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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi Infotech Journal JURNAL MEDIA INFORMATIKA BUDIDARMA InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Tekno Insentif Jurnal Manajemen Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Dharma Raflesia : Jurnal Ilmiah Pengembangan dan Penerapan IPTEKS
Nisa Hanum Harani
Politeknik Pos Indonesia
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Journal : Jurnal Ilmiah Kursor

 1 
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.
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 %.
Co-Authors Andri Fajar Sunandhar Fanny Shafira Damayanti Fikri Aldi Nugraha Hanna Theresia Siregar Indra Firmansyah Josuansef Pardede Mariana Rospilinda Siki Muh. Rifky Prananda Muhammad Yusril Helmi Setyawan Prianto, Cahyo Rahayu, Woro Isti Rd. Nuraini Siti Fathonah Rolly Maulana Awangga, Rolly Maulana Roni Habibi Tasya Wiendhyra