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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.

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Articles 247 Documents

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GRAMMATICAL EVOLUTION FOR FEATURE EXTRACTION IN LOCAL THRESHOLDING PROBLEM Go Frendi Gunawan; Sonny Christiano Gosaria; Agus Zainal Arifin
Jurnal Ilmu Komputer dan Informasi Vol 5, No 2 (2012): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

The various lighting intensity in a document image causes diffculty to threshold the image. The conventional statistic approach is not robust to solve such a problem. There should be different threshold value for each part of the image. The threshold value of each image part can be looked as classifcation problem. In such a classifcation problem, it is needed to find the best features. This paper propose a new approach of how to use grammatical evolution to extract those features. In the proposed method, the goodness of each feature is calculated independently. The best features then used for classification task instead of original features. In our experiment, the usage of the new features produce a very good result, since there are only 5 miss-classification of 45 cases. Variasi intensitas pencahayaan pada citra dokumen akan menyebabkan kesulitan dalam menentukan nilai threshold dari citra tersebut. Pendekatan statistik konvensional tidak cukup baik dalam memecahkan masalah ini. Dalam hal ini, diperlukan nilai threshold yang berbeda-beda untuk setiap bagian citra. Nilai threshold dari setiap bagian citra dapat dipandang sebagai masalah klasifikasi. Dalam permasalahan klasifikasi semacam ini, dibutuhkan pencarian fitur-fitur terbaik. Di sini diusulkan sebuah pendekatan baru untuk mengekstrak fitur-fitur tersebut dengan menggunakan grammatical evolution. Nilai kebaikan dari masing-masing fitur akan dihitung secara saling lepas. Dalam percobaan yang dilakukan, tampak bahwa penggunaan fitur-fitur baru tersebut menghasilkan hasil yang sangat baik. Hanya ditemukan 5 kesalahan pengklasifikasian dalam 45 kasus.

FRACTAL DIMENSION AND LACUNARITY COMBINATION FOR PLANT LEAF CLASSIFICATION Mutmainnah Muchtar; Nanik Suciati; Chastine Fatichah
Jurnal Ilmu Komputer dan Informasi Vol 9, No 2 (2016): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Plants play important roles for the existence of all beings in the world. High diversity of plant’s species make a manual observation of plants classifying becomes very difficult. Fractal dimension is widely known feature descriptor for shape or texture. It is utilized to determine the complexity of an object in a form of fractional dimension. On the other hand, lacunarity is a feature descriptor that able to determine the heterogeneity of a texture image. Lacunarity was not really exploited in many fields. Moreover, there are no significant research on fractal dimension and lacunarity combination in the study of automatic plant’s leaf classification. In this paper, we focused on combination of fractal dimension and lacunarity features extraction to yield better classification result. A box counting method is implemented to get the fractal dimension feature of leaf boundary and vein. Meanwhile, a gliding box algorithm is implemented to get the lacunarity feature of leaf texture. Using 626 leaves from flavia, experiment was conducted by analyzing the performance of both feature vectors, while considering the optimal box size r. Using support vector machine classifier, result shows that combined features able to reach 93.92 % of classification accuracy.

ENVIRONMENT INDEPENDENT DIRECTIONAL GESTURE RECOGNITION TECHNIQUE FOR ROBOTS USING MULTIPLE DATA FUSION Kishore Abishek
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

A technique is presented here for directional gesture recognition by robots. The usual technique employed now is using camera vision and image processing. One major disadvantage with that is the environmental constrain. The machine vision system has a lot of lighting constrains. It is therefore only possible to use that technique in a conditioned environment, where the lighting is compatible with camera system used. The technique presented here is designed to work in any environment. It does not employ machine vision. It utilizes a set of sensors fixed on the hands of a human to identify the direction in which the hand is pointing. This technique uses cylindrical coordinate system to precisely find the direction. A programmed computing block in the robot identifies the direction accurately within the given range.

