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Contact Name
Nurul Fazriah
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jiki@cs.ui.ac.id
Phone
+62217863419
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jiki@cs.ui.ac.id
Editorial Address
"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok - 16424"
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Kota depok,
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INDONESIA
Jurnal Ilmu Komputer dan Informasi
Published by Universitas Indonesia
ISSN : 20887051     EISSN : 25029274     DOI : 10.21609
Core Subject : 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
UTILISING BTTRACE VISUALISER AND LTL FORMULAE PATTERNS FOR ANALYSING COUNTEREXAMPLE Irene Ully Havsa
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.716 KB) | DOI: 10.21609/jiki.v6i1.212

Abstract

The aim of this paper is to demonstrate the utilisation of a Behavior Tree trace visualiser called BTTrace and generalised LTL formulae patterns to help system analysts analyse counterexamples and generate valuable ones. Counterexample generated by SAL model checker from a Behavior Tree model and an LTL formulae is translated into a BTTrace file. This file is rendered by BTTrace to visualise the counterexample on Behavior Tree diagram in animated fashion. Generalised LTL formulae patterns are exploited using a particular technique to assist analyst on constructing new yet meaningful property formulas. These formulas are used to obtain different and valuable counterexamples for further analysis. It is shown that BTTrace and LTL formulae patterns give significant support for analysing counterexamples of Behavior Tree model.
IMPROVED DESIGN OF DTW AND GMM CASCADED ARABIC SPEAKER Shuoshuo Chen; Junbo Zhao; Ruiqi Yang
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (764.823 KB) | DOI: 10.21609/jiki.v6i2.221

Abstract

In this paper, we discuss about the design, implementation and assessment of a two-stage Arabic speaker recognition system, which aims to recognize a target Arabic speaker among several people. The first stage uses improved DTW (Dynamic Time Warping) algorithm and the second stage uses SA-KM-based GMM (Gaussian Mixture Model). MFCC (Mel Frequency Cepstral Coefficients) and its differences form, as acoustic feature, are extracted from the sample speeches. DTW provides three most possible speakers and then the recognition results are conveyed to GMM training processes. A specified similarity assessment algorithm, KL distance, is applied to find the best match with the target speaker. Experimental results show that text-independent recognition rate of the cascaded system reaches 90 percent.
TERM WEIGHTING BASED ON POSITIVE IMPACT FACTOR QUERY FOR ARABIC FIQH DOCUMENT RANKING Rizka Sholikah; Dhian Kartika; Agus Zainal Arifin; Diana Purwitasari
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (247.961 KB) | DOI: 10.21609/jiki.v10i1.408

Abstract

Query becomes one of the most decisive factor on documents searching. A query contains several words, where one of them will become a key term. Key term is a word that has higher information and value than the others in query. It can be used in any kind of text documents, including Arabic Fiqh documents. Using key term in term weighting process could led to an improvement on result’s relevancy. In Arabic Fiqh document searching, not using the proper method in term weighting will relieve important value of key term. In this paper, we propose a new term weighting method based on Positive Impact Factor Query (PIFQ) for Arabic Fiqh documents ranking. PIFQ calculated using key term’s frequency on each category (mazhab) on Fiqh. The key term that frequently appear on a certain mazhab will get higher score on that mazhab, and vice versa. After PIFQ values are acquired, TF.IDF calculation will be done to each words. Then, PIFQ weight will be combine with the result from TF.IDF so that the new weight values for each words will be produced. Experimental result performed on a number of queries using 143 Arabic Fiqh documents show that the proposed method is better than traditional TF.IDF, with 77.9%, 83.1%, and 80.1% of precision, recall, and F-measure respectively.
IMPLEMENTATION OF GENETIC ALGORITHM FOR STUDENT PLACEMENT PROCESS OF COMMUNITY DEVELOPMENT PROGRAM IN UNIVERSITAS GADJAH MADA Nanang Arfandi; Faizah .
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.345 KB) | DOI: 10.21609/jiki.v6i2.226

