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All Journal Journal of Computer Science and Informatics Engineering AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal
Banjarnahor, Wiwin Sry Adinda
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance

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Smart Shopping System: Integration of Web Technology and IoT for Digital Transformation of Small and Medium-Scale Retail Stores Banjarnahor, Wiwin Sry Adinda; Sinuraya, Junus; Prayudani, Santi; Tumanggor, Orli
Journal of Computer Science and Informatics Engineering Vol 4 No 2 (2025): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i2.1217

Abstract

The modern retail sector faces challenges in meeting consumer expectations for efficient and convenient shopping experiences. This research develops a web-based Si-Smart Shop system integrated with Internet of Things (IoT)-based smart shopping cart to optimize retail store operations. The research problem formulation includes reducing customer queue density, providing real-time price information independently, and automating the price label creation process that was previously done manually. The research methodology uses a system development approach with the waterfall model. Implementation results show that the system successfully optimizes operational workflow by reducing consumer waiting time and minimizing price calculation errors. Blackbox testing on 42 test cases demonstrates that all system functionalities meet operational criteria. The main contribution of this research is providing accessible technology solutions for various business scales with affordable investment, addressing operational problems in transaction processes and product information management, as well as improving operational efficiency and service quality in retail environments.
Tree Triple Exponential Smoothing Analysis in Forecasting of Fertilizer Sales Prayudani, Santi; Banjarnahor, Wiwin Sry Adinda; Nugroho, Muhammad Rivan; Tazkiyatun Nisa
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 1 No. 2 (2024): VOLUME 1, NO 2: DECEMBER 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v1i2.49

Abstract

The majority of Indonesia's population relies on the agricultural sector, making fertilizer an essential raw material to increase productivity. PT. Pupuk Iskandar Muda (PIM), faces challenges in maintaining the balance of urea fertilizer production and demand. In 2021, PIM's urea fertilizer production was unable to meet demand, while in 2019, 2020, and 2022 there was overproduction. This inventory non-optimization can lead to productivity bottlenecks and increased storage costs. One solution to this problem is forecasting. This research uses the Triple Exponential Smoothing (TES) forecasting method in forecasting urea fertilizer sales for the next period. The data used is fertilizer sales data from PT PIM for the 2019-2023 period. Evaluation of the accuracy value is done using the MAD, MSE, and MAPE matrices. The results of this study indicate that the TES method with a smoothing weight value of Alpha = 0.4, Beta = 0.2, and Gamma = 0.4 produces a MAD value of 22,017.75, MSE of 990,752,983.08, and MAPE of 22.3% which can be categorized as quite feasible to use in forecasting the demand for urea fertilizer at PT PIM seen from the MAPE value.
Co-Authors Nugroho, Muhammad Rivan Prayudani, Santi Sinuraya, Junus Tazkiyatun Nisa Tumanggor, Orli