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Jurnal Ilmu Komputer dan Informasi

JIKI
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Published by Universitas Indonesia

ISSN : 20887051 EISSN : 25029274 DOI : 10.21609

Core Subject : Science,

Computer Science & IT Library & Information Science

Jurnal Ilmu Komputer dan Informasi is a scientific journal in computer science and information containing the scientific literature on studies of pure and applied research in computer science and information and public review of the development of theory, method and applied sciences related to the subject. Jurnal Ilmu Komputer dan Informasi is published by Faculty of Computer Science Universitas Indonesia. Editors invite researchers, practitioners, and students to write scientific developments in fields related to computer science and information. Jurnal Ilmu Komputer dan Informasi is issued 2 (two) times a year in February and June. This journal contains research articles and scientific studies. It can be obtained directly through the Library of the Faculty of Computer Science Universitas Indonesia.

Arjuna Subject : -

Articles 247 Documents

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AN EVALUATION OF VALIDATION CRITERIA ON INTELLIGENT SYSTEM VALIDATION PROCESS Dyah Sulistyowati Rahayu; Siti Rochimah
Jurnal Ilmu Komputer dan Informasi Vol 6, No 1 (2013): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

In the software development cycle, validation is the important stage which is held in final stage especially in intelligent system. Validation obtains the validity, credibility and trustworthy of the system. It is needed to ensure that the intelligent system has same manner as human expertsâ€™. Whilst with the importance of validation stage, determining the validation criteria is also important. This paper presents the evaluation of validation criteria which is commonly used in intelligent system validation process. The evaluation is carried out by reviewing the literature of intelligent system validation process. The result shows that the validation criteria have its own characteristic so it requires for understanding the validation criteria characteristics, purposes of validation and also the intelligent system itself to hold validation process.

EAODV: A*-BASED ENHANCEMENT AD-HOC ON DEMAND VECTOR PROTOCOL TO PREVENT BLACK HOLE ATTACKS Khalil I Ghathwan; Abdul Razak Yaakub; Rahmat Budiarto
Jurnal Ilmu Komputer dan Informasi Vol 6, No 2 (2013): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Black hole attack is an attack where a node that responds to RREQ from the source node by replying a fake freshness information and false hop count. The black hole nodes do not respond to distributed co-operation in routing protocol to absorb all the packets, as a result, the network performance will drop. Most previous works are focused on anomaly detection through dynamic trusted of the neighbouring nodes. We find out that the internal comparisons take a long time. This loss can be shortened by changing the routing mechanism. We propose an enhancement of AODV protocol, named EAODV, that is able to prevent black hole attacks. The EAODV can find a shortest path of routing discovery using A* heuristic search algorithm. Values of hop count and estimate time to reach the destination node are used as input in the heuristic equation and one-way hash function is used to make a secure value and then to casting it to all neighbouring nodes. Experiments were conducted in NS2 to simulate EAODV in different running time with and without black hole nodes. The EAODV performance results are indicated better in terms Packet loss and Average End-to-End delay.

SISTEM ONTOLOGI E-LEARNING BERBASIS SEMANTIC WEB Bernard Renaldy Suteja; Suryo Guritno; Retantyo Wardoyo; Ahmad Ashari
Jurnal Ilmu Komputer dan Informasi Vol 2, No 1 (2009): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

E-learning content being a barrier for e-learning is no longer true on todays Internet. The current concerns are how to effectively annotate and organize the available content (both textual and non-textual) to facilitate effective sharing, reusability and customization. In this paper, we explain a component-oriented approach to organize content in an ontology. We also illustrate our 3-tier e-learning content management architecture and relevant interfaces. We use a simple yet intuitive example to successfully demonstrate the current working prototype which is capable of compiling personalized course materials. The e-learning system explained here uses the said ontology.

RBF KERNEL OPTIMIZATION METHOD WITH PARTICLE SWARM OPTIMIZATION ON SVM USING THE ANALYSIS OF INPUT DATA’S MOVEMENT Rarasmaya Indraswari; Agus Zainal Arifin
Jurnal Ilmu Komputer dan Informasi Vol 10, No 1 (2017): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

SVM (Support Vector Machine) with RBF (Radial Basis Function) kernel is a frequently used classification method because usually it provides an accurate results. The focus about most SVM optimization research is the optimization of the the input data, whereas the parameter of the kernel function (RBF), the sigma, which is used in SVM also has the potential to improve the performance of SVM when optimized. In this research, we proposed a new method of RBF kernel optimization with Particle Swarm Optimization (PSO) on SVM using the analysis of input data’s movement. This method performed the optimization of the weight of the input data and RBF kernel’s parameter at once based on the analysis of the movement of the input data which was separated from the process of determining the margin on SVM. The steps of this method were the parameter initialization, optimal particle search, kernel’s parameter computation, and classification with SVM. In the optimal particle’s search, the cost of each particle was computed using RBF function. The value of kernel’s parameter was computed based on the particles’ movement in PSO. Experimental result on Breast Cancer Wisconsin (Original) dataset showed that this RBF kernel optimization method could improve the accuracy of SVM significantly. This method of RBF kernel optimization had a lower complexity compared to another SVM optimization methods that resulted in a faster running time.

