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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) KLIK: Kajian Ilmiah Informatika dan Komputer
Hengki Juliansa
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Computer Science & IT Engineering

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Identifikaasi Tingkat Kerusakan Peralatan Laboratorium Komputer Menggunakan Metode Rough Set Hengki Juliansa; Sarjon Defit; Sumijan Sumijan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 2 No 1 (2018): April 2018
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.204 KB) | DOI: 10.29207/resti.v2i1.274

Abstract

Computer laboratory is a means to support college pratikum. This equipment should always be in a ready-made state or suiTabel for use, whether computer or other means. In case of damage, it should be promptly resolved. To further accelerate the handling of damage, it is necessary a method to identify it. The Rought set method is a solution for this identification by means of several stages: Infomation System; Decision System; Equivalence Class; Descernibilty matrix and Descernibilty matrix of module D; Reduction; Generate Rules. The results of this study from 5 equipment in the computer laboratory STMIK Bina Nusantara Jaya Lubuklinggau after performing the steps of settlement by rough set method found 8 rules to get a new decision is whether the equipment is still worthy of use, repaired or replaced, then this method is very suiTabel applied in identifying the extent of damage.
Penerapan Normalisasi Data Metode Decimal Scaling Dan Metode K-Means Dalam Mengelompokkan Kasus Demam Berdarah Ila Yati Beti; Hengki Juliansa
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1925

Abstract

Dengue fever, caused by a virus transmitted through the bite of Aedes aegypti and Aedes albopictus mosquitoes, continues to show an alarming trend of increasing cases. Although prevention and control efforts have been widely implemented, this increase is raising serious concerns among public health experts and governments. The causes of the increase in dengue fever cases in 2024 may vary, including climate change which affects the distribution of mosquitoes that carry the virus, urbanization which increases mosquito habitat, and changes in human behavior that affect the level of environmental cleanliness. However, this data is often scattered and has different scales, making it difficult to directly analyze. Data analysis of dengue fever cases is important to understand the pattern of disease spread and take preventive steps using the Decimal Scaling method and grouping data using the K-Means method helps in understanding patterns of dengue fever cases. Where is the Decimal Scaling method to produce better and balanced data. After the data is normalized, the next process is to explore information on dengue fever data by applying data mining grouping using the K-Means method. Based on the results of the cendroit test results where cluster 0 has a greater value for each dengue fever grade value as seen in Figure 4, the test results were obtained with a total sample of 197 test data from 2019 to 2023 with 2 number of clusters where cluster 0 has 81 members and cluster 1 has 115 members. So it can be concluded that those who get priority for treatment are more important in the C0 cluster group.
Co-Authors Ila Yati Beti Sarjon Defit Sumijan Sumijan