Salah satu bentuk ulasan digital saat ini adalah consumer review website (CRW). Website Zomato merupakan salah satu CRW yang banyak digunakan dan indeks popularitas restoran yang ada di dalamnya memudahkan penggunanya untuk memilih restoran yang terbaik, terutama di Kota Bandung yang terkenal akan kulinernya. Mengingat indeks popularitas di sini penting, perlu diketahui distribusi spasial restoran berindeks popularitas, karakteristiknya, dan faktor yang mempengaruhi distribusi spasial indeks popularitas restoran di Kota Bandung. Data yang diperlukan berupa data atribut restoran, POI fungsional, kawasan CBD, jaringan jalan, penggunaan lahan dan kepadatan penduduk. Metode analisis yang digunakan berupa Nearest Neighbor Analysis (NNA), Kernel Density, Near Analysis, uji ANOVA/Kruskal Wallis, dan uji Pearson Product Moment. Hasil yang didapatkan berupa restoran terbanyak berada pada Kecamatan Bandung Wetan, Kecamatan Coblong, dan Kecamatan Sumur Bandung. Restoran dengan popularitas tinggi, sedang, dan rendah memiliki karakteristik distribusi spasial yang mengelompok dan kepadatan yang besar di lokasi yang memiliki kemudahan aksesibilitas, terdapat POI fungsional yang mendukung, dekat dengan pusat kegiatan, dan berada di permukiman. Rata-rata jarak restoran ke jaringan jalan, POI Fungsional, dan penggunaan lahan dimana restoran tersebut berada menjadi faktor yang berpengaruh terhadap indeks popularitas restoran. Hasil korelasi antara kepadatan penduduk dan indeks popularitas restoran menunjukkan tidak ada korelasi diantara keduanya.

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One form of digital review today is the consumer review website (CRW). The Zomato website is one of the most widely used CRWs and the restaurant popularity index in it makes it easy for users to choose the best restaurant, especially in the city of Bandung which is famous for its culinary. Given the importance of the popularity index here, it is necessary to know the spatial distribution of the popularity indexed restaurant, its characteristics, and the factors that affect the spatial distribution of the restaurant popularity index in Bandung. The data needed are restaurant attribute data, functional POI, CBD area, road network, land use and population density. The analytical methods used are Nearest Neighbor Analysis (NNA), Kernel Density, Near Analysis, ANOVA/Kruskal Wallis test, and Pearson Product Moment test. The results obtained in the form of the most restaurants are in Bandung Wetan District, Coblong District, and Sumur Bandung District. Restaurants with high, medium, and low popularity have the characteristics of clustered spatial distribution and large density in locations that have easy accessibility, have functional POIs that support, are close to the center of activity, and are located in residential areas. The average distance of the restaurant to the road network, functional POI, and land use where the restaurant is located are factors that affect the restaurant popularity index. The correlation between population density and restaurant popularity index shows no correlation between the two.