SIMULATION OF QUANTUM SEARCH ALGORITHM Rina Refianti; Achmad Benny Mutiara
Jurnal Ilmu Komputer dan Informasi Vol 6, No 2 (2013): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

The rapid progress of computer science has been accompanied by a corresponding evolution of computation, from classical computation to quantum computation. As quantum computing is on its way to becoming an established discipline of computing science, much effort is being put into the development of new quantum algorithms. One of quantum algorithms is Grover's algorithm, which is used for searching an element in an unstructured list of N elements with quadratic speed-up over classical algorithms. In this work, Quantum Computer Language (QCL) is used to make a Grover's quantum search simulation in a classical computer document.

APLIKASI JARINGAN KOMUNIKASI ROBOT MULTIHOP TERDISTRIBUSI PADA LINGKUNGAN STATIS TERBATAS: IMPLEMENTASI, SIMULASI DAN ANALISIS PADA KASUS ROBOT LEGO MINDSTORM NXT Wisnu Jatmiko; A. A. Krisnadhi; R. M. Mardian; N. W. Pambudi
Jurnal Ilmu Komputer dan Informasi Vol 2, No 1 (2009): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Paper ini akan membahas tahap awal (prototipe) pengembangan jaringan komunikasi-robot multihop terdistribusi, yaitu suatu aplikasi yang diharapkan dapat dimanfaatkan pada lingkungan yang minim infrastruktur dan fasilitas komunikasi. Pada bagian awal paper disebutkan kondisi yang dapat menerapkan aplikasi jaringan komunikasi multihop ini, yaitu pada daerah bencana alam yang mengalami kerusakan sarana komunikasi, pada daerah terpencil karena faktor alam yang sulit untuk diadakan fasilitas komunikasi, ataupun daerah berbahaya untuk didatangi manusia ataupun kawasan konflik dan peperangan. Salah satu karakteristik yang diharapkan dari aplikasi ini adalah proses penyebaran informasi secara cepat dan mudah, bahkan walaupun tidak tersedia infrastruktur memadai sebelumnya. Selain itu, sistem ini bersifat terdistribusi sehingga diharapkan dapat memberikan beberapa keuntungan, baik saat diimplementasikan maupun kinerja di lapangan nantinya. Paper ini kemudian membahas pengembangan algoritma penyelesaian masalah, yang dilanjutkan dengan verifikasi dan analisis pada level simulasi perangkat lunak. Selanjutkan, algoritma ini diterapkan pada level simulasi perangkat keras dengan menggunakan modul robot Lego Mindstorm NXT. Untuk penyederhanaan masalah, pada tahap ini lingkungan yang digunakan masih bersifat statis dan terbatas sebagai salah satu asumsi.

Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement Vina Ayumi; L.M. Rasdi Rere; Mohamad Ivan Fanany; Aniati Murni Arymurthy
Jurnal Ilmu Komputer dan Informasi Vol 10, No 2 (2017): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Metaheuristic algorithm is a powerful optimization method, in which it can solve problemsby exploring the ordinarily large solution search space of these instances, that are believed tobe hard in general. However, the performances of these algorithms signicantly depend onthe setting of their parameter, while is not easy to set them accurately as well as completelyrelying on the problem's characteristic. To ne-tune the parameters automatically, manymethods have been proposed to address this challenge, including fuzzy logic, chaos, randomadjustment and others. All of these methods for many years have been developed indepen-dently for automatic setting of metaheuristic parameters, and integration of two or more ofthese methods has not yet much conducted. Thus, a method that provides advantage fromcombining chaos and random adjustment is proposed. Some popular metaheuristic algo-rithms are used to test the performance of the proposed method, i.e. simulated annealing,particle swarm optimization, dierential evolution, and harmony search. As a case study ofthis research is contrast enhancement for images of Cameraman, Lena, Boat and Rice. Ingeneral, the simulation results show that the proposed methods are better than the originalmetaheuristic, chaotic metaheuristic, and metaheuristic by random adjustment.

