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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 27, No 2: August 2022" : 64 Documents clear
Application of the simplex method on profit maximization in Baker's Cottage Nur Zafira Mohd Azman; Nurul Akmal Mohamed; Nurul Farihan Mohamed; Muzirah Musa
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1034-1042

Abstract

Linear programming is an operational research technique widely used to identify and optimize management decision. Its application encourages businesses to increase their output. Instead, however, many organizations most commonly adopt the trial-and-error method. As such, companies find it challenging to distribute scarce resources in a manner that maximizes profit. This study focuses on implementing linear programming to optimize the profit of a manufacturing sector based on the optimized (best possible, efficient) use of raw materials. Our study uses the data gathered on five market bread types from Baker's Cottage reports, i.e., chicken floss, spicy floss, Frank Cheese, Mexico bun, and doughnut. This attribute has been recognized as a linear programming problem mathematically built that was solved using Excel software. The result showed that the Baker’s Cottage unit had to produce 332 loaves of Chicken Floss and 196 loaves of Frank Cheese, as these products objectively contributed to the profit. In contrast, other types of bread did not have to be produced, as their value turned to zero to achieve the maximum monthly profit.
The effects of SiO2@Y2O2S:Eu3+ phosphor on the optic characteristics of white light-emitting diodes Van Liem Bui; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp678-684

Abstract

The study investigated the effectiveness of coating silica nanoparticles (SiO2) and resin-silica nanocomposites poly methyl methacrylate (PMMA)-silicaover the surface of Y2O2S:Eu3+ red phosphors. The purpose of this surface coating is to enhance the optical properties, including the photoluminescence (PL) and long-term stability, of Y2O2S:Eu3+. Two methods used to coat the phosphor with 5-mm silica nanoparticles are dip-coating and sol-gel (Stöber) methods. SiO2 nanoparticles were formed via hydrolysis and condensation reactions, while radical polymerization was performed to fabricate the poly (1-vinyl-2-pyrrolidone). The Y2O2S:Eu3+ surface coating of PMMA-silica composite was performed via two reactions. One is the reaction of SiO2 nanoparticles with methyl methacrylate (MMA) monomer, and the other is MMA-tetraethyl orthosilicate (TEOS) reaction. The results showed that by using the latter method, Y2O2S:Eu3+ yielded better PL and long-term stability. Additionally, surface coating with the PMMA-SiO2 nanocomposite using the second technique resulted in 5% enhancement in PL and stabilized the cathode luminescence (CL) intensity of Y2O2S:Eu3+, compared to those properties of uncoated Y2O3S:Eu3+ phosphor particles.
Staff scheduling for a courier distribution centre using evolutionary algorithm Pua Si Ying; Zeratul Izzah Mohd Yusoh
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp1043-1050

Abstract

Staff scheduling is a combinatorics optimization problem and companies face this complex task on daily basis in constructing a schedule fitting all conditions. In a courier distribution center, staffs are assigned to work in processes of a continuous workflow. Staffs have varying work ability for each process. Instead of generating staff schedule instinctively, it is an advantage to optimize staff’s schedule by measuring the performance of each staff. An optimized schedule improves the operation’s efficiency and fully utilize staffs’ work ability, hence, minimizing the cost. This paper proposed evolutionary algorithm, namely genetic algorithm as the solution to courier center staff scheduling. Based on the result, the produced schedule can reduce up to 30% of the staff in schedule while not affecting operation workflow. The cut down on number of working staffs could amount to a substantial reduction of operation cost every month. The generated schedule is significantly customized and take less time to complete an operation. Although the proposed solution is specific to the use case of a courier distribution center, it is however, potentially a generalize model for the logistics industry, introducing a more effective staff scheduling system to cope with the industry’s ever-rising demands.
Received signal strength indication based clustering and aggregating data using Q-learning in mobile Ad Hoc network Surya Narayana Reddy; Jitendranath Mungara
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp867-875

Abstract

Clustering is a significant idea for extending the scalability and enhancing the energy in the mobile ad-hoc network (MANET). In addition, the clustering concept is used to diminishes the cost of communication. The re-clustering procedure makes expensive, and frequent re-clustering procedure makes extra routing overhead and extra energy utilization. To solve these issues, received signal strength indication (RSSI) based clustering and aggregating data (RCAD) using Q-learning in MANET is proposed. In this approach, we build the clusters by node RSSI. The fuzzy logic system (FLS) is used to select the cluster head (CH) by the node mobility and node utilization energy. Q-learning-based data-aggregation for improving mobile node routing efficiency in MANET. Here, we can find an optimum next-hop node utilizing their Q-values established on the rewards (RD). Since the RD rule is used to decide the best solution for the Q-learning technique. This RD is computed by present bandwidth (PB), present energy (PE), present packet delivery (PDD), and hop count (HC) parameter for selecting the data aggregator from sender to receiver. The experimental outcomes illustrate that the RCAD approach increases 155 CH round and raises 24% cluster lifetime in the MANET.

Page 7 of 7 | Total Record : 64

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