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Yeni Kustiyahningsih
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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 160 Documents
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HEURISTIC AND THINK ALOUD TO EVALUATE USABILITY OF ACADEMIC INFORMATION SYSTEM Satrio Agung Wicaksono; Retno Indah Rokhmawati; Mochamad Chandra Saputra; Raden Arief Setiawan
Jurnal Ilmiah Kursor Vol 9 No 1 (2017)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v9i1.101

Abstract

Academic Information System is an essential system in performing academic activities. Universitas Brawijaya are using Academic Information System named SIAKAD-UB. SIAKAD-UB is an information systems that deal with all kinds of student details and academic related reports. SIAKAD-UB encountered many problems along with the growth of data. This study aims to discover factor impact on problems of interface usability found in existing SIAKAD-UB using Heuristic Evaluation and Think Aloud method. This study involving 3 experts and 3 operators with the purpose of the evaluation received input from the experts and users. The result of experiment are find 3 problem heuristic with score 0 which mean no usability problem, 7 problem heuristic with score 1 which mean medium priority refinement, 7 problem heuristic with score 2 which mean low priority refinement, 7 problem heuristic with score 3 which mean high priority refinement. Heuristic evaluation and think aloud find 7 aspect refinement are Visibility of system status, Match between system and the real world, User control and freedom, Consistency and standards, Recognition rather than recall, Flexibility and efficiency of use, Help and documentation.
Smart Mobile Application for Decision Support Systems on Determination of Resident in Dormitory Achmad Jauhari; Fifin Ayu Mufarroha; Muhammad Amfahtori Wijarnoko; Moh. Yusril Ihza Maulana; Ahmad Try Bayu Al Haq; Linawati Linawati
Jurnal Ilmiah Kursor Vol 10 No 3 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i3.236

Abstract

The dormitory is one of the facilities provided with the aim of helping students to get a place to live because some of them come from distant places. The Trunojoyo Madura University dormitory has regulations that serve as a place for the process of character education, spiritual deepening, moral improvement. With these regulations, plus the boarding house is a conducive, economical, and strategic place to stay making many students interested in being able to live there. The problem is that each semester change is carried out by the selection of dorm residents and so far it is still done manually by way of discussion of each individual. Therefore, the purpose of this research is to help the board by building a decision support system in determining residents who are still eligible to live in a dormitory and provide opportunities for other students to live in a dormitory. We develop systems based on mobile applications. TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) is implemented as a multi criteria decision making method with four main criteria including routine absence, non-routine absence, violation and notes. The final results of this decision support system are ranks and colors that indicate the status of boarding residents. Ranking starts from the top (1) to the bottom (216) accompanied by a status of green to red. The color status is divided into 3 namely green (safe), yellow (vulnerable), and red (issued). From 216 boarders we took 10 samples of dormitory data for testing. The results of trials with 10 data samples by applying the TOPSIS method obtained an accuracy of 90%.
EYE-BASED HUMAN-COMPUTER INTERACTION (HCI): A NEW KEYBOARD FOR IMPROVING ACCURACY AND MINIMIZING FATIGUE EFFECT Ronny Mardiyanto; Kohei Arai
Jurnal Ilmiah Kursor Vol 6 No 3 (2012)
Publisher : Universitas Trunojoyo Madura

