Combination of AHP Method and VIKOR Method For Assesing Sunday School Teacher

The performance appraisal of Sunday school teacher in the Imanuel Lurang congregation aims to measure and distinguish the quality of performance achieved by Sunday school teacher and decide various policies such as giving rewards to every Sunday school teacher with the best performance, and for Sunday school teacher who have poor performance scores will be given a guiding, approach, etc. The number of criteria in determining the quality of Sunday school teacher is not an easy thing to do by manual. Then it is essential that a computerized performance appraisal-based performance  app can speed up the process of progressing to be more effective and efficient. This research develops decision support systems (DSS) that is dynamic using the PHP programming language, by combining the AHP method that has been refined by the VIKOR method. The AHP method is used in determining the weight of each criterion, and the VIKOR method is used for the ranking process. Test results indicate that the system can provide a sequence of alternative Sunday school teacher that will be used as recommendations for decision makers to determine which Sunday school teachers are quality and not qualified

EVALUASI PENENTUAN PERSONIL IT INFRASTRUKTUR PADA TNI AL MENGGUNAKAN KOMBINASI METODE AHP DAN VIKOR

In the current development of technology, information technology is not only used in the economic field, but is divided into various fields, including the military world of the Navy.  In order to promote the capability of human resources in the field of IT infrastructure in the Navy, it is necessary to select the right personnel in the maintenance of IT infrastructure assets, so as to obtain competent personnel output in answering future challenges. To facilitate the determination of the right IT infrastructure personnel, the author implements a system by combining the AHP and Vikor methods based on Python. The AHP method is used to determine the weight of criteria in the selection of IT personnel, and the Vikor method is used to rank the appropriate IT personnel. With this system, it is hoped that it can be a supporting application to help select IT personnel according to tactical, technical, strategic criteria.Dalam Perkembangan Teknologi Saat ini, Teknologi informasi tidak hanya digunakan dalam bidang ekonomi namun terbagi menjadi beberapa bidang termasuk dalam dunia militer TNI AL.  Untuk membina kemampuan SDM dalam bidang Infrastruktur IT pada TNI AL, dibutuhkan pemilihan personil yang tepat dalam menjaga asset infrastruktur IT, sehingga didapatkan keluaran SDM yang kompeten dalam menjawab tantangan ke depan. Untuk mempermudah penentuan personil IT Infrastruktur yang tepat penulis melakukan implementasi sistem dengan melakukan kombinasi metode AHP dan Vikor berbasis Python. Metode AHP akan digunakan sebagai penentuan bobot dari kriteria dalam pemilihan personil IT dan Metode Vikor untuk melakukan perangkingan terkait personil IT yang sesuai. Dengan adanya system ini diharapkan dapet menjadi aplikasi pendukung untuk membantu pemilihan personil IT yang sesuai dengan kriteria Taktis , Teknis, Strategis

Daleel:simplifying cloud instance selection using machine learning

Decision making in cloud environments is quite challenging due to the diversity in service offerings and pricing models, especially considering that the cloud market is an incredibly fast moving one. In addition, there are no hard and fast rules; each customer has a specific set of constraints (e.g. budget) and application requirements (e.g. minimum computational resources). Machine learning can help address some of the complicated decisions by carrying out customer-specific analytics to determine the most suitable instance type(s) and the most opportune time for starting or migrating instances. We employ machine learning techniques to develop an adaptive deployment policy, providing an optimal match between the customer demands and the available cloud service offerings. We provide an experimental study based on extensive set of job executions over a major public cloud infrastructure

QoS based Web Service Selection and Multi-Criteria Decision Making Methods

With the continuing proliferation of web services offering similar efficacies, around the globe, it has become a challenge for a user to select the best web service. In literature, this challenge is exhibited as a 0-1 knapsack problem of multiple dimensions and multiple choices, known as an NP-hard problem. Multi-Criteria Decision Making (MCDM) method is one of the ways which suits this problem and helps the users to select the best service based on his/her preferences. In this regard, this paper assists the researchers in two conducts: Firstly, to witness the performance of different MCDM methods for large number of alternatives and attributes. Secondly, to perceive the possible deviation in the ranking obtained from these methods. For carrying out the experimental evaluation, in this paper, five different well-known MCDM methods have been implemented and compared over two different scenarios of 50 as well as 100 web services, where their ranking is defined on an account of several Quality of Service (QoS) parameters. Additionally, a Spearman’s Rank Correlation Coefficient has been calculated for different pairs of MCDM methods in order to provide a clear depiction of MCDM methods showing the least deviation in their ranking. The experimental results comfort web service users in conquering an appropriate decision on the selection of suitable service

