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Journal : Creative Information Technology Journal

 1 
Sistem Penilaian Karakteristik Anjing Menggunakan Metode Weighted Product Christine Christine; Halim Agung
Creative Information Technology Journal Vol 5, No 1 (2017): November-Januari
Publisher : UNIVERSITAS AMIKOM YOGYAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/citec.2017v5i1.127

Abstract

Anjing merupakan hewan yang paling banyak populasinya di tahun 2016 menurut survey populasi hewan kesayangan oleh asosiasi pembuat makanan hewan di Inggris (PFMA). Dengan banyaknya jenis anjing dan perbedaan karakteristik, tidak semua manusia dapat memilih jenis anjing yang sesuai dengan situasi dan kondisi mereka. Maka dari itu sistem penilaian karateristik anjing dibuat yang bertujuan untuk memudahkan user dalam memilih jenis anjing yang sesuai dengan situasi dan kondisi user tersebut. Sistem ini dibuat dengan menggunakan metode weighted product karena metode ini lebih efisien dibandingkan metode lain yang termasuk dalam penyelesaian masalah MADM (Multi Attibute Decision Making). Sistem ini dibuat berdasarkan data anjing yang terdaftar di American Kennel Club. Variabel-variabel yang terdapat dalam sistem ini meliputi kategori kelompok, lingkungan yang cocok, level energi, kerontokan bulu, tingkat kesulitan grooming, tingkat kepatuhan, size anjing, dan seringnya gonggongan. Hasil yang didapatkan dari sistem penilaian ini adalah 20 dari 30 pengujian sesuai dengan perhitungan manual. Sehingga tingkat kecocokan dari metode weighted product adalah 67%. Kesimpulan yang didapat dari penilitian ini adalah metode weighted product cukup efisien untuk diterapkan dalam sistem penilaian karakteristik anjing.Kata Kunci — Rekomendasi Jenis Anjing, Weighted Product, Memilih Anjing, Karakteristik, Sistem Penilaian.The dog is the most populous animal in the year 2016 according to a survey of pets population by the association of animal feed makers in the UK (PFMA). With many dog breeds and characteristic differences, not all humans can choose the type of dog that suits their circumstances. Therefore, the system of characteristic assessment of dogs made that aims to facilitate the user in selecting the type of dog that suits the situation and condition of the user. This system is made using the weighted product method because this method is more efficient than other methods which are included in solving the MADM (Multi Attibute Decision Making) problem. This system is based on dog data registered with American Kennel Club. The variables contained in this systeminclude group categories, suitable environments, energy levels, shedding, grooming difficulty level, adherence level, dog size, and frequent barking. The results obtained from this scoring system are 20 out of 30 tests according to manual calculations. So the match rate of weighted product method is 67%. The conclusion of this research is that the weighted product method is efficient enough to be applied in the dog's characteristic rating system.Keywords — Dog’s Breed Recomendation, Weighted Product, Choosing Dog, Characteristic, Scoring System.
Co-Authors Abdillah, Refa Maulana Abiel Filetus Agung Stefanus Kembau Alvin Juvianto Alvin Juvianto, Alvin Amanda, Mercedes Andreas, Andri Arihta Tarigan Axell Thomas Badri, Wahid Maulana Brigitta Indrawan, Genoveva Budiman Budiman Candra, Ricky Chandra Arief Rahardja Charles Widodo Christanti Christanti CHRISTANTI CHRISTANTI, CHRISTANTI Christian, Michael Christine Christine Christine Citra, Calvin Christopher Claude Calvin Alsher Danny Steveson Edy Andersen Erlando Aubrey Nathaniel Evasaria Magdalena Sipayung, Evasaria Magdalena Farady Marta, Rustono Fauzi, Zidan Wahyu Fendra Mulia Firellsya, Gabriela Fitri Murfianti Hakim, Lukman Handoko, Maulana Bhakti Hariyanto, Ribfan Harvin Seruni I Gede Wisnu Satria Chandra Putra Ivan Ivan Ivan Ivan Januar, Rizky Jeki Sauwani Jessica Jessica Jessica Jessica Jimmy Gunawan Jimmy Sadeli Johanes Fernandes Andry Juardi, Try Juniana, Paula Karlo Geofandy Karman Surya Kenny Kevin Ekaputra Kevin Krisnandi Kevin Laurence Hartono Lieta Septiarysa Linda Linda Lukman Hakim M. Bucci Ryando Marchellius Yana Mario Richie Marlina Marlina Maynacky Muhamad Ali Sukrajap Nico Yunus Marselinus Novara Aulist Zakia Oscar Adriyanto Phoan, Nico Prittania Friska Octavia Rahardja, Chandra Arief Rainhard Rainhard Ramdhan, Syaipul Raphael, Stephanus Rarasati, Dionisia Bhisetya Richard Benedict Ricky Candra Ricky Raymond Ricky Ricky Rini Lestari Rizky Januar Rustono - Rustono Farady Marta Rustono Farady Marta Sandi Gautama, Sandi Septiarysa, Lieta Setiawan, Vincent Sinata, Frans SOFIA, DETIN Stefanus Kembau, Agung Stephanus Raphael Steven Steven Andreas Teady Matius Surya Mulyana, Teady Matius Thomas, Axell Tobing, Fery Tri Yatmo Noveary Try Juardi Valerian Hendri Yono Venness, Venness Vicky Budiman Vina Virshella Vitcky Nanda Putra Wang, Changsong Wilibrodus Wilibrodus Willyam Willyam Wiryadinata, Antonius Yessica Putri Santoso Yogi Swara Hendro Leksmono Yogyawan Yogyawan Yohanes Dianrizkita Yosephine, Maria Yuliana Yuliana