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All Journal Brahmana : Jurnal Penerapan Kecerdasan Buatan
Widya Try Taradipa
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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Penerapan Metode VIKOR Dalam Menentukan Aplikasi Belanja Online Terbaik Berdasarkan Konsumen Rika Setiana; Widya Try Taradipa; Agus Perdana Windarto
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 1 (2022): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i1.105

Abstract

People's lives are becoming more instantaneous as technology advances, and many people have a lot of freedom in their daily activities. This means that people need comfortable goods to meet their daily needs. A marketplace is a type of media that serves as a place for sellers and buyers to do business and trade. People buy things online a lot these days, but a lot of them don't know how to choose an online marketplace, so the authors decided to do some research on how to choose the best online shopping app so that people can easily figure out which app to use and won't be disappointed in the future. So, it's important to figure out which is the best online shopping app. This study uses the VIKOR method to make a decision-making system. In this study, the authors started by doing surveys. They chose a data collection method based on a questionnaire or a Google form questionnaire. Based on how the VIKOR method was used in this study, the best marketplace that can be used is Shoope. With this research, it is hoped that the public will be able to find out how to choose the best app for shopping online.
Penerapan Machine Learning Dalam Memprediksi Produksi Rute Pergerakan Pesawat Domestik di Indonesia Rika Setiana; Widya Try Taradipa; Agus Perdana Windarto
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 1A (2022): Edisi Desember (Spesial Issue)
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i1A.141

Abstract

Seiring terjadinya pandemi Covid-9 di Indonesia, jumlah penumpang pesawat di Indonesia mengalami penurunan. Penurunan jumlah penumpang mengakibatkan jumlah rute pergerakan domestik menurun. Perlu ada kajian yang mendalam mengenai prediksi jumlah rute penerbangan domestik ke depan agar pihak maskapai dapat melakukan pengaturan jadwal penerbangan domestik kembali agar tidak mengalami kerugian akibat operasional yang tidak sesuai dengan pemasukan. Solusi yang digunakan pada permasalahan ini adalah menggunakan metode machine learning untuk memprediksi produksi rute pergerakan pesawat domestik. Algoritma yang digunakan adalah algoritma backpropagation dengan dua metode yaitu conjugate gradient fletcher reeves dan powell-beale. Hasil pelatihan dan pengujian menggunakan algoritma backpropagation dengan kedua metode menujukkan bahwa metode powell-beale adalah metode yang terbaik dengan nilai performance pengujian terkecil adalah = 0,0010 dengan epoch 34.
Co-Authors Agus Perdana Windarto Rika Setiana