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Nurul Fazriah
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jiki@cs.ui.ac.id
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+62217863419
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jiki@cs.ui.ac.id
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"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok - 16424"
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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
BOT SPAMMER DETECTION IN TWITTER USING TWEET SIMILARITY AND TIME INTERVAL ENTROPY Rizal Setya Perdana; Tri Hadiah Muliawati; Reddy Alexandro
Jurnal Ilmu Komputer dan Informasi Vol 8, No 1 (2015): 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 (235.716 KB) | DOI: 10.21609/jiki.v8i1.280

Abstract

The popularity of Twitter has attracted spammers to disseminate large amount of spam messages. Preliminary studies had shown that most spam messages were produced automatically by bot. Therefore bot spammer detection can reduce the number of spam messages in Twitter significantly. However, to the best of our knowledge, few researches have focused in detecting Twitter bot spammer. Thus, this paper proposes a novel approach to differentiate between bot spammer and legitimate user accounts using time interval entropy and tweet similarity. Timestamp collections are utilized to calculate the time interval entropy of each user. Uni-gram matching-based similarity will be used to calculate tweet similarity. Datasets are crawled from Twitter containing both normal and spammer accounts. Experimental results showed that legitimate user may exhibit regular behavior in posting tweet as bot spammer. Several legitimate users are also detected to post similar tweets. Therefore it is less optimal to detect bot spammer using one of those features only. However, combination of both features gives better classification result. Precision, recall, and f-measure of the proposed method reached 85,71%, 94,74% and 90% respectively. It outperforms precision, recall, and f-measure of method which only uses either time interval entropy or tweet similarity.
PEMROGRAMAN DASAR DAN ANALISIS KINERJA APLIKASI DALAM KOMPUTASI MENGGUNAKAN GPU Enrico Budianto; Hary Prabowo; Hafiz .; M. Nanda Kurniawan; Prayoga Dahirsa; Tirmidzi Faisal
Jurnal Ilmu Komputer dan Informasi Vol 4, No 2 (2011): 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 (777.544 KB) | DOI: 10.21609/jiki.v4i2.168

Abstract

GPU atau singkatan dari Graphical Processing Unit merupakan mikroprosesor khusus yang berfungsi memercepat proses rendering grafik 2 dimensi atau 3 dimensi. GPU telah digunakan di beberapa perangkat seperti sistem yang telah ditanam, telepon genggam, komputer, workstation, dan game console. Penggunaan GPU sangat membantu efisiensi penggunaan waktu dalam proses perhitungan. Struktur paralel yang dimilikinya membuat efektivitas GPU lebih baik dibandingkan Control Processing Unit (CPU). Saat ini penggunaan GPU tidak hanya di bidang ilmu komputer saja, kemampuan yang dimiliki GPU dalam proses perhitungan yang rumit dan berulang-ulang menyebabkan penggunaanya telah dimanfaatkan di berbagai bidang. Dalam bidang kedokteran, GPU dimanfaatkan dalam mendiagnosis sebuah penyakit, sementara pada bidang akuntansi GPU digunakan dalam perhitungan data yang sangat banyak. Pada penelitian ini akan dijelaskan mengenai efektivitas penggunaan GPU dalam menjalankan sebuah program dan aplikasi serta perbedaannya dengan penggunaan CPU biasa. GPU stands for Graphical Processing Unit is a specialized microprocessor that serves to accelerate the process of rendering two-dimensional charts or three dimensions. GPUs have been used in several devices such as in embedded systems, mobile phones, computers, workstations, and game console. GPU usage helps the efficiency use of time in the calculation process. Its parallel structure, makes the effectiveness of GPU better than the CPU. Today the use of GPU not only in the field of computer science, the capabilities of the GPU in the complex and repetitive calculations process causes it has been utilized in various fields. In the medical field, a GPU used in diagnosing the disease, while in the field of accounting GPU used in the calculation of very much data. In this research, researcher will explain the effectiveness of using GPU in running a program and applications as well as the differences with ordinary CPU usage.
COVERAGE, DIVERSITY, AND COHERENCE OPTIMIZATION FOR MULTI-DOCUMENT SUMMARIZATION Khoirul Umam; Fidi Wincoko Putro; Gulpi Qorik Oktagalu Pratamasunu; Agus Zainal Arifin; Diana Purwitasari
Jurnal Ilmu Komputer dan Informasi Vol 8, No 1 (2015): 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 (608.144 KB) | DOI: 10.21609/jiki.v8i1.278

