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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 155 Documents
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OPTIMAL RELAY DESIGN OF ZERO FORCING EQUALIZATION FOR MIMO MULTI WIRELESS RELAYING NETWORKS Apriana Toding
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.v9i1.143

Abstract

In this paper, we develop the optimal relay design for multiple-input multiple-output (MIMO) multi wireless relaying networks, when we consider the problem of zero-forcing processing is studied for multi-input multi- output multi-relay communication system in which MIMO source-destination pairs communicate simultaneously. It is assumed that due to severe shadowing effects which communication links can be established only with the aid of relay node. The aim is to design the relay amplification matrix to maximize the achievable communication sum- rate through the relay, which in general amplifying-and- forward relaying mechanisms are considered. The zero forcing (ZF) algorithm has studied for a MIMO multi relay network by comparing its performance in terms of bit- error-rate (BER) at destination algorithm. In particular, we investigate its performance with and without using the ZF at the relay. Our results demonstrate that the system performance can be significantly improved by using the ZF algorithm at relay (optimal relay ZF algorithm)
DEEP LEARNING-BASED OBJECT RECOGNITION ROBOT CONTROL VIA WEB AND MOBILE USING AN INTERNET OF THINGS (IoT) CONNECTION Basuki Rahmat; Budi Nugroho
Jurnal Ilmiah Kursor Vol 10 No 4 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i4.242

Abstract

The paper presents the intelligent surveillance robotic control techniques via web and mobile via an Internet of Things (IoT) connection. The robot is equipped with a Kinect Xbox 360 camera and a Deep Learning algorithm for recognizing objects in front of it. The Deep Learning algorithm used is OpenCV's Deep Neural Network (DNN). The intelligent surveillance robot in this study was named BNU 4.0. The brain controlling this robot is the NodeMCU V3 microcontroller. Electronic board based on the ESP8266 chip. With this chip, NodeMCU V3 can connect to the cloud Internet of Things (IoT). Cloud IoT used in this research is cloudmqtt (https://www.cloudmqtt.com). With the Arduino program embedded in the NodeMCU V3 microcontroller, it can then run the robot control program via web and mobile. The mobile robot control program uses the Android MQTT IoT Application Panel.
TRANSFORMING RHETORICAL DOCUMENT PROFILE INTO TAILORED SUMMARY OF SCIENTIFIC PAPER Masayu Leylia Khodra; Mohammad Dimas; Dwi Hendratmo Widyantoro; E. Aminudin Aziz; Bambang Riyanto Trilaksono
Jurnal Ilmiah Kursor Vol 6 No 3 (2012)
Publisher : Universitas Trunojoyo Madura

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Abstract

Since abstract of scientific paper is author biased, readers’ required information may not be included in the abstract. Tailored summary may help them to get a summary based on their information needs. This research is the first one that implements tailored summary system for scientific paper. Tailored summary applies information extraction that transforms a scientific paper into Rhetorical Document Profile, a structured representation of paper content based on rhetorical scheme of fifteen slots. This research adapted building plan that used rhetorical scheme of seven slots. We also implement tailored summary system. After generating initial summary, surface repair is conducted to improve summary readability. Each sentence in initial summary is combined with template phrase based on syntax-tree combination method. There are five groups of template phrases provided in surface repair. We construct evaluation standards by asking five human raters. The best method for sentence selection subsystem that uses Maximal Marginal Importance-Multi Sentence is employing TF.IDF weighting system with precision/recall of 0.61. The surface repair subsystem has acceptance of 0.91.
SEMANTIC WEB SERVICE COMPOSITIONFOR ERP BUSINESS PROCESS Anang Kunaefi; Dwi Sunaryono; Imam Mukhlash
Jurnal Ilmiah Kursor Vol 7 No 1 (2013)
Publisher : Universitas Trunojoyo Madura

