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Yeni Kustiyahningsih
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ykustiyahningsih@trunojoyo.ac.id
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+6282139239387
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kursor@trunojoyo.ac.id
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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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Kab. bangkalan,
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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 5 Documents
 1 
Search results for , issue "Vol 10 No 2 (2019)" : 5 Documents clear
Electronic Data Interchange (EDI) Applications Use the Decision Tree Method to Determine Vendor Recommendations Mariana Rospilinda Siki; Nisa Hanum Harani; 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.v10i2.217

Abstract

Electronic Data Interchange (EDI) is an electronic data exchange mechanism between a company and another company or Business to Business (B2B) in a supply chain cycle. In this study, EDI's role in managing the procurement of goods as well as the EDI model has been applied. Determination of vendor recommendations is one element of vendor performance evaluation of the procurement process. Lack of information and analysis obtained by PT. Cinovasi Rekaprima makes it difficult to predict vendor recommendations. Predicted vendor recommendations can help the Procurement Division in developing appropriate strategies to determine recommended vendors. This problem can be applied to data mining techniques to make predictions using the classification method. Decision Tree is a method that converts facts into decision trees that represent rules that can be interpreted by humans. Attributes that influence the determination of vendor recommendations consist of the availability of goods, services, ease of ordering and product quality. Sample data obtained directly from the Procurement Division of PT. Cinovasi Rekaprima is primary data in the form of vendor data (quotation) and secondary data in the form of vendor performance evaluation forms. The result of the EDI application is a classification consisting of 2 classes, namely recommended vendors and non-recommended vendors and the Procurement Division can use it for decision making to determine the right vendor, so that the procurement process becomes easier and increases company profitability. The testing model uses k-fold cross-validation with the k value is 1 to 10 fold. This application can determine vendor recommendations with the highest accuracy 87.00 % on k-3 and k-5 fold.
Intelligent Imaging Technology Implementation as Terrorism Prevention in Retail Sectors in 21st Century Bob Foster; Muhamad Deni Johansyah
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.v10i2.188

Abstract

Terrorism is a very dangerous thing and has become a threat both on a national and international scale. Understanding terrorism seeks to instill the seeds of hostility towards a group, government agencies and even the state. Before entering the 21st century terror attacks are blatant in the business sector by sabotaging and damaging public facilities and vital objects. These physical attacks can be prevented by recording personal identities or conducting regular security patrols and placing a large number of security personnel in places of business and places that are considered strategic. However, this is still not optimal where the level of security and the number of personnel are limited in monitoring the place for a long time and are sustainable. The terrorist attacks in the 21st century are different and require different handling. Attacks can be physical or non-physical. On non-physical objects attacks are usually carried out by hacking networks that can damage internet network connections in one area and even one country. Ways to prevent attacks that are physical in nature by utilizing computer vision technology capabilities that are used to record all civil society. An additional feature in this technology lies in the face recognition and pattern matching techniques where a person's face will be searched for unique features. Then from these data will be biometric data, namely data that will not change and disappear. Computer vision algorithms can detect a person's face or object even though it has been modified or changed in physical and color conditions. The advantages of these algorithms are effectively used to record visitor identities and are optimal in recognizing an object with an accuracy of up to 90%. This system is able to help and improve a security feature of a business and tourist area.
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.
Salt Quality Determination Using Simple Additive Weighting (SAW) and Analytical Hirarki Process (AHP) Methods Ach Khozaimi; Yoga Dwitya Pramudita; Eka Mala Sari Rochman; Aeri Rachmad
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.v10i2.227

Abstract

Salt has a salty taste obtained by drying seawater into mineral crystals. However, the quality of industrial salt in Indonesia is still an obstacle, so the need for industrial salt still relies on imported salt. The quality of salt is shown from physical and chemical appearance. Good salt is shown by the crystal form which is smooth and has a clear white color. Good salt quality knowledge must be known so that it can meet Indonesia's national standards and can distinguish salt designation based on its quality category. This study compares the Simple Additive Weighting (SAW) and Analytical Hierarchy Proccess (AHP) methods to determine the highest quality salt. The SAW method gives weight to each of its attributes and the total score finally produces an alternative decision that matches the criteria, thus producing a high-quality salt. While the AHP method starts by creating a hierarchical structure that has the main objectives, criteria, sub criteria and alternatives to be discussed. Pairwise comparisons are used to form relationships in the structure. So it will form a matrix where the ratio scale is derived in the form of the main vector eigen or function-eigen.
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 %.

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