Fuzzy model tahani as a decision support system for selection computer tablet
Keywords:Computer Table, Decision Support System, DSS, Fuzzy, Tahani.
Tablet computer stores as tablet sales continue to keep pace with technology to meet the needs of consumers of tablet computer buyers, where consumers generally always have considerations or factors before taking a decision on a pur-chase, for example price, brand, screen size , memory, hard drive, or features present on the tablet computer and other factors. To be able to assist it, it needs to be supported into a computerized decision support system. Decision support sys-tems in addition to providing information can also help provide various alternatives that can be selected in the decision-making process. Fuzzy logic is a good way to map an input space into the output space. The research is expected to de-termine which type of tablet computer to choose based on the criteria desired by the user so that the user can easily deter-mine the option to buy a tablet computer based on features, facilities, and price, so that the brand of tablet computer can be purchased by the user.
 Computer Hope, â€œComputer vs. Smartphone,â€ computerhope, 2017. .
 C. Anglano, â€œForensic analysis of WhatsApp Messenger on Android smartphones,â€ Digit. Investig. vol. 11, no. 3, pp. 1â€“13, 2014.
 P. harliana and R. Rahim, â€œComparative Analysis of Membership Function on Mamdani Fuzzy Inference System for Decision Making,â€ J. Phys. Conf. Ser., vol. 930, no. 1, p. 012029, Dec. 2017.
 M. Mesran, M. Syahrizal, S. Suginam, N. Kurniasih, and A. D. Gs, â€œExpert System for Disease Risk Based on Lifestyle with Fuzzy Mamdani,â€ Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 88â€“91, 2018.
 A. Indahingwati, M. Barid, N. Wajdi, D. E. Susilo, N. Kurniasih, and R. Rahim, â€œComparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection,â€ Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 109â€“114, 2018.
 N. H. Phuong and V. Kreinovich, â€œFuzzy logic and its applications in medicine,â€ Int. J. Med. Inform., vol. 62, no. 2â€“3, pp. 165â€“173, 2001.
 T. Simanihuruk et al., â€œHesitant Fuzzy Linguistic Term Sets with Fuzzy Grid Partition in Determining the Best Lecturer,â€ Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 59â€“62, Mar. 2018.
 T. Listyorini and R. Rahim, â€œA prototype fire detection implemented using the Internet of Things and fuzzy logic,â€ World Trans. Eng. Technol. Educ., vol. 16, no. 1, pp. 42â€“46, 2018.
 A. S. Ahmar et al., â€œModeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO),â€ J. Phys. Conf. Ser., vol. 954, no. 1, 2018.
 D. Abdullah, Tulus, S. Suwilo, S. Effendi, and Hartono, â€œDEA Optimization with Neural Network in Benchmarking Process,â€ IOP Conf. Ser. Mater. Sci. Eng., vol. 288, no. 1, p. 012041, Jan. 2018.
 D. Siregar, D. Arisandi, A. Usman, D. Irwan, and R. Rahim, â€œResearch of Simple Multi-Attribute Rating Technique for Decision Support,â€ J. Phys. Conf. Ser., vol. 930, no. 1, p. 012015, Dec. 2017.
 R. Risawandi and R. Rahim, â€œStudy of the Simple Multi-Attribute Rating Technique For Decision Support,â€ Int. J. Sci. Res. Sci. Technol., vol. 2, no. 6, pp. 491â€“494, 2016.
 S. Syamsudin and R. Rahim, â€œStudy Approach Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS),â€ Int. J. Recent Trends Eng. Res., vol. 3, no. 3, pp. 268â€“285, Apr. 2017.
 R. Rahim et al., â€œCombination Base64 Algorithm and EOF Technique for Steganography,â€ J. Phys. Conf. Ser., vol. 1007, no. 1, p. 012003, Apr. 2018.
 R. Rahim, M. Dahria, M. Syahril, and B. Anwar, â€œCombination of the Blowfish and Lempel-Ziv-Welch algorithms for text compression,â€ World Trans. Eng. Technol. Educ., vol. 15, no. 3, pp. 292â€“297, 2017.
 R. Rahim, I. Zulkarnain, and H. Jaya, â€œA review: search visualization with Knuth Morris Pratt algorithm,â€ in IOP Conference Series: Materials Science and Engineering, 2017, vol. 237, no. 1, p. 012026.
 R. Rahim, A. S. Ahmar, A. P. Ardyanti, and D. Nofriansyah, â€œVisual Approach of Searching Process using Boyer-Moore Algorithm,â€ J. Phys. Conf. Ser., vol. 930, no. 1, p. 012001, Dec. 2017.
 R. Ratnadewi, E. M. Sartika, R. Rahim, B. Anwar, M. Syahril, and H. Winata, â€œCrossing Rivers Problem Solution with Breadth-First Search Approach,â€ in IOP Conference Series: Materials Science and Engineering, 2018, vol. 288, no. 1.
 R. Rahim et al., â€œBlock Architecture Problem with Depth First Search Solution and Its Application,â€ J. Phys. Conf. Ser., vol. 954, no. 1, p. 012006, 2018.
 R. Rahim, H. Nurdiyanto, A. S. Ahmar, D. Abdullah, D. Hartama, and D. Napitupulu, â€œKeylogger Application to Monitoring Users Activity with Exact String Matching Algorithm,â€ J. Phys. Conf. Ser., vol. 954, no. 1, 2018.
 V. Tahani, â€œA fuzzy model of document retrieval systems,â€ Inf. Process. Manga. vol. 12, no. 3, pp. 177â€“187, 1976.
 A. Aljuaidi, â€œDecision support system analysis with the graph model on non-cooperative generic water resource conflicts,â€ Int. J. Eng. Technol., vol. 6, no. 4, p. 145, Oct. 2017.
 N. Nurmalini and R. Rahim, â€œStudy Approach of Simple Additive Weighting For Decision Support System,â€ Int. J. Sci. Res. Sci. Technol., vol. 3, no. 3, pp. 541â€“544, 2017.
 A. S. Ahmar, â€œA Comparison of Î±-Sutte Indicator and ARIMA Methods in Renewable Energy Forecasting in Indonesia,â€ Int. J. Eng. Technol., vol. 7, no. 1.6, pp. 9â€“11, 2018.
 A. Rahman and A. S. Ahmar, â€œForecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models,â€ in AIP Conference Proceedings, 2017, vol. 1885.
 A. S. Ahmar, A. Rahman, A. N. M. Arifin, and A. A. Ahmar, â€œPredicting movement of stock of â€˜Yâ€™ using sutte indicator,â€ Cogent Econ. Financ. vol. 5, no. 1, 2017.
 P. Singhala, D. N. Shah, and B. Patel, â€œTemperature Control using Fuzzy Logic,â€ Int. J. Instrum. Control Syst., vol. 4, no. 1, pp. 1â€“10, 2014.