IMPLEMENTATION OF THE FUZZY TSUKAMOTO METHOD IN THE FINDKOS WEB-BASED APPLICATION USING LARAVEL

Pandemi Covid-19 tahun 2020 mengubah pola hidup masyarakat, termasuk kebutuhan tempat tinggal yang semakin mendesak. Seiring meredanya pandemi, pencarian tempat tinggal sementara dapat dilakukan secara daring, namun keberagaman opsi sering kali membingungkan pengguna. Oleh karena itu, penelitian ini mengembangkan sistem berbasis web menggunakan framework Laravel yang menerapkan algoritma fuzzy Tsukamoto untuk memberikan prediksi dan rekomendasi tempat tinggal sementara secara akurat. Algoritma ini menggunakan parameter seperti harga, ukuran, dan fasilitas, termasuk kamar mandi, WiFi, parkir, dan penyejuk ruangan. Parameter tersebut membentuk tiga himpunan fuzzy, yaitu ukuran (luas/sempit), fasilitas (banyak/sedikit), dan harga (mahal/murah), dengan empat aturan utama.

Hasil pengujian menunjukkan bahwa algoritma fuzzy Tsukamoto mampu memberikan prediksi harga yang rasional serta rekomendasi kos yang sesuai kebutuhan pengguna. Aplikasi ini juga terbukti fungsional berdasarkan uji coba black-box, yang menunjukkan bahwa semua fitur berjalan normal, termasuk manipulasi data pada database. Dengan demikian, aplikasi berbasis web ini mampu membantu pengguna dalam proses pencarian tempat tinggal sementara secara cepat, efisien, dan terstruktur.

Kata Kunci: Fuzzy Tsukamoto, Prediksi harga kos, Sistem rekomendasi, Framework Laravel, Aplikasi berbasis web

The need for temporary housing has become increasingly significant, especially during and after the COVID-19 pandemic in 2020, which required most activities to be conducted indoors. As the pandemic subsided, online platforms became an efficient and effective way to search for and choose temporary housing. However, the diversity of available options often complicates decision-making. Factors such as price, room size, and facilities are critical considerations in choosing housing. To facilitate the selection process, a web-based system employing the Fuzzy Tsukamoto method was developed to provide accurate predictions and recommendations.

This study implemented the Fuzzy Tsukamoto algorithm in the FindKos web application using the Laravel framework. Parameters used include price, room size, and facilities such as bathrooms, Wi-Fi, parking spaces, and air conditioning. These parameters were grouped into three fuzzy sets: room size (spacious/narrow), facilities (many/few), and price (expensive/cheap), with four primary rules applied. Testing results showed that the Fuzzy Tsukamoto algorithm could deliver rational and fast price predictions. Additionally, the application's functionality was validated through black-box testing, confirming that it operates effectively and provides reliable recommendations.

Keywords: Fuzzy Tsukamoto, Price Prediction, recommendation system, Laravel Framework, Web-Based System