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Abstract

Permasalahan penggunaan keyboard dengan kendali mata adalah tingkat akurasi, kecepatan yang rendah, dan kesulitan dalam menggunakan tombol kombinasi. Penggunaan sistem Interaksi Komputer Manusia (IKM) berbasis mata dalam jangka waktu yang lama dapat menyebabkan kelelahan. Pada penelitian ini diusulkan keyboard baru dengan sifat bergerak. Keyboard yang diusulkan terdiri dari dua bagian yaitu bagian utama (bersifat bergerak, dapat digerakkan oleh pengguna menggunakan mata dalam proses pemilihan hurufnya) dan bagian pengendali gerak (terdiri dari lima tombol besar yang transparan, digunakan untuk mengendalikan gerak keyboard bagian utama). Metode pendeteksi keberadaan pengguna digunakan untuk mengurangi kelelahan. Penambahan tombol shortcut pada layout utama memungkinkan pengguna melakukan fungsi khusus. Keyboard baru ini memiliki kelebihan diantaranya memiliki tingkat akurasi yang tinggi, lebih cepat dalam melakukan pengetikan, memiliki ukuran yang lebih kecil, memungkinkan pengguna menggunakan fungsi tombol kombinasi, dan dapat meminimalkan efek kelelahan saat pengguna menggunakan sistem IKM berbasis mata dalam jangka waktu yang lama. Hasil pengujian yang dilakukan membuktikan bahwa keyboard ini memilki tingkat akurasi yang lebih baik (92.26%) dibandingkan keyboard jenis tetap (78.57%). Juga, dalam melakukan pengetikan 14 huruf keyboard ini lebih cepat (134.69 detik) dibandingkan keyboard jenis tetap (210.28 detik). Pada pengukuran efek kelelahan menggunakan alat Electro Enchephalo Graf (EEG), keyboard ini lebih dapat meminimalkan efek kelelahan dibandingkan keyboard jenis tetap. Kata kunci: Keyboard Bergerak, Sistem IKM Berbasis Mata, Akurasi, Kecepatan, Kelelahan. Abstract The current problems of keyboard on eye-based Human Computer Interaction (HCI) are accuracy, typing speed, fatigue, and the use of combination keys. We propose a new keyboard consist of two parts: the moveable layout and the navigator keys (fixed and transparent). The user appearance detection method is used for reducing the fatigue effect. The adding shortcut keys to the main layout allowing user executes a special functions through combination keys. The new keyboard has advantages on high accuracy, fast, allowing combination keys, and could minimize fatigue effect. The experiment results show that the new keyboard could achieve better accuracy (92.26%) compared to the fixed keyboard (78.57%). Also, the new keyboard improved accuracy 134.69% than the fixed keyboard(210.28%) when used for typing fourteen character over eye-based HCI. Moreover, we measured the fatigue effect by using Electro Encephalo Graph (EEG) over both methods and the result shows that the new keyboard could minimize fatigue better than the fixed keyboard. By implementing the new keyboard on real eye-based HCI, user could type characters easily, fastly, and no burdened with fatigue effect.
ENHANCEMENT OF 3D SURFACE RECONSTRUCTION OF UNDERWATER CORAL REEF BASE ON SIFT IMAGE MATCHING USING CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION AND OUTLIER REMOVAL Pulung Nurtantio Andono; Ricardus Anggi Pramunendar; Catur Supriyanto; Guruh Fajar Shidik; I Ketut Eddy Purnama; Mochamad Hariadi
Jurnal Ilmiah Kursor Vol 7 No 1 (2013)
Publisher : Universitas Trunojoyo Madura

