Decision Making for Biological Tofu Wastewater Treatment to Improve Quality Wastewater Treatment Plant (WWTP) Using Analytical Hierarcy Process (AHP)

  • Simanjuntak N
  • Zahra N
  • Suryawan I
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Abstract

This research aims to build a support system for tofu wastewater treatment using the Analytical Hierarchy Process (AHP)  method. This research was conducted in one of the household tofu industries in Jakarta. AHP method was used to choose/decide the most effective combination of technologies to treat tofu wastewater. Based on the literature study and inlet characterization, Three alternatives were proposed. Alternative 1 consists of a Collecting tank, Neutralization Tank, Preliminary Sedimentation, Anaerobic Digester, Aeration Tank, and Final Settlement Body. While alternative 2 consists of a Collecting tank, Neutralization Tank, Preliminary Sedimentation, Anaerobic Biofilter, Aeration Tank, and Final Settlement Tank. Alternative 3 consists of a Collecting tank, Neutralization Tank, ABR, Aeration Tank, and Final Sedimentation Tank. The decision criteria used for AHP were effluent quality, land requirement, construction cost and easy maintenance. The primary data used were wastewater flow and outlet concentration. While data of area use , maintenance cost and construction cost were extracted from literature study. The result shows that alternative 3 was the most effective sequence of technology.  Eigen Vector Analysis Recapitulation showed that alternative 1 has an overal value of 0.31, alternative 2 has value of 0.2 and alternative 3 has value of 0.5. Using alternative 3, BOD5 can be removed up to 95%, COD can be removed by maximum of  95% by ABR, TSS can be removed by 80% which met the quality standard.

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APA

Simanjuntak, N. A. M. B., Zahra, N. L., & Suryawan, I. W. K. (2022). Decision Making for Biological Tofu Wastewater Treatment to Improve Quality Wastewater Treatment Plant (WWTP) Using Analytical Hierarcy Process (AHP). Jurnal Riset Teknologi Pencegahan Pencemaran Industri, 13(1), 20–34. https://doi.org/10.21771/jrtppi.2022.v13.no1.p20-34

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