The Student Executive Board (BEM) of the University of Timor is a student organization located at the State University of Timor. In its implementation, BEM at the University of Timor acts as a forum or means for all students of the University of Timor to be able to express their opinions and to develop various potentials that students have. The election of the chairman of the BEM of the University of Timor is directly elected by the students by a general election process. The process of selecting the chairman of the BEM is still done manually so that there is a lack of interest from voters to participate because they have to go to the polling station. Therefore, the development of information technology today has brought great changes for humans, including to carry out voting so that the term e-voting (electronic voting) appears which provides convenience in voting. E-Voting is a general election process that utilizes information technology facilities or electronic devices, where part or all of the implementation process, from voter registration, voting, to vote counting, is carried out digitally. The function of voting is to gather the aspirations of all students, and then find a way out that is considered a good cross. Therefore, the researchers helped the election system easily and created an application for the election with the title "E-voting for the election of the chairman of the Mobile-based Student Executive Board (BEM) of the University of Timor using the waterfal method".
Kriminalitas merupakan suatu aspek yang mempengaruhi kelancaran perekonomian dalam masyarakat. Pentingnya peranan pemerintah dalam meminimalisir terjadinya kriminalitas dapat dilakukan dengan mengetahui sebaran karakteristik kriminalitas yang ada di setiap provinsi. Metode Model-Based Clustering dapat membantu mengidentifikasi karakteristik tersebut. Proses Clustering dilakukan dengan memastikan terlebih dahulu sebaran peubah mendekati sebaran normal dilihat dari QQplot dan kebebasan antar peubah. Hasil Clustering menunjukkan bahwa terdapat dua karakteristik kriminalitas yang tersebar di provinsi Indonesia. Identifikasi karakteristik sebaran kriminalitas menggunakan nilai rata-rata pada masing-masing cluster optimal yang sudah didapatkan. Cluster pertama menunjukkan sebaran 16 provinsi dengan kategori kriminalitas cenderung lebih rendah, sedangkan cluster kedua menunjukkan sebaran 18 provinsi dengan kategori kriminalitas tinggi.
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