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Jurnal Ilmiah Kursor
ISSN : -     EISSN : 23016914     DOI : -
Core Subject : Education,
Contributions to KURSOR journal must be in the form of research or review paper relating directly to the development in Computer Science or Information TechnologyContributions to KURSOR journal must be in the form of research or review paper relating directly to the development in Computer Science or Information Technology.
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Articles 85 Documents
Laporan vinda, vinda
Kursor Vol 6, No 2 (2012)
Publisher : Kursor

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Abstract

Laporan resmi
IDENTIFIKASI SINYAL ELEKTRODE ENCHEPALO GRAPH UNTUK MENGGERAKKAN KURSOR MENGGUNAKAN TEKNIK SAMPLING DAN JARINGAN SYARAF TIRUAN -, Hindarto; Hariadi, Moch.; Purnomo, Mauridhi Hery
Kursor Vol 6, No 3 (2012)
Publisher : University of Trunojoyo Madura

Show Abstract | Original Source | Check in Google Scholar | Full PDF (1549.092 KB) | DOI: 10.21107/kursor.v6i1.101

Abstract

This paper describe the application of backpropagation neural networks as classification and sampling technique (ST) for the extraction of features from the signal wave Electro Encephalo Graph (EEG). This research aims to develop a system that can recognize the EEG signal that is used to move the cursor. The data used is the EEG data which is IIIA dataset of BCI competition III (BCI Competition III 2003). This data contains data from three subjects: K3b, K6b and L1b. In this study, EEG signal data separated by the imagination of movement to the left, right, leg movements and tongue movements. Decision making has been carried out in two stages. In the first stage, TS is used to extract features from EEG signal data. This feature is as basic inputs in back propagation neural networks as a process of learning. This research used Back Propagation (20-20-10-5-1) and 90 data files EEG signal for the training process. During the identification process into four classes of EEG signal data files data files plus 60 into 150 EEG signal so that the EEG signal data file. The results obtained for the classification of these signals is 80% of the 150 files examined data signal to the process of mapping.
Router candra, Candra
Kursor Vol 6, No 2 (2012)
Publisher : Kursor

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Laporan router
OPTIMASI FUNGSI MULTI-OBYEKTIF BERKENDALA MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DENGAN PENGKODEAN REAL Mahmudy, Wayan Firdaus; Rahman, Muh. Arif
Kursor Vol 6, No 1 (2011)
Publisher : University of Trunojoyo Madura

Show Abstract | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v6i1.102

Abstract

Multi-objective optimization problem is difficult to be solved as its objectives generally conflict with each other and its solution is not in the form of a single solution but a set of solutions. Genetic algorithms (GAs) is one of meta heuristic algorithms that may be used to solve this problem. However, a standard GAs is easily trapped in local optimum areas and searching process rate will be lower around the optimum points. This paper proposes a GAs with an adaptive mutation rate to balance the exploration and exploitation on the search space. A simple rule has been developed to determine wheter the mutation rate is increased or decreased. If a significant improvment of the fitness value is not achieved, the mutation rate is increased to enable the GAs exploring search space and escaping the local optimum area. In contrast, the mutation rate is decreased if significant improvment of the fitness value is achieved. This mechanism guide the GAs to exploit the local search area. The experiments show that by using the adaptive mutation, the GAs will move faster toward a feasible search space and achieving solutions on sorter time.
Netsim Agustien, Indah
Kursor Vol 6, No 2 (2012)
Publisher : Kursor

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netsim
Desain E-Goverment di Bangkalan Author1, Author1 Author1; Yana, Budi
Kursor Vol 6, No 3 (2012)
Publisher : Kursor

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Abstract

Manajemen Pemerintahan cukup kompleks sehingga berpeluang terjadinya misskomunikasi dan data yang hilang. Sistem Informasi yang terintegrasi antar SKPD akan mampu mengintegrasikan berbagai proses dan data yang ada di pemerintahan. Sistem E-Goverment yang terintegrasi merupakan salah satu solusi untuk memecahkan permasalahan utama. Desain E-Goverment ini spesifik sesuai dengan kebutuhan user dan stakeholder di Kabupaten Bangkalan.
OPTIMASI FUNGSI MULTI-OBYEKTIF BERKENDALA MENGGUNAKAN ALGORITMA GENETIKA ADAPTIF DENGAN PENGKODEAN REAL Mahmudy, Wayan Firdaus; Rahman, Muh. Arif
Kursor Vol 6, No 1 (2011)
Publisher : University of Trunojoyo Madura