Abstract

Community Development Program (CDP) is a required subject in Universitas Gadjah Mada for undergraduate students to earn a bachelor’s degree. One of the big problem in CDP implementation is student placement process into available thematic units. Each unit as much as possible filled by students which have balanced composition based on specified criteria. Balances in gender ratio and clusters composition are needed to have an objective assigned team students in a unit. In this paper, a genetic algorithm is proposed to solve this placement problem. The results of this paper is a simulation in CDP student placement process which using genetic algorithm to produce recommendation units which have good composition.
PENGENALAN KADAR TOTAL PADAT TERLARUT PADA BUAH BELIMBING MANIS BERDASAR CITRA RED-GREEN-BLUE DENGAN ANALISIS KOMPONEN UTAMA SEBAGAI EKSTRAKSI CIRI DAN JARAK EUCLIDEAN SEBAGAI PENGENAL POLA Agus Buono; Irmansyah .
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.734 KB) | DOI: 10.21609/jiki.v2i1.126

Abstract

Pada paper ini, dilakukan pemilihan feature dari citra RGB (Red-Green-Blue) untuk memprediksi tingkat kemanisan buah belimbing yang dicirikan dengan kandungan TPT (Total Padat Terlarut). Dari feature terpilih, dilakukan transformasi komponen utama satu dimensi (1D-PCA) dan dua dimensi (2D-PCA) untuk mereduksi dimensi citra. Kemudian dilanjutkan dengan proses pengenalan tingkat kemanisan yang dalam paper ini dikelompokkan menjadi tiga, yaitu manis, sedang, dan asam. Nilai batas tiap kelompok didasarkan pada bentuk histogram nilai TPT. Dari 300 citra buah belimbing diperoleh hasil bahwa secara akurasi, teknik 1D-PCA maupun 2D-PCA memberikan hasil yang relatif sama. Namun dari segi kecepatan, 2D-PCA jauh lebih cepat dibanding 1D-PCA, khususnya pada bagian pembentukan sumbu. Model hubungan tingkat kemanisan sebagai fungsi dari nilai RGB memberikan tingkat determinasi terbesarnya 69.9%. Percobaan menunjukkan bahwa 1D-PCA maupun 2D-PCA mampu menerangkan sekitar 95% model hubungan tersebut yang dikembangkan pada ruang asal. Teknik PCA digabungkan dengan jarak Euclidean untuk pengenalan mampu mengenali buah kelompok manis dengan akurasi 100%. Sedangkan untuk kelompok asam dan sedang teknik yang dilakukan gagal melakukan pengenalan dengan baik
Automatic Ontology Construction Using Text Corpora and Ontology Design Patterns (ODPs) in Alzheimer’s Disease Denis Eka Cahyani; Ito Wasito
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (679.795 KB) | DOI: 10.21609/jiki.v10i2.374

Abstract

An ontology is defined as an explicit specification of a conceptualization, which is an important tool for modeling, sharing and reuse of domain knowledge. However, ontology construction by hand is a complex and a time consuming task. This research presents a fully automatic method to build bilingual domain ontology from text corpora and ontology design patterns (ODPs) in Alzheimer’s disease. This method combines two approaches: ontology learning from texts and matching with ODPs. It consists of six steps: (i) Term relation extraction (ii) Matching with Alzheimer glossary (iii) Matching with ontology design patterns (iv) Score computation similarity term relation with ODPs (v) Ontology building (vi) Ontology evaluation. The result of ontology composed of 381 terms and 184 relations with 200 new terms and 42 new relations were added. Fully automatic ontology construction has higher complexity, shorter time and reduces role of the expert knowledge to evaluate ontology than manual ontology construction. This proposed method is sufficiently flexible to be applied to other domains.
LOCATION ANALYSIS ON SMART HOUSE USING PROJECTIVE TRANSFORMATION Galih Andi Pradana; Bob Hardian; Tonny Adhi Sebastian; Hanif Rasyidi; Yulistiyan Wardhana; Gladhy Guarddin
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.472 KB) | DOI: 10.21609/jiki.v7i1.254

