The classification of the quality of palm oil in PT Tasma Puja is still done by laboratory testing and then the data is saved manually in Excel. The method of grouping takes time and allows data to be lost. With the development of knowledge, it can be replaced by a data mining approach that can be used to classify the quality of palm oil based on its standards. The k-Means clustering method can be applied to classify the quality of palm oil based on water, dirt and free fatty acids. The data used is the quality data of palm oil in December 2017 as many as 31 data with criteria of good, very good and not good. The test results contained 3 clusters, namely cluster 0 for good categories amounted to 12 data, cluster 1 for very good category amounted to 13 data and cluster 2 for less good categories amounted to 6 data. The k-Means clustering method can be used for data processing using the concept of data mining in grouping data according to criteria.

Every year more than 2 million Americans die from heart disease which is the number one killer in the world. The results of the Sample Registration System (SRS) survey show that heart disease is the highest cause of death at all ages after stroke, which is 12.9%. The method used in this study uses the Naïve Bayes algorithm. The purpose of this study is to determine if anyone with heart disease has a stroke. From the research results obtained by splitting data using 80:20 to get a prediction accuracy rate of 83% for heart disease prediction cases. In the trial results using the label test data obtained, namely no stroke.

This study aims to determine and explain about the effect of service quality and brand image on customer loyalty mediated by customer satisfaction on Kampar Bakery Bangkinang bread products.  The data analysis using path analysis (Path Analysis). This study uses quantitative data. Random data collection techniques. Data sources in this study were from Kampar Bakery Bangkinang from 2013 until 2018. The data analysis techniques were descriptive analysis, normality test, multicollinearity test, autocorrelation test, heteroscedasticity test. The results of this study are as follows 1) Service quality has a positive and significant influence on customer satisfaction Kampar Bread Products Bakery. 2) Brand image has a positive and significant influence on customer satisfaction Kampar Bread Products Bakery. 3) Service quality has a positive and significant influence on customer loyalty Kampar Bread Products Bakery. 4) Brand image has a positive and significant influence on customer loyalty Kampar Bread Products Bakery. 5) Customer satisfaction has a positive and significant influence on customer loyalty Kampar Bread Products Bakery. 6) Service quality has a positive and significant influence on customer loyalty through customer satisfaction Kampar Bread Products Bakery. 7) Brand image has a positive and significant influence on customer loyalty through customer satisfaction Kampar Bread Products Bakery.

Laptop is one type of computer that is in great demand by the public at this time, especially for activities such as processing sales data and also purchasing and others can be done using a laptop. In using a laptop, there are several problems that are often faced at this time, namely the damage that occurs to the laptop and how to solve the problem of dealing with the damage to the laptop. Therefore, a web-based laptop damage expert system was created that serves as a substitute for experts for consulting media. In its manufacture, the system uses the backward chaining method for laptop damage data. The results of this study can detect laptop damage more quickly and precisely in helping users. With this system, it is hoped that it can help laptop users in overcoming the problem of laptop damage.

Transport vehicles in the form of trucks are one of the important components in supporting the logistics system when collecting crops in a plantation company. Fresh fruit bunches (FFB) produced by oil palm plantations must be sent to the location of the crude palm oil (CPO) processing plant at a predetermined time so that fruit quality is maintained. Therefore, scheduling and arranging the route of truck trips plays an important role. Constraints faced in plantations are the absence of a cellular internet network in plantations and limited road infrastructure so that location, time and route data cannot be accurately monitored. Scheduling can be done optimally and can reduce waiting times and queues of trucks that want to enter the shelter location. To overcome this problem, a monitoring system for oil palm trucks was created using a website-based GPS tracking. The components used are GPS Neo-6M, NodeMCU ESP8266, GSM SIM800L. It can be concluded that the tool can display data and information as expected, and the tool works well and can control the coordinates of the oil palm truck remotely.