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Qurrotin Ayunina
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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.
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Articles 194 Documents
PERANCANGAN PENGENDALI ROBOT BERGERAK BERBASIS PERILAKU MENGGUNAKAN PARTICLE SWARM FUZZY CONTROLLER Andi Adriansyah
Jurnal Ilmu Komputer dan Informasi Vol 3, No 1 (2010): 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 (760.436 KB) | DOI: 10.21609/jiki.v3i1.135

Abstract

Paper ini memaparkan perancangan pengendali robot berbasis perilaku menggunakan Fuzzy, di mana parameter Fuzzy ditala secara otomatis menggunakan Particle Swarm Optimization (PSO) yang diistilahkan dengan Particle Swarm Fuzzy Controller (PSFC). Suatu fungsi tertentu dirancang untuk meningkatkan performa proses pencarian PSO. Fungsi tersebut mengubah harga bobot inersia menjadi berkurang secara sigmoid (Sigmoid Decreasing Inertia Weight). Empat buah perilaku robot dirancang menggunakan PSFC. Kemudian seluruh perilaku tersebut juga dikoordinasikan menggunakan PSFC. Beberapa simulasi pengendalian pergerakan robot dan percobaan dengan robot MagellanPro telah dilakukan untuk menguji performa algoritma yang dirancang. Algoritma lain, Genetic Fuzzy Controller (GFC) digunakan sebagai pembanding. Dari hasil pengujian dapat dikatakan bahwa pengendali yang dirancang memiliki kemampuan yang baik untuk menyelesaikan tugasnya pada suatu lingkungan nyata. This paper describes the design of robots controllers based on behaviour using Fuzzy, in which the Fuzzy parameters are automatically tuned using the Particle Swarm Optimization (PSO) which is termed the Particle Swarm Fuzzy Controller (PSFC). A particular function is designed to improve the performance of PSO search process. That particular function changes the value of the inertia weight, so it’s decreased in sigmoid (Sigmoid Decreasing Inertia Weight). Four types of robots behaviour are designed and coordinated using the PSFC. Some simulation of the robot movement control and experiments with the robot MagellanPro have been conducted to test the performance of the algorithm that have been designed. Another algorithm, Genetic Fuzzy Controller (GFC) is used as a comparison. From the test results, it can be said that the controllers that have been designed, have a good ability to accomplish its task in a real environment.
EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST Yuna Sugianela; Qonita Luthfia Sutino; Darlis Herumurti
Jurnal Ilmu Komputer dan Informasi Vol 11, No 1 (2018): 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 (360.748 KB) | DOI: 10.21609/jiki.v11i1.549

Abstract

EEG (electroencephalogram) can detect epileptic seizures by neurophysiologists in clinical practice with visually scan long recordings. Epilepsy seizure is a condition of brain disorder with chronic noncommunicable that affects people of all ages. The challenge of study is how to develop a method for signal processing that extract the subtle information of EEG and use it for automating the detection of epileptic with high accuration, so we can use it for monitoring and treatment the epileptic patient. In this study we developed a method to classify the EEG signal based on Wavelet Packet Decomposition that decompose the EEG signal and Random Forest for seizure detetion. The result of study shows that Random Forest classification has the best performance than KNN, ANN, and SVM. The best combination of statisctical features is standard deviation, maximum and minimum value, and bandpower. WPD is has best decomposition in 5th level.
Bayesian Bernoulli Mixture Regression Model for Bidikmisi Scholarship Classification NUR Iriawan; Kartika Fithriasari; Brodjol Sutija Suprih Ulama; Wahyuni Suryaningtyas; Irwan Susanto; Anindya Apriliyanti Pravitasari
Jurnal Ilmu Komputer dan Informasi Vol 11, No 2 (2018): 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 (584.777 KB) | DOI: 10.21609/jiki.v11i2.536

Abstract

Bidikmisi scholarship grantees are determined based on criteria related to the socioeconomic conditions of the parent of the scholarship grantee. Decision process of Bidikmisi acceptance is not easy to do, since there are sufficient big data of prospective applicants and variables of varied criteria. Based on these problems, a new approach is proposed to determine Bidikmisi grantees by using the Bayesian Bernoulli mixture regression model. The modeling procedure is performed by compiling the accepted and unaccepted cluster of applicants which are estimated for each cluster by the Bernoulli mixture regression model. The model parameter estimation process is done by building an algorithm based on Bayesian Markov Chain Monte Carlo (MCMC) method. The accuracy of acceptance process through Bayesian Bernoulli mixture regression model is measured by determining acceptance classification percentage of model which is compared with acceptance classification percentage of  the dummy regression model and the polytomous regression model. The comparative results show that Bayesian Bernoulli mixture regression model approach gives higher percentage of acceptance classification accuracy than dummy regression model and polytomous regression model
PERANCANGAN KANAL KOMUNIKASI PADA TRANSACTION LEVEL MODELING DALAM PERANCANGAN EMBEDDED SYSTEM Maman Abdurohman; Kuspriyanto .; Sarwono Sutikno; Arif Sasongko
Jurnal Ilmu Komputer dan Informasi Vol 3, No 1 (2010): 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 (752.625 KB) | DOI: 10.21609/jiki.v3i1.140

