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This research discusses the concept of gamification science in the study of literature. The concepts discussed include the basic concepts of gamification based on the opinions of the researchers and presented graphs of the trends in the application of gamification in several fields during the 2015-2019 period. Four gamification models are also described by explaining the basic concepts, ways of working, and the best models currently based on the literature reviewed in this article. Some elements of gamification are explained in two categories based on the study of literature involved. Gamification research has been described as information for the development of gamification which can also be combined with other to produce targeted solutions is to increase user retention.

Pendaftaran mahasiswa pada perguruan tinggi yang di selenggarakan setiap tahunnya membuahkan hasil penumpukan informasi calon mahasiswa baru. Informasi yang berlimpah tersebut alangkah baiknya diolah untuk menghasilkan analisa data yang berguna. Penelitian ini menggunakan sample data penerimaan mahasiswa baru di Universitas Widyagama Malang. Metode dilakukan dengan cara pengelompokan data (cluster) calon mahasiswa baru melalui tahap pemrosesan data / informasi menggunakan algoritma K-Means Clustering. Atribut yang digunakan dalam tahap pemrosesan data ini adalah Nama Calon Mahasiswa, jurusan yang dipilih dan Sekolah Asal. Data yang digunakan adalah data mahasiswa Angkatan 2020/2021 dengan mengambil sampel 100 baris data. Sampel yang didapatkan ini diolah dengan cara membagi 3 cluster sampai didapatkan pemodelan data yang sesuai dengan aturan algoritma K-Means Clustering. Cluster1 menunjukkan peminat jurusan ekonomi banyak dari SMA dan SMK, Cluster 2 Menunjukkan peminat jurusan Teknik dari SMK dan MAN, Cluster 3 menunjukkan peminat jurusan hukum dari SMA. Output penelitian ini digunakan sebagai bahan pertimbangan untuk mengatur strategi pengenalan institusi ke sekolah menengah atas yang ada di Kota Malang khususnya.Keywords: Clustering, K-Means, Student Admission.

One of the problems of SME is the low motivation to collaborate; the lack of research on exploring the motivation to collaborate is an issue that needs to be focused on solving. Objectives. This research aims to explore the level and type of motivation that influences SME's interest in collaborating to provide new insights for SME managers to apply appropriate treatment in developing collaborative activities. This study analyses six octalysis core drives that affect user interest in the use of SME collaboration gamification applications involving 293 SME respondents in the East Java Province. The research method is descriptive and quantitative, using Smart PLS, with a path analysis and analysis model. This study formulates six hypotheses to determine the effect of six core drives on using the collaborative gamification system. The results showed that the four constructs had a p-value less than 0.05 and a T-Statistic value greater than 1.96, while the other two constructs produced the opposite value. This finding reveals that four core drives (Epic Meaning, Development, Social Influence, and Avoidance) affect user interest in using collaborative gamification applications. In contrast, two core drives (Ownership and Unpredictable) do not affect it. The implication of this study is a recommendation for developers of collaboration-gamification systems to consider the results of this hypothesis, especially the role of core-drive catalysis as a reference in revising or developing collaborative gamification systems. Future work could apply the TAM model to analyze the technology acceptance rate of this system.

This study aims to present an attractive collaboration platform to motivate SME players in collaborating activities to support their business development. Therefore, this article introduces the proposed new model, "Intelligent Silaturrahmi-based Gamification Mechanics (ISb-GM)." This model embodies the gamification mechanics of collaboration based on the cultural parameter of "silaturrahmi" found in previous research. The consideration of choosing this parameter is to increase the closeness of the relationship in collaboration. The model is also equipped with an intelligent system to extract the knowledge needed in the collaboration process. The parameter "silaturrahmi" serves as a reference for scenario mechanics to measure the collaboration performance of each player.The intelligent system functions to complement data extraction needs to provide recommendations for suitable SME partners to collaborate. This model is represented in a collaboration gamification prototype and experiments; it is proven to show performance effectively for collaborating media and measure the collaboration performance of each player.