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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 257 Documents

10 11 12 13 14

DETECTION OF DISEASE ON CORN PLANTS USING CONVOLUTIONAL NEURAL NETWORK METHODS Ardi Hidayat; Ucuk Darusalam; Irmawati Irmawati
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

Deep Learning is still an interesting issue and is still widely studied. In this study Deep Learning was used for the diagnosis of corn plant disease using the Convolutional Neural Network (CNN) method, with a total dataset of 3.854 images of diseases in corn plants, which consisted of three types of corn diseases namely Common Rust, Gray Leaf Spot, and Northern Leaf Blight. With an accuracy of 99%, in detecting disease in corn plants.

SIMILARITY BASED ENTROPY ON FEATURE SELECTION FOR HIGH DIMENSIONAL DATA CLASSIFICATION Jayanti Yusmah Sari; Mutmainnah Muchtar; Mohammad Zarkasi; Agus Zainal Arifin
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

Abstract Curse of dimensionality is a major problem in most classification tasks. Feature transformation and feature selection as a feature reduction method can be applied to overcome this problem. Despite of its good performance, feature transformation is not easily interpretable because the physical meaning of the original features cannot be retrieved. On the other side, feature selection with its simple computational process is able to reduce unwanted features and visualize the data to facilitate data understanding. We propose a new feature selection method using similarity based entropy to overcome the high dimensional data problem. Using 6 datasets with high dimensional feature, we have computed the similarity between feature vector and class vector. Then we find the maximum similarity that can be used for calculating the entropy values of each feature. The selected features are features that having higher entropy than mean entropy of overall features. The fuzzy k-NN classifier was implemented to evaluate the selected features. The experiment result shows that proposed method is able to deal with high dimensional data problem with average accuracy of 80.5%.

IMPLEMENTASI SISTEM KLASIFIKASI MOBIL PADA SISTEM PENGATURAN LAMPU LALU LINTAS TERDISTRIBUSI BERBASISKAN JARINGAN SYARAF TIRUAN Arief Ramadhan; Muhammad Fajar; M. Eka Suryana; Big Zaman
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

Sistem Pengaturan Lampu Lalu Lintas Terdistribusi adalah sebuah sistem lampu lalu lintas yang ditujukan untuk memenuhi kebutuhan akan kinerja pengaturan lampu lalu lintas yang cerdas dengan pengambilan data secara real-time. Sistem ini dapat melakukan penjadwalan dan pengaturan jaringan banyakpersimpangan secarareal-time yang tidak bisa dilakukan oleh sistem pengaturan lampu lalu lintas konvensional. Penerapan klasifikasi di dalam sistem ini digunakan untuk meningkatkan akurasi dari pengenalan mobil. Proses klasifikasi diimplementasikan menggunakan tiga algoritma Jaringan Syaraf Tiruan, yakni Backpropagation, FLVQ, dan FLVQ-PSO. Berdasarkan hasil ujicoba, dapat ditunjukkan bahwa algoritma Backpropagationmemiliki performa akurasi yang lebih baik dibandingkan dua algoritma JST yang lainnya. Distributed Traffic Light Control System is a traffic light system intended to meet the need for setting the performance of intelligent traffic lights with real-time data capturing. The system can perform scheduling and network settings of multi-junction in real time that can not be done by a conventional traffic light settings system. Application of classification within this system is used to improve the accuracy of the car recognition. Classification process is implemented using three neural network algorithms, namely Backpropagation, FLVQ, and FLVQ-PSO. Based on the test results, it can be shown that the Backpropagation algorithm performs better accuracy than the other two algorithms.

LEARNING WORD RELATEDNESS OVER TIME FOR TEMPORAL RANKING Dinda Sigmawaty; Mirna Adriani
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

Queries and ranking with temporal aspects gain significant attention in field of Information Retrieval. While searching for articles published over time, the relevant documents usually occur in certain temporal patterns. Given a query that is implicitly time sensitive, we develop a temporal ranking using the important times of query by drawing from the distribution of query trend relatedness over time. We also combine the model with Dual Embedding Space Model (DESM) in the temporal model according to document timestamp. We apply our model using three temporal word embeddings algorithms to learn relatedness of words from news archive in Bahasa Indonesia: (1) QT-W2V-Rank using Word2Vec (2) QT-OW2V-Rank using OrthoTrans-Word2Vec (3) QT-DBE-Rank using Dynamic Bernoulli Embeddings. The highest score was achieved with static word embeddings learned separately over time, called QT-W2V-Rank, which is 66% in average precision and 68% in early precision. Furthermore, studies of different characteristics of temporal topics showed that QT-W2V-Rank is also more effective in capturing temporal patterns such as spikes, periodicity, and seasonality than the baselines.

