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All Journal International Journal of New Media Technology Jurnal ULTIMATICS JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI International Journal Of Science, Technology & Management (IJSTM) Ceddi Journal of Information System and Technology (JST)
kusnadi, adhi
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Public Health Transportation

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Journal : Jurnal ULTIMATICS

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Implementation of SAW Method for Design and Development Apartment Recommendation System in Tangerang Using Mobile-Based Nugraha, Achmad Ilyasa; Kusnadi, Adhi; Tobing, Fenina Adline Twince
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3492

Abstract

The house is no longer the sole type of residence available while looking for a place to live. Apartments are a solution for those who need a place to live in locations with limited land, such as Tangerang, in today’s period. However, criteria are needed to choose an apartment based on a person’s needs, thus in this project, we will develop and create an apartment recommendation system in Tangerang using the SAW approach to make it easy for people to choose the best apartment. The user’s choice will be determined by the recommendation system based on their interests, activity, and other data. To put the recommendation system into action, the FMADM method must be employed. A Simple Additive Weighing (SAW) approach is required to complete this FMADM, which is a mechanism for computing the number of performance appraisals for each alternative based on all criteria. This recommendation system is called APARTKU, and it was created with HTML5, CSS, and AngularJS, as well as the Ionic Framework and the Firebase Database. The system was then put to the test by administering questionnaires to 32 respondents using the DeLone and McLean methodologies, and the results were tallied using the Likert Scale method, yielding a score of 90.64 percent, based on the interval on the Likert Scale technique, these results imply that the application has been constructed and designed very well.
Co-Authors Adline Twince Tobing, Fenina Augustino, Lorentzo Dinarta, Farrel Endariahna Surbakti, Eunike Geneva, Erick Abraham Hin, Alexander Moya Irelynn, Maecyntha Ivan Wijaya, Aurelius Khaeruzzaman, Yaman Nugraha, Achmad Ilyasa Overbeek, Marlinda Vasty Paskah, Richard Prasetya, Syarief Gerald Prawira, Oqke Rayhan Harsono, William Richard Andrew Tisna Kusuma, Irene Tobing, Fenina Adline Twince Vasty Overbeek, Marlinda Wahyu Andrian, Bagas Zuhdi Pane, Ivransa