TERRAIN: FETAL GROWTH TELEHEALTH SYSTEM BASED ON 2D FETAL HEAD IMAGE USING RANDOMIZED HOUGH TRANSFORM Robeth Rahmatullah; Ikhsanul Habibie; Petrus Mursanto; Sani Muhammad Isa
Jurnal Ilmu Komputer dan Informasi Vol 7, No 1 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Abstract Intrauterine growth restriction (IUGR) is one of many fetal abnormalities, which has high contribution on maternal mortality rate and perinatal mortality rate in Indonesia. Apparently, IUGR impact can be reduced if only the symptoms are detected earlier and the correct treatment is applied. However, fetal growth detection and monitoring process in Indonesia is obstructed because the number of physicians is very limited and ultrasonography (USG) devices are expensive. Moreover, both the physicians and USG devices are only available in big cities. To answer those problems, this research proposed an intelligent system that can provide fetal growth telemonitoring in rural areas. This system consists of three components: portable USG device, mobile application which is developed using Android operating system, and server application which is developed using Django. The main feature of this system is automatic fetal head parameter detection and its ability to operate in the limited internet access environment. In this system, automatic fetal head parameter detection uses RHT method to approximate fetal headâ€™s ellipse shape. Experiment result shows that RHT detection ability with âˆ†ellipse average of 79.564 and running time average of 0.373 second.

DIAGNOSIS GANGGUAN SISTEM URINARI PADA ANJING DAN KUCING MENGGUNAKAN VFI 5 Agus Buono; Dhany Nugraha Ramdhany; Aziz Kustiyo; Ekowati Handharyani
Jurnal Ilmu Komputer dan Informasi Vol 2, No 2 (2009): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Sistem urinari hewan dapat dibagi menjadi 2 bagian yaitu sistem urinari bagian atas dan sistem urinari bagian bawah. Ginjal yang merupakan bagian dari sistem urinari memiliki 2 fungsi penting, yaitu filtrasi dan reabsorpsi. Dalam mendiagnosis penyakit yang diderita hewan pada sistem urinarinya terdapat beberapa kendala. Pada penelitian ini, dikembangkan model untuk mendiagnosis gangguan sistem urinari pada anjing dan kucing dengan menggunakan algoritma VFI 5 berdasarkan gejala klinis (terdapat 37 feature) dan pemeriksaan laboratorium (39 feature). Percobaan dilakukan baik pada feature gejala klinis dan juga pada feature pemeriksaan laboratorium. Hasil pengamatan yang dilakukan menunjukkan bahwa akurasi rata-rata sebesar 77,38% untuk percobaan dengan feature gejala klinis, dan 86,31% untuk percobaan dengan feature pemeriksaan laboratorium. Peningkatan ini mengindikasikan bahwa dalam mendiagnosis penyakit dalam sistem urinari, pemeriksaan laboratorium masih sangat dibutuhkan dalam menentukan hasil diagnosis suatu penyakit.

SUPERVISED MACHINE LEARNING MODEL FOR MICRORNA EXPRESSION DATA IN CANCER Indra Waspada; Adi Wibowo; Noel Segura Meraz
Jurnal Ilmu Komputer dan Informasi Vol 10, No 2 (2017): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

The cancer cell gene expression data in general has a very large feature and requires analysis to find out which genes are strongly influencing the specific disease for diagnosis and drug discovery. In this paper several methods of supervised learning (decisien tree, naïve bayes, neural network, and deep learning) are used to classify cancer cells based on the expression of the microRNA gene to obtain the best method that can be used for gene analysis. In this study there is no optimization and tuning of the algorithm to test the ability of general algorithms. There are 1881 features of microRNA gene epresi on 25 cancer classes based on tissue location. A simple feature selection method is used to test the comparison of the algorithm. Expreriments were conducted with various scenarios to test the accuracy of the classification.

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Nurul Fazriah

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Home Page

OAI Link

Editorial Team

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Google Scholar

Contact Name Nurul Fazriah

Contact Email jiki@cs.ui.ac.id

Phone +62217863419

Journal Mail Official jiki@cs.ui.ac.id

Editorial Address "Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok - 16424"

Location Kota depok, Jawa barat INDONESIA

Abstract

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Contact Name
Nurul Fazriah

Contact Email
jiki@cs.ui.ac.id

Phone
+62217863419

Journal Mail Official
jiki@cs.ui.ac.id

Editorial Address
"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok - 16424"

Location
Kota depok,

Jawa barat

INDONESIA