This study aims to examine the effect of supply chain information integration consisting of internal and external Information Integration on organizational performance, which consists of customer satisfaction, supply chain performance, and financial performance. The technique of collecting data is based on a questionnaire distributed to 185 small food industry owners. Methods of data analysis is based on using SEM-PLS. The results show that internal information integration affected customer satisfaction, supply chain, and financial performance. External information integration is proven to have a non-linear effect on customer satisfaction and on the performance of the supply chain. Customer satisfaction and supply chain performance affect financial performance. Internal information integration is more dominant and plays an important role in increasing the performance of the organization.

The research aimed to determine the appropriate weight criteria and sub-criteria in selecting the chemical solvent supplier. It was also to recommend the best alternative suppliers using a comparative analysis method of Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The research was conducted in one of the chemical manufacturing companies in Indonesia. The type of research was descriptive with a quantitative approach that used primary data sources such as questionnaires, interviews, and observations, and secondary data such as books and journals. The criteria studied were cost, quality, delivery, flexibility, supplier profile, and supplier relationship. The results of using FAHP indicate that the criteria with a major influence on the decision making of supplier selection are quality followed by delivery, cost, supplier relationship, flexibility, and supplier profile in sequence. Then, using FTOPSIS, it recommends that the best supplier alternative decision is Supplier A with a weight value of 0,773 and an approved evaluation status. The results have shown that both methods are suitable for supplier selection, particularly in supporting group decision making and modeling uncertainty.

This descriptive and cross - sectional research was conducted to determine the priority criteria in supplier selection and the best supplier for Timber Industry as the unit of analysis. Data were collected through interview and questionnaire with the operational Manager of the company. The analysis method used was Analytical Hierarchy Process (AHP) that could assist decision making with criteria, sub-criteria, and several alternatives that had been determined by the company. The researchers find that there are four criteria which become the consideration in selecting supplier those are price, product, service, and delivery. From the analysis, it is foundthat the company should prioritize price compared to other criteria in selecting the supplier. Meanwhile, the other criteria (product, delivery, and service) sequentially become the second, third, and fourth priority criteria in selecting the suppliers. The other result of this research is the company can find the order of the best suppliers which can be recommended to the company.

This study aims to bridge the literature gap to examine factors that influence customers in buying a beauty product especially product quality.  The type of research used is descriptive. The use of the method in this study is the quality function deployment (QFD) method which has 6 parts namely; customer needs, technical attributes, relationship matrix, technical assessment, correlation matrix, and competitive assessment. The findings of this study are the attributes that meet BPOM standards, ingredients performance, and the probability of failure become one of the attributes that have the highest value on the part of customer needs that can meet customer satisfaction in product development.

Based on the data, there were still shortages of production from year to year and demand wereunstable in motorcycle chains manufacturer in Indonesia. To overcome these problems, the purpose of this research was to make production planning and inventory control consisting of forecasting, aggregate planning, Master Production Schedule (MPS), and Material RequirementsPlanning (MRP). Forecasting used the additive decomposition method (average of all data), multiplicative decomposition (centered on moving average), and winter method (additive and multiplicative). Aggregate planning used chase strategy, level strategy, and transportation model. Moreover, MRP used lot for lot, Economic Order Quantity (EOQ), and Periodic Order Quantity (POQ) methods. The test shows several results. First, the best forecasting is additive decomposition (average of all data) with MAD value of 3.033,57, MSE with 13.590.490,and MAPE with 10,083%. Second, the best aggregate planning is transportation model with the total cost of Rp7.708.398.390,00. Last, the best MRP method is the lot for lot with total cost Rp7.162.567.653,00.