COMPARATIVE STUDY OF RTOS AND PRIMITIVE INTERRUPT IN EMBEDDED SYSTEM Dwi Purnomo; Machmud R Alhamidi; Grafika Jati; Novian Habibie; Benny Hardjono; Ari Wibisono
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

Multitasking is one of the most challenging issues in the automation industry which is highly depended on the embedded system. There are two methods to perform multitasking in embedded system: RTOS and primitive interrupt. The main purpose of this research is to compare the performance of RÂ¬TOS with primitive method while concurrently undertaking multiple tasks. The system, which is able to perform various tasks, has been built to evaluate the performance of both methods. There are four tasks introduced in the system: servo task, sensor task, LED task, and LCD task. The performance of each method is indicated by the success rate of the sensor task detection. Sensor task detection will be compared with the true value which is calculated and measured manually during observation time. Observation time was varied after several iterations and the data of the iteration are recorded for both RTOS and primitive interrupt methods. The results of the conducted experiments have shown that, RTOS is more accurate than interrupt method. However, the data variance of the primitive interrupt method is narrower than RTOS. Therefore, to choose a better method, an optimization is needed to be done and each product has its own standard.

PERBANDINGAN ALGORITMA PERLUASAN JARINGAN TELEKOMUNIKASI DENGAN MOBILE ROBOT DI DAERAH BENCANA MENGGUNAKAN OPEN DYNAMIC ENGINE Arief Ramadhan; Abdullah Hafidh; M. Eka Suryana; Muhammad Fajar
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

Putusnya jaringan komunikasi sebagai dampak suatu bencana merupakan permasalahan yang perlu cepat diatasi agar tidak menimbulkan kerugian yang lebih besar. Komunikasi antara lokasi bencana dengan dunia luar menjadi sangat penting dalam menentukan tindakan yang tepat untuk meminimalisasi kerugian akibat bencana. Kajian penggunaan mobile robot otonom untuk menghubungkan menara-menara komunikasi yang terputus dapat menjadi solusi alternatif untuk mengatasi masalah ini. Dalam penelitian ini, penulis mengkaji beberapa algoritma perluasan jaringan dalam bentuk simulasi menggunakan Library Open Dynamic Engine. Library Open Dynamic Engine merupakan library yang telah menggunakan perhitungan fisika secara efisien dan teruji sehingga dapat mendekati keadaan dunia sebenarnya. Simulasi ini bertujuan untuk mendemontrasikan serta membandingkan bahwa algoritma ini dapat dikembangkan untuk menghubungkan menara komunikasi. The disconnection in communication networks as the impact of a disaster is a problem that needs to be addressed quickly in order to avoid greater losses. Communication between the disaster site with the outside world becomes very important in determining the appropriate action to minimize losses due to disasters. Study the use of autonomous mobile robots for connecting communication towers that was disconnected can be alternative solutions to address these issues. In this study, the authors examine some of the network expansion algorithm in the form of a simulation using Open Dynamics Engine library. Library of Open Dynamic Engine is a library that has used physics calculations in an efficient and tested so can approach the state of the real world. This simulation aims to demonstrate and compare that this algorithm can be developed to connect the communication towers.

ORBITAL TRAJECTORY SIMULATION ON TWIN STARS SYSTEM IN IFS FRACTAL MODEL BASED ON HYBRID ANIMATION METHOD Tedjo Darmanto; Iping Supriana Suwardi; Rinaldi Munir
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

IFS (Iterated Function Systems) is a method to model fractal object based on affine transformation functions. The star-like object rotation effect in the IFS fractal model could be exhibited by using metamorphical method, as a replacement to the affine rotation method on a non metamorphic animation. The advantage of a metamorphic animation method over the metamorphic animation method is that the object's relative position to the fixed point as an absolute centroid is absolute. Therefore, the rotational effect can be exhibited at any positions. In addition, it can also be combined with rotational effect of the local centroid itself around the absolute centroid as a fixed point by the primitive rotational operation to form an interesting behavior of orbital trajectory Based on the hybrid of both animation methods, the animation simulation could be done on orbital trajectory on a twin stars rotating to each other as a system. Both objects are rotated in the same angular direction, but started in the opposite position around two closely different fixed points. So, the orbital trajectory yielded forms an elliptical path. The two similar objects can be created efficiently by cloning-scaling technique. In general, the animation method can be modeled as an animation framework.

