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All Journal JSM (Jurnal SIFO Mikroskil) Jurnal Mantik INFOKUM
Erwin Setiawan Panjaitan
STMIK Mikroskil
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Journal : Jurnal Mantik

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Classification of Breast Cancer Using Support Vector Machine and Forward Selection Leliana Harahap; Erwin Setiawan Panjaitan; Muhammad Fermi Pasha
Jurnal Mantik Vol. 4 No. 2 (2020): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.957.pp1424-1429

Abstract

Breast cancer represents about 12% of all new cancer cases and 25% of all cancers in women. Early detection and classification of cancer is essential to save a person's life. The causes of breast cancer are multi-factorial and involve family history, obesity, hormones, radiation therapy, and even reproductive factors. Each year, one million new women are diagnosed with breast cancer, according to a World Health Organization report, half of them will die, because it is usually too late when doctors detect cancer. After the selected variable is then evaluated based on certain criteria. If the first selected variable meets the criteria for inclusion, the selection continues. The procedure stops, if no other variables meet the entry criteria and adds the variables one by one. The accuracy of the Support Vector Machine is influenced by several factors, including the comparison of the amount of training data and test data adjusted for k-fold validation. In the comparison of training data and test data the resulting accuracy reaches 97.68% with a total composition of 345 training data (50%) and 345 test data (50%). In the tests carried out, the accuracy of Support Vector Machine and Forward Selection was obtained at 97.68%.
Effect of Attitude on Mobile Banking Acceptance Using Extended UTAUT Model Angelia Angelia; Erwin Setiawan Panjaitan; Roni Yunis
Jurnal Mantik Vol. 5 No. 2 (2021): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jurnalmantik.Vol5.2021.1440.pp1006-1013

Abstract

This research aims to evaluate the effect of attitude on mobile banking acceptance using the extended UTAUT Model. Specifically, surveying the Medan city area covered 392 mobile banking users from several banks. By using Structural Equation Modeling (SEM) and SmartPLS software. This research’s man contribution is introducing attitude variables in the combination of UTAUT models, task technology fit, and trust, which have a significant effect on behavior intention. Based on this study results, it shows that social influence and attitude are a significant effect on behavior intention,facilitating condition, and behavior intention is a significant effect use behavior of mobile banking users from several banks. While performance expectancy, effort expectancy, task technology fit, and trust didn’t significantly effect on the behavior intention of mobile banking users from several banks. This Research implies two important policymakers’ findings. First, Banking Management needs to ensure that it always makes necessary improvements in simplifying technology to understand it easily. Second, need to ensure that we regularly evaluate the performance of mobile banking users from several banks to mae benefits of using M-Banking technology to support financial transactions needs.
Co-Authors Angelia Angelia Desi Arisandy Dwi Tio Riky Julprianto Hutabarat Fitri Aryanti Hanes Hanes Leliana Harahap Lidya Veronica Hutabarat Lihardo Rawaja Haloho Marwan Al Fajri Muhammad Fermi Pasha Roni Yunis Salsalina Br Sembiring