Comparative Method of Weighted Product and TOPSIS to Determine The Beneficiary of Family Hope Program

The Family Hope Program (PKH) is a government program that provides cash assistance to impoverished households. The implementation of PKH in Cimrutu Village has not been implemented optimally, namely prioritizing the targets of PKH participants who are not yet on targets. This happened because the officers in registering the poor were still using manual methods. To simplify the work and avoid miscalculation of data with the old system, a decision support system was built that could help make decisions on PKH recipients quickly and more accurately. The calculation method used is the Weighted Product (WP) method. Data collection methods used in this study were interviews and documentation. System development in this study uses waterfall through black-box testing. System design tools in the form of DFD and ERD. The software used in making this application is Visual Studio 2012, Xampp, and Crystal Reports. The programming language used is Java with its supporting database using MySQL. This decision support system is expected to be able to help officers in Cimrutu Village in selecting and determining communities that are eligible for PKH

Strategi Pemasaran dengan Mengurangi Komplain Konsumen pada UKM Skd

Transportasi memegang peranan penting dalam pembangunan dan perkembangan suatu daerah berkaitan dengan mobilisasi pergerakan arus orang dan barang/jasa. Perusahaan yang bergerak dalam bidang jasa tidak lepas dari masalah-masalah yang terjadi selama proses pemberian layanan. UKM SKD merupakan USAha yang bergerak di bidang distribusi dengan menyediakan jasa transportasi barang dengan. SKD sendiri merupakan singkatan dari nama pendiri yaitu Siem Kiat Djing. UKM SKD memiliki kendala dalam mengatasi komplain dari konsumen. Dengan menggunakan Fishbone untuk menentukan penyebab masalah yang terjadi. Untuk mempersempit masalah menggunakan metode Urgency, Seriousness, dan Growth (USG) untuk memprioritaskan masalah. Untuk menentukan strategi dengan mengunakan SWOT( Strength, weakness, opportunity, and threat). Pemilihan strategi dengan menggunakan Technique For Others Reference by Similarity to Ideal Solution (TOPSIS). Hasil dari pemilihan strategi yang telah dianalisis dengan metode TOPSIS adalah memuat regulasi baru. Hasilnya Menerapkan managemen penjadwalan (0,5302), merekut tenaga bantuan dengan (0,4698), memberi pelatihan kepada sopir dengan (0,661), dan menerapkan regulasi baru (0,7216). Dengan menerapakan regulasi baru pemilik dapat membuat masalah bisa berkurang. Penerapan regulasi pemantauan terhadap truk secara berkala yang harus dilakukan bersama antara pemilik dengan sopir. Kata kunci: TOPSIS;SWOT;USG

An integrated model to use drilling modular machine tools

Modular machine tools provide a platform for drilling-related operations within automotive companies. The use of these machine tools is widespread; however, manufacturers wishing to use this technology frequently face the challenge of selecting the most appropriate manufacturing system. Accordingly, a comprehensive feasibility analysis procedure is required to assist decision-makers before any investment is made on the preparation of detailed machine design or purchase one. This paper presents a model, which collects the previous works of the authors. To do this, an integrated framework for decision-making of using machine tools is developed. The aim of this model is to enable users to make a logical decision by assessing the strengths and limitations of machine tools. To do this, the parameters which have a key influence on the decision-making process and relevant procedures are identified and integrated into a model. A case study is presented to illustrate the application of proposed model, and results are discussed. The results show that the proposed model is useful in assisting manufacturers in evaluating the performance of a modular machine tool in comparison with other alternatives

MULTI-CRITERIA DECISION APPROACH WITH AHP AND IF-TOPSIS METHODS FOR R&D PROJECT SELECTION PROCESS

In this study, we examined the project selection process in a mould manufacturing company. We ranked 12 criteria via Analytic Hierarchy Process (AHP) and evaluated the most important 8 criteria. Then we applied Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) method, which is the extended version of the TOPSIS method in intuitionistic fuzzy environment. After expressing the decision makers' evaluations in linguistic terms, we turned them into intuitive fuzzy numbers. In the last step, we obtained the project rankings by calculating the closeness coefficient for 5 projects

