cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Winarno
Contact Email
winarno@staff.unsika.ac.id
Phone
+6285132461564
Journal Mail Official
gointegratif@unsika.ac.id
Editorial Address
Program Studi Teknik Industri, Fakultas Teknik, Universitas Singaperbangsa Karawang Jl. H.S. Ronggowaluyo, Telukjambe Timur, Karawang, Jawa Barat 41361
Location
Kab. karawang,
Jawa barat
INDONESIA
Go-Integratif : Jurnal Teknik Sistem dan Industri
Published by Universitas Singaperbangsa Karawang
ISSN : 27237842     EISSN : 27453510     DOI : https://doi.org/10.35261/gijtsi.v1i01
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering
Go-Integratif : Jurnal Teknik Sistem dan Industri merupakan jurnal ilmiah yang diterbitkan oleh Fakultas Teknik Universitas Singaperbangsa Karawang, dan sebagai sarana publikasi hasil penelitian serta sharing perkembangan ilmu teknik sistem dan industri. Jurnal ini memuat artikel yang belum pernah dipublikasikan sebelumnya yang berupa artikel hasil penelitian, penelitian terapan ataupun artikel telaah yang berkaitan dengan ergonomi, sistem manufaktur, manajemen industri, sistem rantai pasok dan sistem informasi enterprise. Informasi mengenai pedoman penulisan artikel dan prosedur pengiriman artikel terdapat pada setiap penerbitan. Semua artikel yang masuk akan melalui ‘peer-review process’ setelah memenuhi persyaratan sesuai pedoman penulisan artikel. Penerbitan jurnal ini dilakukan dua kali setahun yaitu pada bulan Mei dan November.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 53 Documents
 2   3   4   5   6 
Pemodelan Prediksi Temperatur Freezer Menggunakan Pendekatan Machine Learning Berbasis Framework TensorFlow Davi, Ahmad; Sidiq, Farkhan Jatmiko; Arrizal, Muhammad Aziz; Wibowo, Fahrizal Agil; Gunawan, Taopik Sendy; Aisyah, Andini Nur; Hidayat, Alif Nur
Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 5 No 02 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri
Publisher : Engineering Faculty at Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35261/gijtsi.v5i02.12524

Abstract

Temperature control in freezers is crucial to maintaining product quality and safety, particularly in the food and pharmaceutical industries. Uncontrolled temperature fluctuations can lead to product damage, increased waste, and reduced quality. Machine learning technology offers an effective solution for predicting and controlling temperature, enabling more accurate monitoring and rapid responses to changing conditions. This study aims to develop a machine learning model using the TensorFlow framework to predict freezer temperatures. Temperature data were collected from sensors installed inside the freezer and used to train and test several machine learning architectures, including Long Short-Term Memory (LSTM) and 1D Convolutional (Conv1D) networks. Model development leveraged TensorFlow's advanced features, enabling efficient model creation, training, and testing. The results show that the Conv1D model with a data composition of 90% training, 5% validation, and 5% testing achieved the best predictions, with a test RMSE of 0.02085°C and a test MAPE of 0.33522%. This predictive model has the potential to be used as an early warning system to prevent product damage. This research is expected to significantly contribute to the development of more efficient temperature monitoring and control systems in freezers, with potential applications across industries such as food and pharmaceuticals. The findings also reinforce the substantial potential of machine learning in environmental prediction and monitoring.
Peramalan Permintaan Sepatu Sandal pada UMKM Mulyaharja Kota Bogor Irawan, Suhendi; Sinaga, Antonya Rumondang; Kartinawati, Annisa; Hidayat, Agung Prayudha; Dardanella, Derry; Santosa, Sesar Husen; Indrawan, Purana; Apriliani, Fany; Yusri, Doni; Wijaya, Hendri; Pangestu, Fattah Jati; Rahmawati, Novia
Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 5 No 02 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri
Publisher : Engineering Faculty at Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35261/gijtsi.v5i02.12534

Abstract

MSMEs are one of the important sectors to support economic growth. In the midst of increasingly tight competition, business actors need to implement effective strategies to anticipate fluctuations in market demand so that accurate demand forecasting is a crucial step to ensure optimal stock availability. Currently, MSMEs only make predictions based on instinct and experience, not based on mathematical calculations, so that sometimes there is overstock or understock of the goods produced. This study analyzes the demand for sandals and shoes at MSME Mulyaharja, Bogor City using the moving average and exponential smoothing methods. The purpose of this study is to determine the most accurate forecasting method to optimize inventory management and minimize the risk of shortages or excess stock. Historical sales data for one year is used as the basis for the analysis. The results of the comparative analysis of forecasting errors show that the Moving average method with 2 periods provides the most accurate results, with a Mean Absolute Deviation (MAD) value of 54, Mean Squared Error (MSE) of 3380, and Mean Absolute Percentage Error (MAPE) of 18%. The conclusion of this study is that the 2-period Moving average method is the best method to be applied to Mulyaharja UMKM, by applying this forecasting method, overstock and understock of product inventory can be reduced because the amount of production produced is close to the amount of customer demand.
Penerapan Metode EOQ (Economic Order Quantity) untuk Meningkatkan Efisiensi Pengendalian Persediaan Bahan Baku di Kelana Roaster Adhim, Muhammad Arsil; Zahra, Alyana Mevia; Setiawan, Aulia Nursyifa; Rukmana, Faryal Virgiana Cikal; Pasaribu, Lasma Rintan Antonia
Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 5 No 02 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri
Publisher : Engineering Faculty at Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35261/gijtsi.v5i02.12546

Abstract

Kelana Roaster is a coffee bean supplier that produces roasted coffee beans and sells flavored syrup which has become a coffee provider for 30 coffee shops spread across Bogor City. In order to maintain a safe supply of coffee beans, Kelana Roaster receives supplies of raw coffee beans from farmers in 3 regions, including Garut, Temanggung, and Aceh. The problem faced by Kelana Roaster is the uncertainty of order quantities at certain times so that ordering costs often experience spikes, causing a decrease in profits of 11,877%. This study aims to solve the problem of raw material inventory management at Kelana Roaster through the application of EOQ (Economic Order Quantity). The research method used in this research is a quantitative method with a comparative approach that compares the calculation using ordering costs using the EOQ method with the calculation of ordering costs before EOQ. The results obtained through the application of the EOQ (Economic Order Quantity) method are the total inventory cost of Rp 3,035,645 with an ordering cycle of 2 times per year. This figure shows a savings of 31.936% compared to the calculation of inventory costs previously carried out by Kelana Roaster.

Page 6 of 6 | Total Record : 53

 2   3   4   5   6 

Filter by Year

2020 2024


Reset
Filter By Issues
All Issue Vol 5 No 02 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol. 5 No. 01 (2024): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol. 4 No. 02 (2023): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 4 No 01 (2023): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 3 No 02 (2022): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 3 No 01 (2022): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 2 No 02 (2021): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 2 No 01 (2021): Go-Integratif : Jurnal Teknik Sistem dan Industri Vol 1 No 01 (2020): Go-Integratif : Jurnal Teknik Sistem dan Industri