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Yeni Kustiyahningsih
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Informatics Department, Engineering Faculty University of Trunojoyo Madura Jl. Raya Telang - Kamal, Bangkalan 69162, Indonesia Tel: 031-3012391, Fax: 031-3012391
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INDONESIA
Jurnal Ilmiah Kursor
Published by Universitas Trunojoyo Madura
ISSN : 02160544     EISSN : 23016914     DOI : https://doi.org/10.21107/kursor
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Ilmiah Kursor is published in January 2005 and has been accreditated by the Directorate General of Higher Education in 2010, 2014, 2019, and until now. Jurnal Ilmiah Kursor seeks to publish original scholarly articles related (but are not limited) to: Computer Science. Computational Intelligence. Information Science. Knowledge Management. Software Engineering. Publisher: Informatics Department, Engineering Faculty, University of Trunojoyo Madura
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 135 Documents
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DESIGN OF GOAL-SEEKING BEHAVIOR-BASED MOBILE ROBOT USING PARTICLE SWARM FUZZY CONTROLLER Andi Adriansyah; Badaruddin .; Eko Ihsanto
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

DESIGN OF GOAL-SEEKING BEHAVIOR-BASED MOBILE ROBOT USING PARTICLE SWARM FUZZY CONTROLLER aAndi Adriansyah, bBadaruddin, cEko Ihsanto a,b,c Electrical Engineering Departement, Faculty of Engineering, Universitas Mercu Buana Jl. Meruya Selatan, Kembangan, Jakarta Barat, 11650, Indonesia Email: a andi@mercubuana.ac.id Abstract Behavior-based control architecture has successfully demonstrated their competence in mobile robot development. There is a key issue in behavior-based mobile robot namely the behavior design problems. Fuzzy logic system characteristics are suitable to address the problems. However, there are difficulties encountered when setting fuzzy parameters manually. Therefore, most of the works in the field generate certain interest for the study of fuzzy systems with added learning capabilities. This paper presents the development of fuzzy behavior-based control architecture using Particle Swarm Optimization (PSO). Then, goal-seeking behaviors based on Particle Swarm Fuzzy Controller (PSFC) are developed using the modified PSO with two stages of the PSFC process. A new nonlinear function of modulated inertia weight adaptation with time, named as Sigmoid Decreasing Inertia Weight (SDIW), is designed for improving the performance of PSO. Several simulations and experiments with MagellanPro mobile robot have been performed to analyze the performance of the algorithm. The promising results have proved that the proposed control architecture for mobile robot has better capability to accomplish useful task in real office-like environment. Keywords: behavior-based robot; fuzzy logic; PSO; PSFC
IDENTIFICATION OF DISEASE ON LEAVES SOYBEAN USING MODIFIED OTSU AND LEARNING VECTOR QUANTIZATION NEURAL NETWORKS Candra Dewi; Muhammad Sa’idul Umam; Imam Cholissodin
Jurnal Ilmiah Kursor Vol 9 No 3 (2018)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v9i3.158

Abstract

Disease of the soybean crop is one of the obstacles to increase soybean production in Indonesia. Some of these diseases usually are found in the leaves and resulted to the crop become unhealthy. This study aims to identify disease on soybean leaf through leaves image by applying the Learning Vector Quantization (LVQ) algorithm. The identification begins with preprocessing using modified Otsu method to get part of the diseases on the leaves with a certain threshold value. The next process is to identify the type of disease using LVQ. This process uses the minimum value, the maximum value and the average value of the red, green and blue color of the image. The testing conducted in this study is to identify two diseases called Peronospora manshurica (Downy Mildew) and phakopsora pachyrhizi (Karat). The result of testing by using 60 training data and the value of all recommendations parameters obtained the highest accuracy of identification is 95% %, but the more stable accuracy is 90%. This result shows that the method perform quite well identification of two mentioned disease.
A THE USE OF PARTIAL LEAST SQUARES MODELING IN FINANCE BUSINESS PARTNERING RESEARCH Amin Tohari; Faisol Faisol; aeri rahmad
Jurnal Ilmiah Kursor Vol 11 No 1 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i1.256

Abstract

Structural equation modeling (SEM) is a set of statistical techniques that allows testing a model that is built between one or more endogenous variables with one or more exogenous variables, where each endogenous and exogenous variable can be in the form of latent or a construct built from several variables of manifest or indicator. There is Structural Equation Modeling (SEM) based on covariance and variance, known as Partial Least Square (PLS), SEM-PLS is a powerful and flexible analysis method. This research discusses about the application of SEM-PLS in the field of managerial accounting system, namely the application of non-financial performance’s role that delivers the sustainability of the company's financial performance. Based on the results obtained, it can be concluded that partial least squares can be used to model finance business partnering, and it is known that employee performance and internal process performance contribute to achieve the firm’s financial performance.
A HEURISTIC TEST TO UNDERSTAND USER MENTAL MODEL OF A FLIGHT SCHEDULE SEARCH FORM Paulus Insap Santosa; Rianto Rianto
Jurnal Ilmiah Kursor Vol 6 No 4 (2012)
Publisher : Universitas Trunojoyo Madura