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Abstract

SEMANTIC WEB SERVICE COMPOSITIONFOR ERP BUSINESS PROCESS aAnang Kunaefi, bRiyanarto Sarno, cDwi Sunaryono, d Imam Mukhlash a,b,c,d Institut Teknologi Sepuluh Nopember Surabaya E-Mail: an_kunaefi@yahoo.co.id Abstrak Saat ini, ERP (Enterprise Resource Planning) bergerak menuju layanan SaaS (Software as a Service) dan Multi-Tenancy, di mana aplikasi ERP melayani beberapa penyewa dengan proses bisnis yang berbeda dalam lingkungan berbasisweb service. Pada kasus Provider ERP, sangat penting untuk mencapai fleksibilitas proses bisnis penyewa sebagaimana didefinisikan dalam tingkatkematangan SaaS level 4, yaitu Configurable dan Scalable. Dengan cara ini, Penyedia dapat melayani proses bisnis penyewa secara dinamis.Penelitian ini menggunakan pendekatan komposisi semantik web service untuk menyelesaikan masalah fleksibilitas dalamproses bisnis. Ontologi digunakan sebagai representasi pengetahuan semantik pada domainpengetahuan ERP untuk proses pencarian dan komposisi web service. Selanjutnya, algoritma kemiripan berbasis fitur (Feature-based Similarity) dan kemiripan berbasis struktur (Structurebased Similarity)digunakan untuk melakukan pencarian kemiripan antara permintaan proses bisnis dariPenyewa dan proses bisnis Penyedia layanan ERP di Registry. Hasil penelitian menunjukkan bahwa metode yang diusulkan mampu memenuhi permintaan proses bisnis penyewa, baik workflow sederhana maupun workflow yang lebih kompleks dengan hasil yang baik. Kata kunci: Web Servis Semantik, Komposisi Semantik, Proses Bisnis ERP, Featurebased Similarity, Structure-based Similarity. Abstract Nowadays, ERP (Enterprise Resource Planning) moves toward SaaS (Software as a Service) and Multi-Tenancy, where an ERP application serves multiple tenants with different business processes in a web-service based environment. In the case of ERP provider, it is very important to achieve business process flexibility among tenants as defined in SaaS Maturity Level 4, that is Configurable and Scalable. InThis way, Provider can serve tenant’s business processes request dynamically.This research usingsemantic Web Service Composition approach to address business process flexibility problem. Ontology is used as a semantic representation of ERP domain knowledge for web service discovery and composition. Afterwards, the combination of Feature-based Similarity and Structural-based Similarity algorithms are used to do the discovery and matchmaking process between tenant’s business process request and business process available in the ERP provider’s registry. The result showsthat the proposed method in this paper is able to fulfil tenant’s business process request both for simple workflow and complex workflow with a good result. Keywords: Semantic Web Service, Semantic Composition, ERP Business Process, Feature-based Similarity, Structure-based Similarity
PRE-PROCESSED LATENT SEMANTIC ANALYSIS FOR AUTOMATIC ESSAY GRADING Ruth Ema Febrita; Wayan Firdaus Mahmudy
Jurnal Ilmiah Kursor Vol 8 No 4 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i4.110

Abstract

In education, essay is considered as the best tool to evaluate student’s high order thinking and understanding. In the other hand, manual processing and grading essay answers by a teacher need much time and tending to subjectivity grading. Meanwhile automatic essay grading in e-learning system find the difficulties in comparing model or key answer to student’s answer because student’s can answer the question with so various way. That means a right answer also can be so various, for they have same semantic meaning. This paper proposed automatic essay grading using Latent Semantic Analysis. But before the texts being scored, they will be pre-processed using stop words removal and synonyms checking. Calibration process implemented for dealing with the various possible right answer and help to simplify the term matrix. Implementation of this approach using Java Programming Language and WordNet as lexical database for searching the synonyms of every given words. The accuracy obtained by this method is 54.9289%.
Analisys and Implementation Cloud-based Biometricauthentication in Mobile Platform agostinho marques ximenes; Sritrusta Sukaridhoto; Amang Sudarsono; Hasan Basri
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.v10i2.200

Abstract

Based on the Indonesian Central of Statistics the level of poverty people in September 2018 was 25.95 million, based on data, the government allocation care fund the reduce poverty people, the fund are given through the bank. However, banks cannot allocation funds because the cost for build infrastructure is expensive, such as making an ATM. about that, the banks need to find a new solution to allocation care fund to the poverty people, Mobile Platform Biometric Cloud Authentication is one solution. In this study, the experimentationn of the biometric face recognized( face data enrypt and decript by algoritma AES 256 bit) to secure online payment mobile application based on the QR Code scan and face recognition[8,10]. The concentration of this study lies in the experimentationn of biometric face recognize and QR Code scan on biometric payment based face recognition and QR Code scan mobile applications that play a role in data communication security. The test results on this mobile application show that scanning a QR Code and biometric face recognize can be implemented at an online merchant transaction with an accuracy of 95% and takes 53, 21 seconds in transactions. Keyword: biometric, cloud server, Cryptography, QR Code.
PERBAIKAN METODE PEMERINGKATAN SPESIFIKASI KEBUTUHAN BERDASARKAN PERKIRAAN KEUNTUNGAN DAN NILAI PROYEK DENGAN MENGURANGI PERBANDINGAN BERPASANGAN Daniel Siahaan; Eko Prasetyo
Jurnal Ilmiah Kursor Vol 6 No 2 (2011)
Publisher : Universitas Trunojoyo Madura