Abstract

Pada embedded system terdapat dua bagian penting yaitu komponen komputasi (register) dan komponen komunikasi. Komponen komunikasi menjadi perhatian penting pada mekanisme pemodelan level transaksi (Transaction Level Modeling, TLM). Kanal komunikasi adalah komponen untuk transaksi antar register. Fokus pembahasan TLM adalah perancangan kanal yang dapat mengakomodasi untuk peningkatan level transaksi. Kanal (channel) adalah implementasi bus untuk komunikasi antar komponen pada embedded system. Hal ini adalah kunci penting untuk mencapai impelementasi TLM untuk meningkatkan efisiensi pemodelan. Pada paper ini diusulkan beberapa definisi rancangan kanal sebagai implementasi TLM untuk perancangan embedded system. Hasilnya menunjukan bahwa rancangan kanal dapat berjalan sebagai bus untuk transaksi pada TLM. Paper ini menggunakan SystemC sebagai bahasa pemodelan. On embedded systems, there are two important parts: computational components (registers) and communication components. Communication component becomes an important attention on the mechanism of transaction level modeling (TLM). Communication channel is a component for transactions between registers. The focus of TLM is the design of the channel that could accommodate for the increased level of transactions. Channel is the implementation of the bus for communication between components in embedded systems. This is an important key to achieve the implementation of TLM to improve the efficiency of modeling. This paper proposed a definition of the channel design as the implementation of TLM for embedded systems design. The result shows that the design of the channel can run as a bus for transactions on the TLM. This paper uses SystemC as modeling language.
ABCD FEATURE EXTRACTION OF IMAGE DERMATOSCOPIC BASED ON MORPHOLOGY ANALYSIS FOR MELANOMA SKIN CANCER DIAGNOSIS Bilqis Amaliah; Chastine Fatichah; M. Rahmat Widyanto
Jurnal Ilmu Komputer dan Informasi Vol 3, No 2 (2010): 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 (1704.294 KB) | DOI: 10.21609/jiki.v3i2.145

Abstract

This research present asymmetry, border irregularity, color variation, and diameter (ABCD) feature extraction of image dermatoscopic for melanoma skin cancer diagnosis. ABCD feature is the important information based on morphology analysis of image dermatoscopic lesion. ABCD feature is used to calculate Total Dermatoscopic Value (TDV) for melanoma skin cancer diagnosis. Asymmetry feature consist information of asymmetry and lengthening index of the lesion. Border irregularity feature consist information of compactness index, fractal dimension, edge abruptness, and pigmentation transition from the lesion. Color homogeneity feature consist information of color homogeneity and the correlation between photometry and geometry of the lesion. Diameter extraction is diameter of the lesion. There are three diagnosis that is used on this research i.e. melanoma, suspicious, and benign skin lesion. The experiment uses 30 samples of image dermatoscopic lesion that is suspicious melanoma skin cancer. Based on the experiment, the accuracy of the system is 85% that there are four false diagnoses of 30 samples. Penelitian ini menyajikan ekstraksi fitur citra dermatoskopik untuk diagnosis kanker kulit melanoma berdasarkan asymmetry, border irregularity, color variation, dan diameter (ABCD). Fitur ABCD adalah informasi yang penting berdasarkan analisis morfologi lesi citra dermatoskopik. Fitur tersebut digunakan dalam perhitungan Total Dermatoscopic Value (TDV) untuk diagnosis kanker kulit melanoma. Fitur asymmetry terdiri dari informasi asimetri dan indeks perpanjangan luka. Fitur border irregularity terdiri dari informasi indeks compactness, dimensi fraktal, edge abruptness, dan transisi pigmentasi dari lesi. Warna fitur homogenitas terdiri dari informasi homogenitas warna dan korelasi antara fotometri dan geometri lesi. Ekstraksi diameter adalah diameter lesi. Ada tiga diagnosa yang digunakan pada penelitian ini yaitu melanoma, diduga melanoma, dan benign skin lesion. Percobaan ini menggunakan 30 sampel dari lesi citra dermatoskopik kanker kulit melanoma yang mencurigakan. Berdasarkan percobaan, akurasi dari sistem ini adalah 85% dan terdapat empat diagnosa palsu dari 30 sampel.
CHANGE DETECTION IN MULTI-TEMPORAL IMAGES USING MULTISTAGE CLUSTERING FOR DISASTER RECOVERY PLANNING Muhamad Soleh; Aniati Murni Arymurthy; Sesa Wiguna
Jurnal Ilmu Komputer dan Informasi Vol 11, No 2 (2018): 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 (547.427 KB) | DOI: 10.21609/jiki.v11i2.623