PRESERVING LOCAL ORNAMENT THROUGH ALGORITHM Aswin Indraprastha; Zulhadi Sahputra; Agus Suharjono
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

This study employs fractal algorithms to generate and transform original Aceh ornaments into architectural design elements. The interpretation and generation of this ornaments by fractal method uses L-system based software called jBatik. We studied an approach of preserving local ornaments using three stages: understanding the local ornament geometry function, interpreting and generating new ornament using fractal method, exploring the possible iterations of patterns based on fractal algorithms. We applied this process into architectural design experiments where the 3D patterns used as an architectural design elements. The result shows that the possibility of preserving local ornament by fractal method can open opportunity for architects to explore new approach in design using the iteration and transformation of local ornaments. The endless possibilities offered by fractal method for generating new ornaments justify the digital advancement for its preservation.

ALGORITMA PARALLEL SUPERVISED PNN STRUCTURE DETERMINATION DAN IMPLEMENTASI BERBASIS MESSAGE PASSING INTERFACE Heru Suhartanto; Herry .
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

Probabilistic Neural Network (PNN) adalah salah satu tipe jaringan neural yang umum digunakan untuk memecahkan permasalahan klasifikasi pola. Di samping struktur jaringan dan metode pelatihan yang sederhana, PNN memiliki kelemahan utama yaitu dalam menentukan struktur jaringan yang terdiri dari penentuan nilai parameter smoothing dan jumlah neuron yang digunakan pada lapisan pola. Dengan adanya kelemahan ini, beberapa peneliti mengajukan algoritma Supervised PNN Structure Determination (SPNN) dengan tujuan untuk mempermudah penentuan struktur PNN. Akan tetapi dalam implementasi iteratif yang telah dilaporkan, SPNN masih memerlukan waktu komputasi yang cukup lama untuk menentukan struktur PNN yang baik. Makalah ini menjelaskan usaha perbaikan kinerja waktu proses implementasi SPNN dengan memperhatikan bagian-bagian proses yang independent serta memodifikasi algoritmanya untuk dapat diterapkan pemrosesan secara paralel. Hasil eksperimen menunjukkan percepatan yang cukup berarti.

LEAST SQUARES SUPPORT VECTOR MACHINES PARAMETER OPTIMIZATION BASED ON IMPROVED ANT COLONY ALGORITHM FOR HEPATITIS DIAGNOSIS Nursuci Putri Husain; Nursanti Novi Arisa; Putri Nur Rahayu; Agus Zainal Arifin; Darlis Herumurti
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

Many kinds of classification method are able to diagnose a patient who suffered Hepatitis disease. One of classification methods that can be used was Least Squares Support Vector Machines (LSSVM). There are two parameters that very influence to improve the classification accuracy on LSSVM, they are kernel parameter and regularization parameter. Determining the optimal parameters must be considered to obtain a high classification accuracy on LSSVM. This paper proposed an optimization method based on Improved Ant Colony Algorithm (IACA) in determining the optimal parameters of LSSVM for diagnosing Hepatitis disease. IACA create a storage solution to keep the whole route of the ants. The solutions that have been stored were the value of the parameter LSSVM. There are three main stages in this study. Firstly, the dimension of Hepatitis dataset will be reduced by Local Fisher Discriminant Analysis (LFDA). Secondly, search the optimal parameter LSSVM with IACA optimization using the data training, And the last, classify the data testing using optimal parameters of LSSVM. Experimental results have demonstrated that the proposed method produces high accuracy value (93.7%) for the 80-20% training-testing partition.

EARLY DETECTION AND MONITORING SYSTEM OF HEART DISEASE BASED ON ELECTROCARDIOGRAM SIGNAL Muhammad Anwar Ma'sum; Elly Matul Imah; Alexander Agung Gunawan
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 Heart disease is the number one deadly disease in Indonesia. One of the main causes of fatality is the late detection of the disease. To avoid escalation of mortality caused by heart disease, we need early detection and monitoring system of heart disease. Therefore, in this research we propose an early detection and monitoring system of heart disease based on ECG signal. The proposed system has three main components: ECG hardware, smartphone, and server. Since the proposed system is designed to classify heartbeat signal, heart disease symptom can be detected as early as possible. We use FLVQ-PSO algorithm to classify heartbeat signal. Experiment result shows that classification accuracy of the system can reach 91.63%. Moreover, the proposed system can be used to verify patients heartbeat by cardiologists from distant area (telehealth). Experiment result shows that responsiveness of the system for the telehealth system is less than 0.6 seconds.

