepsi serta perilakunya pengguna dalam penerimaan penggunaan implementasi SAP di masa pandemi. Penelitian dilakukan terhadap 20 responden pengguna SAP pada PT KAI yang diolah menggunakan aplikasi SmartPLS 3.3.9 melalui metode SEM-PLS. Analisa hasil responden dilakukan dan diketahui bahwa variabel Price Value memiliki pengaruh positif, signifikan, dan kuat terhadap Behavioral Intention, lalu variabel Innovation, dan Behavioral Intention berpengaruh positif, signifikan, dan kuat terhadap Use Behaviour. Variabel Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, dan Hedonic Motivation berpengaruh negatif, tidak signifikan, dan lemah terhadap Behavioral Intention, serta variabel Habit berpengaruh negatif, tidak signifikan, dan lemah terhadap Use Behavior
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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