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Abstract

ENHANCEMENT OF 3D SURFACE RECONSTRUCTION OF UNDERWATER CORAL REEF BASE ON SIFT IMAGE MATCHING USING CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION AND OUTLIER REMOVAL aPulung Nurtantio Andono, bRicardus Anggi Pramunendar, cCatur Supriyanto, dGuruh Fajar Shidik,e I Ketut Eddy Purnama, fMochamad Hariadi a,b,c,dFaculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol, No. 207, Semarang 50131, Indonesia e,fFaculty of Industrial Technology, Dept. of Electrical Engineering, ITS, Surabaya, Indonesia Email: a pulung@research.dinus.ac.id Abstrak Penelitian ini menggambarkan peningkatan kualitas rekonstruksi 3D permukaan terumbu karang bawah laut menggunakan sistem kamera stereo. Algoritma Contrast Limited Adaptive Histogram image Equalization (CLAHE) diusulkan untuk meningkatkan kualitas citra bawah laut tersebut, karena menurunnya kualitas citra bawah laut dapat disebabkan oleh penyerapan dan hamburan sinar matahari. Dalam mengembangkan rekonstruksi 3D permukaan bawah laut, pasangan citra stereo diekstrak secara manual dari rekaman video yang diperoleh, yang kemudian dilakukan proses pencocokan citra stereo menggunakan algoritma SIFT. Kelebihan algoritma SIFT tersebut adalah tahan terhadap perubahan skala, transformasi, dan rotasi dari sepasang citra tersebut. Banyaknya matching point antar 2 citra stereo dijadikan ukuran untuk mengetahui kinerja CLAHE terhadap algoritma SIFT. Hasil penelitian menunjukan bahwa penggunaan CLAHE dan outlier removal mampu meningkatkan jumlah matching point sebesar 56%. Keberhasilan CLAHE tersebut perlu diujikan ke beberapa algoritma matching point yang lain. Perbandingan beberapa algoritma matching point yang menerapkan CLAHE dapat membuktikan bahwa CLAHE sangat cocok dalam meningkatkan kinerja algoritma matching point dan rekonstruksi permukaan 3D citra bawah laut. Kata kunci: Rekonstruksi 3D, Citra Bawah Laut, SIFT, CLAHE. Abstract This research describes an enhancement of 3D Reconstruction coral reef images using stereo camera system. Contrast Limited Adaptive Histogram image Equalization (CLAHE) algorithm was proposed to enhance the image quality in preprocessing area, since the quality of underwater images degrades by the absorption and scattering of light. To develop a 3D-representation of the seafloor, image-pairs were first extracted from the video footage manually, then corresponding points are automatically extracted from the stereo-pairs by SIFT matching algorithm, which is invariant to scale, translation, and rotation. Number of matching points is used to evaluate the performance of SIFT with and without CLAHE. As a result, the promising techniques provides better 3D reconstruction details of coral reef imagesin total, the combination of CLAHE and outlier removal performs the enhancement for 56%. For further, CLAHE need to be performed to other image matching techniques. The comparison of different image matching techniques with and without CLAHE can prove that CLAHE is appropriate as image enhancement method for image matching and 3D surface reconstruction. Key words: 3D Reconstruction, Underwater Image, SIFT, CLAHE.
ATTRIBUTE SELECTION F INDONESIAN TELEMATIC SERVICES MSMEs FEASIBILITY ASSISTANCE, USING AHP Eneng Tita Tosida; Kudang Boro Seminar; Yeni Herdiyeni
Jurnal Ilmiah Kursor Vol 8 No 2 (2015)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i2.67

Abstract

The assistance program had not absorbed optimally yet for telematics Micro Small Medium Enterprises (MSMEs). One of the reasons was the data of telematics MSME which still separated in the several institutions. This research aimed to selection of assistance feasibility attributes using Analytical Hierarchy Process (AHP) based on National Socio-Economic Survey (Susenas) data. This data attributes conformed to the criteria of assistance feasibility which was implemented among by Ministry of Cooperative, Small and Medium Enterprises (SMEs), and related institutions. The attributes involved the characteristic of technology, economics, human resources, partnerships, obstacles, prospect and other common conditions. The process of data preparation was needed involving cleaning, discretization, description and transformation of data. The AHP technique aimed to produce rankings and the value of attributes. The finding of this research showed that start-up essence and technology factors became the crucial attributes in the feasibility assessment. The other factors were the economy, human resources, partnerships and development planning. The findings of this research had given the new innovations; in addition of the scope of related substance Telematics Service MSMEs which was still studied limitedly, and the selection technique of assessment feasibility attributes based on Susenas data.
Implementation of Multiple Linear Regression Methods as Prediction of Village Spending on Village Financial Management System Nisa Hanum Harani; Hanna Theresia Siregar; Cahyo Prianto
Jurnal Ilmiah Kursor Vol 10 No 2 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i2.216

