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All Journal JurTI (JURNAL TEKNOLOGI INFORMASI) CCIT (Creative Communication and Innovative Technology) Journal
Tutik Maryana
Universitas AMIKOM Yogyakarta
Computer Science & IT

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Journal : CCIT (Creative Communication and Innovative Technology) Journal

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Comparison Analysis of Best First Search Algorithm with A * (star) in determining the closest route in the district Sleman Tutik Maryana; Ripto Sudiyarno; Kusrini Kusrini
CCIT Journal Vol 13 No 1 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1522.128 KB)

Abstract

There are various pathfinding algorithms that have advantages and disadvantages of each algorithm. The purpose of this study is to compare the best-first search pathfinding greedy algorithm with A * (Star) in terms of determining the shortest route in a tent search. The method used in this study is an analytical method for analyzing what algorithms can be applied in track search. Then, the method continued with the design method for the best-first search and A * greedy algorithm, the user interface for the algorithm testing application. The next method is the implementation method, which is the best-first greedy algarithm search and A * implemented in the algorithm testing application. The last method is the method of testing algorithms that will be compared. The conclusions will be drawn from the results of comparison algorithms. The result of this study is the acquisition of a distance comparison between thegreedy best-first search algorithm with A *. The conclusion of this study is that the A * algorithm is able to provide the shortest and optimal route results compared to the BFS algorithm.
Analisys Of Demand and Optimization Of Medicine Prediction Using ABC Analysis and SVR Method In The “MORBIS” Aplication Tutik Maryana; Kusrini Kusrini; Hanif Al Fatta
CCIT (Creative Communication and Innovative Technology) Journal Vol 13 No 2 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.078 KB) | DOI: 10.33050/ccit.v13i2.1098

Abstract

The problem that occurs in hospitals regarding the processing of drug supplies is about the condition of out of stock medicines because hospitals spend around 33% of the total investment in one year only for the investment costs of drugs. To deal with the above problems the hospital must have good logistics management, one way of managing it is by doing good planning. In this research, the writer will use ABC Analysis and Support Vector Regression (SVR) algorithm. For the use of these methods, the following ABC Analysis will be used for the drug classification process, namely by dividing the torch into three main groups based on interests, namely groups A, B and C. Henceforth, the writer will use the SVR motedo to calculate drug predictions. The results that the authors get from this study are ABC analyys classify drugs. Into three groups namely group A with a total of 276 items with a percentage of 22.96% of the total number of items, group B with a total of 396 items with a percentage of 33.11% and C with a total of 528 with a percentage of 43.94% with a total of 1202 drug items. Prediction testing is done by taking a sample of five drugs derived from group classification. The SVR calculation process is done by comparing linear scaling and z normalization preprocessing methods. The result of this research is that MAPE shows that preprocessing with linear scaling produces a better value than compared to z nomrlization and calculation with ABC analysis.
Co-Authors Agatha Deolika Hanif Al Fatta Kusrini Kusrini Ripto Sudiyarno Victor Saputra Ginting