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Contact Name
santi astawa
Contact Email
santi.astawa@unud.ac.id
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jik@unud.ac.id
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INDONESIA
Jurnal Ilmu Komputer
Published by Universitas Udayana
ISSN : 19795661     EISSN : 2622321X     DOI : -
Core Subject : Science, Education,
JIK is a peer-reviewed scientific journal published by Informatics Department, Faculty of Mathematics and Natural Science, Udayana University which has been published since 2008. The aim of this journal is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of computer science. JIK is consistently published two times a year in April and September. This journal covers original article in computer science that has not been published. The article can be research papers, research findings, review articles, analysis and recent applications in computer science.
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Articles 6 Documents
Search results for , issue "Vol 6 No 2: September 2013" : 6 Documents clear
OTOMATISASI PERBANDINGAN PRODUK BERDASARKAN BOBOT FITUR PADA TEKS OPINI Yufis Azhar; Agus Zainal Arifin; Diana Purwitasari
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Proses otomatisasi perbandingan produk berdasarkan teks opini dapat dilakukan dengan caramengekstrak fitur yang dimiliki produk tersebut. Fitur-fitur inilah yang umumnya dinilai kemudian digunakanuntuk membandingkan suatu produk dengan produk yang lain. Banyak peneliti yang menggunakan kamus kataopini untuk mengekstrak fitur tersebut. Akan tetapi hal tersebut tidak efektif karena sangat bergantung padakelengkapan kamus kata yang digunakan. Oleh karena itu, dalam penelitian ini diusulkan suatu metode untukmembandingkan produk berdasarkan bobot fitur produk tanpa harus menggunakan kamus kata opini yanglengkap. Caranya adalah dengan menjumlahkan bobot dari fitur-fitur unggul yang dimiliki oleh suatu produkuntuk mendapatkan skor tiap produk. Hasil yang didapat menunjukkan bahwa penerapan metode tersebut dapatmeningkatkan akurasi dari proses perbandingan dua buah produk sebesar 81% dari pada metode sebelumnyayang hanya 71%.
METODE WEIGHTED MAXIMUM CAPTURING UNTUK KLASTERISASI DOKUMEN BERBASIS FREQUENT ITEMSETS Gede Aditra Pradnyana; Arif Djunaidy
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Document clustering based on frequent itemsets is one of the new document clustering method that can be usedto overcome the problem of high-dimensional space of the document being clustered. Maximum capturingtechnique is one document clustering algorithm based frequent itemsets that can generate better clusteringquality compared to those produced by other similar algorithms. The maximum capturing technique still has thelack or weakness, ie: not accounting for the weight of a word (item) in the calculation of frequent itemsets whenthe document similarity and the cluster formation process does not take into account the global information ofthe cluster previously formed. In this research developed a new method for clustering documents based frequentitemset namely weighted maximum capturing method (WMC), to correct deficiencies maksimum capturingaccuracy so that the quality of document clustering results can be improved. In the weighted maximumcapturing method, document similarity is computed by combining the cosine similarity method and Jaccardcoefficient based on the same number of frequent itemsets owned so that the weight of items in itemsets can betaken into account, while in the process of constructing cluster adapted single linkage agglomerativehierarchical clustering algorithm. Experimental results show the value of F-measure and purity of WMC methodis better than the earlier method, that is equal to 0.723 for the F-measure with improvement ratio of 2.8% and apurity value of 0.73 with improvement ratio 3.3%.
PEMILIHAN NODE TETANGGA YANG HANDAL DENGAN MEMPERHITUNGKAN SIGNAL STRENGTH DAN LINK QUALITY PADA ZONE ROUTING PROTOCOL DI LINGKUNGAN MANET Ida Bagus Ary Indra Iswara; Waskitho Wibisono
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Zone Routing Protocol (ZRP) is a hybrid routing protocol on MANET, because the routing protocol isbase on two protocols, namely IntrAzone Routing Protocol (IARP) and IntErzone Routing Protocol (IERP).Through IARP, each node identifies distance to all nodes in its routing zone. Although the network is very large,the update process is only distribute locally in its routing zone only and not the whole network. While IERPprotocol is responsible to find a route to a node that is located outside the zone. The selection of neighboringnodes completely done by Neighbor Discovery Protocol (NDP), which is performe by the node selection NDP issending beacons broadcast message. NDP only use TTL to decide whether the neighboring nodes in broken ormaintained.In this research, the method of signal strength based link-sensing stability adaptation into the work processof the NDP. This method works based on the signal strength of a node. Signal strength of a node are reliableif the node does not exceed the predetermined threshold value. Reliable nodes that will be stored in theneighbor table and will be a reference to the IARP routing process. Nodes are not reliable will be disconnectedand will not send beacons at the message again.The selection of reliable neighbor nodes by calculating signal strength and link quality is able to improvethe performance of ZRP routing protocols. Protocols tested in scenarios designed by the wide variationarea. The test results showed an increase of 4:13 kbps increase in throughput, a decrease of 9.98 ms e2e delayand routing overhead decreased by 3.83%.
