1,720,958 research outputs found
Hierarchical Agglomerative Clustering dengan Metode Ward Untuk Pemetaan Pasar Tenaga Kerja Pascapandemi di Jawa Tengah: Pendekatan Machine Learning Berbasis Klasterisasi
Full text linkPandemi COVID-19 telah memberikan dampak signifikan terhadap dinamika ketenagakerjaan di Indonesia, termasuk di Provinsi Jawa Tengah. Ketimpangan distribusi pasar tenaga kerja antarwilayah menjadi tantangan tersendiri dalam perumusan kebijakan pascapandemi. Penelitian ini menerapkan Hierarchical Agglomerative Clustering (HAC) dengan metode Ward untuk memetakan pasar tenaga kerja pascapandemi di Jawa Tengah berdasarkan indikator Tingkat Partisipasi Angkatan Kerja (TPAK), Tingkat Pengangguran Terbuka (TPT), dan Rasio Pencari Kerja terhadap Lapangan Kerja (RPKL). Hasil klasterisasi menunjukkan lima klaster dengan karakteristik pasar tenaga kerja yang berbeda, mulai dari klaster dengan partisipasi kerja di bawah rata-rata dan pengangguran di atas rata-rata hingga klaster dengan kondisi pasar tenaga kerja yang lebih stabil. Validitas klaster dikonfirmasi melalui koefisien Silhouette. Temuan ini memberikan gambaran spasial yang berguna untuk perumusan kebijakan ketenagakerjaan yang adaptif dan berbasis data
HIERARCHICAL CLUSTER ANALYSIS ON PEOPLE'S WELFARE IN SOUTHEAST SULAWESI PROVINCE
Full text linkProblems with people's welfare typically result from the government's development efforts in a region not being done properly or not being done equally. Consider grouping and defining the traits of each region's degree of welfare as a potential answer to ensure that development policies and strategies are well-targeted. This study aims to classify 17 regency/cities in Southeast Sulawesi province based on several indicators of people's welfare. The method used is hierarchical cluster analysis with several approaches, including Single Linkage, Complete Linkage, Average Linkage, and Ward's. The data used in this study is secondary data obtained from the publication of the Central Agency of Statistics (CAS) of Southeast Sulawesi Province. Based on the results of the evaluation the best method used is Ward's method which produces three clusters. The first cluster consists of 9 regencies, namely Buton, North Buton, South Buton, Central Buton, Muna, West Muna, Wakatobi, Konawe Islands, and East Kolaka, the majority of which come from the archipelago. Some of the problems that occur in these areas are the relatively high poverty rate and the low average length of schooling and life expectancy. The same thing happened to the second cluster which consisted of 6 regencies, namely Konawe, South Konawe, North Konawe, Bombana, Kolaka, and North Kolaka with problems of poverty, the average length of schooling, and relatively low sources of proper drinking water when compared to other clusters. The third cluster consists of 2 urban areas, namely Kendari City and Baubau City, the problems that occur are the relatively high unemployment rate and population density. The government ought to offer more initiatives to handle issues with poverty, education, and health in regions in clusters 1 and 2. While in cluster 3, the government ought to offer more initiatives to combat jobless issues and prepare for rising population densities
Model Machine Learning Stacking untuk Prediksi Pembatalan Pemesanan Hotel
Full text linkThe hotel prepares rooms and resources according to the room booking. Advance booking from customers is a relationship between customers and hotels that ensures price stability for customers to enjoy services. Cancellation of hotel bookings and inability to satisfy potential customers is a widespread and alarming problem that can increase hotel operating costs and affect customer satisfaction. Given that the impact on the hospitality industry can be very bad, predicting hotel cancellations can be a solution to help build an appropriate operational strategy. Method used in this research is stacking machine learning model. Stacking consists of two levels, where in this study level 0 (base learner) uses the Naive Bayes, Logistic Regression, and Gradient Boosting Machine algorithms while at level 1 (meta learner) uses the Random Forest algorithm. Accuracy value of the stacking model classification and the gradient boosting machine has the highest accuracy value of 0.87. Sensitivity value of the stacking model is 0.86 and is the highest sensitivity value which means that the stacking model classification is very precise in predicting consumers in canceling hotel reservations. Specificity value of the gradient boosting machine is 0.88 and is the highest specificity value, which means that the gradient boosting machine classification is very precise in predicting consumers who do not cancel hotel reservations. Naive bayes and logistic regression classifications have accuracy, sensitivity, specificity, precision values that are not high.
Hotel mempersiapkan kamar dan sumber daya sesuai dengan pemesanan kamar. Pemesanan di awal dari pelanggan merupakan hubungan antara pelanggan dengan hotel yang memastikan kestabilan harga bagi pelanggan untuk menikmati layanan. Pembatalan pemesanan hotel dan ketidakmampuan untuk memuaskan calon konsumen merupakan masalah yang meluas dan mengkhawatirkan yang dapat meningkatkan biaya operasional hotel dan mempengaruhi kepuasan pelanggan. Mengingat hal itu dampaknya terhadap industri perhotelan bisa sangat buruk, maka dengan memprediksi pembatalan hotel dapat menjadi solusi untuk membantu membangun strategi operasional yang sesuai. Metode yang digunakan pada penelitian ini adalah stacking machine learning model. Stacking terdiri dari dua level, dimana pada penelitian ini level 0 (base learner) menggunakan algoritma Naive Bayes, Logistic Regression, dan Gradient Boosting Machine sedangkan pada level 1 (meta learner) menggunakan algoritma Random Forest. nilai akurasi klasifikasi stacking model dan gradient boosting machine memiliki nilai akurasi tertinggi sebesar 0.87. Nilai sensitivitas stacking model sebesar 0.86 dan merupakan nilai sensitivitas tertinggi yang berarti klasifikasi stacking model sangat tepat memprediksi konsumen dalam pembatalan pemesanan hotel. Nilai Spesifisitas gradient boosting machine sebesar 0.88 dan merupakan nilai spesifisitas tertinggi yang berarti klasifikasi gradient boosting machine sangat tepat memprediksi konsumen yang tidak melakukan pembatalan pemesanan hotel. Klasifikasi naive bayes dan logistic regression memiliki nilai akurasi, sensitivitas, spesifisitas, presisi yang tidak tinggi.
Kata kunci: Stacking Model, Base Learner, Meta Learne
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
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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