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All Journal POSITIF Jurnal TNI Angkatan Udara
Pranata, Aldi Surya
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Aerospace Engineering Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Engineering Environmental Science

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Sistem Pengambil Keputusan Rekomendasi Lokasi Wisata Malang Raya Dengan Metode MOORA Pranata, Aldi Surya; Rosiani, Ulla Delfiana; Mentari, Mustika
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 7 No 1 (2021): Jurnal Positif Vol. 7 No.1
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v7i1.1091

Abstract

Malang Raya, which consists of Malang City, Malang Regency, and Batu City, is one of the favorite tourist destinations in East Java. The number of tourist attraction locations that offer various advantages of each. This often makes it difficult for local and non-local tourists to choose a tourist destination, in order to be able to maximize their visit time, costs and satisfaction. This study aims to build a decision support system (DSS) for determining tourist locations using the Moora method. This method will provide weighting criteria according to user conditions / preferences, and then perform processing on the data. The built DSS is able to produce recommendations by ranking tourist locations to users according to their preferences. The system built was tested using 5 alternative tourist attraction locations in Batu City and 3 criteria consisting of 1 cost and 2 benefit criteria. Experiments carried out were successful in giving different rankings to 5 alternatives.
4. Survei Implementasi Artificial Intelligence Pada Intelligent Visual Aircraft Recognition (I-Vacr) System Sumari, Arwin Datumaya Wahyudi; Adinandra, Dimas Eka; Pranata, Aldi Surya; Nugraheni, Afifah Milatina; Satwika, Satriya Dipa; Syamsiana, Ika Noer
Jurnal TNI Angkatan Udara Vol 1 No 2 (2022): Jurnal TNI Angkatan Udara Triwulan Kedua
Publisher : Staf Komunikasi dan Elektronika, TNI Angkatan Udara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62828/jpb.v1i2.18

Abstract

Objek udara yang terbang rendah dengan ketinggian rendah dari permukaan bumi dengan tujuan menghindari deteksi Radio Detection and Ranging (Radar) dapat mengindikasikan tindakan permusuhan dan dikategorikan sebagai ancaman terhadap kedaulatan negara di udara. Sebagai antisipasi, teknik Visual Aircraft Recognition (VACR) telah dikembangkan oleh Angkatan Darat Amerika Serikat untuk melatih para prajuritnya untuk mengenali dan mengidentifikasi objek udara dari jarak jauh menggunakan binokular. Namun, dengan beragamnya jenis dan nama objek udara memberikan beban kognitif dan dapat berdampak pada ketidaktepatan dalam mengenali dan mengidentifikasi objek udara yang diamati. Dalam artikel ilmiah dilakukan kajian pemanfaatan teknologi Artificial Intelligence (AI) untuk membangun Intelligent VACR (I-VACR) System melalui metode-metode dalam machine learning yakni Jaringan Syarat Tiruan, Naìˆve Bayes Classifier (NBC), K- Nearest Neighbor (KNN), dan Support Vector Machine (SVM). Hasil-hasil penelitian memperlihatkan bahwa keempat metode tersebut prospektif diaplikasikan sebagai elemen cerdas I-VACR.
Co-Authors Adinandra, Dimas Eka Arwin Datumaya Wahyudi Sumari Mustika Mentari Nugraheni, Afifah Milatina Rosiani, Ulla Delfiana Satwika, Satriya Dipa Syamsiana, Ika Noer