Taluk Village, Lintau Buo Subdistrict, Tanah Datar Regency is one of the villages that carries out the distribution of the Village Fund Direct Cash Assistance (BLT-DD) program. This direct cash assistance is one of the government programs whose funds are sourced from village funds whose distribution is to the underprivileged or poor in order to overcome economic recovery for people affected by the pandemic. However, in the evaluation of its implementation in 2021 and 2022, many problems were found in its distribution, especially in determining this assistance to the recipient community. The problems that arise are caused by the occurrence in data processing that uses a direct determination system or mechanism in deliberation by the village government to determine the priority community as recipients of the many who propose as applicants to the nagari government to get this assistance. Besides that, there are also problems such as errors in recipient criteria and often this program is not targeted at the recipients. The K-Means Clustering method is very precise in implementing this BLT-DD beneficiary predictor, because this method is one of the methods used in data grouping as a reference in decision makers for clustering large amounts of data, and in the end it will cluster recipients based on 3 clusters, namely worthy, considered and unworthy. The purpose of this study was to predict the right target recipients of BLT-DD. The data processed is the data proposed by the recipients of the BLT-DD Taluk Village in 2022. Based on the results of data processing using PHP MYSQL Software, from a sample of 25 data, 11 data are produced which are included in cluster 1 with the status of the beneficiary being said to be feasible, 5 data that are classified as eligible. including cluster 2 with considered recipient status and as many as 9 data belonging to cluster 3 with unfit status. From the test results obtained an accuracy rate of 83.33 % so that it can be recommended to assist the government of the village guardian in making policies.

The hospital is one of the health service centers that play an important role in society. Health Centers must provide the best service for their patients. In practice, good or excellent service is not easy to realize because of various factors that exist in the field which are probalistic in nature. To maintain service quality, it is necessary to carry out evaluation, analysis, and improvement activities on the existing system. Evaluation, analysis, and improvement activities on the system can be carried out using system simulations with the aim of producing better services. This research was conducted in an outpatient service system using discrete event simulation with the help of promodel software. The purpose of this study is to apply a discrete event simulation model in outpatient services so that there is an improvement in outpatient services and the efficiency of existing human resources. The simulation results show that the simulation model used is valid and can be used to evaluate the outpatient service system.

In Indonesia, the laying hens business sector experiences many obstacles, farmers often face instability between the price of chicken eggs and the price of feed which tends to always increase. The income received by farmers is not proportional to the cost of feed incurred. The production cost of laying hens can be reduced if there is an increase in feed efficiency. Maintenance of laying hens lies in the provision of feed, water, physical conditions and the state of the cage. Feed is the main source of energy for laying hens. The problem of feed in laying hens must meet the quality and quantity of the feed itself so that the effect is very real and clear on egg production. Feed nutrition must also meet the needs of laying hens. Feeding laying hens without paying attention to the quality of the feed can result in the growth and productivity of chickens being not optimal. Combining feed is an effort that can be made to produce a quality feed composition. This research was conducted to compile the composition of laying hens' feed using the K-Means Clustering algorithm. The K-Means Clustering method is an algorithm used by researchers to group or cluster data on laying hens feed into several clusters by using the nutritional content of each feed as an attribute. In this study, the data analyzed was data on the nutritional content of laying hens feed consisting of attributes such as protein, fat, crude fiber, calcium and phosphorus. This study will produce 3 clusters of feed types consisting of highly optimal clusters, optimal clusters and less than optimal clusters. This research is expected to be used as a recommendation by laying hens in compiling the composition of laying hens to maintain the quality of the eggs produced.