Pengembangan Kalkulator HPP Penentu Harga Jual Berbasis Generative AI Menggunakan Agile dan Cost-Plus Pricing
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Nuraeni Herlinawati
*
Universitas Bina Sarana Informatika, Jakarta,
Indonesia
- Ratnawati Ratnawati Universitas Bina Sarana Informatika, Jakarta, Indonesia
- Surtika Ayumida Universitas Bina Sarana Informatika, Jakarta, Indonesia
- Lukmanul Hakim Universitas Bina Sarana Informatika, Jakarta, Indonesia (*) Corresponding Author
Abstract
Determining the cost of production is an important aspect of business because it directly affects the setting of product selling prices. Errors in production cost calculation often arise due to users’ limited understanding, inconsistent cost recording, and manual calculations that are prone to mistakes. The implementation of an information system provides an effective solution to reduce these risks. This study aims to design and develop a web-based production cost calculator application (HPP) that enables users to calculate production costs and determine product selling prices using the Cost-Plus Pricing method. The system development follows the Agile model, which includes planning, design, development, testing, and evaluation phases. The use of Artificial Intelligence (AI) in the development phase enables the creation of a more efficient and economical digital system with almost no additional cost. Generative AI is utilized during the development phase to assist in preparing the product backlog, creating the initial program code design, and accelerating the process of identifying and fixing errors through debugging. The results show that the developed HPP application can be used directly by the public without requiring software installation or additional database configuration, and can be accessed free of charge through the provided link. The contribution of this study is to provide a practical, economical, and easily accessible HPP calculator application that can be used by various types of businesses as a tool for determining selling prices based on production costs and target profit, while also demonstrating the use of Generative AI in accelerating the application development process efficiently. The black-box testing results show a success rate of 100%, indicating that all main application functions operate according to the specified requirements.
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References
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Copyright (c) 2026 Nuraeni Herlinawati, Ratnawati Ratnawati, Surtika Ayumida, Lukmanul Hakim
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