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Journal : Journal of Engineering Science and Technology Management

The Influence of Warehouse Operational Performance on the Acceleration of Goods Delivery at PT. Satria Antaran Prima Tbk Padang Branch Syifa Tanjung, Lailatul; Kumala Sari, Resy; Yusmita, Yesi; Syahrin Hasibuan, Alfi; Aliza, Nur
Journal of Engineering Science and Technology Management (JES-TM) Vol. 4 No. 1 (2024): Maret 2024
Publisher : Journal of Engineering Science and Technology Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jestm.v4i1.168

Abstract

This research aims to analyze the influence of warehouse operational performance on the acceleration of goods delivery at PT. Satria Antaran Prima Tbk Padang Branch. Optimal warehouse operational performance is one of the key factors in supporting supply chain effectiveness, especially in speeding up the delivery of goods to consumers. The research method used is a descriptive method with data collection through sources in the warehouse and logistics department. The data obtained was analyzed using descriptive methods to test warehouse operational processes regarding the speed of delivery of goods. The research results show that there is a significant influence between warehouse operational performance and the acceleration of goods delivery. This means that improvements in storage processes, inventory management, and distribution arrangements in warehouses can directly increase the speed of delivery of goods to consumers. Therefore, PT. Satria Antaran Prima Tbk is advised to continue evaluating and improving warehouse operational performance as part of a strategy to increase customer satisfaction.
Process of Processing Moringa Leaves into Chocolate Moringa at PT. Mond Nature Sustainable Tanjung, Lailatul Syifa; Silma , Muhammad; Yusmita, Yesi; Sari, Resy Kumala
Journal of Engineering Science and Technology Management (JES-TM) Vol. 4 No. 2 (2024): September 2024
Publisher : Journal of Engineering Science and Technology Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jestm.v4i2.193

Abstract

In addition to considering food ingredients, processing techniques are one of the important factors in producing high-taste food and maintaining nutritional consistency. In Indonesia, there is a term for food processing that uses English. This study aims to analyze food processing techniques. The method used in this study is a qualitative descriptive method. The data collection technique in this study is carried out by observing individuals who work as production heads. The results of the study showed that food processing techniques included harvesting techniques, drying techniques, milling techniques, sieving techniques, chocolate making techniques and packaging techniques.
Application of TOPSIS and K-Means Clustering Methods in Recommendations and Analysis of Study Program Interests for New Students Rusnedy, Hidayati; Kasini; Tanjung, Lailatul Syifa; Yusmita, Yesi
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.v5i1.251

Abstract

The selection of a study program is one of the crucial initial decisions for prospective students when entering college. This decision is ideally based on a good understanding of their interests, talents, and abilities so that prospective students can study optimally and in accordance with their potential. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision-making method where the best alternative has the longest distance from the negative ideal solution and has the shortest distance from the positive ideal solution. The selection of these criteria and alternatives aims to produce relevant and accurate recommendations in helping prospective students determine the choice of study program that best suits their potential and preferences. The results of these recommendations are then further analyzed to group the results of the recommendations based on the category of interest. The K-Means Clustering method using the K-Means method with the results of C1 with 9 Respondentsts of less interested study programs, C2 with 25 Respondentsts of moderately interested study programs, and C3 with 21 Respondentsts of highly interested study programs