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Abstract

Pemeringkatan spesifikasi kebutuhan yang lebih diprioritaskan perlu dilakukan mengingat besarnya jumlah spesifikasi kebutuhan yang muncul diawal pengembangan perangkat lunak. Pemeringkatan juga mendekatkan relevansi keinginan pengguna dengan spesifikasi kebutuhan yang diterapkan. Metode pendekatan perkiraan keuntungan dan biaya merupakan metode multi kriteria yang mengakomodasi peringkat spesifikasi kebutuhan berdasarkan keuntungan bagi pengguna dan biaya pemgembangan bagi pengembang. Terdapat dua masalah utama dalam metode ini. Pertama, jika jumlah spesifikasi kebutuhan besar, maka perbandingan berpasangan yang harus dijawab akan semakin banyak. Kedua, keputusan peringkat akhir masih harus melalui diskusi oleh pelanggan. Dalam penelitan ini diusulkan perbaikan metode pemeringkatan pendekatan perkiraan keuntungan dan biaya dengan 100 points dan fuzzy k-means clustering untuk mengurangi perbandingan berpasangan dalam pemeringkatan spesifikasi kebutuhan berdasarkan metode AHP dan model kuadran. Hal tersebut dapat mengurangi perbandingan berpasangan, sehingga proses pemeringkatan menjadi lebih cepat. Hasil yang didapatkan menunjukkan bahwa jumlah perbandingan berpasangan yang harus dijawab oleh pelanggan dapat dikurangi 63.27% dari jumlah semula. Spesifikasi kebutuhan berhasil diperingkat dengan perbaikan metode yang diusulkan, nilai rasio konsistensi (CR) menunjukkan hasil di bawah 10% yang berarti masih berada dalam batas yang dapat dipertanggungjawabkan hasilnya. Kata kunci: 100-Points, Analitic Hierarchy Process, Fuzzy k-means, Model Kuadran, Pemeringkatan Spesifikasi Kebutuhan, Pendekatan Keuntungan dan Biaya. Abstract Predictions of benefit and cost of individual requirements are necessary for requirements prioritization methods which based on benefit and cost approach. Requirements prioritization pulls relevant requirements of user towards their implementation. A cost-value approach is a multi-criteria method for prioritizing requirements according to their relative values and costs. There were two inherited problems in the method. It requires both customers and developers to apply AHP’s pairwise comparison method to assess the relative value and estimate the relative implementation cost of candidate requirements. The problem is that this method introduces n x n number of comparisons to be assessed by customers and developers. Furthermore, the approach only provides a cost-value diagram as a recommendation for the software managers to further analyze and prioritize the requirements. This paper improves the existing approach by implementing 100p method and fuzzy kmeans to reduce the number of pairs to be compared produced by AHP, which contributed to the computational time. The experimental results show that the improved method can reduce 63.27% of the number of pairs to be compared, with consistency ratio (CR) value below the maximum acceptable threshold.
VOTING OF ARTIFICIAL NEURAL NETWORK PARTICLE SWARM OPTIMIZATION BICLASSIFIER USING GAIN RATIO FEATURE SELECTION Fetty Tri Anggraeny; Monica Widiasri
Jurnal Ilmiah Kursor Vol 7 No 2 (2013)
Publisher : Universitas Trunojoyo Madura