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Abstract

Situs web yang bagus adalah situs yang sederhana dan berguna bagi penggunanya. Antarmuka merupakan salah satu aspek penting yang menentukan keberhasilan suatu situs web. Makalah ini ini melaporkan hasil sebuah studi untuk mengevaluasi ransangan situs tiket online. Secara khusus, studi ini berfokus pada kombinasi warna dan kebiasaan pengguna. Test kebergunaan dilakukan dengan membandingkan situs web Garasitiket (Form1) aktif dengan rancangan alternatifnya (Form2). Form 1 dan Form2 dirancang secara berbeda dalam hal cara memilih jadwal penerbangan. Metode riset yang digunakan dalam studi ini adalah uji heuristik. Responden, berjumlah 99 orang, berasal dari anggota Garasitiket. Uji sampel-berpasangan (paired-sample test) digunakan untuk menentukan apakah Form1 berbeda dengan Form2. Hasil penelitian menunjukkan bahwa kebiasaan responden mempengaruhi pilihan antarmuka yang digunakan. Ada kecenderungan dari anggota Garasitiket untuk tidak tertarik pada kombinasi warna. Mereka lebih fokus pada hasil pencarian dan kesederhanaan rancangan situs. Analisis statistis menunjukkan bahwa ada perbedaan signifikan antara Form1 dan Form2. Lebih lanjut, responden lebih memilih Form1 dibandingkan dengan Form2. Kata kunci: Model Mental, Kebergunaan, Jadwal Penerbangan, Uji Heuristik. Abstract A great web site should be simple and usable to its users. Interface design is one important aspect that determine the success of certain website. This paper reports the result of a study to evaluate the design of an online ticket website. In particular, the study focuses on color combination, and uses’s habit. Usability test was done by comparing the published Garasitiket Website (Form1) and its alternative (Form2). Form 1 and Form2 were designed differently in term of the way respondents determined their flight schedule. Research method used for this study was heuristic test. Respondents, 99 people, were from members of Garasitiket. Paired-sample test was used to determine whether Form1 differs from Form2. The results indicated that members’ habit influences user interface selection. There was a tendency of Garasitiket members to not interested in color combinations. Rather, they were more focus on the search results and Web design simplicity. Statistical analyses indicated that there was significant difference between Form1 and Form2. Furthermore, Form1 was more preferable.
ANALYSIS OF DIALOGUE TECHNIQUE ACCEPTANCE OF DIAGNOSIS BASED CLINICAL DECISION SUPPORT SYSTEM Sulistianingsih N.; Kusumadewi S.; Kariyam Kariyam
Jurnal Ilmiah Kursor Vol 8 No 1 (2015)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i1.69

Abstract

Many decision support systems have been developed to diagnose diseases, but in reality many of these systems fail when applied. This is mainly due to the difficulties in the use of the system due to incompatibility between the system interface and the wishes of physicians. The purpose of this study was to determine the interface design of decision support systems for diseases diagnose in accordance with physician’s wishes and to determine the effects of perceived usefulness and perceived ease of use on the behavioral intention to use the interface design. The data analysis technique used included the Wilcoxon test, the Friedman test, a principal component analysis and a multiple linear regression analysis. From the data analysis it was found that in anamneses and physical examinations, respondents prefer the interface design of natural language processing and a form filling dialogue, whereas in supported examinations, respondents prefer windowing system interface designs. Advanced data analyses found an influence of the variables of perceived usefulness and perceived ease of use on the behavioral intention to use and this influence has a positive effect.
ASPECT EXTRACTION IN E-COMMERCE USING LATENT DIRICHLET ALLOCATION (LDA) WITH TERM FREQUENCY-INVERSE DOCUMENT FREQUENCY (TF-IDF) Satyawan Agung Nugroho; Fitra A Bachtiar; Randy Cahya Wihandika
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.247

Abstract

Social media is a common thing that people use. Posts or comments found on social media describe someone’s feelings and opinions so there have to be important topics that can be extracted from social media. In the e-commerce field, topic is an interesting thing to know because it can describes people’s opinion towards a product. However, the large number of social media users is currently making the process of finding topics from social media difficult, so computer assistance is needed. One method that can be used is Latent Dirichlet Allocation (LDA). LDA is a good method for extracting topics, but the drawback is that sometimes the topics are incomprehensible. To cover up the drawback, TF-IDF feature selection method is used so that less important words can be skipped so LDA can generate a better topic. The best hyperparameter values ​​obtained were 10 iterations, 10 topics, α and β values consecutively 0,1 and 0,01. The best feature selection percentile value is 90. This value is used to find the threshold that can be used as the lower limit of the TF-IDF value of each word so that the word with greater TF-IDF value can be used as feature.
NEURAL NETWORK BACKPROPAGATION FOR KENDANG TUNGGAL TONE CLASSIFICATION I Putu Bayu Wira Brata; I Dewa Made Bayu Atmaja Darmawan
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.258

