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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Brahmana : Jurnal Penerapan Kecerdasan Buatan
Rika Setiana
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.
Population Prediction Using Multiple Regression and Geometry Models Based on Demographic Data M Safii; Rika Setiana
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4121

Abstract

Population growth is an important issue because it significantly impacts a country’s growth and development. Large population growth can impact potential resources that drive the pace of the economy and national development. On the other hand, it can also be a problem of poverty, hunger, unemployment, education, health, and others. The government needs to control population growth to balance it with good population quality. Data sourced from the Population and Civil Registration Office of Simalungun Regency, Tanah Java sub-district has a high population and continues to increase every year. The impact of the population increase is that it affects the population’s welfare, most of whom work as laborers and farmers. To overcome this problem, it is necessary to predict the number of people in the future so that the government can make the right decisions and policies in controlling the population. This study aims to make predictions using two models, namely Multiple Linear Regression, to find linear equations and Geometry Models for population growth projections. This study utilizes multiple regression analysis and geometric models using three independent variables, namely birth rate (X1), migration rate (X2), and death rate (X3), as well as one bound variable, population number (Y). This study’s results show that the Tanah Java sub-district population is expected to increase in the next five years (2024-2028). Predictions show that by 2024, the population is expected to reach 61178 people from 59589 in 2023. Based on the results of the study, the conclusion of this study it can be used as a guide for the authorities in planning strategies and resource allocation and making a significant contribution in estimating population development in the Java region so that there will be no population explosion in the future so that it does not have a negative impact.
Co-Authors Agus Perdana Windarto M Safii Widya Try Taradipa