Sentiment analysis is a computational study of opinions and emotions expressed textually. Sentiment analysis will group text in sentences or documents to find out the opinions expressed in the sentence or document, whether negative or positive. This sentiment analysis research was conducted on the online taxi transportation service. Gojek uses a lot of social media to communicate with its customers, one of the social media used is Instagram. This research takes 1000 comments from the Instagram of the Gojek page which is used to see the public opinion of the online Gojek transportation services. Comments from the page are processed by doing text preprocessing and then classified using the Naive Bayes Classifier (NBC) method to obtain the value of the public value for online transportation services. The results of this study using the Naive Bayes method resulted in an accuracy value of 81.00%, which means that from all the comments on the Instagram page, the subject of the NBC method could be accurately classified by 81.00% whether the comments were negative or positive comments.
Peningkatan mutu dalam penyeleksian karyawan yang dilakukan oleh Divisi Sumber Daya Manusia Perusahaan menyebabkan karyawana terus berupaya dalam meningkatkan kompetensi dirinya. Untuk mengukur kinerja karyawan diperlukan suatu sistem pendukung yang dapat mengukur terhadap kinerja karyawan dengan memberikan penilaian kinerja terhadap karyawan tersebut, sehingga perusahaan dapat melakukan sistem penilaian secara objektif kepada setiap karyawan dengan harapan perusahaan memberikan transparansi terhadap penilaian yang dilakukan terhadap kompetensi dan kualitas karyawan sesuai dengan kebutuhannya. Sistem Pendukung Keputusan ini dibuat untuk Memberikan solusi dan membantu Manajer Sumber Daya Manusia dalam menentukan karyawan terbaik pada PT. Persada Nusantara Telekomunikasi. Metode Simple Additive Weighting (SAW) dipilih sebagai metode yang digunakan sebagai sistem pendukung keputusan untuk memilih karyawan terbaik. Metode Simple Additive Weighting merupakan suatu metode penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. Hasil dari sistem penunjang keputusan ini diharapkan memberi suatu pilihan alternatif yang dimiliki Divisi Sumber Daya Manusia sebagai suatu solusi dalam menentukan karyawan terbaik yang ada diperusahaan. Kata Kunci: Sistem Pendukung Keputusan, Karyawan Terbaik, Simple Additive Weighting.
One important factor for creating a healthy and growing company is the existence of sales rewards for employees to achieve sales targets every month. Assessing employees is not an easy thing when there are so many employees. This will make the assessment team have to look at the criteria carefully and carefully. Data manipulation can occur because it is difficult to make decisions with such large criteria and data without automated data mining. As a result, the company will not get competitive human resources. Sales targets are one of the keys to sales success because with sales targets, the sales prediction value can be used as a guide as a reference in determining product sales. One way to make better sales predictions is by utilizing data mining processing using the Naive Bayes algorithm. The Naive Bayes algorithm calculates the probability value of each of the attributes examined including attendance, sales targets and sales returns. Research with employee absence criteria, monthly sales and monthly sales invoice returns. From the results of the research that has been done, it can be concluded that the application of the Naive Bayes classifier method to the target data set for sales of goods achieves an optimization level of 95.78%, with attendance criteria greatly affecting employee performance so that product sales targets each month can be achieved
Linear programming that can be found in life around is an assignment problem. Common assignment problems include n tasks that must be assigned to m workers assuming each worker has different competencies in completing each task. One of the methods in solving this problem is the Hungarian method. The purpose of this research is to optimize the assignment of employees by looking at the cost of daily wages. The problems that occur at the OneTop Frozen Store are the ineffectiveness of the work process and the swelling of operational costs, especially at work, Order Sorting, Packing, Labeling, Delivery with 4 workers. The application of the Hungarian method and testing of Software Quality Management obtains optimal wage costs so that operational costs can be reduced to a minimum without reducing the quality of service to consumers. Based on data processing in the Hungarian method, an assignment that is in accordance with the work in preparing Frozen Food orders at the OneTop Store can cost a daily wage of Rp.130,000 (one hundred and thirty thousand) to be the optimal wage cost per day. when compared with the previous calculation without using the Hungarian method by paying wages of Rp. 175,000 (one hundred and seventy five) per day. Based on the application of the Hungarian method, it is effective in determining an assignment and placement of workers so that they can work more effectively on a better and optimal Frozen Food ordering process.
Research on Expert Systems to Diagnose Matic Motorcycle Engine Damage by applying Algortima K-means. Research to detect damage to an automatic motorcycle by observing the symptoms of an automatic motorcycle. This study aims to help Matic Motorcycle users to find out about damage to the automatic motorcycle based on the results of the application of the K-Means algorithm without having to meet with experts directly. Research by applying Algortima k-Means by forming groupings based on electrical damage, compression and engine performance, continuous variable transmission timing and automatic sensors so that the damage can be grouped. The results of the expert system research with the K-Means Algorithm can help matic motorcycle users to find out the type of damage based on the grouping that has been determined by the K-Means algorithm.
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