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All Journal Jurnal Pelita Pendidikan Civil Law Aquacoastmarine Jurnal Online Mahasiswa (JOM) Bidang Keguruan dan Ilmu Pendidikan JIM Pendididikan Bahasa dan Sastra Indonesia Jurnal Ilmiah Mahasiswa Ekonomi Pembangunan Scientiae Educatia: Jurnal Pendidikan Sains JKBM (JURNAL KONSEP BISNIS DAN MANAJEMEN) Seminar Nasional Teknologi Informasi Komunikasi dan Industri Master Bahasa Proceedings of the International Conference on Applied Science and Health Jurnal Bumigora Information Technology (BITe) JOURNAL OF LANGUAGE Proceedings of International Conference on Multidiciplinary Research el-Amwal : Jurnal Ekonomi dan Keuangan Islam Prosiding Seminar Nasional Universitas Serambi Mekkah Jurnal Penelitian, Pendidikan, dan Pembelajaran Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Indonesian Journal of Islamic Counseling Open Access DRIVERset JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah
Nurul Azmi
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Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Jurnal Bumigora Information Technology (BITe)

 1 
Prediksi Penjualan Produk Unilever Menggunakan Metode Regresi Linear Anthony Anggrawan; Hairani Hairani; Nurul Azmi
Jurnal Bumigora Information Technology (BITe) Vol 4 No 2 (2022)
Publisher : Prodi Ilmu Komputer Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v4i2.2416

Abstract

Barokah Shop is a retail store that sells various basic necessities for daily needs. Too much inventory will result in losses such as storage costs and the possibility of a decrease in the quality of goods. On the other hand, a small amount of inventory will reduce a larger profit. This study aims to build a web-based Unilever sales prediction system using a simple linear regression method. Testing the accuracy of the prediction results of sales of Unilever products using MEA and MAPE to see the level of error in the prediction results. The dataset uses Unilever product sales data for 15 months, from January 2021 to March 2022. The dataset is divided into 12 months as training data and 3 months as testing data. Prediction results in the next 3 periods of each type of product produce the same value between the system results and the results of manual linear regression calculations. Testing the error rate on the prediction results for 3 periods, namely January to March 2022, each Ax Deodorant, Bango Kecap, Buavita, Citra Lotion, Citra Soap, Clear Shampoo, Sariwangi, Sunsilk Conditioner, Vixal and Wall's Ice Cream products belong to the category of very accurate forecasting results. With the smallest MAPE value in Sunsilk Conditioner products of 1%. Thus, the linear regression method is very accurate for predicting sales of Unilever types goods.
Co-Authors Aditiya Mario Zai Putra Ahmad Fauzul Hakim Ahmad Muhtadi Anggrawan, Anthony Apriliani Apriliani Asriani Ariani Asriani Asriani Cindy Claudia* Cut Faizah Cut Fauziah Dinda Saputri Eli Nurliza Erfinawati Erfinawati Ettie Rukmigarsari Faisal Faisal Fatikah Rahma Dewi Hairani Hairani Helmi Apriliyatmi Hapwiyah Hery Syahrial Ichsan Ichsan Indani Indani Isbadar Nursit Junaidi Junaidi Lailani Fitria Lazim. N Lazim. N M. Manugeren Maslena Maslena Meutia Nanda* Mujiburrahman Mujiburrahman Mukhlis Mukhlis Mukhlish Muhammad Nur Mukhriza Harahap Munardi Munardi Nayla Husna Afila Nazli Hasan Novianti Muspiroh Nuraiza Nuraiza Nurhabibah Nasution Nurhasanah Nurhasanah Nursafiah, Nursafiah Puji Prastowo Purwarno, Purwarno Rajab Bahry Ria Yulia Gloria Rini Nurul Amla Saadiah Saadiah Siti Komariah Siti Naila Fauzia Suci Rakhmawati Tasya Amalia Vera Devani Vera Wardani Yunasfi Djayus Zariul Antosa