Abstract

Change detection analysis on multi-temporal images using various methods have been developed by many researchers in the field of spatial data analysis and image processing. Change detection analysis has many benefit for real world applications such as medical image analysis, valuable material detector, satellite image analysis, disaster recovery planning, and many others. Indonesia is one of the most country that encounter natural disaster. The most memorable disaster was happened in December 26, 2004. Change detection is one of the important part management planning for natural disaster recovery. This article present the fast and accurate result of change detection on multi-temporal images using multistage clustering. There are three main step for change detection in this article, the first step is to find the image difference of two multi-temporal images between the time before disaster and after disaster using operation log ratio between those images. The second step is clustering the difference image using Fuzzy C means divided into three classes. Change, unchanged, and intermediate change region. Afterword the last step is cluster the change map from fuzzy C means clustering using k means clustering, divided into two classes. Change and unchanged region. Both clustering’s based on Euclidian distance.
SISTEM QUESTION ANSWERING BAHASA INDONESIA UNTUK PERTANYAAN NON-FACTOID Ayu Purwarianti; Novi Yusliani
Jurnal Ilmu Komputer dan Informasi Vol 4, No 1 (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 (892.394 KB) | DOI: 10.21609/jiki.v4i1.151

Abstract

Fokus dari penelitian ini adalah untuk mengembangkan data dan sistem Question Answering (QA) Bahasa Indonesia untuk pertanyaan non-factoid. Penelitian ini merupakan penelitian QA non-factoid pertama untuk Bahasa Indonesia. Adapun sistem QA terdiri atas 3 komponen yaitu penganalisis pertanyaan, pengambil paragraf, dan pencari jawaban. Dalam komponen penganalisis pertanyaan, dengan asumsi bahwa pertanyaan yang diajukan merupakan pertanyaan sederhana, digunakan sistem yang berbasis aturan sederhana dengan mengandalkan kata pertanyaan yang digunakan (“apa”, “mengapa”, dan “bagaimana”). Paragraf diperoleh dengan menggunakan pencarian kata kunci baik dengan menggunakan stemming ataupun tidak. Untuk pencari jawaban, jawaban diperoleh dengan menggunakan pola kata-kata khusus yang ditetapkan sebelumnya untuk setiap jenis pertanyaan. Dalam komponen pencari jawaban ini, diperoleh kesimpulan bahwa penggunaan kata kunci non-stemmed bersamaan dengan kata kunci hasil stemming memberikan nilai akurasi jawaban yang lebih baik, jika dibandingkan dengan penggunaan kata kunci non-stemmed saja atau kata kunci stem saja. Dengan menggunakan 90 pertanyaan yang dikumpulkan dari 10 orang Indonesia dan 61 dokumen sumber, diperoleh nilai MRR 0.7689, 0.5925, dan 0.5704 untuk tipe pertanyaan definisi, alasan, dan metode secara berurutan. Focus of this research is to develop QA data and system in Bahasa Indonesia for non-factoid questions. This research is the first non-factoid QA for Bahasa Indonesia. QA system consists of three components: question analyzer, paragraph taker, and answer seeker. In the component of question analyzer, by assuming that the question posed is a simple question, we used a simple rule-based system by relying on the question word used (“what”, “why”, and “how”). On the components of paragraph taker, the paragraph is obtained by using keyword, either by using stemming or not. For answer seeker, the answers obtained by using specific word patterns that previously defined for each type of question. In the component of answer seeker, the conclusion is the use of non-stemmed keywords in conjunction with the keyword stemming results give a better answer accuracy compared to non-use of the keyword or keywords are stemmed stem only. By using 90 questions, we collected from 10 people of Indonesia and the 61 source documents, obtained MRR values 0.7689, 0.5925, and 0.5704 for type definition question, reason, and methods respectively.
Shared Memory Architecture for Simulating Sediment-Fluid Flow by OpenMP Putu Harry Gunawan; Ardhito Utomo
Jurnal Ilmu Komputer dan Informasi Vol 12, No 1 (2019): 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 (1459.71 KB) | DOI: 10.21609/jiki.v12i1.635

