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Operational Productivity Index Patterns in Logistics Services Using Mundel Model: Pola Indeks Produktivitas Operasional dalam Layanan Logistik Menggunakan Model Mundel Putra, Boy Isma; Ardiansah, Ach. Yoga
Indonesian Journal of Law and Economics Review Vol. 20 No. 3 (2025): August
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijler.v20i3.1505

Abstract

General Background Productivity measurement is essential for logistics companies to maintain operational performance and resource efficiency. Specific Background The operational activities of Ninja Xpress during 2024 experienced fluctuating output and rising costs of labor, energy, and maintenance, requiring systematic evaluation. Knowledge Gap Previous studies discussed the Marvin E. Mundel method separately from strategic analysis, while integrated measurement and strategy formulation within a single logistics company remain limited. Aims This study measures operational productivity and formulates improvement strategies using the Marvin E. Mundel quantitative approach combined with SWOT analysis. Results The calculated productivity index shows monthly variation, with the highest value recorded in September at 129.81% and the lowest in April at 97.56%, while the SWOT matrix positions the company in Quadrant I, indicating strong internal capacity and favorable opportunities. Novelty The integration of numerical productivity indices with structured internal–external evaluation provides a comprehensive diagnostic framework. Implications The findings support data-driven decision making, periodic performance monitoring, and strategic planning to strengthen logistics operations and competitiveness. Keywords: Operational Productivity, Marvin E Mundel Method, SWOT Analysis, Logistics Operations, Productivity Index Key Findings Highlights: Monthly values varied widely across the 2024 period Strong internal capabilities aligned with external opportunities Integrated quantitative and strategic assessment guides planning
Work Posture Risk Classification Using OWAS QEC and Nordic Body Map: Klasifikasi Risiko Postur Kerja Menggunakan OWAS QEC dan Peta Tubuh Nordic Pranoto, Wiji; Putra, Boy Isma
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.2041

Abstract

General Background Poor work posture in manual tasks is frequently associated with musculoskeletal complaints and reduced occupational safety. Specific Background Ergonomic assessment tools such as Ovako Work Posture Analysis System, Quick Exposure Check, and Nordic Body Map are commonly applied to evaluate physical workload and body discomfort among workers. Knowledge Gap However, integrated evaluation using multiple assessment methods within the same workplace remains limited, resulting in incomplete risk characterization. Aims This study aims to identify work posture risk levels, determine body parts experiencing discomfort, and propose corrective actions through combined OWAS, QEC, and Nordic Body Map assessments. Results Observational scoring and questionnaire analysis reveal several postures categorized as moderate to high risk, with dominant complaints in the back, shoulders, and lower limbs, indicating the need for immediate ergonomic intervention. Novelty The study provides a comprehensive cross-method comparison that strengthens consistency of risk identification within a single case study. Implications The findings support practical redesign of tasks, tools, and working positions to promote safer and more sustainable work systems in industrial settings. Keywords: Ergonomics, Work Posture, Musculoskeletal Disorders, OWAS, Quick Exposure Check Key Findings Highlights Several tasks classified into urgent corrective category Back and upper limb discomfort most frequently reported Task redesign proposed to reduce physical strain
Workload Analysis Reveals Excess Operator Capacity and Incentive Requirements: Analisis Beban Kerja Menunjukkan Kelebihan Kapasitas Operator dan Persyaratan Insentif Shabirin, Muhammad; Putra, Boy Isma
Indonesian Journal of Innovation Studies Vol. 27 No. 2 (2026): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i2.2043

Abstract

General Background: Workload measurement is a critical component in manufacturing management to ensure balanced labor allocation and cost control. Specific Background: PT. XYZ, a wooden board manufacturing company, faces high production targets requiring operators to maintain consistent productivity without additional staffing. Knowledge Gap: Although workload analysis is commonly applied to determine optimal workforce levels, limited studies explicitly connect workload measurement results with structured incentive determination in manufacturing settings. Aims: This study aims to calculate operator workload using the Workload Analysis (WLA) method and determine appropriate incentives based on workload exceeding normal capacity. Results: Work sampling revealed productive percentages of 78%–83%, and WLA calculations showed workload levels of 106%–115%, indicating overcapacity conditions. The excess workload ranged from 6% to 15%, forming the basis for incentive allocation proportional to overload levels. Novelty: This study integrates work sampling, allowance calculation based on ILO standards, and workload analysis to establish a quantitative linkage between workload percentage and incentive determination. Implications: The findings provide a managerial framework for incentive policy formulation without increasing the number of operators, supporting cost control while maintaining production targets in manufacturing operations. Keywords: Workload Analysis, Work Sampling, Operator Productivity, Incentive Determination, Manufacturing Operations Key Findings Highlights Operator capacity levels exceeded standard workload thresholds across all stations. Productive activity percentages ranged between seventy-eight and eighty-three percent. Incentive allocation was proportionally calculated from quantified overload values.
Co-Authors Achmad Nuzul Amri Affandi , Ghozali Rusyid Agil, Mochamad Sofwan Aldy Tasandy Andriansyah Alfian Fajar Gunawan Ali Akbar Ardana, Muhammad Rizky Ardiansah, Ach. Yoga Aska Putra Pamungkas Athika Sidhi Cahyana Atikha Sidhi Cahyana Atok Irawan Cahyana , Atikha Sidhi Cholifah Cholifah, Cholifah Damayanti, Titik Nur Dani Budihamsyah Dedy Dedy Dewi Andriyani Diwanti Faradiba, Nabila Edi Widodo, Edi Faizal Mega Hardiansyah Fajar Alifka Hadi Fandra Prastyo Al Havish Fazrur Suman Prambahan Felly Denia Rochman Ghozali Rusyid Affandi GR, Sayid Hana Catur Wahyuni Handaru A. Putra Hayatal Falah, Agus Ifan Wahyu Pranata Dewantara Indah Apriliana Sari Irawan, Atok Irma Dwi Setyowati iswanto Iswanto Iswanto Jakaria, Ribangun B Jamaaluddin Kharisma, Aditya Nur Khatamy, Mohammad Reza Lazuardani, Zidan Rasyidi Luhur Arif Santoso Marodiyah, Inggit Marzuki Ibrahim Masad Hariyadi Misbaghi, Yoni Fajar Mochamad Andre Firdiansyah Mochamad Nuri Affa Mochammad Imam Mashuri Much Syafiudin Muhammad Bayu Aji Saputra Muhammad Kelvin Alfindo Muhammad Rifqi Maulana Nasoik, M. Kholisun Novitasari, Melisa Pamungkas, Aska Putra Pranoto, Wiji Pratama, Muchammad Ikbal Pratama, Setya Adi Prayoga Dwi Firmansyah Puspista Handayani Putri, Natasya Kurniawan R. Erik Hidayat Ramadhani, Satria Ribangun Bamban Jakaria Rita Ambarwati Rohman, Ahmad Fathur Romi, Mochammad Sari, Indah Apriliana Satria Ramadhani Seftiardiyah, Yenni Setiyono, Wisnu Panggah Setya Adi Pratama Setya Budi Shabirin, Muhammad Shazana Dhiya Ayuni Sofillauny, Zahara Sultan Afli Susanto, Dani Tedjo Sukmono Thurmudhi, Moch Ibad Titik Nur Damayanti Wachidatul Bahiyyah, Siti Wafika Urfa Maulidah Wiwik Sulistiyowati Wiwik Sumarmi Wulandari, Indah Apriliana Sari Yulianto, Rizky