15 research outputs found

    The memory kernel of velocity autocorrelation function on a NiZr-tiquid: theory and simulation

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    Based on sjtigren und sjolander's Mode-coupling(MC)-Model, we have re- formulated and calculated the memory kernel (MK) of the velocity autocorre- lation function (vACF)on a Ni6.2Zrs.3-liquid. Reformulating means here that we have constructed the memory kernel of vACF for our binary system, in- stead of one for one atomic system of the Sjtigren und Sjolander's model. The data required for the theoretical calculations have been obtained from molec- ular dynamics (MD) simulations. The theoretical results then are compared with those directly obtained from computer simulation. we found, although it exists a qualitative agreement between theoretical predictions and simula- tion results, that quantitatively there is an deviations between both results, especially for Zr-subsystem

    EVALUASI KINERJA DOSEN TETAP MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS DAN WEIGHTED PRODUCT

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    STMIK Balikpapan meningkatkan kualitas dari sumber daya manusia dalam bidang TI yaitu dengan menjaga kualitas dari tenaga pendidik yang menjadi tiang utama dari sebuah perguruan tinggi. Demi menjaganya kualitas dari tenaga pendidik dilakukan suatu sistem pendukung keputusan dengan menggunakan metode yang memanfaatkan perhitungan bobot serta hasil akhir berupa perangkingan untuk tenaga pendidik yang setiap kriterianya berdasarkan acuan yang diberlakukan di STMIK Balikpapan. Sistem pendukung keputusan yang akan digunakan yaitu Analytical Hierarchy Process (AHP) untuk menghitung bobot dari kriteria yang terdiri dari 9 kriteria dan bobot yang telah didapatkan dari perhitungan AHP dari masing masing kriteria dihitung dengan nilai pada penilaian menggunakan metode Weighted Product (WP) yang digunakan untuk melakukan perangkingan pada setiap alternatif–alternatif yang ada sehingga membantu dalam melakukan proses penentuan kualitas kinerja dosen tetap yang berada di STMIK Balikpapan. Hasil perhitungan pada 9 kriteria yang diterapkan memiliki konsistensi indeks dibawah 0,1 yaitu sebesar 0, 057 sehingga bobot dari masing–masing kriteria dinggap konsisten

    IT GOVERNANCE AUDIT AT PT PERUSAHAAN GAS NEGARA USING COBIT FRAMEWORK

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    The use of information and communication technology in a company gives an important contribution for the achievement of business objectives. PT Perusahaan Gas Negara, especially in the Business Solutions and Services Operations (BSSO), plays a significant role in the utilization of information and communication technology assets to PT Perusahaan Gas Negara. It takes a good IT governance for BSSO to improve the efficiency and effectiveness of IT usage. Audit of IT governance maturity using COBIT 4.1. Maturity model level used to determine the maturity level of IT usage in the enterprise with a scale of 0 (non-existent) to 5 (optimized). This study focused on two domains namely Plan and Organise (PO) and Monitor and Evaluate (ME) model to measure the maturity level of IT maturity levels in PT Perusahaan Gas Negara. From this study, the results of the maturity level domain PO is 3.13 and ME is 2.98, it can be given the conclusion that the maturity level of IT governance at PT PGN is in level 3 (defined). At this level means that all the procedures in the company are standardized and documented, but the company is still not able to detect the deviations that have occurred

    Reviewer Atas nama Achmad Benny Mutiara Q.N.

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    Pengujian Algoritma Clustering Affinity Propagation dan Adaptive Affinity Propagation terhadap IPK dan Jarak Rumah

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    Clustering which is a method to classify data easily is used for a purpose of looking at the correlation among data attributes. Clustering is also a data point grouping based on similarity value to determine the cluster center. Affinity Propagation (AP) and Adaptive Affinity Propagation (Adaptive AP) are clustering algorithms that produce number of cluster, cluster members and exemplar of each cluster. This research is conducted to find out a more effective algorithm when clustering data. Besides, to know the correction offered by Adaptive AP Algorithm which is the developed form of AP Algorithm, the researcher implemented and tested both algorithms by using Matlab R2013a 8.10 with 250 data taken from students’ GPA and the distance from their houses to campus. The analysis of test result application from both algorithms shows that the best algorithm is Adaptive AP because it produces optimal clustering. Another result is no correlation between GPA and home distance

    A Preference Model on Adaptive Affinity Propagation

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    In recent years, two new data clustering algorithms have been proposed. One of them isAffinity Propagation (AP). AP is a new data clustering technique that use iterative message passing and consider all data points as potential exemplars. Two important inputs of AP are a similarity matrix (SM) of the data and the parameter ”preference” p. Although the original AP algorithm has shown much success in data clustering, it still suffer from one limitation: it is not easy to determine the value of the parameter ”preference” p which can result an optimal clustering solution. To resolve this limitation, we propose a new model of the parameter ”preference” p, i.e. it is modeled based on the similarity distribution. Having the SM and p, Modified Adaptive AP (MAAP) procedure is running. MAAP procedure means that we omit the adaptive p-scanning algorithm as in original Adaptive-AP (AAP) procedure. Experimental results on random non-partition and partition data sets show that (i) the proposed algorithm, MAAP-DDP, is slower than original AP for random non-partition dataset, (ii) for random 4-partition dataset and real datasets the proposed algorithm has succeeded to identify clusters according to the number of dataset’s true labels with the execution times that are comparable with those original AP. Beside that the MAAP-DDP algorithm demonstrates more feasible and effective than original AAP procedure

