ANALISIS MODEL PERAMALAN PERMINTAAN MINUMAN KOPI MENGGUNAKAN PENDEKATAN TIME SERIES DI COFFEE SHOP

    Cicilia Pradita, - and Yusep Sukrawan, - and Dwi Novi Wulansari, - (2025) ANALISIS MODEL PERAMALAN PERMINTAAN MINUMAN KOPI MENGGUNAKAN PENDEKATAN TIME SERIES DI COFFEE SHOP. S1 thesis, Universitas Pendidikan Indonesia.

    Abstract

    Industri kopi di Indonesia mengalami pertumbuhan pesat, dimana Kota Bandung menjadi salah satu kota yang menunjukkan peningkatan jumlah coffee shop dan pengunjung yang signifikan. Koromi Sip & Slurp sebagai coffee shop yang baru berdiri di Kota Bandung menghadapi tantangan dalam menyusun strategi bisnis untuk pengelolaan persediaan yang optimal. Penelitian ini bertujuan untuk mengidentifikasi pola data dan melakukan peramalan permintaan pada ketiga jenis kopi (sweet coffee, non-sweet coffee, dan manual brew) di Koromi Sip & Slurp. Penelitian ini berfokus pada analisis peramalan permintaan menggunakan pendekatan time series, diantaranya single moving average, weighted moving average, single exponential smoothing, dan double exponential smoothing holt’s. Menggunakan software R Studio dan Microsoft Excel, tahapan yang dilakukan yaitu mengidentifikasi pola data, melakukan peramalan, menentukan peramalan terbaik berdasarkan nilai error, dan melakukan uji validasi. Hasil penelitian ini adalah pola data yang terbentuk dan hasil peramalan pada ketiga jenis kopi. Pola data yang terbentuk pada sweet coffee dan non-sweet coffee adalah pola data trend sementara pada manual brew adalah pola data horizontal. Hasil peramalan pada periode ke-48 untuk sweet coffee adalah 380 cup, untuk non-sweet coffee 95 cup, dan untuk manual brew 18 cup. Hasil peramalan permintaan menggunakan pendekatan time series pada ketiga jenis kopi menunjukkan hasil peramalan yang baik, dilihat dari nilai error yang dihasilkan pada setiap metode terpilih tidak melebihi 20% dan berada dalam batas kontrol moving range chart sehingga dapat dijadikan sebagai dasar pengambilan keputusan dalam menyusun strategi bisnis untuk mengelola persediaan kopi yang lebih baik. The coffee industry in Indonesia is experiencing rapid growth, with Bandung being one of the cities showing a significant increase in the number of coffee shops and visitors. Koromi Sip & Slurp, a newly established coffee shop in Bandung, faces challenges in developing a business strategy for optimal inventory management. This study aims to identify data patterns and forecast demand for the three types of coffee (sweet coffee, non-sweet coffee, and manual brew) at Koromi Sip & Slurp. The study focuses on demand forecasting analysis using time series approaches, including single moving average, weighted moving average, single exponential smoothing, and double exponential smoothing holt’s. Using R Studio and Microsoft Excel software, the steps taken include identifying data patterns, conducting forecasting, determining the best forecast based on error values, and performing validation tests. The results of this study are the data patterns formed and the forecasting results for the three types of coffee. The data patterns formed for sweet coffee and non-sweet coffee are trend patterns, while for manual brew, they are horizontal patterns. The forecasting results in the 48th period for sweet coffee are 380 cups, for non-sweet coffee 95 cups, and for manual brew 18 cups. The forecasting results for demand using the time series approach for the three types of coffee show good forecasting results, as seen from the error values produced by each selected method, which do not exceed 20% and are within the control limits of the moving range chart, so that they can be used as a basis for decision making in developing business strategies for better coffee inventory management.

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    Official URL: https://repository.upi.edu/
    Item Type: Thesis (S1)
    Additional Information: https://scholar.google.com/citations?view_op=list_works&hl=en&user=tdSwtsoAAAAJ ID SINTA Dosen Pembimbing: Yusep Sukrawan: 5978341 Dwi Dovi Wulansari: 6745877
    Uncontrolled Keywords: Deret Waktu, Kedai Kopi, Peramalan, Persediaan, Pola Data Coffee Shop, Data Pattern, Forecasting, Inventory, Time Series
    Subjects: H Social Sciences > HA Statistics
    H Social Sciences > HB Economic Theory
    H Social Sciences > HD Industries. Land use. Labor
    L Education > L Education (General)
    Divisions: Fakultas Pendidikan Teknik dan Industri > Teknik Logistik - S1
    Depositing User: Cicilia Pradita
    Date Deposited: 09 Oct 2025 03:58
    Last Modified: 09 Oct 2025 03:58
    URI: http://repository.upi.edu/id/eprint/142228

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