PROZIMA (Productivity, Optimization and Manufacturing System Engineering) PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Universitas Muhammadiyah Sidoarjo en-US PROZIMA (Productivity, Optimization and Manufacturing System Engineering) 2541-5115 Risk Evaluation of Musculoskeletal Disorders and Design of Lifting-carrying Facilities <p><em>There are main activities of the worker in UD Askan such as splitting the fish, carrying, and lifting the tubs. Work activities are done manually and the production process continually undergoes. The frequency of activity (15 cycles) in a day causes the risk of fatigue, injury, and Musculoskeletal Disorders (MSDs). Evaluation of the work posture of four workers by Ovako Working Posture Analysis System (OWAS) and Job Strain Index (JSI) methods showed high risk in the process of lifting and carrying a tank. The previous posture caused the worker to bend forward, both legs standing or squatting with both knees, and walk by carrying a tub. The results recommend solving soonest due to the danger to the musculoskeletal. The recommendation shows that lifting methods are required and the design of lifting and transporting equipment is needed. The evaluation posture by OWAS show that the process of carrying a tank is 3 level (immediate repair because it is harmful to the musculoskeletal), and after improvement, it is 1 level (not harmful to the musculoskeletal).</em>&nbsp;<em>Then,</em>&nbsp;<em>JSI indicates any improvement from the 3 levels (posing a hazard) to level 1 (safe work).</em></p> Fitri Agustina Nachnul Ansori Trisita Novianti Ernaning Widiaswanti Ravida Ayu Anggraeni Copyright (c) 2023 Nachnul Ansori, Fitri Agustina, Trisita Novianti, Ernaning Widiaswanti, Ravida Ayu Anggraeni 2023-03-24 2023-03-24 7 1 1 10 10.21070/prozima.v7i1.1605 Salt Packaging Redesign Using Quality Function Deployment (Qfd) Method to Increase Sales (Case Study: Saboh Hate Farmers Group, Kuala Idi Cut, East Aceh) <p><em>Salt is one of the great potentials on the coast of East Aceh Regency which can be developed to boost the economic growth of the community. The location of the research was carried out in the Saboh Hate group located in Darul Aman District, Kuala Idi Cut Village, Aron Muda Hamlet, East Aceh Regency, Aceh Province. Currently, the salt on the market has an attractive packaging design, while the Saboh Hate Farmers Group does not yet have a good or simple packaging, so research is needed to design packaging that can increase competitiveness. The purpose of this study is to determine the characteristics of the salt packaging that consumers want at the Saboh Hate Farmer Group through packaging redesign. The method used is statistical test and Quality Function Deployment (QFD). The research phase includes observation and interviews through questionnaires and processing data through statistical tests, SPSS 20 and House of Quality (HOQ). The results show the characteristics of the salt packaging that consumers want based on the relative weight results including the information needed for salt packaging including weight, halal brand and logo with a value of 28.28%, the salt packaging material used is ordinary clear plastic with a value of 24.27%, The color of the desired salt packaging design is blue with a value of 23.71 and the size of the salt packaging that consumers want is generally a 250 g package with a value of 23.71%.</em></p> Dian Saputra Nurlaila Handayani Yusnawati Copyright (c) 2023 Dian Saputra, Nurlaila Handayani, Yusnawati 2023-03-24 2023-03-24 7 1 11 23 10.21070/prozima.v7i1.1600 Measurement of Supply Chain Management Performance in Sago Flour Business Using the Supply Chain Operation Reference (SCOR) Method to Increase SME Productivity <p><em>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sago Flour UKM Pak Hamid is one of the players in the sago flour industry in Meunaro Village, Peureulak District, East Aceh Regency. The problems experienced were the difficulty of obtaining sago raw materials in the nearest area, delays in sago raw materials from the time of ordering, and the weather often rained in certain months so that the river water was cloudy. The purpose of the following experiment is to see what aspects are the influence of management capacity on Peureulak Sago Flour SMEs, calculate supply chain processing capacity in Sago Flour SMEs using supply techniques, find out the proposed supply chain management performance restoration. The method used means method (SCOR) which is a reference example of supply chain management activities based on procedures which are divided into 5 systems, namely planning, sourcing, creating, delivering, and returning. The results of this study share the final value of supply chain performance in sago flour SMEs is 56.9117 in the average category (Average), then the proposed improvements that can be made by sago flour SMEs in plan activities by adding suppliers to meet the shortage of raw materials, sago flour SMEs are expected to have their own sago stem plants, source by discussing business rules with suppliers, make by adding some new employees, deliver by improving good communication with consumers, improve service to consumers, and make tubs for clean water supplies, return by throwing water when the flour has settled and replaces it with clean water, wash the dregs filter cloth.