Smart Urban Mobility System Evaluation Model Adaptation to Vilnius, Montreal and Weimar Cities

To date, there is no developed and validated way to assess urban smartness. When evaluating smart city mobility systems, different authors distinguish different indicators. After analysing the evaluation indicators of the transport system presented in the scientific articles, the most relevant and influential indicators were selected. This article develops a hierarchical evaluation model for evaluating a smart city transportation system. The indicators are divided into five groups called “factors”. Several indicators are assigned to each of the listed groups. A hybrid multi-criteria decision-making (MCDM) method was used to calculate the significance of the selected indicators and to compare urban mobility systems. The applied multi-criteria evaluation methods were simple additive weighting (SAW), complex proportional assessment (COPRAS), and technique for order preference by similiarity to ideal solution (TOPSIS). The significance of factors and indicators was determined by expert evaluation methods: the analytic hierarchy process (AHP), direct, when experts evaluate the criteria as a percentage (sum of evaluations of all criteria 100%) and ranking (prioritisation). The evaluation and comparison of mobility systems were performed in two stages: when the multi-criteria evaluation is performed according to the indicators of each factor separately and when performing a comprehensive assessment of the smart mobility system according to the integrated significance of the indicators. A leading city is identified and ranked according to the smartness level. The aim of this article is to create a hierarchical evaluation model of the smart mobility systems, to compare the smartness level of Vilnius, Montreal, and Weimar mobility systems, and to create a ranking.

Analisis Sistem Pendukung Keputusan Pemilihan Asisten Dosen Menggunakan Metode SAW di STMIK Amikom Surakarta

Asisten dosen merupakan sumber daya manusia yang sangat membantu dosen saat berlangsungnya matakuliah praktek. Agar asisten dosen yang direkut sesuai dengan kebutuhan dan memiliki kemampuan yang baik dalam mendampingi mahasiswa saat belajar di laboratorium, maka dalam penelitian ini diusulkan sebuah analisis sIstem pendukung keputusan pemilihan asisten dosen di STMIK Amikom Surakarta. Metode yang digunakan untuk melakukan perhitungan dalam pemilihan asisten dosen adalah Simple Additive Weighting (SAW). Kriteria yang digunakan dalam pemilihan asisten dosen adalah minimal nilai ipk 3,0 dan jenjang semester minimal semester 3, nilai tes tertulis dan nilai tes wawancara. Hasil akhir dari perhitungan menggunakan SAW akan menjadi pertimbangan Ketua UPT laboratorium dapat menentukan mahasiswa yang lolos menjadi asisten dosen, yaitu mahasiswa yang telah menjalani seleksi dan memiliki urutan ranking berdasarkan nilai teratas hingga terbawah dari keseluruhan peserta yang mengikuti seleksi. Kata Kunci: pemilihan asisten dosen, simple additive weighting, sistem pendukung keputusan

Sistem Pendukung Keputusan Penerimaan Pegawai PT. Andalusia Nur Ramadhan dengan Metode Simple Additive Weighting

The purpose of the hiring decision support system is to assist and speed up the decision-making process. There are so many methods that companies can apply in determining employee acceptance to rank prospective employees according to the results of the assessment, examples of methods that can be used are the SAW method or Simple Additive Weighting using the Java Netbeans application and the MySQL database. This research produces a system that can assist in providing decision support for hiring employees. So as to help the main director to determine and select employees who are accepted by the company PT. Andalusia Nur Ramadhan.

Implementasi Sistem Penunjang Keputusan Dalam Pemilihan Calon Team Leader Menggunakan Metode Simple Additive Weighting (SAW)

So far, the selection of prospective Team Leaders in companies is still manual so it is not in accordance with the standard operating procedures for selection. The system designed in this study aims to ensure the accuracy of HRD in selecting candidates Team Leader to match the expectations of the company itself. From the comparison of the methods that have been carried out by researchers, themethod is the Simple Additive Weighting (SAW)right choice and the researcher will implement it with the provisions of the criteria that have been set including, Communication, Problem Solving Skills, Time Management, English, Achievement. To build this system, researchers used the programming languages PHP and MySQL. From the calculation of the level of accuracy, manual calculations get a percentage of 86.6% while the calculation with the proposed system achieves the maximum result with a percentage of 100%. It can be concluded that the calculation with the system is able to determine a suitable candidate as a Team Leader very accurately and on target.