    Component-connected Feature for Signature Identification

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    A signature is the oldest security techniques to verify the identification of a person. This is due to every person has a different signature and each signature has the characteristic physiological and behavior. There are two kinds of signature such as offline and online signatures used to verify someone identity. Offline signatures were used in this study because offline signature does not have dynamic features such as an online signature. This study proposed an identification system of offline signature by using k-NN based on the features that were stored in the database. The proposed identification system consists of preprocessing, feature extraction and verification stages. We collected the data samples from 10 persons. Each person wrote 10 signatures. Total data was 100 signatures. The first stage used in this study was preprocessing such as noise removal, binarization, skeleton, and cropping.  The second stage was feature extraction. Feature extraction had some important information such as height-width ratio, the ratio of the density of signatures, edge distance ratio, the ratio of the number and proximity of the column, and the number of connected components in the signature. That information was stored in a separate database. We separated 10 signatures of each person into 6 signatures as data sample and 4 signature as test data. We verified 40 signatures of test data from 10 persons using k-NN. It is shown that from 40 signatures used in our test data, 28 signatures were correctly identified and 12 signatures belong to others

    Automated hierarchical classification of scanned documents using convolutional neural network and regular expression

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    This research proposed automated hierarchical classification of scanned documents with characteristics content that have unstructured text and special patterns (specific and short strings) using convolutional neural network (CNN) and regular expression method (REM). The research data using digital correspondence documents with format PDF images from pusat data teknologi dan informasi (technology and information data center). The document hierarchy covers type of letter, type of manuscript letter, origin of letter and subject of letter. The research method consists of preprocessing, classification, and storage to database. Preprocessing covers extraction using Tesseract optical character recognition (OCR) and formation of word document vector with Word2Vec. Hierarchical classification uses CNN to classify 5 types of letters and regular expression to classify 4 types of manuscript letter, 15 origins of letter and 25 subjects of letter. The classified documents are stored in the Hive database in Hadoop big data architecture. The amount of data used is 5200 documents, consisting of 4000 for training, 1000 for testing and 200 for classification prediction documents. The trial result of 200 new documents is 188 documents correctly classified and 12 documents incorrectly classified. The accuracy of automated hierarchical classification is 94%. Next, the search of classified scanned documents based on content can be developed

    TESTING IMPLEMENTASI WEBSITE REKAM MEDIS ELEKTRONIK OPELTGUNASYS DENGAN METODE ACCEPTANCE TESTING

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    Website rekam medis elektronik OpeltGunaSys dibuat guna mendukung Indonesia Sehat 2015. Website ini punya enam kategori formulir hasil pemeriksaan dokter seperti observasi, riwayat, eksaminasi, investigasi,evaluasi dan instruksi. Berguna untuk menuliskan hasil rekam medis secaraonline pada http://opeltgunasys.org. Website ini dikelola oleh administrator, selain itu ada dokter, staf, laboran dan pasien sebagai user. Setiap user punya hak akses berbeda-beda saat menggunakan sistem. Dalam penelitian ini, digunakan usability principles untuk mengetahui seberapa mudah website ini digunakan, lalu penelitian ini juga ditunjang Standar Operasional Prosedur untuk memberikan panduan bagi user ketika menggunakan sistem. Tujuan penelitian ini adalah menemukan masalah, mengevaluasi kesesuaian sistem dengan kebutuhan bisnis, mengetahui apakah modul panduan website ini sesuai dengan kondisi saat user menggunakan sistem dan mendapatkan masukan tentang sistem. Acceptance test ini melibatkan tiga user dari instansi kesehatan danterdapat masukan dari user yang diharapkan berguna demi kebaikan website ini kedepannya. Sehingga hal ini dapat menjadi pendukung untuk diwujudkannya program Indonesia Sehat 2015

    PEMGEMBANGAN APLIKASI BIBTEX UNTUK PENYIMPANAN INFORMASI BIBLIOGRAFI

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    Kegiatan penelitian membutuhkan informasi yang banyak. Informasi dibutuhkan untuk mengikuti perkembangan penelitian sejenis yang telah dilakukan, sehingga tidak terjadi penelitian yang berulang-ulang untuk masalah yang sama. Di dalam melakukan pencarian informasi tersebut yang berasal dari Indonesia sangatlah jarang. Walaupun telah ada yang menyediakannya tetapi bersifat internasional. Penelitian ini dilakukan untuk mengembangkan suatu aplikasi web yang dapat menyimpan informasi bibliografi dalam sebuah berkas yang berformat bibtex. Di dalam aplikasi web tersebut terdapat fasilitas untuk mengkonversi berkas bibtex menjadi RDF. Selain itu terdapat juga informasi mengenai bibliografi dari para penulis baik penulis buku maupun penulis artikel ilmiah.Kata kunci : Bibtex, XML, ZK, Java, RDF, Bibliograf
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