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Journal : chain journal of computer technology computer engineering and informatics

Used Car Sale Application Design in Car Shoowroom Using Extreme Programming A. Ferico Octaviansyah Pasaribu; Agung Deni Wahyudi
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 1 No. 1 (2023): Volume 1 Number 1 January 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v1i1.6

Abstract

Information technology is an activity of collecting, processing, managing, storing, disseminating and utilizing information. Apart from involving hardware and software, this technology also pays attention to human interests in its utilization. Car Showroom is a company engaged in buying and selling used cars. As a growing company and from its stagnant sales chart data for the last 5 years, Car Showroom took the initiative to make the internet a marketing medium. Judging from the reality, so far it has been difficult to provide information regarding the product. Making it easier to design a system that is created, as well as implementing a used car sales application in a car showroom made using the PHP programming language with the MySql database so that the information held by the showroom can be accessed by users online and in real time. With this application, it can help users find used cars online. Based on the results of the recapitulation of the 7 testing criteria that have been carried out, the results show that the number of answers from respondents has a value of 100% in accordance with testing system functionality using blackbox testing.
Evaluasi Kualitas dan Penentuan Mitra Reseller Terbaik Berbasis Sistem Pendukung Keputusan Menggunakan TOPSIS Agung Deni Wahyudi
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 3 No. 2 (2025): Volume 3 Number 2 April 2025
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v3i2.218

Abstract

Pemilihan reseller terbaik merupakan aspek krusial dalam strategi distribusi sebuah perusahaan. Proses ini melibatkan penilaian cermat terhadap sejumlah kriteria, termasuk kinerja penjualan sebelumnya, reputasi, kemampuan finansial, lokasi geografis, dan kualitas layanan pelanggan. Penelitian ini bertujuan untuk melakukan pemilihan reseller terbaik dengan menerapkan model sistem pendukung keputusan menggunakan metode TOPSIS, sehingga dapat membantu perusahaan dalam menentukan reseller terbaik yang akan membantu keberlangsungan kinerja penjualan perusahaan. Hasil perangkingan reseller terbaik berdasarkan metode TOPSIS menunjukan rangking 1 dengan nilai akhir sebesar 0,5845 didapat oleh Reseller E, rangking 2 dengan nilai akhir sebesar 0,5838 didapat oleh Reseller G, dan rangking 3 dengan nilai akhir sebesar 0,5612 didapat oleh Reseller J. Perangkingan reseller terbaik tidak hanya memberikan pandangan mendalam terhadap kinerja mitra bisnis, tetapi juga menjadi landasan bagi perusahaan untuk mengoptimalkan strategi distribusi dan meningkatkan pangsa pasar.
Integration of Data Assessment Method Weighting and Proximity Indexed Value for Best Employee Selection in Decision Support Systems Setiawansyah Setiawansyah; Dyah Ayu Megawaty; Faruk Ulum; Agung Deni Wahyudi; Fadila Shely Amalia
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 4 No. 4 (2026): Volume 4 Number 4 October 2026 (Issue in Progress)
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v4i4.378

Abstract

The selection of the best employee is a multi-criteria decision-making problem because employee performance is evaluated using several criteria with different levels of importance. Subjective criterion weighting may not fully represent the characteristics of the assessment data and can influence the resulting decision. This study proposes the integration of Data Assessment Method (DAM) Weighting and Proximity Indexed Value (PIV) within a Decision Support System for best employee selection. DAM Weighting is employed to determine objective criterion weights based on the information contained in the assessment data, while PIV is used to evaluate the relative proximity of each employee alternative to the reference condition. The results show that the criterion weights are relatively balanced, with R1 obtaining the highest weight of 0.1494 and R4 the lowest weight of 0.1381. The PIV calculation produces different proximity values among the nine employee alternatives, with Alt-08 obtaining the lowest value of -2.2864, followed by Alt-09 at -1.8580 and Alt-06 at -1.7148. Based on the resulting ranking, Alt-08 is identified as the best employee. These findings indicate that the integration of DAM Weighting and PIV can provide an objective, quantitative, and data-oriented mechanism for supporting best employee selection in a Decision Support System.