Pemilihan Daerah Penerima Bantuan Logistik Menggunakan Metode Simple Additive Weighting (SAW)

Deputy for Logistics and Equipment is a unit that handles requests for logistical assistance along with equipment in areas that need assistance related to disasters that occur. Provision of Logistics Assistance so far there are still some obstacles including the process of calculating each region that proposes logistics assistance is done with a simple calculation and using microsoft excell and aspects calculated only based on disaster-prone categories without taking into account other aspects. So that areas that really deserve logistical assistance become unable to get help. The solution to the problem is to use Simple Additive Weighting (SAW) algorithm that is applied to a decision support system. The results of the study in the form of a decision support system and the results of the system output showed that the recipient area was Aceh which was chosen with a score of 81.17.

Evaluating Freight Forwarders in the Air Cargo Industry

Freight forwarders are of great importance in the air cargo industry. As the cargo revenue constitutes an important source for airline companies, the evaluation of freight forwarders is vital for airlines’ success. This study employs DEMATEL method in order to prioritize the determined criteria for evaluating freight forwarders from the point of view of an airline. The calculated importance weights are used in an illustrative problem where the ranking of freight forwarders are obtained by employing the simple additive weighting method.

Implementation of Simple Additive Weighting Method in Evaluating Employee Performance for Job Promotion Recommendations

The implementation of decision support system tools in providing decision support for management is absolutely necessary. In its application, this aims to make the decision effective so that the decisions produced can be objective. This research discusses employee performance appraisal by implementing a decision support system. Many methods of decision support systems that can be used to rank, but in this study, the authors use the ranking method known as Simple Additive Weighting (SAW). The SAW method works by summing the weighted attributes that are interrelated. This method is quite simple and is able to provide the right decisions for employees who have the best performance to be recommended in job promotions. In this research, assessment attributes are used, namely education, experience, expertise, collaboration, work quality, and discipline. The final results show that employees on behalf of Ferdinal have the highest value with a value of 0.850.

A Combined Interval Type-2 Fuzzy MCDM Framework for the Resilient Supplier Selection Problem

Selecting the most resilient supplier is a crucial problem for organizations and managers in the supply chain. However, due to the inherited high degree of uncertainty in real-life projects, developing a decision-making framework in a crisp or fuzzy environment may not present accurate or reliable results for the managers. For this reason, it is better to evaluate the potential suppliers in an Interval Type-2 Fuzzy (IT2F) environment for better dealing with this ambiguity. This study developed an improved combined IT2F Best Worst Method (BWM) and IT2F technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model “Atieh Sazan” Co. as a case study, such that the IT2FBWM was employed for obtaining the weight of criteria. The IT2FTOPSIS was utilized for ranking the potential suppliers based on Hamming distance measure. In both phases, the opinions of experts as IT2F linguistic terms were employed for weighting the criteria and obtaining the relative importance of the alternatives in terms of the evaluative criteria. After obtaining the final results, the proposed model was validated by replacing Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) approaches separately instead of BWM for weighting the criteria. After executing both new models, it was found that the final ranking was similar to the final ranking of the proposed model, representing the reliability and accuracy of the obtained results. Moreover, it was concluded that the resilient criteria of “Reorganization” and “Redundancy” are the most determinant measures for selecting the best supplier rather than measures in the Iranian Construction Industry.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK PADA CV. EL GLORY MENGGUNAKAN METODE SAW

Kualitas sumber daya manusia adalah faktor penentu keberhasilan bisnis dari sebuah perusahaan. Dengan mempunyai sumber daya manusia yang baik maka suatu perusahaan dapat menjalankan proses bisnisnya dengan lancar serta sesuai dengan tujuan perusahaan. CV. El Glory merupakan salah satu perusahaan yang bergerak dibidang perdagangan barang dan jasa. CV. El Glory didirikan pada bulan Agustus tahun 2019. Dalam rangka mendorong terciptanya produktivitas kinerja yang terus meningkat, maka CV. El Glory melaksanakan pemilihan karyawan terbaik. Sistem pendukung keputusan dapat membantu pengambil keputusan untuk mendapatkan rekomendasi karyawan terbaik menggunakan metode SAW (Simple Additive Weighting). Pada penelitian ini data yang digunakan berasal dari data internal dan data eksternal. terdapat beberapa kriteria yang dibutuhkan dalam membantu pengambil keputusan untuk memilih karyawan terbaik, yaitu disiplin, kualitas pekerjaan, dan perilaku. Berdasarkan seluruh kriteria dan alternatif yang ada dalam penelitian ini menghasilkan Indah Lestari sebagai karyawan terbaik di CV. El Glory dengan total nilai preferensi yaitu 2,5. Metode SAW merupakan metode yang efektif serta praktis dalam perhitungan untuk menentukan rekomendasi karyawan terbaik di CV. El Glory sehingga pengambil keputusan dapat mempertimbangkan rekomendasi tersebut sesuai dengan prioritas yang ditentukan