Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Optimasi Sistem Industri Journal of Engineering Science and Technology Management
Rini Syahfitri, Rini
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Optimizing Pharmaceutical Logistics through Sales Forecasting of Black Cough Syrup 100 ml to Support Competitive Advantage at PT "X" Yulia M. Zai, Yovita; Syahfitri, Rini
Journal of Engineering Science and Technology Management (JES-TM) Vol. 5 No. 1 (2025): Maret 2025
Publisher : Journal of Engineering Science and Technology Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jestm.v5i1.225

Abstract

The pharmaceutical industry faces increasing pressure to maintain efficient supply chain operations amid dynamic market conditions. This study aims to identify the most accurate sales forecasting method to optimize pharmaceutical logistics and support the competitive advantage of PT “X” in producing Black Cough Syrup 100 ml. Using historical monthly sales data from August 2023 to January 2025, the study applies four quantitative forecasting techniques: Single Moving Average (SMA), Weighted Moving Average (WMA), Single Exponential Smoothing (SES), and Linear Regression. Forecast accuracy is evaluated using Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). The results reveal that the 3-period SMA method yields the lowest forecast error (MAD: 954; MAPE: 21.09%) and is the most suitable model for the case. These findings highlight the strategic importance of integrating forecasting methods into pharmaceutical logistics to improve production planning, reduce stockout risks, and enhance customer satisfaction. By adopting accurate forecasting tools, PT “X” can strengthen interdepartmental coordination, improve inventory turnover, and build a sustainable competitive edge in the pharmaceutical market.
Algoritma Heuristik untuk Menentukan Biaya Crashing Minimum pada Project Network dengan Dua Jalur Kritis: Studi Kasus Proyek Produksi Electrical House oleh PT X Yuliandra, Berry; Syahfitri, Rini
Jurnal Optimasi Sistem Industri Vol. 14 No. 2 (2015): Published in October 2015
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v14.n2.p259-278.2015

Abstract

PT X is a company engaged in the production of the module, ship relay station (Electrical House)as well as oil and gas mining equipment. The company uses a project-based production system in the production process of that equipment. Type of project usually performed is the Engineering-Procurement-Construction (EPC) project. EPC is a type of project that involves process engineering, material procurement, and products construction. PT X main product is a module or electrical house (E-House). Activities can be disrupted by a variety of conditions in the project implementation phase, such as weather and other unforeseen events. These conditions can hamper the process and affect the performance on the field.Activity scheduling and load out process which often suffer from delays caused project deadlines are often past the limit is given by the client. As in the case of E-House project examined in this study, its implementation has been delayed and should be accelerated for 8days. Therefore, the crashing project can greatly assist in adjusting the implementation plan with the actual condition. Crashing project analysis conducted based on project network diagram. The critical path is determined using Critical Path Method (CPM). Based on analysis results, project execution time can be shortened up to 8 days earlier. (From the normal time of 94 days to 86 days) at the cost $ 4.203.093,25.
Co-Authors Berry Yuliandra Yulia M. Zai, Yovita