Having a rapidly growing economy without proper waste handling system and infrastructure has made Indonesia one of the top contributors of plastic marine debris in the world: 3.22 million metric tons of mismanaged plastic waste per year. The mismanagement of waste is worse in the rural area where the number of available public trashcan is limited and the people have no idea where their trash actually ends up. In this research, a case study of waste management in Kampung Cipare - Tenjo, a small village 80 kilometers away from Jakarta, is conducted. The biggest purpose of the research is to educate people about sanitation and waste management, initiated by computing the most optimum number and locations of the public trashcans. The problem is addressed as Maximum Covering Location Problem (MCLP) to determine a set of facility locations that maximizes the total demand population served by the facilities within a prespecified maximum service distance. Two greedy heuristics algorithms: Greedy Adding Algorithm (GAA) and Greedy Adding with Substitution Algorithm (GAAS) are utilized to solve the problem. A sensitivity analysis is also done to check the result on the effect of trashcan number and maximum service distance to demand coverage. Out of the 26 location candidates, it is concluded that the final 10 locations are the most optimum in terms of demand coverage and service distance. The result of the research has been implemented in Kampung Cipare-Tenjo.
In order to increase customer satisfaction and maintain customer loyalty, logistics service providers must pay attention to the quality of service provided, one of which is effecive warehouse management, especially in scheduling the arrival and departure of products transporting vehicles. Therefore, this study discusses warehouse management in form of delivery and pickup scheduling at PT XYZ’s cross-docking warehouse. This study aims to obtain effective delivery and pickup scheduling and minimize operational costs. The Cross-docking Distribution Problem is an np-hard problem, so the Particle Swarm Optimization algorithm is used, which is a metaheuristic method in finding solutions. Based on the result, it was found that effective delivery and pickup scheduling was able to save inventory cost by 3.12% and reduce the percentage of delays from 73% to 0%. The scheduling process using Particle Swarm Optimization requires an average computation time of 26.2 seconds.
This paper is about the selection process of packaging design for liquid organic fertilizer made of chicken slaughterhouse waste in South Jakarta. The purpose of using packaging is to contain, transport, protect, provide product-related information, and market the product. The research aims to determine the most appropriate design, additional features, and the type of plastic as the liquid organic fertilizer container that applies the reverse logistics concept: refillable. Quality Function Deployment (QFD) is applied to select the best packaging type that fulfils consumers’ requirements. This QFD method analyses the features and helps to select the best design out of various liquid container designs available in the market. The results showed that the liquid organic fertilizer to be used is made of thick High-Density Polyethylene (HDPE) plastic bottle with sprays on its screw-type lid that enables the reverse logistics concept.
In material sourcing, one of the procurement processes that should be completed before evaluating and selecting the vendor is making an Owner Estimate (OE). The most common way to arrange an OE is by making Data Inquiry, where the arranger asks for a certain product’s price from a list of providers or vendors. However, this method does not describe in detail how the price of the product is constructed, so the company, which is doing the procurement process, tends to set a higher OE. To reduce this risk, another method to determine OE is introduced. This method applies a Cost Structure method to calculate production and transportation costs, the expenses a vendor should cover when manufacturing the products. Using a total of 20 scenarios that varied the percentage of profits, the increase in carbon steel plate costs, and the overhead costs, using Cost Structure Method can lower the Owner Estimate between 0.51% to 24.46%. The last scenario with 20% increase in profit, 20% increase in carbon steel plate cost and 20% increase in the overhead cost resulted to -2.55% reduce of Owner Estimate. This new method is proven effective as an alternative way to arrange OE for similar material.
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