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All Journal Jurnal Ilmiah Teknik Informatika dan Komunikasi Intellektika: Jurnal Ilmiah Mahasiswa
Hari Noer Fazri
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences

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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 : Lembaga Pengembangan Kinerja Dosen

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.
Analisis Efektivitas Penerapan A/B Testing dalam Meningkatkan Performa Website pada PT Pamor Putra Mandiri Hari Noer Fazri; Ina Najiyah
Intellektika : Jurnal Ilmiah Mahasiswa Vol. 4 No. 3 (2026): Mei : Intellektika : Jurnal Ilmiah Mahasiswa
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/intellektika.v4i3.3669

Abstract

. A website is a crucial digital promotion medium for companies to convey information and attract potential customers. However, many websites experience low user interaction despite having high visitor traffic. This study aims to analyze the effectiveness of A/B Testing implementation in improving the performance of the PT Pamor Putra Mandiri website. A quantitative experimental approach was used, applying A/B Testing to two page variations: Variation 1 (Rafting & Outdoor Activity theme) and Variation 2 (Camping & Accommodation theme). The evaluation focused on three main performance metrics: Click, Page Visit, and Engagement. The results show that Variation 1 consistently outperformed Variation 2 across all metrics. Statistical testing using a two-proportion z-test confirmed that these differences were statistically significant (p-value < 0.05). Therefore, A/B Testing proves to be an effective method in identifying superior content strategies and page structures, as well as a relevant tool for data-driven decision-making in corporate website development.
Co-Authors Arifin Yusuf Permana Ina Najiyah M.Fakhrizal Nur Athoilah Mohammad Robi Ricky Firmansyah