Show Abstract | Original Source | Check in Google Scholar | Full PDF (188.479 KB) | DOI: 10.21107/kursor.v6i1.103

Abstract

Multi-objective optimization problem is difficult to be solved as its objectives generally conflict with each other and its solution is not in the form of a single solution but a set of solutions. Genetic algorithms (GAs) is one of meta heuristic algorithms that may be used to solve this problem. However, a standard GAs is easily trapped in local optimum areas and searching process rate will be lower around the optimum points. This paper proposes a GAs with an adaptive mutation rate to balance the exploration and exploitation on the search space. A simple rule has been developed to determine wheter the mutation rate is increased or decreased. If a significant improvment of the fitness value is not achieved, the mutation rate is increased to enable the GAs exploring search space and escaping the local optimum area. In contrast, the mutation rate is decreased if significant improvment of the fitness value is achieved. This mechanism guide the GAs to exploit the local search area. The experiments show that by using the adaptive mutation, the GAs will move faster toward a feasible search space and achieving solutions on sorter time.
Pemilihan Jurusan menggunakan AHP Aliman, Aliman
Kursor Vol 6, No 3 (2012)
Publisher : Kursor

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Abstract

Siswa mengalami kendala kita harus menentukan jurusan mana yang harus di pilih untuk ke jenjang Perguruan Tinggi. AHP merupakan salah satu metode dalam Multicretia Decision Making. AHP cukup sederhana dengan melibatkan banyak kriteria. AHP dapat di masukkan dalam modul Enrollment System sehingga menjadi bagian sistem terintegrasi dalam pemilihan jurusan.
PERINGKAT WEBSITE PERGURUAN TINGGI BERBASIS ANALISA HYPERLINK MENGGUNAKAN FACTOR ANALYSIS -, Yuhefizar; Hariadi, Mochamad; Suprapto, Yoyon K
Kursor Vol 6, No 1 (2011)
Publisher : University of Trunojoyo Madura

Show Abstract | Original Source | Check in Google Scholar | Full PDF (181.741 KB) | DOI: 10.21107/kursor.v6i1.104

Abstract

Factor analysis is a multivariate method that is used to analyze correlation among indicator variables so that it can be mapped into some factors. Previous research has defined the importance of the role of a hyperlink from a website, but did not examine the most influential variables from some specified hyperlink variables. It is therefore necessary to obtain a factor analysis of the factors that affect the quality of a website from some specified hyperlink variables. Due to this analysis, top 25 university websites from webometrics of January 2011 edition rank have been selected as the research objects. The hyperlink data was obtained by utilizing two search engines, Google.com and Yahoo.com, then this hyperlink data were analyzed using factor analysis methods. The result should that the role of hyperlink total factor (0,254) and external hyperlinks factor (0,253) greatly affect the quality of a website on the review in terms of hyperlink perspective with analysis factor. This research also resulted in a new rank of university websites that can be used as one parametric for a good websites according to hyperlink analysis. The results of this analysis was tested at the level of correlation with parameters of size and visibility webometrics using Pearson correlation method with a highly significant result of 0.575.
IDENTIFIKASI SINYAL ELEKTRODE ENCHEPALO GRAPH UNTUK MENGGERAKKAN KURSOR MENGGUNAKAN TEKNIK SAMPLING DAN JARINGAN SYARAF TIRUAN -, Hindarto
Kursor Vol 6, No 1 (2011)
Publisher : Kursor

Show Abstract | Original Source | Check in Google Scholar

Abstract

This paper describe the application of backpropagation neural networks as classification and sampling technique (ST) for the extraction of features from the signal wave Electro Encephalo Graph (EEG). This research aims to develop a system that can recognize the EEG signal that is used to move the cursor. The data used is the EEG data which is IIIA dataset of BCI competition III (BCI Competition III 2003). This data contains data from three subjects: K3b, K6b and L1b. In this study, EEG signal data separated by the imagination of movement to the left, right, leg movements and tongue movements. Decision making has been carried out in two stages. In the first stage, TS is used to extract features from EEG signal data. This feature is as basic inputs in back propagation neural networks as a process of learning. This research used Back Propagation (20-20-10-5-1) and 90 data files EEG signal for the training process. During the identification process into four classes of EEG signal data files data files plus 60 into 150 EEG signal so that the EEG signal data file. The results obtained for the classification of these signals is 80% of the 150 files examined data signal to the process of mapping.