This paper describes the design and manufacture of virtual campuses with auto-stitching techniques. The automatic stitching technique using Insta360 allows getting a panoramic view of the 3600 campus area. The creation of a virtual campus is built by each campus to support campus promotion more fully and more closely. The prototype of the Virtual Campus Exploration (Jejakatua) application was implemented at the Faculty of Computer Science UPN “Veterans” Jatim the Jejakatua application page and evaluated by users using a set of questionnaires distributed using Google Forms. The results of testing by the black box test the built system is in accordance with the design and can be operated properly. Studying the questionnaire to 30 respondents from UPN “Veteran” Jatim academicians gave a pretty good average response. So Jejakatua is fully built using the auto-stitching method using Insta360 and is quite feasible to be implemented on Campus.

YouTube as the world's largest video content service provider that can be accessed by various groups of people provides facilities to share videos easily widely to its consumers. With the development of YouTube as a social network site (SNSs), this study aims to identify the motivations of consumers who wish to participate in SNSs, as well as examine the effect of the relationship of facilities to intention to use through the perspective of Uses & Gratification (U & G). Data collection was carried out by distributing online questionnaires with non-probability sampling techniques to obtain empirical testing from the research model. The findings of identification of self-presentation (SP), passing time (PT), and information sharing (IS), Enjoyment (Enjoy), and media appeal (MA) are motives that support the condition of continuance intention (CI). The results of the study confirm that appeal gratification media and enjoyment of gratification as gratuities are needed by YouTube users to strengthen continuance intention.

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Pengguna internet di Indonesia berkembang pesat mampu mengubah gaya hidup masyarakat. Masyarakat memanfaatkan internet untuk mengakses informasi pada berita online. Berita online yang beragam jenis dan kategori membuat penyedia layanan berita online harus menyediakan informasi sesuai dengan permintaan pengguna. Pada paper ini menjelaskan proses pengkategorian berita online secara otomatis. Tujuan pengkategorian secara otomatis untuk mempermudah penyedia layanan dalam membuat sebuah berita. Proses pengkategorian berita secara otomatis menggunakan metode probabilistyc laten semantic analysis (PLSA). Dari 60 dokumen berita sebagai dataset yang diambil pada tiga berita online : kompas, sidomi, liputan6 menghasilkan 4 kelompok kategori (labels) berita. Sehingga dapat disimpulkan dengan metode PLSA mampu menghasilkan nilai presisi tertinggi sebesar 0,68 dengan iterasi sebanyak 300 kali