</em></p> Juwairiah Juwairiah Nurlaila Handayani Yusri Nadya Copyright (c) 2023 Juwairiah Juwairiah, Nurlaila Handayani, Heri Irawan 2023-07-10 2023-07-10 7 1 24 34 10.21070/prozima.v7i1.1604 Minimizing Cost of Milk Raw Material Inventory Using the Economic Order Quantity (EOQ) Method <p><em>Inventory in raw materials is a very important thing to pay attention to by the company in carrying out its business processes. Economy Order Quantity (EOQ) is a method that is generally used in determining raw material availability policies in order to obtain minimum yields. This method will help plan raw material inventory in a company to be more efficient. In a manufacturing company, inventory is classified into three parts, specifically raw goods, semi-finished goods and finished goods. If a supply is sufficient then the production process will run smoothly. The purpose of this study is to make an analysis and make a control plan for milk raw materials contained in CV. Milkinesia Nusantara using the EOQ method. After analyzing the results obtained, the optimal purchase frequency is 240 times a year because milk raw materials are easily spoiled with a total purchase of milk raw materials every time one order is 119 liters, the main raw material is considered safe as much as 183 liters with what was ordered back when the raw material amounted to 457 liters. Then the total cost of availability of the company's raw materials, which was originally Rp. 85,023,395.55 - can be saved to Rp. 42,006,726, - so that the savings that occur are Rp. 43,016,669.55.</em></p> <p><strong><em>&nbsp;</em></strong></p> Anugerah Dany Priyanto Yekti Condro Winursito Isna Nugraha Fitriatus Sholeha Handre Syahrul Fanani Copyright (c) 2023 Anugerah Dany Priyanto, Yekti Condro Winursito, Isna Nugraha, Fitriatus Sholeha, Handre Syahrul Fanani 2023-07-10 2023-07-10 7 1 35 45 10.21070/prozima.v7i1.1611 Supply Chain Optimization Model for Fresh Cow's Milk to Reduce Carbon Emissions and Food Waste <p><em>The food and beverage industry occupies an important position in Indonesia, with growth in 5 (five) years, an average of 8.16%. In 2022, the food and beverage industry contributed more than one-third or 37.77% of the GDP of the non-oil and gas processing industry. However, growth considered positive for the economy is actually a threat to the environment. With the high demand for food, food waste and carbon emissions from all food supply chain (FSC) activities increase. This study raises a case of a dairy product processing supply chain in the West Java region with multiple milk suppliers (KUD Susu), a single processing production plant, multi distributors, and multi-consumer retail with multi-echelon, multi-period, and multi-product friendly conditions. Environment by considering food waste and carbon emissions as a function of the objective model. In solving this problem, the Mixed Integer Linear Programming (MILP) model is used in modeling supply chain processes to optimize total cost/TC, total food waste/TFW, and total carbon emissions/TCE. The results of the completion of the research showed a total cost of IDR 18,036,770,000, a total food waste/TFW of 21,734 liters, and a total carbon emission/TCE of 109,526 l.CO2-eq.</em></p> Nofariza Aulia Jeremi Iwan Vanany Copyright (c) 2023 Nofariza Aulia Jeremi, Iwan Vanany 2023-07-10 2023-07-10 7 1 46 58 10.21070/prozima.v7i1.1617 Analysis of Self-Estimated Pricing (HPS) in the Procurement Department Units 1&2 PT. PJB UP Paiton <p><em>Self-Estimated Price (HPS) is an assumed cost for the procurement of goods and services in accordance with predetermined provisions and sourced from accountable data. In the field of procurement PT. PJB UP Paiton Unit 1&amp;2 still has several errors in determining the HPS which can result in a failed auction. This study uses simple statistical techniques and also uses the Statistical Product and Service Solutions (SPSS) application so that the price intervals used are maximum HPS and minimum HPS. The price interval is the lowest and highest price limits used as the basis for determining the price of goods and services. In determining the HPS in the procurement of goods and services PT. PJB UP Paiton, calculates the HPS using an operational budget that uses five data sources in its determination. Data sources used in determining the HPS are market price data, previous contact prices, target price proposal prices and comparative study prices. The results of the HPS calculation for the procurement of 500 work vests, so that a minimum HPS of Rp. 52,250,000 and a maximum HPS of Rp. 56,080,200. In addition, the authors calculated the procurement of panel wall installation services with a size of 2.5 x 10 meters, so that a minimum HPS of Rp. 9,761,345 and a maximum HPS of Rp. 9,996,250.</em></p> Abdur Rizki Dwi Iryaning Handayani Yustina Suhandini Copyright (c) 2023 Abdur Rizki, Dwi Iryaning Handayani, Yustina Suhandini 2023-07-10 2023-07-10 7 1 59 72 10.21070/prozima.v7i1.1612 Determination the Number and Schedule of Security Officers for Pandemic Period and Hybrid Learning at University <p><em>The recovery condition after the Covid-19 pandemic in various sectors from the economic sector, education, and even tourism requires many adjustments in various factors. A university is an educational institution that applies the concept of online learning in pandemic conditions. Restrictions on activities carried out on campus have an influence on the workload of security officers. In this study, the number of security officers was determined during the pandemic and hybrid learning so as to minimize the costs that must be incurred by the university. Determining the number of security officers needed uses a workload analysis based on interviews and considers several factors such as the target level of environmental security, the wide coverage of the security area, and the workload of the security officers themselves. After knowing the number of security officers needed, then scheduling based on work shifts uses the Tibrewala, Philippe, and Brown algorithm so that the workload is evenly distributed. The results obtained show that during the pandemic 35 security officers are needed with an estimated allocation of IDR 156,103,200 per month and get a savings of IDR 84,287,500,- per month (35.1%). For hybrid learning, it takes 51 personnel with an estimated allocation of IDR 224,303,200,- per month. This cost increases by IDR 68.200.000,- per month (43.7%) of pandemic conditions. This research is expected to provide consideration for universities as one of the steps to make savings and be useful during the pandemic and hybrid learning.</em></p> Rainisa Maini Heryanto Kartika Suhada Winda Halim Grace Vania Copyright (c) 2023 Rainisa Maini Heryanto, Kartika Suhada, Winda Halim, Grace Vania 2023-07-18 2023-07-18 7 1 73 83 10.21070/prozima.v7i1.1618