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All Journal Teknika TEKMAPRO Journal of Industrial Engineering and Management Jurnal technoscientia AKUNTANSI DEWANTARA Journal of Industrial Engineering Management JOURNAL OF MECHANICAL ENGINEERING, MANUFACTURES, MATERIALS AND ENERGY Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri JURNAL REKAYASA SISTEM INDUSTRI INTECOMS: Journal of Information Technology and Computer Science Jurnal Serambi Engineering JURNAL PENDIDIKAN TAMBUSAI JKIE (Journal Knowledge Industrial Engineering) JIEMS (Journal of Industrial Engineering and Management Systems) SAINTEK: Jurnal ilmiah Sains dan Teknologi Industri STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Procuratio : Jurnal Ilmiah Manajemen Jurnal Sistem Teknik Industri Jurnal Migasian Akamigas Balongan Indramayu Unistek: Jurnal Pendidikan dan Aplikasi Industri Jurnal Media Teknik dan Sistem Industri Jurnal Teknik Industri Terintegrasi (JUTIN) Reswara: Jurnal Pengabdian Kepada Masyarakat JURMATIS : Jurnal Manajemen Teknologi dan Teknik Industri JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Ilmiah Wahana Pendidikan Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Industrika : Jurnal Ilmiah Teknik Industri Go-Integratif : Jurnal Teknik Sistem dan Industri Jurnal Migasian KREATIF Jurnal Pengabdian Masyarakat Sains dan Teknologi Journal of Integrated System
Agustian Suseno
Universitas Singaperbangsa Karawang
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Journal of Industrial Engineering Management

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COMPARATIVE ANALYSIS OF MOVING AVERAGE AND DOUBLE EXPONENTIAL SMOOTHING METHODS FOR FORECASTING ASTM A252 GR 2 PIPE DEMAND AT PT XYZ Agustin, Ardita Dwi; Momon S, Ade; Suseno, Agustian; Maulidin, Wildan Fatchan
Journal of Industrial Engineering Management Vol 9, No 3 (2024): Journal of Industrial Engineering and Management
Publisher : Center for Study and Journal Management FTI UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33536/jiem.v9i3.1897

Abstract

Raw material inventory planning is a crucial aspect in the manufacturing industry to ensure smooth production and cost efficiency. However, PT XYZ has not implemented a forecasting method in its raw material planning system, so that procurement decisions are still reactive to actual demand. This study aims to analyze and compare forecasting methods using Double Exponential Smoothing (DES) and Moving Average (MA) to determine the most accurate method in projecting raw material needs for Non-API spec pipe products, type ASTM A252 GR 2 at KT 24 PT XYZ. The data used is historical demand data, which is then analyzed using POM-QM for Windows software. The results of the analysis show that the Moving Average method with a two-month period (MA-2) has the smallest Mean Squared Error (MSE), which is 182067, and a Mean Absolute Percentage Error (MAPE) value of 1.24%, which indicates a higher level of accuracy than other methods. Thus, the MA-2 method is recommended to be implemented in PT XYZ's raw material planning system to improve production efficiency and reduce the risk of excess or shortage of stock. For further research, it is recommended to develop a forecasting model by considering external factors such as market trends and seasonality, and integrating machine learning or hybrid forecasting methods to improve prediction accuracy. In addition, the implementation of an Enterprise Resource Planning (ERP)-based system with a forecasting module can also be a solution for long-term planning efficiency.
COMPARATIVE ANALYSIS OF MOVING AVERAGE AND DOUBLE EXPONENTIAL SMOOTHING METHODS FOR FORECASTING ASTM A252 GR 2 PIPE DEMAND AT PT XYZ Agustin, Ardita Dwi; S, Ade Momon; Suseno, Agustian; Maulidin, Wildan Fatchan
Journal of Industrial Engineering Management Vol 9, No 3 (2024): Journal of Industrial Engineering and Management
Publisher : Center for Study and Journal Management FTI UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33536/jiem.v9i3.1889

Abstract

Raw material inventory planning is a crucial aspect in the manufacturing industry to ensure smooth production and cost efficiency. However, PT XYZ has not implemented a forecasting method in its raw material planning system, so that procurement decisions are still reactive to actual demand. This study aims to analyze and compare forecasting methods using Double Exponential Smoothing (DES) and Moving Average (MA) to determine the most accurate method in projecting raw material needs for Non-API spec pipe products, type ASTM A252 GR 2 at KT 24 PT XYZ. The data used is historical demand data, which is then analyzed using POM-QM for Windows software. The results of the analysis show that the Moving Average method with a two-month period (MA-2) has the smallest Mean Squared Error (MSE), which is 182067, and a Mean Absolute Percentage Error (MAPE) value of 1.24%, which indicates a higher level of accuracy than other methods. Thus, the MA-2 method is recommended to be implemented in PT XYZ's raw material planning system to improve production efficiency and reduce the risk of excess or shortage of stock. For further research, it is recommended to develop a forecasting model by considering external factors such as market trends and seasonality, and integrating machine learning or hybrid forecasting methods to improve prediction accuracy. In addition, the implementation of an Enterprise Resource Planning (ERP)-based system with a forecasting module can also be a solution for long-term planning efficiency.
Co-Authors Agustin, Ardita Dwi Amelia Mikhalin Amin, Moh. Rizha Fauzi Aminatin, Nita Arafat, Yasir Ari Teguh Septiansyah Arief Wahyu Pamungkas Aripin Aripin Aulia Fashanah Hadining Billy Nugraha Billy Nugraha Bimo Setyo Wibowo Dede Andriyan Dhani Ilham Abdilah Dhimas Igo Pratomo Putro Haniswanto Dimas Nurwinata Rinaldi Donny A. Ferdiansyah Endang Endang, Endang Erdin Arya Perwira Fahriza Nurul Azizah Fajar Tri Aji Fernando Agusto P Firmansyah, Ryan Fitriani, Risma Hamidah, Putri Sekar Hanan, Ahmad Irfan Fauzi Hengky Hengky Hisyam Al Ghifary Ikhsan Galih Prayoga Ilman Firmansyah Jauhari Arifin Jauhari Arifin Jauhari Arifin Jauhari Arifin Kurnia, Mutiara Kusnadi Kusnadi, Kusnadi Lestari, Lugina Lumayani, Puri M. Dhiemas Agung Kurnia Maulana Alfin Faiz Maulidin, Wildan Fatchan Momon S, Ade Muhammad Harun Muhammad Harun Muhammad Rais Budiman Muhammad Ridwan Muhammad Ridwan Muhammad Ridwan Mukhammad Azhari Isfirory Muslimah Ayu Anggraini Nugraha, Asep Erik Nugraha, Asep Erik Nugraha, Billy Prasetyo, Permadi Gilang Reza Setiawan Rianita Puspa Sari Rifki Achmad Rizaldi Risma Fitriani Rizaldi Muarif Ramadhan Rodison Malau Satria, Soma Silvia Indah Lestari Sindy Anggraeni Siti Nurrohmah Steven Andeas Sukanta Sukanta Sukanta Sulthan Ariefta Sunakalis, Geraldo Cikal Surya Kancana, Raden Mas Galih Sutanto, Agung Dwi Sutrisna Sunjaya Stepanus Pamungkas Sitorus Sutrisno Sutrisno Sutrisno Sutrisno, Sutrisno Talsania Pratiwi Vera Pangni Fahriani Wahyudin Wahyudin Wahyudin Wahyudin Winarno Winarno Yulianty, Eka