MEKANISME PEMILIHAN MPR DENGAN CONGESTION DETECTION DALAM OLSR PADA MANET I Nyoman Buda Hartawan; Waskitho Wibisono
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

MANET (Mobile Ad-hoc Network) is a collection of mobile nodes which comunicate each others usingwireless network. MANET does not have fixed network infrastructure. OLSR (Optimized Link State Routing) is arouting protocol in MANET. In OLSR there is a selection of neighbor nodes as MPR (Multi Point Relay) forforwading packet data from source to destination. MANET characteristics which shared medium to comunicatewirelessly, causing congestion vulnerable occurs in intermediate node when packet data transmission fromsource to destination. The congestion that occurs in network can lead to high packet loss and long delay, thuscausing reduction of network performance. This study aims to perform the selection of MPR in OLSR withcongestion detection methods in MANET. Results of the study showed that MPR selection with congestiondetection in OLSR can improve packet delivery ratio and network throughput when packet transmission fromsource to destination. This study simulated on Network Simulator version 2 (NS-2).
PENDEKATAN POSITIONAL TEXT GRAPH UNTUK PEMILIHAN KALIMAT REPRESENTATIF CLUSTER PADA PERINGKASAN MULTI-DOKUMEN I Putu Gede Hendra Suputra; Agus Zainal Arifin; Anny Yuniarti
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Coverage and saliency are major problems in Automatic Text Summarization. Sentence clusteringapproaches are methods able to provide good coverage on all topics, but the point to be considered is theselection of important sentence that can represent the cluster’s topic. The salient sentences selected asconstituent to the final summary should have information density so that can convey important informationcontained in the cluster. Information density from the sentence can be mined by extracting the sentenceinformation density (SID) feature that built from positional text graph approach of every sentence in the cluster.This paper proposed a cluster representative sentence selection strategy that used the positional text graphapproach in multi-document summarization. There are three concepts that used in this paper: (1) sentenceclustering based on similarity based histogram clustering, (2) cluster ordering based on cluster importance and(3) representative sentence selection based on sentence information density feature score. The candidatesummary sentence is a sentence that has greatest sentence information density feature score of a cluster. Trialsconducted on task 2 DUC 2004 dataset. ROUGE-1 measurement was used as performance metric to comparethe use of SID feature with other method namely Local Importance and Global Importance (LIGI). Test resultshowed that the use of SID feature was successfully outperform LIGI method based on ROUGE-1 values wherethe greatest average value of ROUGE-1 that achieved by SID features is 0.3915.
PENJADWALAN ALOKASI JOB BERBASIS METODA HEURISTIK PADA LINGKUNGAN GRID INDONESIAN EDUCATION GRID I Nyoman Rudy Hendrawan; Waskitho Wibisono
Jurnal Ilmu Komputer Vol 6 No 2: September 2013
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Scheduling mechanism on a grid system became one of important factor in measuring performance of thegrid system. Moreover, building a grid system which is used for experiment or research is time and cost consuming,and then a grid system simulation can be an alternative. In a previous study has been conducted by designing andsimulating of the grid system which is called Indonesian Education Grid (IndoEdu-Grid). A random allocation jobscheduling method was used in the previous study (the method is called UD-IndoEdu-Grid in the next section).Therefore, in this paper we proposed an allocation job scheduling based on heuristic method called TS-IndoEdu-Grid, and thus expected to improve the performance of the IndoEdu-Grid environment. Experiment results show thatby using the TS-IndoEdu-Grid method could reduce makespan by 20% to UD-IndoEdu-Grid. In flowtime parameterthe TS-IndoEdu-Grid method also produces 94% smaller than the UD-IndoEdu-Grid method

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