Community Based Organizations are one of the non-governmental organizations involved in the development of local communities as the main actors. Local communities as local based non-commercial organizations that work on instruments for groups, for people to convey public interests, and for those that related to members to improve and stabilize their lives. Participation is considered an important role as a part of human growth. The main objective of this research is to construct a model for the implementation of public services that involves the participation of local communities so that they are efficient and help local communities obtain fair and non-supportive services. This model tries to solve complex problems in the implementation of Service Public Accountability Performance by involving all stakeholders by using resources so it runs effectively and efficiently. Based on the results of the pattern matching technique and time series showing the implementation of land needs the help of the local community. The local community in this study is Karang Taruna, this community is in an urban village area. As a local community, it will be very easy to organize the community. Karang Taruna also provides facilities for poor communities or beneficiary families for local governments to obtain social justice services.
Food is the ingredient that enables people to grow, develop, and achieve. For this reason, food quality and types of food must be considered so that they are safe for consumption and managed. Some plant-based foodstuffs are often processed and consumed by the community, even the most needed in food processing. In this case, the research was carried out using data mining with market basket analysis algorithms to obtain very valuable information to decide the inventory of the type of material needed. Market Based Analysis method is used to analyze all data and create patterns for each data. One method of Market Based Analysis in question is the association rule with a priori algorithm. This algorithm produces sales transactions with strong associations between items in the transaction which are used as sales recommendations that help users (owners) get recommendations when users see details of the itemset purchased. From the results of the trials in this study, it was found that the greater the minimum support (minsup) and minimum confidence (minconf), the less time it takes to produce recommendations and the fewer recommendations are given, but the recommendations given come from transactions that often appear.
The backpropagation algorithm has many training and activation functions that can be used to influence or maximize prediction results, all of which have their respective advantages and disadvantages. The purpose of this paper is to analyze one of the training functions of the backpropagation algorithm which can be used as a reference for use in data prediction problems in the form of models and best performance. The training function is the Bayesian Regularization method. This method is able to train the network by optimizing the Levenberg-Marquardt by updating the bias and weights. The research dataset used to analyze the data in this paper is Formal Education Participation in Indonesia 2015-2020 which consists of the School Participation Rate, the Gross Enrollment Rate, and the Pure Enrollment Rate. The 2015-2016 dataset is used as training data with a 2017 target, while the 2018-2019 dataset is the test data with a 2020 target. The models used are 2-10-1, 2-15-1, and 2-20-1. Based on the analysis and calculation process, the results of the 2-15-1 model are the best with an epoch of 217 iterations and an MSE of 0.00002945, this is because the epoch is not too large and has the smallest MSE compared to the other 2 models.
Public policy accountability seems to pose an everdeveloping challenge all around the globe. The increasing rate of complexity at the global scale compels bureaucracies to enhance their capabilities. In reality, however, bureaucracies become the most frequent targets of complaints from civic community organizations with respect to public policy implementations. On the other hand, they are seen as necessary multilateral, but much-in-need-of-reform, actors in global development. The main objective of this study is to build an agile bureaucracy model for public accountability in the implementation of the street vendor (PKL) policy in Indonesia. This model will observe whether agile bureaucracy management is helpful or inhibitory instead to the implementation of public policies. This study will also reveal the demanded accountability and politicization in policy actors' relationships. Data were collected by interview through focus group discussion (FGD) technique with twenty street vendor groups, with 10 to 15 members in each group. Documentation of informants who were directly involved in activities was also carried out. Data analysis processes included data reduction, data presentation, and conclusion drawing. The results of this research showed that building an agile model for the implementation of public policies helps teams with governance to generate high-quality outputs quickly. This features changes to the mindset which prioritizes clear, thorough vision over prescriptive details. This facilitates flexible leadership and organizational structures, cross-functional teams, talent ecosystems, and collaborative cultures and behaviors. Upon improvement and application to all organizations, agile breaks down functional silos, heightens transparency and accountability, and empowers employees.
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