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Sari YP, Kusumawati E, Saleh C, Kustiawan W, Sukartingsih. 2018. Effect of sucrose on callogenesis and preliminary secondary metabolic of different explant (Myrmecodia tuberosa). Nusantara Bioscience 10: 183-192. Myrmecodia tuberosa Jack is a medicinal plant that contains bioactive compounds, such as flavonoids, tannins, tocopherols, phenols, and an abundance of minerals, that are useful as antioxidants. With the constant increases in popularity of the medicinal plant, the M. tuberosa is threatened by extinction if over-exploitation continues. Thus, the effort to conserve this plant is vital. Tissue culture is an alternative method to conserve and produce active compounds that are similar to those of the native ant nest plant with callus. The addition of certain compounds such as sucrose can affect the secondary metabolite content through in vitro plant or callus. The aim of this research was to find the explant sources (cotyledon, stem, tuber, and root), determine the best growth regulator to produce the callus, and evaluate the optimum sucrose concentration to enhance secondary metabolite production of the callus. The results showed that callus was obtained from all explant sources and all growth regulators. The best callus that was marked by a friable green and yellowish green callus was provided by cotyledon with the growth regulator of 2 mg⋅L-1 of 2.4-dichlorophenoxyacetic acid (2.4-D) and 2 mg⋅L-1 of kinetin. Calli treated with 30 g of sucrose resulted in the best secondary metabolites, containing alkaloids, phenols, flavonoids, saponins, and steroids.

Considerable attention to coordinate the system between buyer and vendor has become an interesting issue to efficiently increase the performance of supply chain activities. Joint economic lot size model (JELS) has been introduced by many researchers as the spirit of coordinating the flow of material from the vendor to its downstream. As an inventory replenishment technique, JELS model is centered on reducing joint total cost of vendor and buyer by simultaneously deciding optimal delivery lot size, number of deliveries, and batch production lot. It is appropriate to take into account transportation costs as the function shipping weight and distance since delivery lot size has interrelated with shipping weight. Hence, this study constitutes an effort to develop the model of JELS by incorporating transportation cost. The solution procedure of the model is developed for solving two problems which are incapacitated and capacitated model. In addition, numerical examples were provided to illustrate the feasibility of the solution procedure in deriving optimal solution. The result presents central decision making which is useful for coordination and collaboration between vendor and buyer.

This paper deals with the problem of transportation and quality within a Just-in-Time (JIT) inventory replenishment system. Formerly, transportation and quality problem are often modelled separately in most integrated inventory lot-sizing models. Hence, this paper develops an integrated vendor-buyer lot-sizing model by considering transportation and quality improvements into a JIT environment. The model is developed for minimising a total vendor–buyer system cost by optimising decisions such as delivery quantity, production batch, number of shipments, and process quality. Numerical examples and sensitivity analysis are provided to illustrate the proposed model. The developed model was also compared with an enumeration method to analyse the effectiveness of the proposed model to find the optimum solution. The results emphasise that the proposed model contributes to a new approach and obtains a near optimum solution for inventory replenishment decisions. The results are also beneficial to JIT practices as the model can improve the transport payload and reduce the chance of defective products and improving quality-related costs.

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A company needs to implement production planning to minimize time and cost. Forecasting and scheduling are two methods which should be conducted in production planning. By implementing the learning and forgetting curve methods, the labor needs as well as the decrease of labors performance after break can be predicted. Firstly, various learning curve models are presented, then each model was analyzed one by one so that the model with the smallest error rate could be determined. A case study conducted in the learning curve model is presented with data derived from the production floor. The four main purposes of this study were to calculate the percentage of each station learning curve, learning and forgetting curves in the company, minimum initial cost, and predict the number of employees needed for the lowest in the number of the work station company. The results in the percentage achieved for the learning curve is 91.47%, the gluing station 78.46%, variation sewing station 98.10%, thumb sewing station 88.17%, omo connect sewing station 89.65%, machine sewing station 87.33%, omo folding sewing station 85.42, rubber tide sewing station 92.51%, sewing station tide studs 72.37%, omo tape sewing station 61.74%, and vilcro sewing station 75.89%, respectively. By analyzing the percentage of each station learning curve, a comparison between the highest and lowest percentage learning curve on the company was made.  Thus, it is known that omo tape sewing station needs another operator as the additional labor. The percentage of the forgetting curve is 91.59%. Through a search conducted on the cumulative hours of the productive company, the initial cost of production can be minimized to 15.600 Indonesian rupiah.

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