Article Per Year (5 Year)
p-Index From 2021 - 2026
1.704
P-Index
This Author published in this journals
All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer MUST: Journal of Mathematics Education, Science and Technology Jurnal Sains dan Informatika Jurnal Sustainable: Jurnal Hasil Penelitian dan Industri Terapan Elsains : Jurnal Elektro Jurnal Inotera EIGEN MATHEMATICS JOURNAL ScientiCO : Computer Science and Informatics Journal Jurnal Pengabdian Kepada Masyarakat (Mediteg) J-ADIMAS (Jurnal Pengabdian kepada Masyarakat) Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Jurnal Humaniora Teknologi Jurnal Humaniora Teknologi Journal of System and Computer Engineering Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Herfia Rhomadhona
Politeknik Negeri Tanah Laut
Religion Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

Published : 31 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 31 Documents
Search

 1   2   3   4 
Peramalan Pendapatan Penjualan Pada Toko Kiki Tirtajaya Menggunakan Metode Regresi Linear Sederhana Herfia Rhomadhona; Ahda Kamalia; Desy Novita Sari; Muhammad Iqbal
Jurnal Sains dan Informatika Vol. 10 No. 1 (2024): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/jsi.v10i1.1230

Abstract

Kiki Shop is a small business focusing on selling various basic necessities in Tirtajaya Village. In response to tight market competition, optimizing stock management and data-driven marketing strategies is highly essential. This study aims to apply a data mining technique specifically the Simple Linear Regression method to project daily store revenue. To comprehensively evaluate model reliability, accuracy performance was tested using three error metrics: Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Based on computational results from historical transaction data, the regression model yielded a MAPE of 18.92%, an MAE of IDR 397,657.14, and an RMSE of IDR 492,237.13. Referring to standard classification, the MAPE value of 18.92% indicates that this forecasting model falls into the Good Forecasting category. The discrepancy between the RMSE and MAE values indicates the influence of extreme values (outliers) in the form of revenue spikes on certain days. Overall, this model is considered valid and representative to assist the business owner in inventory planning and minimizing operational risk.
Co-Authors Ahda Kamalia Apriliyani, Nora Desy Novita Sari Hendrik Setyo Utomo Ines Saraswati Machfiroh Jaka Permadi Khairul Anwar Hafizd, Khairul Anwar Kurnia Dwi Artika Melda Rosalina Muhammad Fajar Muhammad Fajar Muhammad Iqbal Muhammad Khoirul Anam Muhammad Noor Muhammad Noor Ningsih, Tri Murti Noor, Agustian Novia, Risda Nurul Hasanah Nurul Hasanah Rosalina, Melda Tri Murti Ningsih Widiya Astuti Alam Sur Winda Aprianti Wiwik Kusrini Yuniska Fithriyyah Yunita Prastyaningsih