How to cite (IEEE): S. Wahyuni, N. Khanom, & Y. Astuti "K-Means Algorithm Analysis for Election Cluster Prediction," JOIV : International Journal on Informatics Visualization, vol. 7, no. 1, , pp. 1-6, Jan. 2023. https://doi.org/10.30630/joiv.7.1.1107

How to cite (APA): Wahyuni, S., Khanom, N., & Astuti, Y. (2023). K-Means Algorithm Analysis for Election Cluster Prediction. JOIV : International Journal on Informatics Visualization, 7(1), 1-6. https://doi.org/10.30630/joiv.7.1.1107

How to cite (Chicago): Wahyuni, Sri Ngudi, Khanom, Nazmun, AND Astuti, Yuli. "K-Means Algorithm Analysis for Election Cluster Prediction" JOIV : International Journal on Informatics Visualization [Online], Volume 7 Number 1 (21 January 2023) https://doi.org/10.30630/joiv.7.1.1107

How to cite (Vancouver): Wahyuni S, Khanom N, & Astuti Y . K-Means Algorithm Analysis for Election Cluster Prediction. JOIV : International Journal on Informatics Visualization [Online]. 2023 Jan; 7(1):1-6. https://doi.org/10.30630/joiv.7.1.1107

How to cite (Harvard): Wahyuni, S., Khanom, N., & Astuti, Y. ,2023. K-Means Algorithm Analysis for Election Cluster Prediction. JOIV : International Journal on Informatics Visualization, [Online] 7(1), pp. 1-6. https://doi.org/10.30630/joiv.7.1.1107

How to cite (MLA8): Wahyuni, Sri Ngudi, Nazmun Nahar Khanom, & Yuli Astuti. "K-Means Algorithm Analysis for Election Cluster Prediction." JOIV : International Journal on Informatics Visualization [Online], 7.1 (2023): 1-6. Web. 1 Jun. 2023 , https://doi.org/10.30630/joiv.7.1.1107

BibTex Citation Data :

@article{JOIV1107,
    	author = {Sri Ngudi Wahyuni and Nazmun Khanom and Yuli Astuti},
    	title = {K-Means Algorithm Analysis for Election Cluster Prediction},
    	journal = {JOIV : International Journal on Informatics Visualization},
    	volume = {7},
    	number = {1},
    	year = {2023},
    	keywords = {K-Means algorithm; cluster; prediction; election; Davies Bouldin index.},
    	abstract = {The general election is a democratic process that is carried out in every country whose system of government is presidential, including Indonesia, which conducts it every five years. In fact, some people abstain, leading to budget wasting and missing target. Thus, it is very important to identify clusters of general election districts and map the number of voters to map the budget for the upcoming election. This process needs prediction to help reduce budgeting risk as an early warning. Based on the latest election data taken from Margokaton, Yogyakarta, Indonesia, many people voted in 2021, but the number of abstainers is high. In this case, cluster prediction is important to identify the election participants in each area. The K-Means algorithm could also predict abstainer areas in election activities to facilitate early mitigation in drafting election budgeting. Therefore, this study aimed to identify the pattern of voters in the election using the K-means algorithm. The data parameters comprised the list of voters, Unused ballot papers, and the sum of abstainers. This study is important because it contributes to reducing the election budget of each area. The data obtained from the Indonesia Ministry of Internal Affairs official website in 2021 were processed using the RapidMiner tool. The results showed more than 11% of the non-voters in cluster 1, 16% in Cluster 2, and 8% in cluster 3. The evaluation of clusters value is 2.04, indicating that the clustering using K-means is suitable, as shown by the DBI value close to 0. The results indicate that testing the cluster optimization of the K-Means algorithm using DBI is highly recommended. Based on this prediction result, the government needs special attention to clusters with many abstainers to decrease the number of abstainers and prevent overbudgeting. These results indicate the need to review the election participant data in 2024. Furthermore, there is a need for continuous socialization and education about election activities to reduce the number of abstainers and prevent overbudgeting.},
        	issn = {2549-9904},    	pages = {1--6},    	doi = {10.30630/joiv.7.1.1107},
        	url = {http://joiv.org/index.php/joiv/article/view/1107}
    }
    

Refworks Citation Data :

@article{{JOIV}{1107}, author = {Wahyuni, S., Khanom, N., Astuti, Y.}, title = {K-Means Algorithm Analysis for Election Cluster Prediction}, journal = {JOIV : International Journal on Informatics Visualization}, volume = {7}, number = {1}, year = {2023}, doi = {10.30630/joiv.7.1.1107}, url = {} }