Abstract

The realization of village welfare and improvement of Village development can be started from the financial management aspects of the village. The village government has authority ranging from planning, implementation, reporting to accountability. There are two important variables as the financial aspects, there is village income, and village expenditure. The village budget process is a plan that will be compiled systematically. Planning has an association with predictions which is an indication of what is supposed to happen and predictions relating to what will happen. To provide a good village budget planning the village budget prediction feature is required. This prediction feature is done using data mining which is modeled i.e. multiple linear regression algorithm. The variable is selected using a purposive sampling technique and the sample count is 29 villages. Dependent variables are village Expenditure as Y, and independent variables i.e. village funds as X1 and village funding allocation as X2. The best values as validation were gained in the 3rd fold with a correlation coefficient of 0.8907, Mean Absolute Error value of 87209395.37, the value of Root Mean Squared Error of 114867675.6, Roll Absolute Error (RAE) Percentage was 42 %, and Root Relative Squared Error was 44 %.
ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS Joko Pitono; Adi Soepriyanto; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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Abstract

ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS a Joko Pitono, bAdi Soepriyanto, cMauridhi Hery Purnomo aDepartment of Electrical Engineering, PPPPTK/VEDC Malang b,cDepartment of Electrical Engineering, Sepuluh Nopember Institute of Technology, Surabaya Email: j_pitono@yahoo.com Abstract The classical economic dispatch problem could be solved based on single objective function of power system operation by minimizing the fuel cost. However, the single objective function is not sustainable because the environmental issues arise from the emissions generated by fossil-fueled thermal electric power plants. Various pollutants such as sulfur dioxide (SO2), nitrogen oxides (NOX) and carbon dioxide (CO2) affect environmental issues. The economy-environment dispatch problem has been generally solved by considering each objective separately or by applying Weighted Sum Method on both objectives. This paper formulates the solution of dispatch PSO method that considers the impact of various pollutants and various factors such as the price penalty Min-Max, MaxMax, and Average in solving multi-objective problems using cubic criterion function for the cost of fuel and emission values. Multi-objective functions method proposed in this research was validated using IEEE 30-bus systems with six generating units. The results of simulation using Min-Max penalty factor indicated less total fuel cost value compared to the simulation using Max-Max and Average penalty factor. In general, the comparison of Min-Max type= 100%, Max-Max type= 266.9%, and Average type= 191.8%; Max-Max penalty factor provided less emission value with comparison to Min-Max and Average penalty factors. In general, the comparison Max-Max type= 100%, Min-Max type= 102%, and Average type= 100.2% to ETSO while for ETNO and ETCO is not significantly different; Average penalty factor provided less fuel cost value compared to Max-Max and Average penalty factor. In general, the comparison of Average type= 100%, Min-Max type= 101.8%, and Max-Max type= 100.3%. Keywords: Economic-Emission Dispatch, Multi-Objective, Cubic Criterion Function, Price Penalty Factors, Particle Swarm Optimization.
CAN K-NEAREST NEIGHBOR METHOD BE USED TO PREDICT SUCCESS IN INDONESIA STATE UNIVERSITY STUDENT SELECTION Harits Ar Roysid; Aris Maulana; Utomo Pujianto
Jurnal Ilmiah Kursor Vol 9 No 4 (2018)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v9i4.186

Abstract

Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN) is one of the selection pathways for student admissions to enter state universities (PTN) in Indonesia. This study aims to predict the chance of being accepted in the desired PTN and the lack of early monitoring of students for SNMPTN. The data source from the grades reports card of SMAN 1 Pakong, SMAN 8 Kediri, and SMAN 1 Pamekasan by using the average input of compulsory subjects, majors (Science / Social Sciences) and semester 1 to semester 5 which later the output to be accepted or not accepted An imbalanced dataset potentially affect the performance of the classification method used. Hence, we need to eliminate the imbalance class using SMOTE. Using 10-fold cross validation, this study compared K-Nearest Neighbor (KNN) without SMOTE and K-NN with SMOTE. The goal is to find the best prediction model between the two methods. The prediction model is applied to software for teachers to monitor student grades and ensuring students to pass the SNMPTN. The results show that KNN without SMOTE has higher accuracy than KNN with SMOTE. However, KNN with SMOTE outperform than KNN without SMOTE in precision and recall, KNN with SMOTE with K = 3 reached 80.08% Accuracy, 74.42% Precision and 91.68% Recall.
IMPRESSION DETERMINATION OF BATIK IMAGE CLOTH BY MULTILABEL ENSEMBLE CLASSIFICATION USING COLOR DIFFERENCE HISTOGRAM FEATURE EXTRACTION Hani Ramadhan; Isye Arieshanti; Anny Yuniarti; Nanik Suciati
Jurnal Ilmiah Kursor Vol 7 No 4 (2014)
Publisher : Universitas Trunojoyo Madura