A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey

[EN] The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.Özcan, S.; Çelik, AK. (2021). A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey. International Journal of Production Management and Engineering. 9(2):81-92. https://doi.org/10.4995/ijpme.2021.14734OJS819292Ahmed, M., Qureshi, M.N., Mallick, J., Kahla, N.B. (2019). 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A fuzzy AHP approach to evaluating machine tool alternatives. Journal of Intelligent Manufacturing, 17(2), 179-190. https://doi.org/10.1007/s10845-005-6635-1Belton, V., Stewart, T.J. (2002). Multiple criteria decision analysis: An integrated approach. Berlin: Kluwer Academic Publishers.https://doi.org/10.1007/978-1-4615-1495-4Camcı, A., Temur, G.T., Beşkese, A. (2018). CNC router selection for SMEs in woodwork manufacturing using hesitant fuzzy AHP method. Journal of Enterprise Information Management, 31(4), 529-549. https://doi.org/10.1108/JEIM-01-2018-0017Çakır, S. (2018). An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design. Journal of Intelligent Manufacturing, 29(7), 1433-1445. https://doi.org/10.1007/s10845-015-1189-3Çelen, A. (2014). Comparative analysis of normalization procedures in TOPSIS method: With an application to Turkish deposit banking market. 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A novel evaluation approach for tourist choice of destination based on grey relation analysis. Scientific Programming, 2016, 1-10. https://doi.org/10.1155/2016/1812094Gurmeric, V.E., Dogan, M., Toker, O.S., Senyigit, E., Ersoz, N.B. (2013). Application of different multi-criteria decision techniques to determine optimum flavour of prebiotic pudding based on sensory analyses. Food and Bioprocess Technology, 6(10), 2844-2859. https://doi.org/10.1007/s11947-012-0972-9Hwang, C.L., Yoon, K. (1980). Multiple attribute decision making methods and applications: A state-of-the-art survey. New York: Springer-Verlag.Jahan, A., Yazdani, M., Edwards, K.L. (2021). TOPSIS-RTCID for range target-based criteria and interval data. International Journal of Production Management and Engineering, 9(1), 1-14. https://doi.org/10.4995/ijpme.2021.13323Kabak, M., Dağdeviren, M. (2017). A hybrid approach based on ANP and Grey Relational Analysis for machine selection. Technical Gazette, 24(Supplement 1), 109-118. https://doi.org/10.17559/TV-20141123105333Kang, H.Y., Lee, A.H.I., Yang, C.Y. (2012). A fuzzy ANP model for supplier selection as applied to IC packaging. Journal of Intelligent Manufacturing, 23(5), 1477-1488.https://doi.org/10.1007/s10845-010-0448-6Karaman, S.,Toker, Ö.S., Yüksel, F., Çam, M., Kayacier, A., Dogan, M. (2014). Physicochemical, bioactive, and sensory properties of persimmon-based ice cream: Technique for order preference by similarity to ideal solution to determine optimum concentration. Journal of Dairy Science, 97(1), 97-110. https://doi.org/10.3168/jds.2013-7111Karim, R., Karmaker, C.L. (2016). Machine selection by AHP and TOPSIS methods. American Journal of Industrial Engineering, 4(1), 7-13. https://doi.org/10.12691/ajie-4-1-2Kumru, M., Kumru, P.Y. (2015). A fuzzy ANP model for the selection of 3D coordinate-measuring machine. Journal of Intelligent Manufacturing, 26(5), 999-1010. https://doi.org/10.1007/s10845-014-0882-yNguyen, H.T., Dawal, S. Z. Md., Nukman, Y., Aoyama, H. (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes. Expert Systems with Applications, 41(6), 3078-3090. https://doi.org/10.1016/j.eswa.2013.10.039OECD/FAO. (2019). OECD-FAO Agricultural Outlook 2019-2028. OECD Publishing, Paris.Önüt, S., Kara, S.S., Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2), 3887-3895. https://doi.org/10.1016/j.eswa.2008.02.045Özceylan, E., Kabak, M., Dağdeviren, M. (2016). A fuzzy-based decision making procedure for machine selection problem. Journal of Intelligent and Fuzzy Systems, 30(3), 1841-1856. https://doi.org/10.3233/IFS-151895Özdağoğlu, A., Yakut, E., Bahar, S. (2017). Machine selection in a dairy product company with Entropy and SAW methods integration. Faculty of Economics and Administrative Sciences Journal, 32(1), 341-359. https://doi.org/10.24988/deuiibf.2017321605Özgen, A., Tuzkaya, G., Tuzkaya, U.R., Özgen, D. (2011). A multi-criteria decision making approach for machine tool selection problem in a fuzzy environment. International Journal of Computational Intelligence Systems, 4(4), 431-445. https://doi.org/10.1080/18756891.2011.9727802Ozturk, G., Dogan, M., Toker, O.S. (2014). Physicochemical, functional and sensory properties of mellorine enriched with different vegetable juices and TOPSIS approach to determine optimum juice concentration. Food Bioscience, 7, 45-55. https://doi.org/10.1016/j.fbio.2014.05.001Pang, B., Bai, S. (2013). An integrated fuzzy synthetic evaluation approach for supplier selection based on analytic network process. Journal of Intelligent Manufacturing, 23(5), 163-174. https://doi.org/10.1007/s10845-011-0551-3Paramasivam, V., Senthil, V., Ramasamy, N.R. (2011). Decision making in equipment selection: an integrated approach with digraph and matrix approach, AHP and ANP. The International Journal of Advanced Manufacturing Technology, 54(9-12), 1233-1244. https://doi.org/10.1007/s00170-010-2997-4Pavličić, D.M. (2001). Normalisation affects the results of MADM methods. Yugoslav Journal of Operations Research, 11(2), 251-265. Retrieved May 6, 2020 from http://scindeks.ceon.rs/article.aspx?artid=0354-02430102251PSamanta, B., Sarkar, B., Mukherjee, S.K. (2002). Selection of opencast mining equipment by a multi-criteria decision-making process. Mining Technology, 111(2), 136-142. https://doi.org/10.1179/mnt.2002.111.2.136Seçme, N.Y., Bayrakdaroğlu, A., Kahraman, C. (2009). Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS. 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MULTI-CRITERIA DECISION APPROACH WITH AHP AND IF-TOPSIS METHODS FOR R&D PROJECT SELECTION PROCESS

