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Journal : Jurnal Teknik Informatika (JUTIF)

ANALYSIS OF DIGITAL LIBRARY SERVICE QUALITY ON USER SATISFACTION USING WEBQUAL, LIBQUAL AND IPA METHODS Rahman, Eman; Jazman, Muhammad; Zarnelly, Zarnelly; Permana, Inggih
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.942

Abstract

Universitas Pahlawan Tuanku Tambusai has used the information system Senayan Library Management System (SLiMS) version 7. SliMS is an integrated system to provide information to support operational, management and decision-making functions in libraries. However, there are still obstacles in its use, namely, the lack of tools and technology to support the implementation of the SLiMS system, the unattractive SliMS content, the OPAC service menu is less effective in searching for references in the library, and the book collection is rarely updated so it does not meet what the user needs. This study aims to measure the service quality of SLiMS from the user's perspective. This research instrument used Web Quality (WebQual), Library Quality (LibQual), and Importance Performance Analysis (IPA) methods. The results of this study resulted in a good level of system service quality but GAP was still found from perceived performance which still had a value of <0 or -0.63 and a conformity level of 78%, which meant that there were still results of user dissatisfaction with the performance provided by the service. SLiMS Hero University of Tuanku Tambusai. Quadrant A results are a top priority to be improved. the variables are: Easy to navigate (UQ3), Attractive appearance (UQ5), Latest available information (SI1), Provides detailed information (SI4), Provides up to date information (IC3), Cleanliness and beauty (LP2), Lighting and temperature settings (LP3), Guidance from the librarian (AS5).
COMPARISON OF DATA MINING ALGORITHM FOR CLUSTERING PATIENT DATA HUMAN INFECTIOUS DISEASES Nurfadilla, Nadia; Afdal, M.; Permana, Inggih; Zarnelly, Zarnelly
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.983

Abstract

Tuberculosis is known as an infectious disease whose transmission through air intermediaries is caused by the germ Mycobacterium Tuberculosis. This disease has become a case that has almost spread throughout the pelalawan Regency with the number continuing to increase every year so that it is possible to be able to group the areas where this disease spreads. Grouping of tuberculosis data distribution areas using data mining methods in the form of clustering with the data used coming from the Pelalawan Regency Health Office from 2020 to 2022. The data obtained earlier will then be processed using k-medoids, k-means, and x-means algorithms. The beginning of this research was by processing data from each year using these three algorithms. Determination of the most optimal algorithm using DBI or known as the Davies Bouldin Index. The results of the processing of existing indicators are grouped into three sections, namely areas with a high, medium, and low number of cases. From the results of the study, the optimal algorithm in 2020 data is the k-medoids algorithms with a DBI value of 0,553 and in 2021 data, the most optimal algorithm is the k-means and x-means algorithm with similar DBI values of 0,582. Furthermore, the data in 2022 the most optimal algorithms are the k-means and x-means algorithms because they have the same DBI value, which is 0,510.