INVESTIGATION OF FLIP-FLOP PERFORMANCE ON DIFFERENT TYPE AND ARCHITECTURE IN SHIFT REGISTER WITH PARALLEL LOAD APPLICATIONS Dwi Purnomo; Machmud Roby Alhamidi; Ari Wibisono; Muhammad Iqbal Tawakal
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

Register is one of the computer components that have a key role in computer organisation. Every computer contains millions of registers that are manifested by flip-flop. This research focuses on the investigation of flip-flop performance based on its type (D, T, S-R, and J-K) and architecture (structural, behavioural, and hybrid). Each type of flip-flop on each architecture would be tested in different bit of shift register with parallel load applications. The experiment criteria that will be assessed are power consumption, resources required, memory required, latency, and efficiency. Based on the experiment, it could be shown that D flip-flop and hybrid architecture showed the best performance in required memory, latency, power consumption, and efficiency. In addition, the experiment results showed that the greater the register number, the less efficient the system would be.

MODEL SELECTION OF ENSEMBLE FORECASTING USING WEIGHTED SIMILARITY OF TIME SERIES Agus Widodo; Indra Budi
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

Several methods have been proposed to combine the forecasting results into single forecast namely the simple averaging, weighted average on validation performance, or non-parametric combination schemas. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar training dataset. Thus, the selected methods may differ at each point to forecast. The similarity measures used to compare the time series for testing and validation are Euclidean and Dynamic Time Warping (DTW), where each point to compare is weighted according to its recentness. The dataset used in the experiment is the time series data designated for NN3 Competition and time series generated from the frequency of USPTOâ€™s patents and PubMedâ€™s scientific publications on the field of health, namely on Apnea, Arrhythmia, and Sleep Stages. The experimental result shows that the weighted combination of methods selected based on the similarity between training and testing data may perform better compared to either the unweighted combination of methods selected based on the similarity measure or the fixed combination of best individual forecast. Beberapa metode telah diajukan untuk menggabungkan beberapa hasil forecasting dalam single forecast yang diberi nama simple averaging, pemberian rata-rata dengan bobot pada tahap validasi kinerja, atau skema kombinasi non-parametrik. Metode ini menggunakan kombinasi tetap pada individual forecast untuk mendapatkan hasil final dari forecast. Dalam paper ini, pendekatan berbeda digunakan untuk memilih metode forecasting, di mana setiap titik dihitung dengan menggunakan metode terbaik yang digunakan oleh dataset pelatihan sejenis. Dengan demikian, metode yang dipilih dapat berbeda di setiap titik perkiraan. Similarity measure yang digunakan untuk membandingkan deret waktu untuk pengujian dan validasi adalah Euclidean dan Dynamic Time Warping (DTW), di mana setiap titik yang dibandingkan diberi bobot sesuai dengan keterbaruannya. Dataset yang digunakan dalam percobaan ini adalah data time series yang didesain untuk NN3 Competition dan data time series yang di-generate dari paten-paten USPTO dan publikasi ilmiah PubMed di bidang kesehatan, yaitu pada Apnea, Aritmia, dan Sleep Stages. Hasil percobaan menunjukkan bahwa pemberian kombinasi bobot dari metode yang dipilih berdasarkan kesamaan antara data pelatihan dan data pengujian, dapat menyajikan hasil yang lebih baik dibanding salah satu kombinasi metode unweighted yang dipilih berdasarkan similarity measure atau kombinasi tetap dari individual forecast terbaik.

PERFORMANCE COMPARISON OF USART COMMUNICATION BETWEEN REAL TIME OPERATING SYSTEM (RTOS) AND NATIVE INTERRUPT Novian Habibie; Machmud Roby Alhamidi; Dwi Marhaendro Jati Purnomo; Muhammad Febrian Rachmadi
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

Comunication between microcontrollers is one of the crucial point in embedded sytems. On the other hand, embedded system must be able to run many parallel task simultaneously. To handle this, we need a reliabe system that can do a multitasking without decreasing every task’s performance. The most widely used methods for multitasking in embedded systems are using Interrupt Service Routine (ISR) or using Real Time Operating System (RTOS). This research compared perfomance of USART communication on system with RTOS to a system that use interrupt. Experiments run on two identical development board XMega A3BU-Xplained which used intenal sensor (light and temperature) and used servo as external component. Perfomance comparison done by counting ping time (elapsing time to transmit data and get a reply as a mark that data has been received) and compare it. This experiments divided into two scenarios: (1) system loaded with many tasks, (2) system loaded with few tasks. Result of the experiments show that communication will be faster if system only loaded with few tasks. System with RTOS has won from interrupt in case (1), but lose to interrupt in case (2).

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Contact Name Nurul Fazriah

Contact Email jiki@cs.ui.ac.id

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

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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