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All Journal International Journal of Organizational Business Excellence (IJOBEX)
Yuli Eni
Bina Nusantara University, Jakarta
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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THE FACTORS AFFECTING EFFICIENCY OF CRUDE PALM OIL IN INDONESIA PALM OIL INDUSTRY Yuli Eni; Christy Agustina; Metta Merlinna; Risya Bella; Roberto M. Arguelles; Sheryl Satorre-Estella
International Journal of Organizational Business Excellence Vol. 3 No. 1 (2020): June 2020
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijobex.v3i1.7129

Abstract

This research aim is to determine the factors affecting efficiency of crude palm oil (CPO) in Indonesia by using simpleregression (T-partial) and multiple regression (F-simultaneous) analysisthrough EViewssoftware. The results of this study indicate that partially is the independent variables that affecting Crude Palm Oil (Y) with a T-Statistic value greater than T table (1.65) are the total concession (7.214855), issued capital(2.087724), total investment (6.538604) andtotal employees (5.167861) with an alpha value of 0.05. While simultaneously,the independent variables that affecting the dependent variable are total concession, authorized capital, issued capital, paid up capital, total investment, total employees with F-statistic value of 16,65554, F table value of 1.94 with alpha value of 0.05 . Therefore, the palm oil industry in Indonesia can improveefficiency and production through maximum use of total concession inputs, issuedcapital, total investment and total employees.
Aggregate Planning using Overtime and Adding Number of Employees to Meet the Convection Industry’s Demand Yuli Eni; Bachtiar H. Simamora
International Journal of Organizational Business Excellence Vol. 5 No. 1 (2022): June 2022
Publisher : Bina Nusantara University

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Abstract

The research aimed to propose the implementation of prediction (forecast) using the approaches of overtime and adding the number of employees in convection industry. This study uses a descriptive type of research with time series method. The research data is quantitative data, which is processed by forecasting methods through Zaitun Time Series, as well as aggregate planning. The data collection techniques are such as interviews, documentation and observations. The results show that the best methods to calculate the prediction in Convection Industry are the Decomposition Multiplicative and Decomposition Additive methods. Conducting aggregate planning in Convection Industry with overtime approach for the Wool Peach product(s) costs about Rp 38,689,840,000; for the Max Mara product(s) it costs about Rp 8,344,647,000; while for the Rayon product(s) it costs about Rp 10,769,950,000. Meanwhile, conducting aggregate planning in Convection Industry with the approach of adding the number of employees for the Wool Peach product(s) costs about Rp 38,630,470,000; for the Max Mara product(s) it costs about Rp 8,343,099,000; while for the Rayon products(s) it costs about Rp 10,768,180,000. Convection Industry is recommended to apply the approach of adding the number of employees so as to increase production rather than using the overtime approach (ARRR, AR).
Co-Authors Bachtiar H. Simamora Christy Agustina Metta Merlinna Risya Bella Roberto M. Arguelles Sheryl Satorre-Estella