1,720,961 research outputs found
System Engineering for Online Monitoring and Early Warning of Water Environment
No full textMeasurement activity usually performed at a time or in a certain time period. In the case of measurements at one time, measurements manually by visiting the location of measurements, take measurements and write them down, then left the location is not a problem. However, measurements made within a certain period of time or year would be verydraining, costly, and time consuming if perfomed manually. Thus, design and implementation of embedded system for online monitoring and early warning of water environment is proposed. The system consists of two parts i.e. monitoring stations (site) and monitoring center (server). A monitoring station is an embedded system that has interface with a logger. Monitoring center is a computer that runs the service that gets the data sent by the monitoring stations, process it and put it into the database. Monitoring center also runan http service to display data acquired from monitoring stations to end users both in tabular or graphical view . The system can perform continuous measurements and its results can be monitored remotely
WebGIS-based Decision Support System for Estimating the Selling Value of Land Tax Objects in Indonesia
Full text linkCurrently, people get data and information about the Tax Object Selling Value (Nilai Jual Objek Pajak [NJOP]) through their domicile village authority. NJOP is the base for imposition of PBB P2 which is obtained from the average value of the sale transaction conducted fairly. However, if there were no sale or purchase transactions occurred, the price of the object is determined by other alike objects, or new approval values, or NJOP. The problem is that the village party cannot correct the NJOP that have been issued by the Regional Revenue Agency (Badan Pendapatan Daerah) if there is disagreement in the NJOP determination, e.g., the position of an object is closer to the city center but its NJOP is smaller than other objects that are further away. In order to determine a more accurate NJOP, another approach to estimation is needed. The purpose of this study is to develop a decision support system for estimating fairly NJOP. The method used is the combination of the Von Thunen model, the Analytical Hierarchy Process (AHP) and land information overlay based on position selection using four criteria, namely: (1) land use, (2) slope or topography, (3) road function and classification and (4) crowd center or central business district (CBD). The system was developed in a form of a WebGIS application. The result shows that the estimation of NJOP in Bubulak Urban Village area are considered close to the local prices. This system is expected to make it easier for related parties to make decisions, determination, uniformity, justice, and identify various problems regarding land prices in the community, so that they can quickly determine the NJOP more accurately
SISTEM PAKAR IDENTIFIKASI KERUSAKAN SEPEDA MOTOR SUZUKI SATRIA F150 DENGAN TEOREMA BAYES
Full text linkSepeda motor merupakan jenis kendaraan beroda dua yang digerakkan oleh mesin. Sepeda motor terkadang mengalami kerusakan yang disebabkan oleh komponen yang telah aus, pemeliharaan yang tidak teratur, atau kesalahan pemakaian. Kerusakan tersebut ada yang bersifat ringan, sedang, atau berat. Sistem pakar identifikasi kerusakan sepeda motor Suzuki Satria F150 dibangun untuk dapat membantu mengidentifikasi kerusakan dan menawarkan solusi yang harus dilakukan untuk mengatasi kerusakan tersebut. Teorema Bayes digunakan sebagai model untuk pendugaan bagian atau komponen yang rusak. Metode inferensi backward chaining digunakan untuk menelusuri penyebab kerusakan sesuai dengan gejala-gejala yang diamati. Sistem pakar diimplementasikan dalam bentuk aplikasi berbasis web. Sistem pakar ini selain berguna bagi mekanik bengkel sepeda motor untuk mendukung pekerjaannya, juga bermanfaat bagi pengguna motor Suzuki Satria F150 sebagai alat bantu identifikasi awal kerusakan sehingga dapat diambil tindakan lebih lanjut
PERBANDINGAN METODE DEEP LEARNING DAN MACHINE LEARNING UNTUK KLASIFIKASI (UJICOBA PADA DATA PENYAKIT KANKER PAYUDARA)
Full text linkPERBANDINGAN METODE DEEP LEARNING DAN MACHINE LEARNING UNTUK KLASIFIKASI (UJI COBA PADA DATA PENYAKIT KANKER PAYUDARA). Penyebab kematian utama di seluruh dunia merupakan penyakit kanker, salah satunya adalah kanker payudara. Faktor penentu penyakit tersebut termasuk kategori ganas atau jinak bisa dilihat dari sembilan faktor utama berdasarkan ciri kanker tersebut. Tujuan dari penelitian ini adalah mendapatkan perbandingan metode yang paling akurat terhadap pengklasifikasian penyakit kanker payudara dan melihat selisih nilai mean square error (MSE) dari metode deep learning dan machine learning serta pencocokan hasil klasifikasi kedua metode dengan pernyataan klasifikasi yang sudah ada sehingga didapatkan nilai perbandingan metode yang paling akurat. Data yang digunakan pada penelitian ini diambil dari UCI Edu, dengan data latih sebanyak 546 data dan data uji sebanyak 137 data. Dari proses pengklasifikasian menggunakan FFNN pada machine learning dan RBM pada deep learning, maka dapat dilihat ada empat (2.92%) data kanker payudara pada proses FFNN yang tidak memenuhi class klasifikasi, sedangkan data yang tidak memenuhi class klasifikasi pada proses RBM ada dua (1.46%) data. Dalam kasus klasifikasi penyakit kanker payudara, akurasi metode machine learning lebih kecil dibandingkan dengan akurasi deep learning dan hasil hipotesa menggunakan uji t menunjukkan bahwa nilai signifikansi (2-tailed) lebih kecil dari α = 0.05 yaitu sebesar 8,68844E-16 yang menandakan bahwa deep learning lebih baik dibandingkan machine learning. Dengan akurasi metode machine learning sebesar 97.0803% dan deep learning sebesar 98.5401%. Nilai MSE pada pengklasifikasian menggunakan FFNN adalah sebesar 0.0814, sedangkan pada RBM sebesar 0.058
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
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