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Sri Mutia
Universitas Malikussaleh
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Supply Chain Risk Analysis With MAFMA Method Approach Fatimah Fatimah; Indah Asmara; Sri Mutia; M Sayuti
International Journal of Engineering, Science and Information Technology Vol 1, No 4 (2021)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (275.531 KB) | DOI: 10.52088/ijesty.v1i4.196

Abstract

Palm oil mill is a palm oil and palm kernel processing industry which is a semi-finished product. The palm oil industry is currently growing rapidly in line with the demand for large quantities of CPO and Kernal and their derivatives. In its operation, it is always faced with various risks, from the field to the processing plant. These risks will cause losses to the factory, especially in the form of financial. From the results of field observations obtained 13 kinds of supply chain risks, namely damaged trucks, FFB not up to standard, damaged FFB, insufficient FFB, network error, FFB damaged in the sorting field, boiling problems, problematic polisyndrom, abnormal steem, abnormal processes. /stops, viber cyclone plugs and leaks pipe. Therefore, it is necessary to identify, measure and manage risks to reduce losses caused by supply chain risks. The method used in this study is the MAFMA (Multi Attribute Failure Mode Analysis) method. The MAFMA method is a development of the FMEA method. The results showed that the risk level value contained 4 critical risks on the part of the factory, namely FFB less with a risk level value of 0.096, FFB not according to standards with a risk level value of 0.085, network error with a risk level value of 0.083 and the process running abnormally. /stop with a risk level of 0.073. These 4 critical risks are the priority to be handled. The handling carried out is planning for the right FFB procurement, providing guidance on the harvesting process, stabilizing the network by providing copper rods and planning machine scheduling.
The Effect of Natural Fiber Percentage on the Tensile Strength of Paper Using ANOVA Reza Syahputra; Muhammad Sayuti; Fatimah Fatimah; Sri Mutia
International Journal of Engineering, Science and Information Technology Vol 3, No 2 (2023)
Publisher : Department of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v3i2.448

Abstract

Paper is generally made of cellulose fibers derived from wood raw materials. Increased demand for production will have an impact on forest exploitation which can lead to environmental stability. Alternative natural fibers containing cellulose fiber are biomass waste such as Galangal Stems (Alpinia Galanga), Pineapple Leaves (Ananas Cosmosus), Banana Stems (Musa Paradisiaca), and others. The use of natural fibers can reduce the exploitation of wood as a raw material for paper. The purpose of this study was to determine the effect of natural fibers consisting of galangal stems, pineapple leaves, banana contains, and waste paper on the tensile strength of paper using ANOVA. The ratio of the percentage of fiber passed is galangal stems 50:10 and 50:40, pineapple leaves 50:10 and 50:40, banana contains 50:10 and 50:40, and waste paper 100% or without comparison. Tensile strength was carried out according to ASTM-D638, then data processing was carried out using the One Way ANOVA method. The results showed that the highest tensile strength value of banana stem paper and waste paper with a ratio of 50:10 was obtained at 7.04262 MPa resulting in the best tensile strength compared to other fibers. Factors that affect the tensile strength are the length of the fiber, and the bonds between the fibers are related to the fiber content. The results of this study concluded that the greater the number of material components in the manufacture of recycled paper, the greater the tensile strength of the report produced.
Co-Authors Fatimah Fatimah Indah Asmara M Sayuti Reza Syahputra