Abstract

A great summarization on multi-document with similar topics can help users to get useful information. A good summary must have an extensive coverage, minimum redundancy (high diversity), and smooth connection among sentences (high coherence). Therefore, multi-document summarization that considers the coverage, diversity, and coherence of summary is needed. In this paper we propose a novel method on multi-document summarization that optimizes the coverage, diversity, and coherence among the summary's sentences simultaneously. It integrates self-adaptive differential evolution (SaDE) algorithm to solve the optimization problem. Sentences ordering algorithm based on topical closeness approach is performed in SaDE iterations to improve coherences among the summary's sentences. Experiments have been performed on Text Analysis Conference (TAC) 2008 data sets. The experimental results showed that the proposed method generates summaries with average coherence and ROUGE scores 29-41.2 times and 46.97-64.71% better than any other method that only consider coverage and diversity, re-spectively.
SIMULATION OF LANDMARK APPROACH FOR WALL FOLLOWING ALGORITHM ON FIRE-FIGHTING ROBOT USING V-REP Sumarsih Condroayu Purbarani; Qurrotin A’yunina; Muhammad Anwar Ma’sum; Muhammad Febrian Rachmadi
Jurnal Ilmu Komputer dan Informasi Vol 8, No 2 (2015): 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 (737.768 KB) | DOI: 10.21609/jiki.v8i2.308

Abstract

Autonomous mobile robot has been implemented to assist humans in their daily activity. Autonomous robots have also contributed significantly in human safety. Autonomous mobile robot have been implemented to assist humans in their daily activity. Autonomous robots Have also contributed significantly in human safety. An example of the autonomous robot in the human safety sector is the fire fighting robot, which is the main topic of this paper. As an autonomous robot, the fire fighting robot needs a robust navigation ability to execute a given task in the shortest time interval. Wall-following algorithm is one of several navigating algorithm that simplifies this autonomous navigation problem. As a contribution, we propose two methods that could be combined to make the existing wall-following algorithm more robust. The combined wall-flowing algorithm will be compared to the original wall-following algorithm. By doing so, we could determine which method has more impact on the robot’s navigation robustness. Our goal is to see which method is more effective when combined with the wall-following algorithm.
THE CONSTRUCTION OF INDONESIAN-ENGLISH CROSS LANGUAGE PLAGIARISM DETECTION SYSTEM USING FINGERPRINTING TECHNIQUE Zakiy Firdaus Alfikri; Ayu Purwarianti
Jurnal Ilmu Komputer dan Informasi Vol 5, No 1 (2012): 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 (763.802 KB) | DOI: 10.21609/jiki.v5i1.182

Abstract

Cross language plagiarism detection is an important task since it can protect person intellectual property right. Since English is the most popular international language, we proposed an Indonesian-English cross language plagiarism detection to handle such problem in Indonesian-English domain where the suspected plagiarism document is written in Indonesian and the source document is written in English. To minimize translation error, we build the system by translating the Indonesian document into English and then compare the translated document with the English document collection. The detection system consists of preprocess component, heuristic retrieval component, and detailed analysis component. The main technique used in retrieval process is fingerprinting which can extract lexical features from text which is suitable to be used to detect plagiarism done using literal translation method. In this paper, we also propose additional methods to be implemented in heuristic retrieval component to increase the performance of the system: phrase chunking, stop word removal, stemming, and synonym selection. We evaluated system’s performance and the effects of additional methods to system’s performance, provided several data test sets which represents a plagiarism type. From the experiments, we concluded that the system works on 83.33% of test cases. We also concluded that mainly all additional methods except the phrase chunking have good effects in enhancing the system accuracy. Deteksi plagiarisme lintas bahasa merupakan hal yang penting untuk melindungi hak kekayaan intelektual. Bahasa Inggris adalah bahasa internasional yang paling populer, karenanya peneliti mengusulkan deteksi plagiarisme lintas bahasa Indonesia-Inggris untuk menangani masalah tersebut di mana domain dokumen yang diduga plagiat ditulis dalam bahasa Indonesia dan dokumen sumber ditulis dalam bahasa Inggris. Untuk meminimalkan kesalahan terjemahan, peneliti membangun sistem dengan menerjemahkan dokumen bahasa Indonesia ke bahasa Inggris dan kemudian membandingkan dokumen yang diterjemahkan dengan koleksi dokumen bahasa Inggris. Sistem pendeteksian ini terdiri dari komponen preprocess, komponen pencarian heuristik, dan komponen analisis detail. Teknik utama yang digunakan dalam temu kembali informasi adalah fingerprinting yang dapat mengekstrak fitur leksikal dari teks yang cocok digunakan untuk mendeteksi plagiarisme dengan menggunakan metode terjemahan harfiah. Dalam tulisan ini, peneliti juga mengusulkan metode-metode tambahan yang akan diimplementasikan dalam komponen pengambilan heuristik untuk meningkatkan kinerja system seperti chunking frase, penghilangan stop word, stemming, dan pemilihan sinonim. Peneliti mengevaluasi kinerja sistem dan efek dari metode tambahan untuk kinerja sistem, dengan menyediakan sekumpulan skenario tes beberapa data yang merepresentasikan plagiarisme. Dari pengujian diperoleh kesimpulan bahwa sistem bekerja pada 83,33% kasus uji. Peneliti juga menyimpulkan bahwa terutama semua metode tambahan kecuali chunking frase memiliki efek yang baik dalam meningkatkan akurasi sistem.
ROBUST INTEGER HAAR WAVELET BASED WATERMARKING USING SINGULAR VALUE DECOMPOSITION Prajanto Wahyu Adi; Farah Zakiyah Rahmanti
Jurnal Ilmu Komputer dan Informasi Vol 9, No 1 (2016): 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 (522.18 KB) | DOI: 10.21609/jiki.v9i1.363