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Abstract

VOTING OF ARTIFICIAL NEURAL NETWORK PARTICLE SWARM OPTIMIZATION BICLASSIFIER USING GAIN RATIO FEATURE SELECTION a Fetty Tri Anggraeny, bMonica Widiasri aTeknik Informatika Universitas Pembangunan Nasional “Veteran” Jawa Timur Jl. Raya Rungkut Madya Gunung Anyar Surabaya Indonesia aUniversitas Surabaya Jawa Timur Jl. Raya Kalirungkut Surabaya Indonesia E-Mail: fetty_ta@yahoo.com Abstrak Seleksi fitur merupakan tahapan penting dalam proses klasifikasi. Proses ini menganalisa data (fitur) sehingga menghasilkan fitur yang berperan atau kurang berperan dalam proses klasifikasi. Fitur yang kurang berperan dapat tidak digunakan dalam proses klasifikasi. Peranan sebuah fitur dalam klasifikasi dapat dikalkulasi dengan suatu rumusan, dalam penelitian ini digunakan metode gain ratio untuk mendapatkan bobot atribut dalam proses klasifikasi. Gain ratio pengembangan dari information gain yang digunakan untuk membangun pohon keputusan (decision tree). Metode seleksi fitur gain ratio menggunakan pendekatan seleksi fitur filter, karena dilakukan terlepas dari mesin klasifikasi. Mesin klasifikasi yang digunakan adalah Artificial Neural Network Particle Swarm Optimization (ANNPSO), dimana mesin ini menggabungkan konsep kecerdasan buatan saraf manusia (neural networks) dengan kecerdasan hewan (particle swarm intelligence). Metode yang diusulkan akan diuji coba terhadap 3 dataset UCI, antara lain iris, breast Wisconsin dan dermatology. Uji coba dengan variasi nilai batas gain ratio fitur menunjukkan nilai akurasi yang cukup tinggi terhadap 3 dataset yaitu 97,6%, 96,41%, dan 99,29%. Kata kunci: Gain Ratio, klasifikasi suara terbanyak, ANNPSO biclassifier.. Abstract Feature selection is an important step in classification process, it analyze the data (features) resulting role each features in the classification process. The role of a feature in the classification can be calculated with a formula, in this research the gain ratio method is used to get the attribute/feature weights. Gain ratio is the development of information gain. Information gain is used to form the induction of decision tree (ID3). Gain ratio feature selection method using the filter feature selection approach, as is done separately from classification engine. Classification engine used is Voting of Artificial Neural Network Particle Swarm Intelligence (ANNPSO) Biclassifier, where this engine combines the concept of artificial intelligence human nerve (neural network) with animal intelligence (particle swarm intelligence). The proposed method is tested on three datasets of UCI, including iris, breast wisconsin and dermatology. Trials with the variation of the boundary gain ratio feature showed a high accuracy of the three datasets are 97.6%, 96.41%, and 99.29%. Keywords: Gain Ratio, Voting Classification, ANNPSO Biclassifier
GREY FORECASTING MODEL IMPLEMENTATION FOR FORECAST OF CAPTURED FISHERIES PRODUCTION muhammad shodiq; Budi Warsito; Rachmat Gernowo
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.v9i4.170

Abstract

The increasing need for fish causes problems related to production in the fisheries sector. In fisheries production all information related to (fishing ground) is well known, but on the other hand it is not easy to predict the amount of production due to unclear information. This is also related to the number of ships that make trips, the length (time) of the trip, the type of fishing gear, weather conditions, the quality of human resources, natural environmental factors, and others. The purpose of this study is to apply Grey forecasting model or GM (1,1) to predict fisheries production. Grey forecasting models are used to build forecast models with limited amounts of data with short-term forecasts that will produce accurate forecasts. This study employs the data of captured fish from 2010 to 2018 to analyze calculations using the GM model (1,1). The results showed that the Grey forecasting model or GM (1.1) produced accurate forecasts with an ARPE error value of 9.60% or the accuracy of the forecast model reached 90.39%.
DESIGNING AN ENVIRONMENTAL INFORMATION MANAGEMENT SYSTEM (EIMS): THE CASE OF WEB MAPPING PORTAL FOR FARMERS Wahyudi Agustiono
Jurnal Ilmiah Kursor Vol 7 No 4 (2014)
Publisher : Universitas Trunojoyo Madura

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Abstract

Today concerns for environmental sustainability practices are getting lots of attention due to the regulatory requirements, market pressure and natural resources deterioration. While many businesses have responded these demands by incorporating sustainable thinking into their strategies, in the same vein, researchers have attempted to provide different ground in understanding environmental sustainability best practices. IS researchers is no exception due to the growing recognition that the ICT and IS as being part of the solution to the environmental sustainability problem. This study, therefore, addresses this call by presenting the results of longitudinal and indepth investigation of an IS design for supporting environmental information management and referred as Environmental Information Management System (EIMS). To better understand how a new EIMS can be designed, it then considers the design of a new Web Mapping Portal to assist farmers in land management and monitoring as a fruitful empirical context of investigation. Overall, the findings of this study show the value of IS scholars going beyond the dominant research on IS designed for supporting business (e.g. ERP, SCM and ERP) into more emerging research stream by addressing research question on how can IS be designed to address the complex problem in environmental sustainability.

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