1,720,959 research outputs found
Prediksi Fase Pertumbuhan Padi Berdasarkan Data Citra Multitemporal Landsat-8 Dengan Metode Convolutional Neural Network (CNN) Dan Rotation Forest Multiclass (Rotfor) (Studi Kasus Sampel Survei Ksa Kabupaten Poso, Provinsi Sulawesi Tengah)
Get PDFPada tahun 2018 dibentuk Survei Kerangka Sampel Area (KSA) yang dilaksanakan oleh BPS untuk menghitung luas panen padi. Dalam rangka mengatasi keterbatasan KSA, maka dilakukan usulan menggunakan satelit Landsat-8 dengan menggunakan metode Machine learning (CNN dan rotfor multiclass) untuk mengklasifikasikan area panen. Kombinasi data satelit dan data offisial merupakan inovasi yang perlu dilakukan untuk mengatasi suatu keterbatasan khususnya pada Survei KSA yang dilaksanakan BPS. CNN merupakan metode yang sering digunakan dalam mendeteksi objek pada sebuah citra, sedangkan rotfor merupakan metode berbasis pohon yang memiliki kemampuan baik dalam klasifikasi dengan tipe prediktor merupakan data kontinyu dengan memanfaatkan PCA. Penelitian ini bertujuan melihat metode yang terbaik dalam memprediksi fase pertumbuhan padi. Hasil prediksi menunjukkan kinerja yang dihasilkan model CNN menghasilkan hasil yang terbaik dibandingkan dengan metode rotation forest multiclass dengan nilai sensitivity sebesar 0,9807, specificity 0,9773, accuracy 0,9766, MCC 0,9682 dan cohen kappa 0,9680 dengan G-mean sebesar 0,9742. rotfor multiclass OVO memiliki kinerja cukup baik dengan nilai nilai sensitivity sebesar 0,9106, specificity 0,9700, accuracy 0,9063, MCC 0,8760 dan cohen kappa 0,9594 dengan G-mean sebesar 0,9238. Model rotfor multiclass OVA sendiri memiliki kinerja prediksi sensitivity sebesar 0,9084, specificity 0,9699, accuracy 0,9063, MCC 0,8737 dan cohen kappa 0,9595 dengan G-mean sebesar 0,9229.
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In 2018 the Area Sample Framework Survey (ASF) was formed, which was carried out by BPS to calculate the rice harvested area. In order to overcome the limitations of ASF, a proposal was made to use the Landsat-8 satellite using Machine learning (CNN and rotfor multiclass) methods to classify harvested areas. The combination of satellite data and official data is an innovation that needs to be done to overcome a limitation, especially in the ASF Survey conducted by BPS. CNN is a method that is often used in detecting objects in an image, while rotfor is a tree-based method that has good ability in classification with predictor types being continuous data using PCA. This study aims to see the best method in predicting the growth phase of rice. Prediction results show that the performance generated by the CNN model produces the best results compared to the rotation forest multiclass method with a sensitivity value of 0.9807, specificity 0.9773, accuracy 0.9766, MCC 0.9682, and cohen kappa 0.9680 with a G-mean of 0.9742. Rotfor OVO multiclass has a fairly good performance with sensitivity values of 0.9106, specificity 0.9700, accuracy 0.9063, MCC 0.8760, and cohen kappa 0.9594 with a G-mean of 0.9238. In comparison, the rotfor multiclass OVA model itself has a sensitivity prediction performance of 0.9084, specificity 0.9699, accuracy 0.9063, MCC 0.8737, and cohen kappa 0.9595 with a G-mean of 0.9229
MODEL HYBRID NONLINEAR REGRESSION LOGISTIC (NLR) –DOUBLE EXPONENSIAL SMOOTHING (DES) DAN PENERAPANNYA PADA JUMLAH KASUS KUMULATIF COVID-19 DI INDONESIA DAN BELANDA
Get PDFThe economic relationship between Indonesia and the Netherlands is a good trade relationship, but the spread of COVID-19 disrupts the two countries' economies. Both countries need to have an explanation regarding the condition of COVID-19 to raise economic market sentiment. Based on this, Hybrid and non-hybrid models are used to predict the dispersion conditions and compare them through the MAPE value. The double-exponential nonlinear logistic regression hybrid model on the cumulative number of COVID-19 is not suitable for use in the Netherlands COVID-19 cases but is suitable for use in the cumulative number of COVID-19 cases Indonesia. The hybrid nonlinear regression logistic-double exponential model is one way to optimize MAPE, especially in training data. Based on the hybrid non-client regression logistic model, the peak incidence of Covid-19 in the Netherlands is estimated at 22 November 2020, and the hybrid nonlinear regression logistic-Double exponential model predicts that the peak of Covid-19 occurs in Indonesia on 28 November 2020. the Netherlands wave is around 2.83 percent and Indonesia 1.62 percent. Therefore the decline in Indonesia is predicted to be faster, but the Netherlands will reach the peak of the Indonesian news wave