Aplikasi Pendukung Keputusan untuk Pemilihan Produk Asuransi dengan Metode Entropy dan Vikor pada AJB Bumiputera 1912 Jepara

AJB Bumiputera 1912 Jepara merupakan perusahaan yang bergerak dalam bidang asuransi. Perusahaan tersebut menawarkan berbagai produk dengan bermacam-macam manfaat untuk masyarakat yang ingin menjadi nasabah. Memilih produk asuransi adalah masalah yang sering dihadapi oleh masyarakat. Untuk membantu menyelesaikan masalah pemilihan produk asuransi dibuat perangkat lunak dengan menggunakan dua metode, yaitu Metode Entropy yang digunakan untuk melakukan pembobotan terhadap data dan metode Vikor digunakan untuk melakukan perangkingan terhadap alternatif. Penggunaan kedua metode tersebut menghasilkan akurasi sebesar 63.33%. Akurasi dihitung dengan membandingkan pilihan yang hasilkan secara manual oleh agen asuransi dengan pilihan yang diberikan oleh perangkat lunak. Kata Kunci : Entropy, Vikor, Asuransi, Multi Attribute Decision Makin

Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making

[EN] The hesitant fuzzy linguistic term sets can retain the completeness of linguistic information elicitation by assigning a set of possible linguistic terms to a qualitative variable. However, sometimes experts cannot make sure that the objects attain these possible linguistic terms but only provide the degrees of confidence to express their hesitant cognition. Given that the interval numbers can denote the possible membership degrees that an object belongs to a set, it is suitable and convenient to provide an interval-valued index to measure the degree of a linguistic variable to a given hesitant fuzzy linguistic term set. Inspired by this idea, we introduce the concept of interval-valued 2-tuple hesitant fuzzy linguistic term set (IV2THFLTS) based on the interval number and the hesitant fuzzy linguistic term set. Then, we define some interval-valued 2-tuple hesitant fuzzy linguistic aggregation operators. Afterwards, to overcome the instability of subjective weights, we propose a method to compute the weights of attributes. For the convenience of application, a method is given to solve the multiple attribute decision making problems with IV2THFLTSs. Finally, a case study is carried out to validate the proposed method, and some comparisons with other methods are given to show the advantages of the proposed method.The work was supported in part by the National Natural Science Foundation of China (Nos. 71501135, 71771156), the China Postdoctoral Science Foundation (2016T90863, 2016M602698), the Fundamental Research Funds for the central Universities (No. YJ201535), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).Si, G.; Liao, H.; Yu, D.; Llopis Albert, C. (2018). Interval-valued 2-tuple hesitant fuzzy linguistic term set and its application in multiple attribute decision making. Journal of Intelligent & Fuzzy Systems. 34(6):4225-4236. https://doi.org/10.3233/JIFS-171967S4225423634

HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth

Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method

Ship Hull Principal Dimensions Optimization Employing Fuzzy Decision-Making Theory

The paper presents an optimization method for the ship hull principal dimensions scheme employing the fuzzy decision-making theory. First of all, the paper establishes the fuzzy decision-making model of the ship hull principal dimensions optimization, and then a series of ship hull principal dimensions schemes are accordingly constructed by employing the variable value method. On the basis of this, the fuzzy decision-making method is employed to evaluate the series ship hull principal dimensions schemes. Finally, the optimal ship hull principal dimensions scheme is obtained. The example demonstration verified the proposed method’s validity for ship hull principal dimensions optimization economic performance

Green Logistic Provider Selection with a Hesitant Fuzzy Linguistic Thermodynamic Method Integrating Cumulative Prospect Theory and PROMETHEE

In the process of evaluating the green levels of cold-chain logistics providers, experts may hesitate between several linguistic terms rather than give precise values over the alternatives. Due to the potential profit and risk of business decisions, decision-making information is often based on experts’ expectations of programs and is expressed as hesitant fuzzy linguistic terms. The consistency of evaluation information of an alternative can reflect the clarity of the alternative in the mind of experts and its own controversy. This paper proposes a method to use the value transfer function in the cumulative prospect theory to convert the original hesitant fuzzy linguistic terms into evaluation information based on reference points. We also introduce the parameters related to the disorder of the systemin the hesitant fuzzy thermodynamic method to describe the quantity and quality characteristics of the alternatives. In these kinds of multi-criteria decision-making problems, the weights of criteria are of great importance for decision-making results. Considering the conflicting cases among criteria, the weights were obtained by utilizing the PROMETHEE method. An illustrative example concerning green logistics provider selection was operated to show the practicability of the proposed method.The work was supported in part by the National Natural Science Foundation of China (Nos. 71501135, 71771156, and 71771153), the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23), and the Scientific Research Foundation for Scholars at Sichuan University (No. YJ201535)