Abstract

In this paper, a method of location analysis for smart house is proposed. The proposed method uses projective transformation to process the input from visual sensor for determining coordinate of resident and also the entire device inside the smart house. With a good calculated coordinate, each device function in the smart house can be optimized for the good of the resident. From the experiment results, the proposed method successfully maps all coordinates of any device in the smart house up to 81% accuracy.
PERBANDINGAN KINERJA BASIS DATA RELASIONALDENGAN BASIS DATA BERORIENTASI-OBJEK STUDI KASUS: APLIKASI JPETSTORE Petrus Mursanto; Muntasir Rahman
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (379.509 KB) | DOI: 10.21609/jiki.v2i2.130

Abstract

Basis Data Berorientasi Objek (BDBO) menggunakan model berorientasi objek untuk penyimpanan data. Selama ini penggunaan BDBO tidak populer disebabkan oleh beberapa standar yang berbeda dalam pemodelan dan perancangan skema data, serta kinerja yang dianggap kurang baik. Padahal dengan pengembangan aplikasi berorientasi objek seyogyanya penggunaan BDBO dapat menurunkan kerumitan dan meningkatkan kualitas kode aplikasi. Penelitian ini bertujuan mengkaji standar penerapan model objek data dan metode perancangan skema data pada BDBO melalui pengukuran kinerja dan kualitas kode dari aplikasi. Penelitian ini mengkaji penerapan model data ODMG 3.0 dan notasi UML pada aplikasi JPetStore dengan menggunakan transformasi Muller untuk perancangan skema data. Aplikasi JPetStore versi MySQL (BDR) dibandingkan kinerjanya dengan versi DB4O (BDBO). Hasil kajian adalah beberapa tambahan pada model ODMG 3.0 dan tambahan notasi UML untuk pemodelan data pada BDBO serta penyesuaian proses transformasi Muller. Kinerja aplikasi versi DB4O secara umum lebih cepat dibandingkan versi MySQL, kecuali dalam membaca data sederhana secara berurut. Kualitas kode aplikasi versi DB4O lebih baik dibandingkan versi MySQL.
Sparse Coding-Based Method Comparison For Land-Use Classification Dewa Made Sri Arsa; Grafika Jati; M H Hilman
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (448.73 KB) | DOI: 10.21609/jiki.v10i2.480

Abstract

Land-use classification utilize  high-resolution remote sensing image. The image is utilized for improving the classification problem. Nonetheless, in other side, the problem becomes more challenging cause the image is too complex. We have to represent the image appropriately. On of the common method to deal with it is Bag of Visual Word (BOVW).  The method needs  a coding process to get the final data interpretation. There are many methods to do coding such as Hard Quantization Coding (HQ), Sparse Coding (SC), and Locality-constrained Linear Coding (LCC). However, that coding methods use a different assumption. Therefore, we have to compare the result of each coding method. The coding method affects classification accuracy. The best coding method will produce the better classification result. Dataset UC Merced consisted 21 classes is used in this research. The experiment result shows that LCC got better performance / accuracy than SC and HQ. LCC method got 86.48 % accuracy. Furthermore, LCC also got the best performance on various number of training data for each class.
DIVERSITY-BASED ATTRIBUTE WEIGHTING FOR K-MODES CLUSTERING Muhammad Misbachul Huda; Dian Rahma Hayun; Annisaa Sri Indarwanti
Jurnal Ilmu Komputer dan Informasi Vol 7, No 2 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (194.677 KB) | DOI: 10.21609/jiki.v7i2.258

Abstract

Abstract Categorical data is a kind of data that is used for computational in computer science. To obtain the information from categorical data input, it needs a clustering algorithm. There are so many clustering algorithms that are given by the researchers. One of the clustering algorithms for categorical data is k-modes. K-modes uses a simple matching approach. This simple matching approach uses similarity values. In K-modes, the two similar objects have similarity value 1, and 0 if it is otherwise. Actually, in each attribute, there are some kinds of different attribute value and each kind of attribute value has different number. The similarity value 0 and 1 is not enough to represent the real semantic distance between a data object and a cluster. Thus in this paper, we generalize a k-modes algorithm for categorical data by adding the weight and diversity value of each attribute value to optimize categorical data clustering.

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