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All Journal Jurnal Teknimedia: Teknologi Informasi dan Multimedia
Rachmawati Oktaria Mardiyanto
MTI Universitas AMIKOM Yogyakarta
Computer Science & IT Control & Systems Engineering Engineering

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PEMETAAN LOKASI KEBAKARAN HUTAN DAN LAHAN DI NTB DENGAN MENGGUNAKAN ALGORITMA NAIVE BAYES Rachmawati Oktaria Mardiyanto; Fitriani Fitriani; Ridwan Joko Purnomo; Kusrini Kusrini; Dina Maulina
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 2 No. 2 (2021): Desember 2021
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.49 KB) | DOI: 10.46764/teknimedia.v2i2.44

Abstract

Forest and land fires are one of the environmental problems in terms of economic and ecological harm. The number of cases of forest fires in the province of NTB has increased dramatically, causing dangerous smog. The increasing incidence of forest and land fires is evidenced by the increasing area burned and the frequency of fires in the last few decades. This study aims to classify the locations of forest and land fires and the causes of fires that occur in NTB. This research has used 104 data in three years (2017-2019) taken from the website of the Department of Environment and Forestry of the province of NTB. The classification model for mapping forest and land fires and the causes of fires uses the Naïve Bayes algorithm with an accuracy value of 55.555%. Thus, it can be concluded that the classification model using Naïve Bayes has the potential to be used effectively so that it can classify the location of forest and land fires and the causes of fires.
ANALISIS SENTIMEN PENGGUNA APLIKASI BANK SYARIAH INDONESIA DENGAN MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) Rachmawati Oktaria Mardiyanto; Kusrini Kusrini; Ferry Wahyu Wibowo
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 4 No. 1 (2023): Juni 2023
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v4i1.85

Abstract

Several new Islamic banking products have been created as a result of the increasing popularity of Islamic banking in Indonesia. Due to the technical advances made possible by the globalization era, all operations, including transactions, can be carried out easily and practically. One of the sharia banks that offers mobile banking services is Bank Syariah Indonesia. BSI Mobile still occupies the 49th position in the banking category according to statistics taken from Google Playstore, while other institutions are already in the top 20 positions. 5 linguists will annotate or manually label the app's 55,416 user-submitted reviews and ratings. 13568 review and rating data collected by app users after annotating or labeling and eliminating duplicate data will be used in this research. In the early stages of the sentiment analysis process, case folding, punctuation mark re-moval, stop word removal, and stemming were carried out on review and rating data. The Support Vector Machine (SVM) approach is used to evaluate training data and data testing using stemmed findings. In this study, the results of the training and precision tests were each worth 87.309%, and the results of the training and memory tests were both worth 86.958%. The training accuracy value is 85.87%, the projected sentiment analysis results have an accuracy rate of 85.87%, and the training results and precision testing are each worth 86.958%.
Co-Authors Dina Maulina Ferry Wahyu Wibowo Fitriani Fitriani Kusrini Kusrini Kusrini Kusrini Ridwan Joko Purnomo