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Journal : Proceeding of the Electrical Engineering Computer Science and Informatics

Makassar Smart City Operation Center Priority Optimization Using Fuzzy Multi-Criteria Decision- Making Fachrul Kurniawan; Aji Prasetya Wibawa; Munir Munir; Supeno Mardi Susiki Nugroho; Mochamad Hariadi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.284 KB) | DOI: 10.11591/eecsi.v4.1010

Abstract

The development of smart city operation room of Makassar possesses several equally important stages which are equally important. There are four stages of development that are 1) data center construction, 2) camera distribution around the city , 3) wall room monitoring construction, and 4) smart operation room architecture construction. Since the time and cost are limited, it forces the project manager to be able to manage and  control the  priority in  conducting the  project. There are several usable criteria to determine the priority in conducting the project development through criteria consideration of the entire project stages. Project priority optimization system aims at making every single project activity effective including its evaluation process. It also exposes a ranking illustration of foremost project priority by providing cost preference of the entire development stages. Fuzzy Multi-Criteria Decision-Making is used to illustrate the project priority rank and further to determine the alternative optimal option in conducting the project. This enforces particular project to  allocate its  cost to  the  project  with  a higher level of cost necessity. The company, therefore, enables to make effective funding for the entire project based on the level of importance and time achievement and subsequently it promotes  accessible  technology integration.  The  conducted experiment suggests that the first construction of the project is data center construction followed by wall room construction and  CCTV  distribution. This  is  relevant  with  optimization value result of data center 0,405 higher than A2 0,42 for wall room construction and A3 CCTV distribution 0,24.
Opinion Detection of Public Sector Financial Statements Using K-Nearest Neighbors Ahmad Dwi Arianto; Achmad Affandi; Supeno Mardi Susiki Nugroho
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (248.178 KB) | DOI: 10.11591/eecsi.v4.1113

Abstract

The identification of ethical violations committedby the auditor is very difficult to do. Artificial intelligence offersanomaly detection as an alternative method for detecting theopinion anomaly which can be an early indicator of the opiniontrading occurrence. This paper proposes the use of originalfeatures from public sector rather than the use of modifiedfeatures from the private sector to be applied in opinion detectionin public sector. By using 60% Holdout validation, 1-NNclassification showed that original featured from the public sectoroutperformed the modified featured from the private sector by5.82% through 13.10% under F-Measure Criterion and by4.22% through 9.56% under AUC criterion.