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All Journal PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Jurnal Teknik Industri Terintegrasi (JUTIN) Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) JISO : Journal of Industrial and Systems Optimization Jurnal Ilmiah Wahana Pendidikan Jurnal Pengabdian Masyarakat Aufa (JPMA) Abdimas Awang Long: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Sosial dan Sains eProceedings of Engineering RESLAJ: Religion Education Social Laa Roiba Journal
Paramaditya Arismawati
Telkom University
Religion Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : eProceedings of Engineering

 1 
Perencanaan Kebijakan Persediaan Untuk Meminimasi Biaya Total Persedian Dengan Pendekatan Metode Periodic Review (r,s,s) Pada Part Aksesoris Paramaditya Arismawati; Ari Yanuar Ridwan; Budi Santosa
eProceedings of Engineering Vol 2, No 2 (2015): Agustus, 2015
Publisher : eProceedings of Engineering

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Abstract

Abstrak PT.XYZ merupakan salah satu perusahaan yang bergerak di bidang distribusi, after sales service dan retailer kendaraan merk xxx. Permasalahan yang terjadi pada PT.XYZ yaitu tingginya permintaan material aksesoris periode Juni 2014 – Januari 2015 tetapi tidak diimbangi stok persediaan material di gudang yang menyebabkan terjadinya stockout pada gudang. Permasalahan stockout terjadi karena belum adanya kebijakan persediaan, termasuk belum adanya penentuan besarnya safety stock untuk meredam fluktuasi permintaan. Pada peneltian ini, akan dikembangkan kebijakan persediaan untuk PT.XYZ termasuk menghitung biaya total persediaan dan besarnya safety stock. Metode yang digunakan adalah periodic review (R,s,S). Pada metode ini akan ditentukan parameter interval pemesanan (R) , kombinasi antara s (reorder point) dan S (maximum level) yang berpengaruh terhadap pengendalian persediaan. Sedangkan, material aksesoris yang dianalisis pada penelitian ini sebanyak 350 SKU. Berdasarkan analisis berdasarkan pola permintaan, terdapat pola lumpy dengan 58% dan pola erratic 42% yang mempunyai pola distribusi tidak seragam. Maka untuk membantu menentukan forecast demand menggunakan perhitungan Simulasi Monte Carlo. Hasil dari perhitungan simulasi ini kemudian akan menjadi input-an demand dalam metode yang digunakan. Hasil dari perhitungan biaya total persediaan kondisi usulan di PT.XYZ menggunakan kebijakan periodic review (R,s,S) yang mampu menurunkan biaya total persediaan hingga 63% lebih rendah dibanding biaya tota persediaan kondisi aktual. Menggunakan usulan kebijakan persediaan periodic review (R,s,S) mampu meningkatkan service level, sebesar 10% lebih tinggi dibanding service level kondisi aktual. Kata kunci : Material Aksesoris Mobil, stockout, backorder, Periodic Review (R,s,S), Monte Carlo Abstract
Analysis of The Service System In The General Poly RS Husada Utama With Discrete Simulation Alisa Audria Fadillah, Pinkkan; Sayid Albana, Abduh; Arismawati, Paramaditya
eProceedings of Engineering Vol. 12 No. 2 (2025): April 2025
Publisher : eProceedings of Engineering

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Abstract

Hospitals require high efficiency, with one major challenge being the management of patient queues. At Husada Utama Hospital, long queues lead to waiting times of up to 90 minutes due to an imbalance between patient arrivals and service capacity. This study aims to reduce waiting times and improve service levels by modeling the queuing system using discrete simulation. Observation data from 08.00 to 17.00 on busy days (excluding special holidays) were used, processed, and simulated using Arena Software. Model verification and validation were conducted by comparing simulation results with actual data through T-tests. Under current conditions, the average waiting time at the Nurse Station is 47.86 minutes (72% utility), at the General Poly 144.86 minutes (89%), and at the Specialist Poly 163.97 minutes (89%). After applying improvement scenario 1, which adds one APKM unit, waiting times dropped to 26.80 minutes (68% utility) at the Nurse Station, 94.03 minutes (83%) at the General Poly, and 105.23 minutes (84%) at the Specialist Poly. This represents a reduction in waiting time of 60.82%, 35.08%, and 35.83% respectively. Scenario 1 is proven to be the most effective in reducing average waiting times with optimal utility. Kata kunci— Queue, Arena, Hospital, Discrete Simulation
Co-Authors Abduh Sayid Albana Agnia , Nilna Alisa Audria Fadillah, Pinkkan Ari Yanuar Ridwan Ayu Endah Wahyuni Budi Santosa Diba, Elsa Rachma Farah Febrianti, Putri Amelia Friska Nur Azizah Huki Chandra Iwan Vanany Maulidia Eka Erlina Muhammad Fikri Julianugerah Najwa Zuklizatuz Zahiroh Prasetyo, Muhammad Bayu Prihardianto, Rahaditya Dimas Putra, Reinardus Andoni Nasera Rafsanjana, Sasotya Rigan Safitri, Berliana Zunaidi, Rizqa Amelia