In this study, we examined the project selection process in a mould manufacturing company. We ranked 12 criteria via Analytic Hierarchy Process (AHP) and evaluated the most important 8 criteria. Then we applied Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) method, which is the extended version of the TOPSIS method in intuitionistic fuzzy environment. After expressing the decision makers' evaluations in linguistic terms, we turned them into intuitive fuzzy numbers. In the last step, we obtained the project rankings by calculating the closeness coefficient for 5 projects

Technology assessment with IF-TOPSIS: An application in the advanced underwater system sector

Technologies are pivotal for firms' success, but also resource consuming. Therefore, managers have to assess and select technologies carefully in order to allocate resources on the most promising ones, grounding their decisions on adequate sets of criteria on which experienced people can express their opinion.This work proposes an application of Multi Criteria Decision Aids to technology assessment, where Decision Support Systems offer an effective support for evaluating technology impact on firms' success, building on experts' judgments.The method is based on a peer-based modification to Intuitionistic Fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSIS). A case study in which this methodology is applied to a company operating in the military sector (Advanced Underwater System) is also presented.Besides the empirical proof of the method's suitability and value in assisting managers in their decision, the paper's contributions are both methodological and theoretical. Methodologically, while allowing a peer-based voting procedure, the method enhances the consensus in the firm and limits the possible biases that a supra-decision maker could introduce. Theoretically, the set of proposed criteria includes many facets of the assessment problem, and avoids being tailored to the investigated technological field, so enhancing its generalizability

Assessment of grinding machine performance in substrate hard disc drive industry

This cross-sectional study investigated the reciprocal relationship between productivity, capabilities and quality towards performance of grinding machine within a model which draws on the performance theory. Specifically, this study also examined the selection factor in productivity, capabilities, quality and performance of grinding machine based on employee’s position and experiences. This study utilized a probability sampling method in the forms of simple random sampling. The questionnaires were personally administered and collected from 146 employees working in one of the substrate hard disc plant (Seagate Technology, Johor). Secondary data was used to support the research result. Factor analysis has confirmed the appropriateness of the aggregation of the questionnaire items in each variable and the values of Cronbach alpha indicated that all the measures are reliable. The data analysis was used SPSS/PASW version 24. Statistical analysis techniques used in order to achieve objective of research are descriptive analysis, different test including t-test and ANOVA, the multiple regression analysis method. Based on different test, workers who had more than 20 years working experiences and non-executive staffs were more satisfied with productivity, quality, capabilities and performance of machine. From a practical data analysis perspective, the results from the current study indicated that productivity was significantly related to the performance of grinding machine. Among six items in productivity, it can be seen that machine should have emergency button system that easy to push during emergency case is the most important criteria in determining the performance of machine. The result indicated that there is significant associated between capabilities and performance. The main item which mostly contributed performance of machine is can be handling with 1 operator/3 machines or equipment simultaneous. Next, there is exists relationship between quality of operation with performance and the main items in quality criteria contributed is the specification machine can come out with better product quality up to 80 percent performance yield. Secondary recorded that yield performance of machine was lies between 99.38 percent until 99.60 percent. The percentage of handling defects was low; less than 1 percent (range between 0.072 to 0.085 percent). Overall, the main factor influenced performance of machine is capabilities facto

Decision Support System Classification And Its Application In Manufacturing Sector: A Review

The purpose of this paper is to review decision support system application trend in manufacturing sector. Following the introduction of decision support system, the paper has discussed the application of decision support system in manufacturing sector and identifies the trend in term of decision support system types and their application types. In year 2011 until 2015, the most preferred decision support system were developed by using the model application. It also been found that, most of the developed decision support system are used to support evaluation activities in manufacturing operations. This review provides research trend on decision support system for the recent five years (2011 -2015) in the context of decision support system application in manufacturing industry

A peer IF-TOPSIS based decision support system for packaging machine selection

Selecting the appropriate manufacturing machine is a very important and complex problem for firms which usually have to deal with both qualitative and quantitative criteria and involve different decision makers whose knowledge is often vague and imprecise. This paper proposes a peer-based modification to intuitionistic fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSIS) and applies it to a packaging machine selection problem. Intuitionistic fuzzy weighted averaging (IFWA) operator has been selected both to obtain the group opinion on the relevance of the single decision makers and to aggregate individual opinions of decision makers for rating the importance of criteria and alternatives. A case study illustrates the application of the modified IF-TOPSIS method in order to select a Vertical Form Fill and Seal (VFFS) for Double Square Bottom Bag (DSBB) machine in food packaging. © 2013 Elsevier Ltd. All rights reserved