Data Mining using K-means method for feasibility selection of Non-cash food Assistance recipients in the Era of Covid-19

All countries in the world are currently experiencing a severe economic crisis following the outbreak of the COVID-19 outbreak. In Indonesia, the Large-Scale Social Restriction (PSBB) policy is reported to have increased the number of poor people. Social assistance is a government program to improve the social welfare of the lower economic community. In carrying out the program, the central government and local governments coordinate with each other so that the program is right on target without any element of fraud. In the neighbourhood of Rukun Warga 001, Kelapa Dua Village, there are still obstacles in selecting the eligibility for social assistance recipients, namely Non-Cash Food Aid. The data on the poor are not in accordance with the actual conditions. In this study, to implementing data mining with the K-Means Algorithm. The K-Means Clustering algorithm is used to classify people who are classified as eligible to receive social assistance and those who are not entitled to receive social assistance. The data sample used is the data of Rukun Warga 001, Kelapa Dua Village. The results of this study indicate that cluster 1 with the appropriate category of receiving social assistance according to government programs in the Rukun Warga 001 neighbourhood of Kelapa Dua sub-district amounted to 13 families. And cluster 2 in the category of not eligible to receive social assistance amounted to 97 heads of families out of a total of 110 heads of families in RW 001.

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The Indonesian Government's Inconsistency in Handling The Covid-19 Pandemic

Yuridika ◽

10.20473/ydk.v36i3.27515 ◽

2021 ◽

Vol 36 (3) ◽

pp. 745

Author(s):

Syamsuddin Radjab ◽

Muhammad Ikram Nur Fuady

Keyword(s):

Natural Disaster ◽

Local Governments ◽

Large Scale ◽

Central Government ◽

Criminal Sanctions ◽

Public Health Emergencies ◽

Legal Sanctions ◽

Social Restriction ◽

The Government ◽

Administrative Sanctions

A clear legal umbrella is a basis for the effectiveness of a policy, including in dealing with the Covid-19 pandemic. However, the inconsistency of the legal umbrella in giving birth legal uncertain, and the public becomes confused. This research aims to critique the Indonesian government's attitude in dealing with the Covid-19 pandemic, which began in early 2020 due to the legal umbrella's inconsistency in enforcing different and ineffective legal sanctions at the central government and local governments. The research method used is normative research with a statutory approach. In contrast, the research explained in a descriptive-qualitative way. This research shows that the government considers the Covid-19 pandemic a non-natural disaster and does not lockdown. Meanwhile, the legal umbrella used is the health quarantine law, which requires implementing public health emergencies, almost the same as lockdowns. On the other hand, the Large-Scale Social Restriction (PSBB) policy has a legal basis for a health quarantine law. At the same time, the Covid-19 pandemic situation is a non-natural disaster that should refer to the disaster management law. Furthermore, other results also show ineffective enforcement of legal sanctions, such as criminal sanctions in regional head decisions that can not enforce because PSBB only includes administrative sanctions. In conclusion, the inconsistency of the legal umbrella in dealing with the Covid-19 pandemic is very detrimental to the community due to limited human rights, which can lead to legal uncertainty and public distrust of the government.

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The Transformation of social aid during large-scale social restrictions and public activity restriction

Monas: Jurnal Inovasi Aparatur ◽

10.54849/monas.v3i1.69 ◽

2021 ◽

Vol 3 (1) ◽

pp. 257-268

Author(s):

Azwar Anas

Keyword(s):

Local Governments ◽

Large Scale ◽

Central Government ◽

Safety Net ◽

Activity Restriction ◽

Public Activity ◽

Restriction Policy ◽

Social Restriction ◽

The Government ◽

Negative Impacts

The COVID-19 pandemic has affected 220 countries and territories in the world. Based on WHO data as of June 25, 2021, as many as 179 million people have been infected and 3.89 million people have died. Lockdown policies, border closures, flight restrictions and social restrictions have been implemented to prevent the spread of COVID-19. The Government of Indonesia applied the Large-Scale Social Restrictions policy in 2020, and has implemented a Public Activity Restriction policy since 2021. Some impacts include the decrease of economic activity, the increase of unemployment, and the growth of poverty rates. To minimize the negative impacts of the COVID-19 pandemic, the government then applied a social safety net program by providing social aid to the poor and affected communities. This study aims to explain the transformation of social aid in the era of the COVID-19 pandemic when the Large-Scale Social Restriction and Public Activity Restriction were and are implemented. To answer this, a descriptive qualitative analysis method was used. The results of this study indicate that there has been a transformation of social aid in the form of synergies between central government and local governments, regulations adjustments, the increment of aid recipients, the increase of social aid rate, the alteration of aid types from basic food to cash, data update, the changes in aid distribution mechanisms, the collaboration among various stakeholders and the innovation in using information technology systems.

