Fuadi, Rifqi Syamsul and Maylawati, Dian Sa'adillah and Pratama, Ramdhan Nugraha and Firdaus, Akhdan Musyaffa and Sari, Dea Puminda and Hamdani, Maulana and Nurhanivah, Novia (2022) Data Clusterization of Muslim Majority Countries to Find Out the Most Factors Causing Gender Issues Using the K-Means Algorithm. In: 2022 10th International Conference on Cyber and IT Service Management (CITSM), 20-21 September 2022, Yogyakarta.
|
Text (Artikel)
Data_Clusterization_of_Muslim_Majority_Countries_to_Find_Out_the_Most_Factors_Causing_Gender_Issues_Using_the_K-Means_Algorithm.pdf Download (621kB) | Preview |
|
|
Text (Turnitin)
Turnitin_Proceeding 9.pdf Download (1MB) | Preview |
|
|
Text (Korespondensi)
Korespondensi 9 CITSM.pdf Download (1MB) | Preview |
Abstract
Islam is a religion that upholds the dignity of women. Even Islam teaches that heaven is at the feet of a mother. However, in countries where most of the population is Muslim, gender issues persist. Therefore, this article was created to know the factors that most contribute to gender issues in various countries where most of the population is Muslim. These factors are divided into internal factors and external factors. Internal factors include those that are relevant to oneself. External factors include things other than oneself, such as culture. The author uses the K-Means algorithm as the algorithm used to manage the retrieved data. The author uses a collection of survey data found on the Internet about the reactions of men and women to Islam and gender issues in Muslim-dominated countries.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Technology, Applied Sciences |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
| Depositing User: | Dian Sa'adillah Maylawati |
| Date Deposited: | 04 Apr 2023 02:02 |
| Last Modified: | 04 Apr 2023 02:02 |
| URI: | https://digilib.uinsgd.ac.id/id/eprint/66664 |
Actions (login required)
 |
View Item |
