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All Journal Jurnal Informatika Dan Tekonologi Komputer (JITEK) Jurnal Ilmiah Teknik Informatika dan Komunikasi
Hari Noer Fazri
ARS University
Computer Science & IT Education Electrical & Electronics Engineering Other

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IMPLEMENTASI STRUKTUR DATA TREE PADA WEB BLOG SEBAGAI MEDIA PEMBELAJARAN Serly Agustin; Arifin Yusuf Permana; Hari Noer Fazri; M. Rahssyal Daffa H; Mohammad Robi; Ricky Firmansyah
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 2 No. 2 (2022): Juli : Jurnal Informatika dan Teknologi Komputer
Publisher : AMIK Veteran Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v2i2.316

Abstract

In writing this study aims to review the implementation of tree data structures on web blogs as learning media, starting from a discussion of the implementation of data structures. After that, it was continued with the use of blogs as an applied learning medium. The use of tree data structures is one of the most common data structures used in the development of a web. One of the efforts to streamline and provide a variation in the realm of learning media is to create a web blog, especially in the era of globalization, everyone who lives in that era should at least know about one of the results of technological and communication advances. This study will see how the description or description of the application of tree data structures on blogs as learning media. The making of this research uses a qualitative descriptive method in which the data is obtained from observation and documentation of matters relating to the topic under study. The core discussion of this research is the implementation of data structures on blogs as learning media.
Penerapan Data Mining Dalam Analisis Prediksi Kanker Paru Menggunakan Algoritma Random Forest Arifin Yusuf Permana; Hari Noer Fazri; M.Fakhrizal Nur Athoilah; Mohammad Robi; Ricky Firmansyah
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 3 No. 2 (2023): Juli : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Barenlitbangda Kabupaten Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v3i2.472

Abstract

Lung cancer is one of the one of the leading causes of death in the world. From this data there are several categories of people who are positive and negative for lung cancer, Here the researcher will display information on the exact number of people who contracted lung cancer from the data, and in this study using the Random Forest algorithm because Random Forest This research uses the Random Forest algorithm because Random Forest has a data set selection process. Has a data set selection process. to improve the performance of classification model. With feature selection, Random Forest can certainly work efficiently on big data with complex parameters, which will greatly facilitate the classification of positive and negative lung cancer patients. Observations will be a reference for analyzing the prognosis of lung disease. Observation will be a reference for analyzing the prognosis of lung disease here how the application of data data mining techniques on the prediction analysis of lung cancer analysis and how performance of the random forest algorithm in predicting lung cancer.by applying data mining techniques and has been tested using a survey dataset of lung cancer survey dataset and using software called Rapidminer toanalyze and predict positive patients with lung cancer It was concluded that the It is concluded that the Random Forest algorithm that has obtained the greatest accuracy obtained accuracy results worth 90.61% with an AUC value of 0.941.
Co-Authors Arifin Yusuf Permana M. Rahssyal Daffa H M.Fakhrizal Nur Athoilah Mohammad Robi Ricky Firmansyah Serly Agustin