Motorcycle Credit Purchase Decision Support System With Additive Ratio Assesstment (ARAS) Method

Azzahra, Jecika; Maulita, Yani; Syari, Milli Alfhi

doi:10.55227/ijhet.v1i2.23

Cited by 6 publications

(6 citation statements)

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“…Metode ini berfokus pada pembentukan suatu fungsi kegunaan yang mengintegrasikan semua kriteria penilaian untuk setiap alternatif dengan cara yang aditif [16]. Inti dari metode ARAS adalah menghitung skor kegunaan untuk setiap alternatif dengan cara menghitung rasio dari penjumlahan produk bobot kriteria dan nilai kinerja setiap alternatif terhadap nilai ideal atau nilai optimal yang dapat dicapai [17].…”

Section: Penerapan Pendekatan Arasunclassified

Sistem Pendukung Keputusan Pemilihan Wireless Router Menggunakan Pendekatan Rank Reciprocal dan ARAS

Tonggiroh,

Nurhayati,

Yakub

et al. 2024

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Internet telah menjadi kebutuhan esensial, menjadikan wireless router sebagai infrastruktur yang tak terpisahkan dalam menyediakan akses internet. Namun, dalam memilih perangkat router wireless yang tersedia di pasaran, pengguna sering kali dihadapkan pada kompleksitas informasi dan kebingungan dalam menentukan pilihan terbaik. Tujuan dari penelitian ini yaitu untuk mengembangkan sistem pendukung keputusan dalam menentukan perangkat wireless router yang tepat dan cepat melalui kombinasi pendekatan pembobotan Rank Reciprocal dan metode Additive Ratio Assessment (ARAS). Pendekatan Rank Reciprocal dapat memberikan bobot pada setiap kriteria berdasarkan peringkatnya, di mana bobot tersebut merupakan nilai kebalikan dari peringkatnya. Sedangkan alternatif terbaik ditentukan menggunakan metode ARAS melalui perhitungan skor kegunaan untuk setiap alternatif dengan cara menghitung rasio dari penjumlahan produk bobot kriteria dan nilai kinerja setiap alternatif terhadap nilai optimal yang dapat dicapai. Penelitian ini menghasilkan SPK yang dapat merekomendasikan wireless router terbaik dengan menunjukkan perangkingan alternatif. Output yang dihasilkan oleh sistem dan perhitungan manual dari studi kasus pada penelitian ini, didapatkan nilai utilitas untuk altertantif terbaik yang sama yaitu TP-Link Archer AX23 (A3) dengan skor 0,8999. Pengujian usability testing mencapai rata-rata nilai sebesar 87,5%, mengindikasikan bahwa sistem tersebut dapat diterapkan karena telah sesuai dengan kebutuhan penggunanya.

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Section: Penerapan Pendekatan Arasunclassified

Sistem Pendukung Keputusan Pemilihan Wireless Router Menggunakan Pendekatan Rank Reciprocal dan ARAS

Tonggiroh,

Nurhayati,

Yakub

et al. 2024

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“…This method is highly preferred by the decision makers to solve selection-based decision problems. This method is applied to compute ideal solutions to various problems and some of the recent applications are based on transportation analysis [14], green supplier selection [11], personnel selection [16,18], efficiency analysis [4,12,19], mobile game selection [15], indicators selection [1] and many other. This method is also used in combination with other methods such as VIKOR [8] with picture fuzzy sets, CRITIC [3], Entropy, TOPSIS [10], SWARA [21], MEREC [17].…”

Section: Introductionmentioning

confidence: 99%

Design of Experiment with ARAS in Technology Selection for Effective Cognitive Supply Chain Management

2023

rmc

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The core principle of Industry 4.0 is the augmentation of artificial intelligence components with almost all the business activities. The manufacturers are preferring cognitive supply chain management (COGSCM) to conventional logistic practices for exercising effective planning and control. Automatic monitoring of production and inventory levels with less manual interference are the highlighting features of COGSCM. As the right choice of technology makes COGSCM more effective, this paper proposes a hybrid method of decision making to make optimal selection of the technology. The technique of Design of experiment (DOE) is combined with Additive Ratio Assessment (ARAS) to develop a new method. The competency and consistency of the model is tested with the secondary data sets and further analysed with other similar combined methods. It is observed that the proposed method is yielding better results in comparison to the existing methods of making decisions.

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“…In other words, decision support systems provide information, models, and data processing that supports decision making [8]. DSS aims to provide information, guide, recommend and provide direction to the best alternatives to decision makers in order to find the right decision, and can use it to make rational decisions based on the da ta and informed facts of the system [9]. The decision-making process through DSS begins with the stages of investigating and learning about certain circumstances that require someone to decide something.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Profile Matching in the Decision Support System for Best Student Selection

Rumandan

Nuraini

Sari

2022

bits

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The determination of outstanding students is carried out by schools, which provide scholarships to their students in order to provide motivation to improve their academic achievement. The selection of the best students is usually done by looking at the student's report card scores, followed by the homeroom meeting. This is considered not objective and requires a long time to select the best students. Through a decision-support system, the best students can be selected based on the best criteria and alternatives. In a decision support system, a method is needed to determine the best alternative. The profile matching method is considered to have a better level of objectivity because, to measure the value of each indicator, the valuation variable is derived again with sub-indicators and is weighted using assessment parameters. This study aims to solve the problem of selecting the best student through a decision-support system with the output in the form of a ranking using the profile matching method. Based on the calculation of profile matching, it shows that the results of calculating the final score of the best student 1 are a final score of 3.000, the best student 2 gets a final score of 2.955, and the best student 3 gets a final score of 2.693. From the final score, first place in the selection of the best student was Putri Nurlandari with a final score of 3.000.

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Motorcycle Credit Purchase Decision Support System With Additive Ratio Assesstment (ARAS) Method

Cited by 6 publications

References 0 publications

Sistem Pendukung Keputusan Pemilihan Wireless Router Menggunakan Pendekatan Rank Reciprocal dan ARAS

Sistem Pendukung Keputusan Pemilihan Wireless Router Menggunakan Pendekatan Rank Reciprocal dan ARAS

Design of Experiment with ARAS in Technology Selection for Effective Cognitive Supply Chain Management

Implementation of Profile Matching in the Decision Support System for Best Student Selection

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