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Abstract

IMPRESSION DETERMINATION OF BATIK IMAGE CLOTH BY MULTILABEL ENSEMBLE CLASSIFICATION USING COLOR DIFFERENCE HISTOGRAM FEATURE EXTRACTION aHani Ramadhan, b Isye Arieshanti, cAnny Yuniarti, d Nanik Suciati a,b,c,d Informatics Engineering, Faculty of Information Technology, Institut Teknologi Sepuluh Nopember (ITS) E-Mail: hani.its.042@gmail.com Abstrak Hampir setiap orang akan memperhatikan impresi busana yang dipakai, termasuk busana dengan motif batik. Namun, perpaduan berbagai motif dan warna batik memberikan impresi yang beragam. Sehingga, penentuan impresi dari satu kain batik menjadi sulit. Untuk membantu seseorang dalam menentukan impresi dari busana batik yang dipilih, dibutuhkan sistem yang mampu mengklasifikasikan impresi citra kain batik secara otomatis. Akan tetapi, pembuatan sistem klasifikasi label jamak merupakan memiliki tantangan tersendiri. Penelitian sebelumnya membuktikan bahwa metode klasifikasi ansambel label jamak dengan pencarian threshold mampu menjawab tantangan tersebut dengan kehandalannya dalam menangani himpunan data label jamak. Studi ini bertujuan untuk mengembangkan sistem yang menerapkan metode klasifikasi ansambel label jamak untuk menentukan impresi citra kain batik. Sistem ini memanfaatkan fitur tekstur dan warna yang dihasilkan dari Histogram Perbedaan Warna. Hasil uji coba metode ini memberikan performa yang baik dalam evaluasi label jamak. Nilai evaluasi tersebut antara lain Hamming Loss sebesar 0,173 dan Average Precision 0,866. Kata kunci: Histogram Perbedaan Warna, Impresi Citra Kain Batik, Klasifikasi Label Jamak Abstract Many people will consider the fashion products’ impression that will be worn, including the one with batik motif. Unfortunately, diverse impressions could be produced from combinations of the motif and color from a single batik cloth. Therefore, impression determination becomes a difficult case. To overcome this difficulty, an automatic batik cloth multi-impression classification system should be necessary to aid in choosing certain batik cloth. Nevertheless, this system implementation has its own intriguing challenge. Previous researches implied that multilabel ensemble classification method could deal with the problem against the highly imbalanced dataset. Thus, the aim of this study is to develop the multilabel classification system, which features come from the color and texture feature by Color Difference Histogram. From the test, this method demonstrated good performance by several multilabel evaluations, which are 0.173 by Hamming Loss and 0.866 by Average Precision. Keywords: Color Difference Histogram, Batik Cloth Image Impression, Multi-Label Classification.
CRITICAL TRAJECTORY - EXTREME LEARNING MACHINE TECHNIQUE FOR COMPUTING CRITICAL CLEARING TIME Irrine Budi Sulistiawati; Ardyono Priyadi; Adi Soepriyanto
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.v8i1.73

Abstract

Electric power system is called reliable if the system is able to provide power supply without interrupted. However, in large systems changing on the system or disturbance may affect the power supply. Critical clearing time is the time for deciding the system is a stable or an unstable condition. Critical clearing time has also relationship with setting relay protection to keep the system in the stable condition. Prediction of critical real time for online assessment is expected to be used for preventive action system. That’s why critical clearing time still an interesting topic to be investigated.This paper calculating time of Extreme Learning Machine to predict critical clearing tim on system. Before predicted by Extreme Learning Machine, critical clearing time calculated using numerical calculation critical trajectory method with load changing and different fault occuring. Tested by Java-Bali 500 kv 54 machine 25 bus give result that Extreme learning machine is able to perform faster prediction of neural network.

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