Analisis Bicluster Algoritma CC untuk Mengidentifikasi Pola Rawan Pangan di Indonesia
Get PDFIndonesia is known as an agricultural country. This means that most of the population work in the agricultural sector related to food. However, food insecurity still occurs in Indonesia. With the COVID-19 pandemic, the Food and Agriculture Organization (FAO) stated that there was a threat of food scarcity which had an impact on food insecurity conditions. This would undermine the second goal of the SDGs, which is to end hunger and create sustainable agriculture. The purpose of this study was to determine the spatial pattern of food insecurity in each province in Indonesia using the bicluster method. The data used are data from Susenas and Sakernas by BPS in 2019. Several studies show that the bicluster method with the CC algorithm shows that each province group has a different characteristic pattern. In the bicluster approach, the researcher runs parameter tuning to select the best parameter based on the Mean Square Residual in Volume (MSR / V). The CC algorithm tries to get a bicluster with a low MSR value, therefore the best parameter is the one that produces the smallest MSR / V value, in this study the smallest MSR / V is 0,01737 with δ = 0,01. The application of the CC biclustering algorithm to the food insecurity structure in Indonesia results in 5 bicluster. Bicluster 1 consists of 15 provinces with 8 variables, Bicluster 2 consists of 10 provinces with 5 variables, Bicluster 3 consists of 3 provinces with 7 variables, Bicluster 4 consists of 4 provinces with 4 variables and Bicluster 5 consists of 2 provinces with 5 variables. Biculster 4 represents a cluster of food insecurity areas with the characteristics of the bicluster P0, P1, P2 and calorie consumption of less than 1400 KKAL.Indonesia dikenal sebagai negara agraris. Artinya, sebagian besar penduduknya bekerja di sektor pertanian yang berkaitan dengan pangan. Namun kerawanan pangan masih terjadi di Indonesia. Adanya pandemi COVID-19, Organisasi Pangan dan Pertanian (FAO) menyatakan adanya ancaman kelangkaan pangan yang berimbas kepada kondisi rawan pangan. Hal tersebut akan mengganggu tujuan kedua SDGs yaitu untuk mengakhiri kelaparan dan menciptakan pertanian berkelanjutan. Tujuan penelitian ini untuk mengetahui pola kerawanan pangan di setiap Provinsi di Indonesia secara spasial dengan menggunakan metode bicluster. Data yang digunakan adalah data dari Susenas dan Sakernas oleh BPS tahun 2019. Beberapa hasil studi menunjukkan bahwa dengan metode bicluster dengan algoritma CC terlihat setiap kelompok Provinsi memiliki pola karakteristik yang berbeda-beda. Pada pendekatan bicluster, peneliti menjalankan tuning parameter untuk memilih parameter terbaik berdasarkan Mean Square Residual dalam volume (MSR / V). Algoritma CC berusaha mendapatkan bicluster dengan nilai MSR yang rendah, oleh karena itu parameter yang terbaik adalah yang menghasilkan nilai MSR/V terkecil, dalam penelitian ini MSR/V terkecil 0,01737 dengan δ=0.01. Penerapan algoritma CC biclustering pada struktur kemiskinan di Indonesia menghasilkan 5 bicluster. Bicluster 1 Terdiri dari 15 Provinsi dengan 8 Variabel, Bicluster 2 terdiri dari 10 Provinsi dengan 5 Variabel, Bicluster 3 terdiri dari 3 Provinsi dengan 7 Variabel, Bicluster 4 terdiri dari 4 Provinsi dengan 4 Variabel dan Bicluster 5 terdiri dari 2 Provinsi dengan 5 variabel. Variabel P0, P1 dan P2, sebagai pengukuran kerawanan pangan absolut termasuk dalam semua bicluster
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
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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