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Considerations on Relationship Between Central and Local Governments During Huge Disasters – Necessity and Application of Special Rules on Evacuation Measures and Relief –

Journal of Disaster Research ◽

10.20965/jdr.2020.p0503 ◽

2020 ◽

Vol 15 (4) ◽

pp. 503-519

Author(s):

Tetsuo Murota ◽

Fumio Takeda ◽

◽

Keyword(s):

Local Governments ◽

Large Scale ◽

Central Government ◽

Nankai Trough ◽

Prevention Measures ◽

Nuclear Disaster ◽

Application Procedure ◽

Special Rules ◽

National Emergency ◽

The Relationship

The relationship between the Central and local governments during an emergency has been primarily discussed at the Diet, in connection with the Constitution’s amendment, including the emergency provisions. However, opinions from the various fields are divided and discussions are typically based on whether an emergency state should be tackled principally by the Central Government or municipalities. The increasing risk of a super wide-area disaster (huge disaster) that can be expressed as national emergency state, such as the Great Nankai Trough Earthquake and large-scale flood, makes it imperative for advancing the previously mentioned discussions. It should be examined whether a state of emergency state could be managed appropriately within the administrative framework of the municipalities based on the Disaster Countermeasures Basic Act. In addition, necessary measures should be adopted within the purview of the existing laws apart from the discussions on the amendment of the Constitution. In this case, detailed discussions are needed on, for example, what kind of special rules should be established regarding the relationship between the Central and local governments. In this paper, the Great Nankai Trough Earthquake, large-scale flood in metropolitan areas, nuclear disaster, and complex disaster along with natural disaster are considered; the plans created by the Central Government in terms of the disaster prevention measures for such disasters are examined; and the items requiring special rules on the relationship between the Central and local governments are extracted from the disaster emergency measures. Furthermore, the per item application procedure of these special rules is also determined.

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Parallel Cleaning Algorithm for Similar Duplicate Chinese Data Based on BERT

Scientific Programming ◽

10.1155/2021/5916748 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Biqiu Li ◽

Jiabin Wang ◽

Xueli Liu

Keyword(s):

Data Mining ◽

Large Scale ◽

Clustering Algorithm ◽

Parallel Implementation ◽

Data Cleaning ◽

Position Vector ◽

Data Sets ◽

Implementation Scheme ◽

Mining Work ◽

Context Features

Data is an important source of knowledge discovery, but the existence of similar duplicate data not only increases the redundancy of the database but also affects the subsequent data mining work. Cleaning similar duplicate data is helpful to improve work efficiency. Based on the complexity of the Chinese language and the bottleneck of the single machine system to large-scale data computing performance, this paper proposes a Chinese data cleaning method that combines the BERT model and a k-means clustering algorithm and gives a parallel implementation scheme of the algorithm. In the process of text to vector, the position vector is introduced to obtain the context features of words, and the vector is dynamically adjusted according to the semantics so that the polysemous words can obtain different vector representations in different contexts. At the same time, the parallel implementation of the process is designed based on Hadoop. After that, k-means clustering algorithm is used to cluster similar duplicate data to achieve the purpose of cleaning. Experimental results on a variety of data sets show that the parallel cleaning algorithm proposed in this paper not only has good speedup and scalability but also improves the precision and recall of similar duplicate data cleaning, which will be of great significance for subsequent data mining.

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DEVELOPMENT STRATEGY PORT OF BIAS MUNJUL IN TOURISM RECOVERY AT THE POST COVID-19

ASTONJADRO ◽

10.32832/astonjadro.v11i1.5779 ◽

2021 ◽

Vol 11 (1) ◽

pp. 108

Author(s):

I Gede Wahyu Kusuma ◽

Ngakan Ketut Acwin Dwijendra ◽

Ni Made Yudantini

Keyword(s):

