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All Journal Journal of Engineering and Management in Industrial System Jurnal Ilmiah Teknik Industri
Indah, Andi Besse Riyani
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Transportation

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ANALYSIS OF CONSUMER BEHAVIOR IN SHOPPING CHANNEL PREFERENCES IN A DUAL CHANNEL SUPPLY CHAIN STRUCTURE Novawanda, Olyvia; Indah, Andi Besse Riyani
Jurnal Ilmiah Teknik Industri Vol. 12 No. 2 (2024): Jurnal Ilmiah Teknik Industri : Jurnal Keilmuan Teknik dan Manajemen Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jitiuntar.v12i2.30029

Abstract

Physical stores and online stores are one way that companies can continue to survive amidst competition by increasing profits from these two channels. Clothing is one of the textile commodities that is widely traded through physical stores and also online stores. This research identifies the factors that have the most significant influence on consumer preferences in choosing physical stores or online stores. Determining the factors involved adopts the results of previously conducted research. Based on existing research, there are several factors, namely Financial Risk (FR), Performance Risk (PerR), Psychological Risk (PsyR), Perceived Risk (PR), Environment Quality (EQ), Service Quality (SQ), Internet Experience (IE ), and Switching Intention (SI). From these variables, 8 hypotheses were formed. All hypotheses from the model were processed using Structural Equation Modeling with SmartPLS 3 software, it was found that H1, H2, H3, H4, H5, and H7 were accepted. H6 and H8 are rejected.
PROTOTYPING AN IOT-BASED SMART FACTORY SYSTEM FOR LEAN TPS EDUCATION AND SME APPLICATIONS Andi Nurwahidah; Ramadhan, Della Ginza; Lutfi; Azis, Muhammad Fadli; Indah, Andi Besse Riyani
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 13 No. 2 (2025)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

The Production System Laboratory hosts hands-on TPS sessions. Yet, despite efforts to digitize the session experience, until they are recorded it's impossible for us to view adequately what's occurring at workstations.On the other hand, this research project uses the smart factory prototype which is based on the Internet of Things (IoT) to realize the sights and control of production processes. Using MQTT, Node-RED and MySQL, real time production data is captured and can be displayed in this prototype system.Tests of this system were carried out in four TPS work stations. These results show that on average it took 3000 ms to process the data, with an accuracy rate of 99% for recorded production data, and less than one second delay when data was visualized. Moreover, the introduction of this system turned around accrued writing mistakes on WIP tracking by 99 % and shortened it time for recording by up to 90%. The final overall results indicated that the system improved lean-based lab components operations substantially and has potential to be used by small to medium enterprise enterprises (SMEs) looking for economical ways to increase production and process visualization.
Co-Authors Andi Nurwahidah Della Ginza Ramadhan Lutfi Muhammad Fadli Azis Olyvia Novawanda