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Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City

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@article{IJASEIT14487,
   author = {N. Tri Suswanto Saptadi and Phie Chyan and Vanessa Putri Taga},
   title = {Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {4},
   year = {2021},
   pages = {1455--1462},
   keywords = {Algorithm; behavior; urban communities; waste management; smart city.},
   abstract = {

Urban communities' behavior in disposing and managing waste around the house is still very concerning. This study aims to analyze and classify community behavior patterns related to waste disposal to help the Makassar City Government overcome waste problems. The methods and techniques applied are using the Waterfall model and the K-Means Algorithm. The stages of analysis and classification of behavior patterns can assist city governments in making strategic decisions. The variables determined include education, age, occupation, free time, smoking status, and questionnaire (outreach, law, knowledge, and facilities). The K-Means algorithm calculation results are 39 people in cluster 1 and 10 people in cluster 2. In cluster 1, it is known that the community tends to take care of the environment in the sub-district where the community lives. Cluster 2 has a low average yield, such as people who do not know the impact laws, inadequate sanitation facilities, and lack of proper waste management towards smart city governance. Based on testing for each method, the Cyclomatic Complexity value generated is four. Therefore, it can be concluded that the white box testing on the K-Means algorithm runs well because each test produces the same value. The government and the community have a responsibility to carry out waste management properly, make use of goods and refill facilities, know the legal impact of littering and follow the socialization held by the Makassar City Government.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14487},    doi = {10.18517/ijaseit.11.4.14487} }

EndNote

%A Saptadi, N. Tri Suswanto
%A Chyan, Phie
%A Taga, Vanessa Putri
%D 2021
%T Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City
%B 2021
%9 Algorithm; behavior; urban communities; waste management; smart city.
%! Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City
%K Algorithm; behavior; urban communities; waste management; smart city.
%X 

Urban communities' behavior in disposing and managing waste around the house is still very concerning. This study aims to analyze and classify community behavior patterns related to waste disposal to help the Makassar City Government overcome waste problems. The methods and techniques applied are using the Waterfall model and the K-Means Algorithm. The stages of analysis and classification of behavior patterns can assist city governments in making strategic decisions. The variables determined include education, age, occupation, free time, smoking status, and questionnaire (outreach, law, knowledge, and facilities). The K-Means algorithm calculation results are 39 people in cluster 1 and 10 people in cluster 2. In cluster 1, it is known that the community tends to take care of the environment in the sub-district where the community lives. Cluster 2 has a low average yield, such as people who do not know the impact laws, inadequate sanitation facilities, and lack of proper waste management towards smart city governance. Based on testing for each method, the Cyclomatic Complexity value generated is four. Therefore, it can be concluded that the white box testing on the K-Means algorithm runs well because each test produces the same value. The government and the community have a responsibility to carry out waste management properly, make use of goods and refill facilities, know the legal impact of littering and follow the socialization held by the Makassar City Government.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14487 %R doi:10.18517/ijaseit.11.4.14487 %J International Journal on Advanced Science, Engineering and Information Technology %V 11 %N 4 %@ 2088-5334

IEEE

N. Tri Suswanto Saptadi,Phie Chyan and Vanessa Putri Taga,"Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 4, pp. 1455-1462, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.4.14487.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Saptadi, N. Tri Suswanto
AU  - Chyan, Phie
AU  - Taga, Vanessa Putri
PY  - 2021
TI  - Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 4
Y2  - 2021
SP  - 1455
EP  - 1462
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Algorithm; behavior; urban communities; waste management; smart city.
N2  - 

Urban communities' behavior in disposing and managing waste around the house is still very concerning. This study aims to analyze and classify community behavior patterns related to waste disposal to help the Makassar City Government overcome waste problems. The methods and techniques applied are using the Waterfall model and the K-Means Algorithm. The stages of analysis and classification of behavior patterns can assist city governments in making strategic decisions. The variables determined include education, age, occupation, free time, smoking status, and questionnaire (outreach, law, knowledge, and facilities). The K-Means algorithm calculation results are 39 people in cluster 1 and 10 people in cluster 2. In cluster 1, it is known that the community tends to take care of the environment in the sub-district where the community lives. Cluster 2 has a low average yield, such as people who do not know the impact laws, inadequate sanitation facilities, and lack of proper waste management towards smart city governance. Based on testing for each method, the Cyclomatic Complexity value generated is four. Therefore, it can be concluded that the white box testing on the K-Means algorithm runs well because each test produces the same value. The government and the community have a responsibility to carry out waste management properly, make use of goods and refill facilities, know the legal impact of littering and follow the socialization held by the Makassar City Government.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14487 DO - 10.18517/ijaseit.11.4.14487

RefWorks

RT Journal Article
ID 14487
A1 Saptadi, N. Tri Suswanto
A1 Chyan, Phie
A1 Taga, Vanessa Putri
T1 Using K-Means Algorithm to Investigate Community Behavior in Treating Waste toward Smart City
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 4
YR 2021
SP 1455
OP 1462
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Algorithm; behavior; urban communities; waste management; smart city.
AB 

Urban communities' behavior in disposing and managing waste around the house is still very concerning. This study aims to analyze and classify community behavior patterns related to waste disposal to help the Makassar City Government overcome waste problems. The methods and techniques applied are using the Waterfall model and the K-Means Algorithm. The stages of analysis and classification of behavior patterns can assist city governments in making strategic decisions. The variables determined include education, age, occupation, free time, smoking status, and questionnaire (outreach, law, knowledge, and facilities). The K-Means algorithm calculation results are 39 people in cluster 1 and 10 people in cluster 2. In cluster 1, it is known that the community tends to take care of the environment in the sub-district where the community lives. Cluster 2 has a low average yield, such as people who do not know the impact laws, inadequate sanitation facilities, and lack of proper waste management towards smart city governance. Based on testing for each method, the Cyclomatic Complexity value generated is four. Therefore, it can be concluded that the white box testing on the K-Means algorithm runs well because each test produces the same value. The government and the community have a responsibility to carry out waste management properly, make use of goods and refill facilities, know the legal impact of littering and follow the socialization held by the Makassar City Government.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=14487 DO - 10.18517/ijaseit.11.4.14487