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All Journal International Journal of Industrial Engineering and Engineering Management Jurnal Teknik Industri dan Manajemen Rekayasa
Yosef Daryanto, Yosef
Industrial Engineering Department Universitas Atma Jaya Yogyakarta
Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

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Business Intelligence for Decision Support System for Replenishment Policy in Mining Industry Seto, Franklin Chandra Pragnyono; Daryanto, Yosef; Diar Astanti, Ririn
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.7245

Abstract

The mining industry has unique characteristics in the sense that usually, the plant is located in a remote area while the headquarters are located in an urban area. These conditions pose challenges for the industry related to coordination within companies. This coordination is very important, especially in relation to the decision-making that must be carried out by the company. One of the important managerial decisions is related to the replenishment policy. To make replenishment decisions, companies need past data, such as biodiesel consumption rate, and current data, such as current stock and storage capacity, where the source of those data is in the plant. Often, decisions must be taken quickly because they have impacts on the continuousness of production operations at the plant. However, the remote location and shipping routes across rivers have created new challenges in the flow of goods and services supply because the shipment depends on the tides of the river. This research proposes a business intelligence system that collects, sorts, and visualizes data, then analyzes the replenishment decision to support decision-making in the mining industry. The system uses Microsoft Power BI software which is integrated with the company’s ERP system. To illustrate the applicability of the proposed system, it is applied to a coal mining company, especially in relation to the replenishment policy of biofuel. The result of this study indicates that the proposed system can work. In addition, it can reduce decision-making time by 220.65%.  
Perancangan aplikasi untuk peramalan penjualan dan perencanaan pembelian persediaan ayam potong Dewi, Agnes Nanda Puspita; Daryanto, Yosef
Jurnal Teknik Industri dan Manajemen Rekayasa Vol 2 No 1 (2024)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jtimr.v2i1.9016

Abstract

Many web-based applications have been developed to help business activities. Web-based applications can be accessed from computers or mobile phones with various specifications and memory capacities, making it easier for many users. In this research, a web-based application was developed to assist in forecasting and planning activities for purchasing broiler chickens to be sold by a small business. Forecasting and purchase planning for broiler chickens were carried out to overcome shortages and excess supplies caused by fluctuating demand and the absence of sales recording and evaluation. Forecasting is carried out using the FB Prophet method which has the smallest error. Purchase calculation takes into account weight loss and losses due to dead chickens. The design starts with designing the user interface, creating source code, testing, and deploying the program. The application was built with Visual Studio Code with the Python programming language, Flask micro-framework, and XAMPP localhost. The web-based application that has been created helps owners and workers determine purchase amounts and show previous historical data. This application helps make planning easier and more accurate.
Business Intelligence for Decision Support System for Replenishment Policy in Mining Industry Seto, Franklin Chandra Pragnyono; Daryanto, Yosef; Diar Astanti, Ririn
International Journal of Industrial Engineering and Engineering Management Vol. 5 No. 1 (2023)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v5i1.7245

Abstract

The mining industry has unique characteristics in the sense that usually, the plant is located in a remote area while the headquarters are located in an urban area. These conditions pose challenges for the industry related to coordination within companies. This coordination is very important, especially in relation to the decision-making that must be carried out by the company. One of the important managerial decisions is related to the replenishment policy. To make replenishment decisions, companies need past data, such as biodiesel consumption rate, and current data, such as current stock and storage capacity, where the source of those data is in the plant. Often, decisions must be taken quickly because they have impacts on the continuousness of production operations at the plant. However, the remote location and shipping routes across rivers have created new challenges in the flow of goods and services supply because the shipment depends on the tides of the river. This research proposes a business intelligence system that collects, sorts, and visualizes data, then analyzes the replenishment decision to support decision-making in the mining industry. The system uses Microsoft Power BI software which is integrated with the company’s ERP system. To illustrate the applicability of the proposed system, it is applied to a coal mining company, especially in relation to the replenishment policy of biofuel. The result of this study indicates that the proposed system can work. In addition, it can reduce decision-making time by 220.65%.  
Waste reduction of 3PL warehouse operation to overcome excessive overtime Asmoro, Evelyn Nathaniela; Daryanto, Yosef
Jurnal Teknik Industri dan Manajemen Rekayasa Vol 3 No 2 (2025)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jtimr.v3i2.13358

Abstract

Excessive overtime was a persistent issue in the warehouse operations of a 3PL company, where employees frequently exceeded the Indonesian government’s legal limit of 18 overtime hours per week due to daily working hours surpassing the 11-hour threshold. To analyse and address this problem, several structured methods were applied. Process Activity Mapping was used to classify activities into value-added, non-value-added, and necessary non-value-added categories, followed by Value Stream Mapping to visualize process flow and measure total cycle time. The 5 Whys analysis was then employed to identify root causes of delays and inefficiencies, leading to the application of the ECRS principle (Eliminate, Combine, Rearrange, Simplify) to redesign workflows and propose targeted improvements. As a result, the redesigned processes, supported by the modification of stock card formats, implementation of a kanban board, and development of Standard Operating Procedures, successfully reduced average working hours to 10.72 hours per day and decreased total process cycle time by 16.7 percent (65.9 minutes), demonstrating a notable improvement in warehouse efficiency and regulatory compliance.
Co-Authors Asmoro, Evelyn Nathaniela Dewi, Agnes Nanda Puspita Diar Astanti, Ririn Krämer, Klaus Seto, Franklin Chandra Pragnyono