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    IMPLEMENTASI SISTEM INFORMASI GEOGRAFIS DAERAH WISATA DI WILAYAH KABUPATEN GROBOGAN BERBASIS WEB.

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    Laporan Akhir ini berkaitan dengan SIG dengan memanfaatkan teknologi internet yang sering disebut dengan sistem informasi Geografis Berbasis Web

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    Optimasi Convolutional Neural Networks untuk Deteksi Kanker Payudara menggunakan Arsitektur DenseNet

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    Breast cancer is a disease commonly suffered by women worldwide, ranking as the second-largest disease burden. In response to the urgent need for improved detection accuracy, Convolutional Neural Networks (CNNs) promise significant advancements. The objective of this research is to optimize the use of CNNs with the DenseNet architecture for breast cancer detection. The study employs quantitative methods, leveraging Deep Learning through CNNs. Mammography data is sourced from Kaggle, specifically the “Breast Histopathology Images” dataset. This dataset comprises 90,000 digital mammography images, which are preprocessed and divided proportionally for training, validation, and model testing. Research variables encompass CNN model parameters, training techniques, and the integration of imaging modalities to enhance breast cancer detection performance. The research focuses on processed mammography data, with accuracy and image quality as key evaluation metrics for breast cancer sample identification. Our findings demonstrate that the DenseNet architecture within CNNs achieves an impressive 92% accuracy in breast cancer detection. This remarkable performance signifies success in enhancing image quality and class prediction, aligning with the DenseNet architecture’s flow diagram. Ultimately, these results contribute significantly to effective breast cancer diagnosis by optimizing CNNs with the DenseNet architecture to improve image quality during breast cancer sampling

    Variations on the Author

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    “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

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    We 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

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    We 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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We 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

    IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS POLA PEMBELIAN KONSUMEN PADA TOSERBA YUSUF SEMARANG

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    Pada aktivitas jual beli barang atau jasa, data transaksi selalu tercatat sebagai bukti pembelian, namun data yang ada tidak dimanfaatkan secara optimal oleh Toserba Yusuf. Data tersebut memiliki potensi untuk diolah guna memberikan informasi bermanfaat yang dapat meningkatkan nilai penjualan bagi para pelaku bisnis. Salah satu tantangan yang sering dihadapi oleh Toserba Yusuf adalah kehabisan stok produk tertentu yang dibutuhkan oleh konsumen. Untuk mengatasi hal ini, biasanya diperlukan waktu yang cukup lama karena toko harus mendata barang yang habis terlebih dahulu setelah itu baru melakukan restok barang untuk menyediakan kembali persediaan. Untuk mengatasi permasalahan yang ada, penelitian ini mengembangkan aplikasi Data Mining membantu dalam mengidentifikasi kebiasaan pembelian konsumen. Tujuan utama penelitian adalah mencari informasi mengenai produk yang paling sering terjual bersamaan. Hal ini bertujuan untuk memungkinkan pemilik toko untuk mengantisipasi kebutuhan stok produk di masa mendatang. Penelitian ini menggunakan algoritma apriori untuk memudahkan dalam mengolah data, selain itu penelitian ini memanfaatkan association rule untuk menemukan kombinasi antar item dalam dataset yang memenuhi nilai support dan confidence yang telah ditetapkan sebelumnya. Hasil penelitian ini menunjukkan bahwa kombinasi pembelian dan penjualan 2 itemset barang berbeda secara bersamaan. Hasil pengujian yang memperhitungkan keakuratan dengan menggunakan lift ratio sebagai persentase menghasilkan beberapa aturan. Salah satunya adalah jika pelanggan membeli kentang goreng dengan lift ratio yang tinggi, maka ada kemungkinan bahwa pelanggan juga akan membeli telur dengan tingkat confidence sebesar 0,19, support 0,039, dan lift ratio 1,308. Hal ini membuktikan bahwa algoritma apriori dapat membantu dalam menganalisa pola pembelian konsumen
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