Abstract

This paper proposed a hybrid watermarking method that used dither quantization of Singular Value Decomposition (SVD) on average coefficients of Integer Haar Wavelet Transform (IHWT). The watermark image embeds through dither quantization process on singular coefficients value. This scheme aims to obtain the higher robustness level than previous method which performs dither quantization of SVD directly on image pixels value. The experiment results show that the proposed method has proper watermarked images quality above 38dB. The proposed method has better performance than the previous method in term of robustness against several image processing attacks. In JPEG compression with Quality Factor of 50 and 70, JPEG2000 compression with Compression Ratio of 5 and 3, average filtering, and Gaussian filtering, the previous method has average Normalized Correlation (NC) values of 0.8756, 0.9759, 0.9509, 0.9905, 0.8321, and 0.9297 respectively. While, the proposed method has better average NC values of 0.9730, 0.9884, 0.9844, 0.9963, 0.9020, and 0.9590 respectively.
SIMPLE EXPERT VISION SYSTEM FOR RECOGNITION OF BEARING'S DEFECTS Agustian K. Herdianta; Aulia M.T. Nasution
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1091.482 KB) | DOI: 10.21609/jiki.v5i2.188

Abstract

Defects on a bearing is usually determined by observing its vibration characteristics. This method unfortunately can not detect the visual defects on the inner and outer ring bearing surface. A pattern recognition is implemented in this paper to solve the problem. A backpropagation neural network architecture is used to recognize the visual defect pattern. This architecture is integrated in a digital image processing chain. Recognition rate of good bearing is obtained at 92.93 %, meanwhile for defected bearing is obtained at 75 % respectively. This rate shows integrated artificial neural network with digital image processing can be implemented to detect the presence of visual bearing defect. Cacat pada bearing biasanya ditentukan dengan mengamati karakteristik getaran. Metode ini sayangnya tidak dapat mendeteksi kecacatan visual pada permukaan dalam dan luar cincin bearing. Sebuah pengenalan pola diimplementasikan dalam paper ini untuk memecahkan masalah tersebut. Sebuah arsitektur jaringan saraf backpropagation digunakan untuk mengenali pola kecacatan visual. Arsitektur yang diusulkan ini terintegrasi dalam sebuah alir pengolahan citra digital. Tingkat pengenalan bearing yang baik adalah 92.93%, sedangkan untuk bantalan yang cacat adalah 75%. Angka ini menunjukkan integrasi jaringan syaraf tiruan dengan pengolahan citra digital dapat diterapkan untuk mendeteksi kecacatan visual pada bearing.
IMPLEMENTATION OF SERIAL AND PARALLEL BUBBLE SORT ON FPGA Dwi Marhaendro Jati Purnomo; Ahmad Arinaldi; Dwi Teguh Priyantini; Ari Wibisono; Andreas Febrian
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.207 KB) | DOI: 10.21609/jiki.v9i2.378

Abstract

Sorting is common process in computational world. Its utilization are on many fields from research to industry. There are many sorting algorithm in nowadays. One of the simplest yet powerful is bubble sort. In this study, bubble sort is implemented on FPGA. The implementation was taken on serial and parallel approach. Serial and parallel bubble sort then compared by means of its memory, execution time, and utility which comprises slices and LUTs. The experiments show that serial bubble sort required smaller memory as well as utility compared to parallel bubble sort. Meanwhile, parallel bubble sort performed faster than serial bubble sort
ANALYSIS RESOURCE AWARE FRAMEWORK BY COMBINING SUNSPOT AND IMOTE2 PLATFORM WIRELESS SENSOR NETWORKS USING DISTANCE VECTOR ALGORITHM Muhammad Ilyas Syarif; Andi Wawan Indrawan; Jumadi M Parenreng; Supeno Djanali; Ary Masharuddin Shiddiqi
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1608.763 KB) | DOI: 10.21609/jiki.v5i2.195

Abstract

Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs) are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA) framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC) and Light Weight Frequent Item (LWF). The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to ± 16.62%. Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN) adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA) framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC) dan Light Weight Frequent Item (LWF). Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.
A NOVEL APPROACH TO STUTTERED SPEECH CORRECTION Alim Sabur Ajibola; Nahrul Khair bin Alang Md. Rashid; Wahju Sediono; Nik Nur Wahidah Nik Hashim
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (283.148 KB) | DOI: 10.21609/jiki.v9i2.382

Abstract

Stuttered speech is a dysfluency rich speech, more prevalent in males than females. It has been associated with insufficient air pressure or poor articulation, even though the root causes are more complex. The primary features include prolonged speech and repetitive speech, while some of its secondary features include, anxiety, fear, and shame. This study used LPC analysis and synthesis algorithms to reconstruct the stuttered speech. The results were evaluated using cepstral distance, Itakura-Saito distance, mean square error, and likelihood ratio. These measures implied perfect speech reconstruction quality. ASR was used for further testing, and the results showed that all the reconstructed speech samples were perfectly recognized while only three samples of the original speech were perfectly recognized.

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