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All Journal Jurnal Teknik Informatika (JUTIF) Jurnal Penelitian Inovatif
Susi Setianingsih
Informatika, Fakultas Teknik, Universitas Jenderal Soedirman, Indonesia
Humanities Computer Science & IT Education Engineering Public Health Social Sciences

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Journal : Jurnal Teknik Informatika (JUTIF)

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IMPLEMENTATION OF THE WATERFALL METHOD IN THE DESIGN OF A WEBSITE-BASED BOOK LENDING SYSTEM Teguh Cahyono; Susi Setianingsih; Dadang Iskandar
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.3.285

Abstract

The application of information technology in the library can increase the acceleration of information to the public. One of the library activities that quite a lot of using paper media is borrowing books. The use of ledgers in borrowing books is tantamount to spending a lot of paper with large data and will cause piles later. Therefore, it is necessary to update the book lending system with integrated information technology in order to increase efficiency and effectiveness in the library. The Book Borrowing System or known as TEMANKU is a book lending system that is integrated with the internet to improve operations in book lending activities in the library. In carrying out this activity, a method must be used to implement it. The waterfall method was chosen because it is easy to implement and the system implementation can be implemented in a better and structured manner. On the other hand, the approach used in the design uses data flow diagram ( DFD). The results of this study resulted in the design of a website-based book lending system.
IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION IN K-NEAREST NEIGHBOR ALGORITHM AS OPTIMIZATION HEPATITIS C CLASSIFICATION Susi Setianingsih; Maria Ulfa Chasanah; Yogiek Indra Kurniawan; Lasmedi Afuan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.2.980

Abstract

Hepatitis has become a public health problem that is generally caused by infection with the hepatitis virus. One type of hepatitis caused by a virus is Hepatitis C. This disease can cause patients to experience inflammation of the liver. In the worst conditions, it can even lead to death. Initial predictions need to be made to increase the awareness of each individual against the threat of Hepatitis C by using the K-Nearest Neighbor method. K-Nearest Neighbor is a classification method that can give a pretty good percentage result in classifying, especially when using large training data. However, K-Nearest Neighbor still has a weakness, namely the determination of the value of K that is less precise so that it can reduce classification performance. To overcome these shortcomings, the researchers used the implementation of Particle Swarm Optimization on K-Nearest Neighbor to find the optimal K value. The existence of this implementation is expected to be able to increase the value of accuracy in classification and overcome solutions to weaknesses in the K-Nearest Neighbor algorithm. From the results of the K-Nearest Neighbor test, the accuracy value is 97.24% at K=5 and K=3. As for the results of testing the implementation of Particle Swarm Optimization on the K-Nearest Neighbor, there was an increase in the accuracy value of 2.07% to 99.31%. This test shows that the implementation of PSO can overcome the shortcomings of KNN and this model can be used as the best solution to determine the classification of Hepatitis C disease.
Co-Authors Dadang Iskandar Delvi Fitri Assary Kurniawan, Yogiek Indra Lasmedi Afuan Maria Ulfa Chasanah Nur Hasna Amatullah Shilna Paradisa Teguh Cahyono