Development Strategy ◽

Local Governments ◽

Large Scale ◽

Swot Analysis ◽

Central Government ◽

Local Communities ◽

Tourism Industry ◽

Descriptive Data ◽

Data Presentation ◽

Prime Condition

<p>Indonesia implements Large-Scale Social Restrictions (PSBB) which are enforced per region based on the severity of the outbreak and the assessment is determined by the central government through the Ministry of Health. Restrictions on activities for traveling have a great impact on areas that utilize the tourism industry. Restrictions on activities lead to a decline in the economy of the community, especially in areas that rely on the tourism industry. Infrastructure has an important role in efforts to recover the economy and tourism after the pandemic. The infrastructure used as the object of research is the project Port Munjul Bias, which is one of the ongoing port projects on Ceningan Island. The purpose of the study was to look at the strategy for developing the Port Bias Munjul in the post-Covid-19 pandemic recovery. The type of research used is qualitative research with descriptive data presentation. The approach used is a SWOT analysis to see the strategy for developing the Port Bias Munjul in the midst of the Covid-19 Pandemic. The results obtained are the construction of the Port Bias Munjul in prime condition (SO), which shows that the existence of the Port Bias Munjul project will play a very important role in the recovery of tourism and the economy in Nusa Ceningan or its surroundings. Strategies that can be carried out are in the form of cooperation between local governments and the private sector, empowerment of local communities and improvement of logistical support facilities.</p>

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Penerapan Algoritma Decision Tree Untuk Memprediksi Penerima Bantuan Keluarga Harapan

Jurnal ICT : Information Communication & Technology ◽

10.36054/jict-ikmi.v19i1.93 ◽

2020 ◽

Vol 19 (1) ◽

pp. 70-76

Author(s):

Agus Bahtiar ◽

Parasian DP Silitonga

Keyword(s):

Data Mining ◽

Poverty Reduction ◽

Poor People ◽

Assistance Program ◽

Assistance Programs ◽

The Family ◽

C4.5 Algorithm ◽

The Government ◽

Best Parameter ◽

To Receive

The Family of Hope Program (PKH) is a poverty reduction program in the education and public health aspects provided by the government either directly or indirectly. The government continues to make efforts in order to educate the community through social assistance programs to tackle the poor. In order to create a smart society, the government should make programs that are empowering so that people can solve their own problems. There are many in Indonesia who receive the family hope program (PKH), one of which is in the Cirebon district. Problems often occur with the empowerment assistance program from the government, one of which is the PKH assistance, which still does not target the residents who receive the assistance. The emergence of this problem, due to the ineffective data verification in determining which citizens are entitled to receive PKH assistance, this has resulted in many very poor people who do not receive PKH assistance and those classified as capable are still given PKH assistance. Therefore, it is necessary to conduct a study of PKH beneficiary data, so that the results of the analysis can be used as a reference for whether or not residents are eligible to receive PKH assistance. The research that was conducted to predict the data of recipients of the expected family assistance using the data mining classification method using the C4.5 algorithm. The results of the data mining process are used as evaluation material for the government. After testing with the C4.5 algorithm, the test results for the best parameter of the C4.5 algorithm are criterion = accuracy, confidence = 0.25 and a minimum gain = 0.1 to produce an accuracy value of 98.30%

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Pandemic, SDGs, and CSR: Case Study of Indonesia

E3S Web of Conferences ◽

10.1051/e3sconf/202020203007 ◽

2020 ◽

Vol 202 ◽

pp. 03007

Author(s):

Sudharto P Hadi ◽

Hairy Mohd Ibrahim ◽

Prabawani Bulan ◽

Sri Suryoko

Keyword(s):

Content Analysis ◽

Literature Review ◽

Large Scale ◽

Well Being ◽

Poor People ◽

Economic Activities ◽

Descriptive Research ◽

Social Restriction ◽

Zero Hunger

Pandemic covid-19 does not only threat lives and health of people but also hit economic, social, and well-being. Large scale social restriction (PSBB) paralyze all economic activities, in turn, causing unemployment and escalating the number of poor people. Indonesian government provide direct social assistance and other measures to ease the burden of impacted people. Pandemic covid-19 also threats the target of achieving SDGs specifically dealing with pillar 1 (no poverty) and pillar 2 (zero hunger). Through CSR, corporates have important role in dealing with pandemic covid-19 at the stage of emergency and rehabilitation. This paper observed two corporates, holder of Gold Proper ranking, in responding pandemic covid-19 at their areas. This is a descriptive research in which the content analysis, literature review, and webinar are employed to collect the data. The data gathered analysed qualitatively. The CSR adopted by two corporates do not only deal with emergency and rehabilitation stages but also empower people to produce products needed during the pandemic covid-19.

