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Supply chain performance measurement on small medium enterprise garment industry: application of supply chain operation reference Qurtubi, Qurtubi; Yanti, Roaida; Maghfiroh, Meilinda F.N.
Jurnal Sistem dan Manajemen Industri Vol. 6 No. 1 (2022)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v6i1.4536

Abstract

In 2020, the textile industry contributed nearly 7% of Indonesia's gross domestic product. The garment industry is still dominated by small and medium enterprises (SMEs) among the textile products. Although these SMEs are considered one of the economic pillars in Indonesia, many challenges require strategical scale-up to improve their competitiveness. One of the aspects to be improved is supply chain performance, as the supply chain controls material, information, and financial flow from both supply and demand sides. This study seeks to measure and evaluate supply chain performance in the garment industry, focusing the case on small and medium-scale enterprises. The Supply Chain Operation Reference (SCOR) is used for Key Performance Index (KPI) determinants. Performance measurement starts by determining the criteria based on the performance measurement literature and expert opinion. Then, the weight of each criterion on the performance score is determined using the Analytical Hierarchy Process (AHP). Paired comparison questionnaires for the criteria weighting were distributed to experts, and the answers were analyzed. The final performance value is obtained by multiplying the weight with the normalized performance value using the Snorm-De Boer formula. This study obtained 23 indicators from five processes: plan, make, source, deliver, and return, with the final value of SCM performance classified as good. The result can evaluate the company's current condition and propose a strategy to improve its performance.
Halal blockchain: Bibliometric analysis for mapping research Yanti, Roaida; Febrianti, Melinska Ayu; Qurtubi; Sulistio, Joko
Asian Journal of Islamic Management (AJIM) VOLUME 4 ISSUE 1, 2022
Publisher : Faculty of Business & Economics, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/AJIM.vol4.iss1.art6

Abstract

Purpose – The main purpose of this study is to identify patterns and directions of halal blockchain research and find out the development of halal blockchain research trends.Methodology – This study used data from various articles in the Google Scholar database with the publication year limited from 2011 to 2022. Data collection used Harzing's Publish or Perish software. There were 353 articles that matched the keyword and they were processed by bibliometric analysis. Findings – This study found the basic pattern in halal blockchain research, trends in halal blockchain research, the relationship among research, research gaps, researchers who research a lot on halal Blockchain and the most published publications.Implications – This study contributes an overview of bibliometric studies in the halal blockchain literature, which can widen the previous literature and show more focused study topics by examining the abstracts and content of published articles. Findings related to evaluative and relational techniques can be helpful information for researchers, especially those new to this field of study. This bibliometric approach can be invaluable, especially for graduate students in supply chain management, logistics management, and industrial engineering.Originality – The originality offered by this research is to process research documents based on halal blockchain journals on Google Scholar. Thus, a lot of information and knowledge about halal Blockchain over the last 10th years can be useful for further research.
Determining the retail sales strategies using association rule mining Yanti, Roaida; Maradjabessy, Prita Nurkhalisa; Qurtubi, Qurtubi; Rachmadewi, Ira Promasanti
International Journal of Advances in Applied Sciences Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i3.pp530-538

Abstract

Competitive competition in the retail industry requires retailers to maintain improvements and formulate accurate strategies to maintain their competitiveness. A small number of daily visitors visit retail store Y if compared to other retail stores, which leads to decreased store revenue due to the small number of products sold. Therefore, it is crucial to formulate the right business strategy to increase sales by utilizing customer shopping behavior derived from transaction data. The method used is association rule mining (ARM) with a frequent pattern growth (FP-growth) algorithm to determine consumer buying patterns. Data processing results generate five valid rules that meet the specified criteria for an association relationship. Utilization rules are acknowledged by determining retail sales strategies by recommending store layouts, shopping catalogs, and voucher discounts to attract customers.
Bibliometric study of association rule-market basket analysis Yanti, Roaida; Elquthb, Jundi Nourfateha; Rachmadewi, Ira Promasanti; Qurtubi, Qurtubi
International Journal of Advances in Applied Sciences Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i2.pp282-290

Abstract

Association rule-market basket analysis (AR-MBA) is a data mining technique for finding distinguished relationship patterns from a collection of items. The application of AR-MBA is also increasingly widespread, starting from retail and hotels to hospitals. So, bibliometrics related to AR-MBA needs to be done to reveal what research opportunities can be later carried out by reviewing and analyzing publications about AR-MBA. 91 bibliographies in 1 decade from 2012-2022 were collected using Harzing's Publish or Perish (PoP). VOSviewer is also employed to map authorship and publication topic trends. This paper is innovative because it identifies trends and future research directions in data mining, specifically in association with AR-MBA. The findings show publication productivity, top authors, types of publications, annual topic trends within a decade, term distribution, most cited and most influential articles, and research gaps that can be opportunities for further research.