Abstract

Kendang Bali is one of the instruments incorporated in this karawitan art. Balinese kendang can be played alone, called a kendang tunggal, where this type of game has a high level of difficulty understanding the tone of the Balinese drums played because some variations of the tone have similar sounds to other tones. Knowing the tone that is in the kendang song automatically can make it easier to learn it. The first approach method used to classify the tone of a kendang tunggal song is segmentation. The onset detection method is used to segment a kendang song with a variation of the hop size parameter. The segmented tone of the punch will be classified using the Backpropagation method. Feature values of autocorrelation, ZCR, STE, RMSE, Spectral Contrast, MFCC, and Mel spectrogram will be used in the classification process. This study performed variations in hop size values in onset detection and obtained the proper configuration at a value of 110. The addition of the normalization process to the onset detection method also helps the segmentation process of kendang songs correctly. The optimal backpropagation architecture obtained is learning rate 0.9, neuron hidden layer 10, and epoch 2000 produces an accuracy of 60.92%.
METHOD COMPARISON IN THE DECISION SUPPORT SYSTEM OF A SCHOLARSHIP SELECTION Mohammad Iqbal Bachtiar; Hadi Suyono; M. Fauzan Edy Purnomo
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.263

Abstract

Commonly, the current scholarship selection process has different targets and various criteria for its prospective scholarship recipients. This causes the decision-making process for scholarship selection to be complex, whereas in the general scholarship selection is time-limited. The solution that can be done is to use a DSS (Decision Support System) to improve consistency and speed up decision-making. The available methods for making a DSS used in this study are the Analytical Hierarchy Process, TOPSIS, and the second model using a deep learning approach. The performance of the DSS will then be evaluated using a Confusion Matrix to determine the cost level of each DSS and analyze the strengths and weaknesses of each DSS. The DSS model with the AHP-TOPSIS approach has been successfully created, with the accuracy performance for introducing data on merit, bidikmisi, and independent scholarship schemes are 56.72%, 65.21%, and 95.87%, respectively. While the DSS model with a deep learning approach has been successfully created with accuracy performance of 71.93%, 100%, and 100%, respectively. There are considerable differences between these two approaches. This may be due to the weighting process in the AHP approach which cannot be carried out with precision.
IMPLEMENTATION OF FACE RECOGNITION USING GEOMETRIC FEATURES EXTRACTION Risanuri Hidayat; Muhammad Oka Bagus Wibowo; Brama Yoga Satria; Anggun Winursito
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.284

Abstract

The face is among the biometric objects used to recognize one’s identity. There are various face recognition system methods that can be applied, one of which is geometric features-based face recognition. Geometric features are unique features extraction of one’s facial components. These features are obtained by calculating the comparison values of the distance measurement between facial components served as a reference like eyes, nose, and mouth. This research implemented a face recognition system using the geometric features method on a significantly low-spec computer system. This implementation was carried out by building a system, installing it on a computer system, and then testing it using laptops or computer devices and the camera web. The face recognition system would process the facial input images, extract their geometric features, and match the results with the data stored in the database. The research results were a low-spec computer system that could recognize its users by providing real-time feedback in the form of users’ names with an accuracy of 98%.
COMPARISON OF STEMMING AND SIMILARITY ALGORITHMS IN INDONESIAN TRANSLATED AL-QUR'AN TEXT SEARCH Ika Oktavia Suzanti; Achmad Jauhari
Jurnal Ilmiah Kursor Vol 11 No 2 (2021)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v11i2.280

Abstract

The long history of information retrieval did not begin with Internet. Prior to widespread public daily use of search engines, in the 1960s information retrieval systems were discovered in commercial and intelligence applications. There are two stages in Information Retrieval in doing its main job which is to preprocessing text and to calculate similarity between term (word) and query (keyword) user searched for in a document. Stemming is final stage of pre-processing in an information retrieval system. The way stemming works is to remove affixes from a word, in form of prefixes, suffixes and insertions into form of basic word. Thus, in this paper we did compare search on information retrieval system without using stemming algorithm, using stemming Porter, Nazief & Adriani and Enhanced Confix Stripping with similarity method used is cosine similarity and dice similarity. Based on test results, text search ability on dice similarity is faster in stemming process with Porter Stemmer and ECS algorithms. While in Nazief & Adriani algorithm and without stemming, cosine similarity is faster than dice similarity.

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