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All Journal JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) JUTIS : Jurnal Teknik Informatika
Firmansyah, Fahrul
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics

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Pengukuran Validitas Website “mengundangkamu.online” Menggunakan SPSS dengan Kombinasi Metode R-Table dan Coehn’s Cappa Parlika, Rizky; Shahab, Muhammad Syaugi; Nurilhaq, Muhammad Sabilli; Firmansyah, Fahrul; Prayoga, Julio Cahya
JURNAL TEKNIK INFORMATIKA UNIS Vol. 10 No. 1 (2022): Jutis (Jurnal Teknik Informatika)
Publisher : Universitas Islam Syekh Yusuf

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33592/jutis.v10i1.2624

Abstract

In this study, the validity test was carried out on the website "inviting you.online" by calculating the validity value of the respondents' answers to the questionnaire to determine the level of operational feasibility of the website. Meanwhile, the questions from the questionnaire are the attributes contained on the website with a sample of 30 students and college students in the East Java region randomly and when the research was conducted in July 2022. From the results of processing the questionnaire data using SPSS by applying the method R-Table and the combination of Coehn's Cappa, then the R-Table method obtained the percentage of validity of 100% and invalidity of 0%. Then, with the combination of the Coehn's Cappa method, a value of 0.737 was obtained with a significant value of 0.016, which is where the level of strength of the appraiser's agreement on the website is moderate.
Pemanfaatan Multi-Layer Perceptron (MLP) untuk Deteksi Kanker Firmansyah, Fahrul; Sari, Anggraini Puspita; Sugiarto, Sugiarto
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.13438

Abstract

Cancer is one of the deadliest diseases in the world. This is because patients often do not realize the presence of cancer in their bodies, leading to delayed treatment and the cancer becoming aggressive. Early diagnosis of cancer in women is necessary since the majority of cancer patients are women. One of the markers that can be used to diagnose cancer is the anti-Mullerian hormone, accompanied by other indicators such as lifestyle, BMI, and others. Early diagnosis can utilize the Multi-Layer Perceptron (MLP) algorithm, which is currently a rapidly developing technology. By using the MLP algorithm, an accuracy of 84% is achieved on the training data and test data, with a training-to-testing data ratio of 65:35.
Co-Authors Anggraini Puspita Sari Nurilhaq, Muhammad Sabilli Prayoga, Julio Cahya Rizky Parlika, Rizky Shahab, Muhammad Syaugi Sugiarto S