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MENU ENGINEERING FOR DECISION MAKING IN THE HOSPITALITY INDUSTRY: EVIDENCE FROM SALES AND CONTRIBUTION MARGIN ANALYSIS Bimo Kuncoro Jati; Shafa Radiva Assyam; Meisya Anggraini; Kezia Elsty; Rr Christiana Mayang Anggraeni Stj
Jurnal Pariwisata Tawangmangu Vol 4 No 3 (2026): September 2026
Publisher : Institut Teknologi dan Bisnis Kristen Bukit Pengharapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61696/juparita.v4i3.1220

Abstract

This study examines the performance of menu items at Maya at Sailendra Restaurant, JW Marriott Hotel Jakarta, using a menu engineering approach. The study was motivated by the need for data-driven tools to improve menu profitability and operational decision-making in the highly competitive hospitality industry. A quantitative descriptive method was employed using secondary data on selling prices, food costs, and sales volumes. Menu performance was evaluated through Contribution Margin (CM), Menu Mix Percentage (MM%), Average Contribution Margin (ACM), and Average Menu Mix (AMM%), followed by classification into stars, plowhorses, puzzles, and dogs. The findings identified Sarson Da Saag and Paneer Tikka Masala as star items, while Tandoori Roti and Laccha Paratha were classified as plowhorses. The study demonstrates that integrating CM, MM%, ACM, and AMM% provides an objective framework for menu classification and supports strategic decisions regarding pricing, promotion, and menu optimization.