Abstract

Simulation of fluid flow using Shallow water equations (SWE) and sediment movement below it using Exner equation is given. Both of the equations will be combined using splitting technique, in which SWE would be computed using Harten-Lax-van Leer and Einfeldt (HLLE) numerical flux, then Exner would be computed semi-implicitly. This paper elaborates the steps of constructing SWE-Exner model. To show the agreement of the scheme, two problems will be elaborated: (1) comparison between analytical solution and numerical solution, and (2) parallelism using OpenMP for Transcritical over a granular bump. The first problem is going to tell the discrete $L^{1}$-, $L^{2}$-, and $L^{\infty}$-norm error of the scheme, and the second one will show the simulation result, speedup, and efficiency of the scheme, which is around $56.44\%$.
IMPLEMENTASI PENDIKTEAN BAHASA INDONESIA Ayu Purwarianti; Hari Bagus Firdaud
Jurnal Ilmu Komputer dan Informasi Vol 4, No 1 (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 (982.439 KB) | DOI: 10.21609/jiki.v4i1.152

Abstract

Paper ini memaparkan hasil penelitian dalam membangun aplikasi pendiktean Bahasa Indonesia untuk waktu nyata. Dalam membangun sebuah aplikasi pendiktean, terdapat beberapa masalah seperti perintah suara (voice command), Out Of Vocabulary (OOV), noise, dan filler. Adapun yang menjadi fokus dalam penelitian ini adalah penanganan perintah suara dan OOV dari kata yang didiktekan. Pendiktean suara merupakan pengembangan lanjut dari pengenalan suara secara waktu nyata dengan tambahan metode untuk menangani hal-hal yang telah dinyatakan sebelumnya. Untuk menangani perintah suara, sebuah modul ditambahkan untuk mengecek hasil decoding dari sistem pengenalan suara. Adapun untuk menangani OOV, ditambahkan modul penanganan pengejaan setelah sebelumnya dinyatakan status ejaan. Model perintah suara dan model huruf ditambahkan ke dalam kamus dan digunakan sebagai pelatihan dari model bahasa n-gram. Dalam pengujian, dilakukan evaluasi terhadap sistem pengenalan suara, penanganan perintah suara, dan modul pengejaan sebagai strategi untuk menangani kata OOV. Untuk modul pengenalan suara, akurasi yang dicapai adalah 70%. Untuk modul penanganan perintah suara, pengujian menunjukkan bahwa perintah suara dapat ditangani dengan baik. Sedangkan untuk modul pengejaan, pengujian menunjukkan bahwa hanya 20 dari 26 huruf yang berhasil dikenali. In this paper, we presented the results of research in building applications dictation of the Bahasa Indonesia for real-time. In developing a dictation application, there are some problems such as voice command, Out of Vocabulary (OOV), noise, and filler. As the focus in this research is the handling of voice command and OOV from dictated words. Voice dictation is a further development of real time voice recognition with an additional method to deal with things that have been stated before. To handle voice commands, a module is added to check the results of decoding of the voice recognition system. To handle OOV, spelling handling module is added after the previously stated spelling status. Voice command model and the model letter are added to the dictionary and used as the training of n-gram language model. In testing, we conducted an evaluation of speech recognition systems, voice commands and spelling handling module as a strategy to deal with OOV words. For the speech recognition module, the achieved accuracy is 70%. For voice commands handling module, the test showed that voice commands can be handled properly. As for the spelling module, testing showed that only 20 of the 26 letters that successfully recognized.
APPLICATION OF THE FORWARD CHAINING METHOD IN DOWN SYNDROME PATIENTS kurniati .
Jurnal Ilmu Komputer dan Informasi Vol 12, No 2 (2019): 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 (598.989 KB) | DOI: 10.21609/jiki.v12i2.694

Abstract

According to WHO data, the incidence of Down syndrome is 1 in 1,000 live births in the world. Down syndrome is a backward condition in the physical and mental development of children that results from abnormal chromosome development. However, these conditions are often too late to be realized by the parents of the sufferer. By conducting this study using the forward chaining method aims to help parents to do early detection of the level of retardation of Down syndrome. So, with the existence of this application, it is very petrifying for parents to carry out treatment from an early age in the right way. Thus, sufferers of dwon syndrome get maximum support and attention from the people closest and nearby so that children with dwon syndrome can grow happily and have a decent life like other normal children even though this dwon syndrome cannot be cured. 

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