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All Journal Jurnal Sinergitas PkM & CSR Universal Journal of Science and Technology
Sylvia sylvia
Universitas Pelita Harapan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences

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ANALYSIS OF SNACK G SALES FORECAST AT CV. GATSU JAYA PERKASA ABADI USING NAIVE FORECAST, EXPONENTIAL SMOOTHING AND LINEAR REGRESSION METHOD Sylvia Sylvia
UJoST- Universal Journal of Science and Technology Vol. 2 No. 2 (2023): September 2023
Publisher : Faculty of Science and Technology University of Pramita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11111/ujost.v2i2.135

Abstract

Forecast is important tool and method for effective and efficient company operation. In the midst of food and beverage fierce competition, the accurate forecast for product sales has important role for company’s competitive edge. This research is conducted at CV Gatsu Jaya Perkasa Abadi (food and beverage industry), located in North Sumatra. Currently the sales forecast by CV Gatsu Jaya Perkasa Abadi are using the previous period sales data and intuitive to forecast sales for the next period, thus, the forecast is not accurate and results in inefficient and ineffective. In this research, the forecast methods that will be analyzed are exponential smoothing and linear regression method and comparing the forecast deviation versus actual data among exponential exponential smoothing, linear regression and naïve forecast (which currently used by company). The purpose of the research is to recommend the accurate forecast method to company which the recommendation will be based on minimum error (deviation) using MAD dan MAPE between actual data and forecast of snack G product. Research methods that are used in this paper are interview, observation, historical data collection and literature study to support the discussion and analysis of the research. The research analysis result shows the best forecast method for snack G sales at CV Gatsu Jaya Perkasa Abadi is using linear regression method with smallest MAD and MAPE.
PELATIHAN PENINGKATAN DAN PENGEMBANGAN DESAIN PRODUK RAK SEPATU DI UMKM “FURNITURE TANGERANG” Sylvia Sylvia; Boryenko Venjamin; Felippe Matthew Harianto; Kenth Santoso Budiharto; Marvin Warrentan; Nicholas Syahputra; Satriyanto Beka
Jurnal Sinergitas PKM & CSR Vol. 10 No. 3 (2026): June
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jspc.v10i3.10834

Abstract

Furniture Tangerang merupakan usaha mikro, kecil dan menengah (UMKM) yang memproduksi produk furnitur interior seperti lemari, kursi, meja, dan sejenisnya. Meskipun memiliki pengalaman yang cukup kuat, mitra masih menghadapi permasalahan berupa keterbatasan inovasi desain yang selaras dengan tren pasar serta pemanfaatan ruang yang belum efisien pada produk furnitur yang ada. Program pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kemampuan inovasi desain produk Furniture Tangerang melalui pelatihan dan pendampingan dalam pengembangan rak sepatu multifungsi. Metode yang digunakan meliputi observasi lapangan, wawancara dengan mitra dan pelanggan, analisis kebutuhan pelanggan (voice of customer), penyusunan hierarki kebutuhan pelanggan, penentuan spesifikasi target, pengembangan dan pemilihan konsep, serta pembuatan prototipe. Hasil kegiatan menunjukkan bahwa program ini berhasil menghasilkan alternatif desain rak sepatu multifungsi yang berfungsi sebagai tempat penyimpanan sekaligus bangku duduk dengan sistem lipat, sehingga menawarkan efisiensi ruang yang lebih baik dan nilai fungsi tambahan. Program ini memberikan dampak positif bagi mitra dengan meningkatkan pemahaman terhadap pengembangan produk berbasis kebutuhan pelanggan serta memperluas variasi desain produk yang dimiliki.
Co-Authors Boryenko Venjamin Felippe Matthew Harianto Kenth Santoso Budiharto Marvin Warrentan Nicholas Syahputra Satriyanto Beka