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Improving Local Governments’ Financial Sustainability by Using Open Government Data: An Application of High-Granularity Estimates of Personal Income Levels in Romania

Sustainability ◽

10.3390/su11205632 ◽

2019 ◽

Vol 11 (20) ◽

pp. 5632 ◽

Cited By ~ 5

Author(s):

Bulai ◽

Horobeț ◽

Belascu

Keyword(s):

Local Governments ◽

Clustering Algorithm ◽

Central Government ◽

Personal Income ◽

Open Government ◽

Financial Sustainability ◽

Income Levels ◽

Market Intelligence ◽

Open Government Data ◽

Government Data

The availability of open government data has expanded considerably in recent years. This expansion is expected to generate significant benefits not just for increasing government transparency, but also for the economy. The aim of this study is to illustrate the use of open government data in estimating personal income levels for all 3181 municipalities, towns, and communes in Romania. The novelty of our work comes from the high granularity of the estimates obtained. We use tax revenues collected by local governments in Romania on vehicles and buildings owned by natural persons, as well as data on energy subsidies. The classification is conducted using the k-means clustering algorithm. We find three distinct clusters of communities, which we map. The results can benefit both businesses and policymakers. The former can use the income level estimates for market intelligence purposes, while for the latter, these may aid in determining the financial sustainability of local governments and a better allocation of central government resources at the subnational level.

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Sponge city construction in China: policy and implementation experiences

Water Policy ◽

10.2166/wp.2018.021 ◽

2018 ◽

Vol 21 (1) ◽

pp. 19-37 ◽

Cited By ~ 5

Author(s):

Chenyao Xiang ◽

Jiahong Liu ◽

Weiwei Shao ◽

Chao Mei ◽

Jinjun Zhou

Keyword(s):

Local Governments ◽

Flood Control ◽

Large Scale ◽

Central Government ◽

Low Impact Development ◽

Economic Conditions ◽

Chinese Government ◽

Urban Water ◽

Sponge City ◽

City Construction

Abstract To deal with the three universal urban water problems – namely storm floods, water pollution and water shortage – China has implemented a comprehensive solution: the Sponge City Construction Project. Sponge cities aim to reduce runoff and pollution, and also to restore downstream ecologies. They combine low impact development methods with grey infrastructures, large-scale flood control projects and rehabilitation. This paper describes Chinese experiences of construction and financing for implementation of sponge cities, which could provide references to other countries for building sustainable, climate-resilient cities and urban water management systems. It illustrates the objectives and methods of the sponge city design and demonstrates the differences in configuration and funding structures in cities of different climates and economic conditions. The total construction area involved in the pilot cities covers 449 km2. The configurations are distinct due to different economic conditions, climates and land forms: a humid district inclines to drainage-efficient approaches and pollution control devices, while a semi-humid district prefers green infrastructures and rainwater reuse facilities. The Chinese government plays an important role in the funding of sponge cities: Chinese central government provided CNY (¥)20.7 billion for the construction of 16 cities during 2015–2017, while the rest came from local governments and non-governmental investors.

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Analysis of University Students’ Behavior Based on a Fusion K-Means Clustering Algorithm

Applied Sciences ◽

10.3390/app10186566 ◽

2020 ◽

Vol 10 (18) ◽

pp. 6566

Author(s):

Wenbing Chang ◽

Xinpeng Ji ◽

Yinglai Liu ◽

Yiyong Xiao ◽

Bang Chen ◽

...

Keyword(s):

Data Mining ◽

Large Scale ◽

Clustering Algorithm ◽

Learning Performance ◽

Practical Significance ◽

Digital Campus ◽

Data Mining Algorithms ◽

Density Peaks ◽

Data Points ◽

The University

With the development of big data technology, creating the ‘Digital Campus’ is a hot issue. For an increasing amount of data, traditional data mining algorithms are not suitable. The clustering algorithm is becoming more and more important in the field of data mining, but the traditional clustering algorithm does not take the clustering efficiency and clustering effect into consideration. In this paper, the algorithm based on K-Means and clustering by fast search and find of density peaks (K-CFSFDP) is proposed, which improves on the distance and density of data points. This method is used to cluster students from four universities. The experiment shows that K-CFSFDP algorithm has better clustering results and running efficiency than the traditional K-Means clustering algorithm, and it performs well in large scale campus data. Additionally, the results of the cluster analysis show that the students of different categories in four universities had different performances in living habits and learning performance, so the university can learn about the students’ behavior of different categories and provide corresponding personalized services, which have certain practical significance.

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