OPTIMASI FUZZY LEARNING VECTOR QUANTIZATION UNTUK SISTEM PENGENALAN AROMA CAMPURAN Wisnu Jatmiko; Rochmatullah .; H. R. Sanabila
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

Kehandalan dari sebuah sistem pengenalan aroma tidak hanya tergantung pada kemampuan perangkat sensor melainkan juga tergantung pada sistem pengenalan pola yang menggunakan jaringan syaraf tiruan. Struktur jaringan syaraf yang sederhana memiliki performa yang buruk untuk memisahkan berbagai campuran aroma. Kombinasi antara teori fuzzy dan jaringan syaraf tiruan digunakan karena teori fuzzy dapat menangani masalah data yang samar-samar sedangkan jaringan syaraf tiruan mempunyai kemampuan untuk pembelajaran yang bagus. Algoritma LVQ digunakan sebagai proses pembelajaran dalam sistem karena algoritma ini mempunyai kecepatan pembelajaran dan keakuratan yang cukup tinggi. Namun penggunaan LVQ dengan teori fuzzy masih menemui kendala utama yaitu pemilihan inisialisasi vektor referensi. Dalam paper ini kami mengusulkan metode baru dalam tahap inisialisasi vektor referensi, yaitu memilih vektor referensi awal yang terbaik dengan menggunakan fungsi fitness. Selanjutnya kami juga telah mengembangkan aplikasi berbasis GUI untuk menampilkan hasil dari klasifikasi aroma. Hasil eksperimen menunjukkan bahwa penggunaan fungsi fitness dalam pemilihan vektor referensi mampu meningkatkan tingkat pengenalan aroma dalam sistem.

SENTENCE ORDERING USING CLUSTER CORRELATION AND PROBABILITY IN MULTI-DOCUMENTS SUMMARIZATION I Gusti Agung Socrates Adi Guna; Suci Nur Fauziah; Wanvy Arifha Saputra
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

Most of the document summary are arranged extractive by taking important sentences from the document. Extractive based summarization often not consider the connection sentence. A good sentence ordering should aware about rhetorical relations such as cause-effect relation, topical relevancy and chronological sequence which exist between the sentences. Based on this problem, we propose a new method for sentence ordering in multi document summarization using cluster correlation and probability for English documents. Sentences of multi-documents are grouped based on similarity into clusters. Sentence extracted from each cluster to be a summary that will be listed based on cluster correlation and probability. User evaluation showed that the summary result of proposed method easier to understanding than the previous method. The result of ROUGE method also shows increase on sentence arrangement compared to previous method.

PEER ASSESSMENT RATING (PAR) INDEX CALCULATION ON 2D DENTAL MODEL IMAGE FOR OVER JET, OPEN BITE, AND TEETH SEGMENTATION ON OCCLUSION SURFACE Muhammad Febrian Rachmadi; Ratna Rustamadji; Miesje Karmiati Purwanegara; sani Muhammad Isa; Benny Hardjono
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 Malocclusion is a clinical symptom, in which the teeth of maxilla and mandible are not located at the proper location. If malocclusion left untreated, it can lead to complications in the digestive system, headache, and periodontal disease disorders. Malocclusion problems involving abnormalities of teeth, bones, and muscles around the jaw are obligation of orthodontic specialists to treat them. The treatments can be varying based on the type of malocclusion, including tooth extraction and tooth braces. To know certain degree of malocclusion experienced by the patient, an assessment method called Peer Assessment Rating (PAR) Index is usually used by the specialist. To help the works of orthodontic specialists in Indonesia, a new automated calculation system based on 2D image of tooth model for PAR Index is being developed. In this paper, the calculation system for over-jet, open-bite, and teeth segmentation is developed. The result of the developed system is then compared with manual assessment done by orthodontic specialist, in order to verify the accuracy of the system.

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Nurul Fazriah

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Home Page

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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

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