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All Journal Jurnal Teknik Industri Golden Ratio of Data in Summary
Ats-Tsauri, M. Ibrahim
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Control & Systems Engineering Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Strategi Peningkatan Akreditasi Pusat Kegiatan Belajar Masyarakat (PKBM) dengan Pendekatan Interpretive Structural Modeling (ISM) Putera, Hilmana Radhia; Ats-Tsauri, M. Ibrahim; Ropandi, Yaya
JURNAL TEKNIK INDUSTRI Vol. 3 No. 02 (2022): JURNAL TEKNIK INDUSTRI : NOVEMBER 2022
Publisher : DPPM UNIVERSITAS PELITA BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jutin.v3i02.1624

Abstract

PKBM XYZ is a non-formal educational institution that received the recognition of C. This result illustrates that the quality assurance of education is still low there. This research aims to analyze PKBM's accreditation improvement strategy using the Interpretive Structural Modeling (ISM) approach so that it is known which accreditation instruments need to be prioritized for improvement to produce better education and accreditation at PKBM. The data collection method was carried out by distributing questionnaires to experts who are teachers and one of the founders of PKBM. Data analysis and processing using ISM equipped with MICMAC. The results of this study show that in order to improve accreditation at PKBM it is necessary to implement several activities: The first priority is to increase the points of educator experience and educator qualifications; The second priority is to increase the competence points of educators and the suitability of teaching materials; The third priority is to increase the number of learning methods.
A Multi-Criteria Decision Making for Automated Storage System Selection in the Warehousing Industry Using AHP-TOPSIS Purwanto, Cipto; Ats-Tsauri, M. Ibrahim; Syahliantina, Annisa; Azizah, Ghina Farhah; Pratiwi, Christa Dian
Golden Ratio of Data in Summary Vol. 6 No. 1 (2026): November - January
Publisher : Manunggal Halim Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52970/grdis.v6i1.1929

Abstract

The growing demand for customized products and shorter delivery times has intensified the pressure on logistics and warehouse operations to become more efficient, flexible, and responsive. In this context, selecting an appropriate automated storage and retrieval system (AS/RS) is a complex multi-criteria decision-making (MCDM) problem that requires a systematic, quantitative evaluation approach. This study proposes an integrated decision-making framework that combines the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the most suitable automated storage technology for warehousing operations. Four key criteria were identified—Throughput, Accuracy, Ergonomics, and Space Utilization—and three alternatives were evaluated: Miniload, Vertical Carousel, and Vertical Lift. The AHP method was used to derive the relative importance of the criteria, producing consistent weights with a CR value of 8.28%. These weights were subsequently applied in the TOPSIS analysis to rank the alternatives based on their closeness to the ideal solution. The results indicate that Vertical Lift emerged as the optimal choice (CC = 0.6657), followed by Vertical Carousel (CC = 0.4657) and Miniload (CC = 0.3688). Sensitivity analysis, conducted through both One-at-a-Time (OAT) and scenario-based approaches, confirmed the robustness of the decision model under varying preference scenarios. This research contributes to the body of knowledge on warehouse automation decision-making by providing a transparent, quantitative, and adaptable framework that supports managers in enhancing operational performance and optimizing resource utilization.
Co-Authors Azizah, Ghina Farhah Christa Dian Pratiwi Purwanto, Cipto Putera, Hilmana Radhia Ropandi, Yaya Syahliantina, Annisa