Deteksi Dini Kanker Kulit menggunakan K-NN dan Convolutional Neural Network

Kanker kulit adalah salah satu jenis kanker yang dapat menyebabkan kematian sehingga diperlukan sebuah aplikasi perangkat lunak yang dapat digunakan untuk membantu melakukan deteksi dini kanker kulit dengan mudah. Sehingga diharapkan deteksi dini kanker kulit dapat terdeteksi lebih cepat. Pada penelitian ini terdapat dua metode yang digunakan untuk melakukan deteksi dini kanker kulit yaitu deteksi dengan klasifikasi secara regresi dan artificial neural network dengan arsitektur convolutional neural network. Akurasi yang diperoleh dengan menggunakan klasifikasi secara regresi adalah sebesar 75%. Sementara, akurasi deteksi yang didapatkan dengan menggunakan convolutional neural network adalah sebesar 76%. Hasil yang diperoleh dari kedua metoda ini masih dapat ditingkatkan pada penelitian lanjutan, yaitu dengan cara melakukan prapengolahan pada set data citra yang digunakan. Sehingga set data yang digunakan memiliki tingkat pencahayaan, sudut (pengambilan), serta ukuran citra yang sama. Apabila tersedia sumber daya komputasi yang besar, akan dilakukan penambahan jumlah citra yang digunakan, baik itu sebagai set data latih maupun uji. AbstractSkin cancer is one type of cancer that can cause death for many people. Because of this, an application is needed to easily detect skin cancer early that the cancer can be handled with more quickly. In this study there were two methods used to detect skin cancer, namely detection by regression classification and detection by classifying using artificial neural networks with network convolutional architecture. Detection with regression classification gives an accuracy of 75%. While detection using convolutional neural networks gives an accuracy of 76%. These proposed early detection systems can be improved to increase the accuracy. For further development, several image processing techniques will be applied, such as contrast enhancement and color equalization. For future works, if there is more computational resource, more images can be used as dataset and implement the deep learning algorithm to improve the accuracy

Proposed Business Strategy to Increase the Number of Customers for A Conveyor Belt Company

PT. XYZ is a company that provides conveyor belt needs for its clients with an office location in Central Java. PT. XYZ is currently getting a profit that is deemed not high enough for its shareholders even though it has established business relationships with leading companies. Some of the causes that make the low profit are the lack of a number of clients to work with, the limited company resources, and the high cost of packaging goods. This research will focus on the problem of the lack of a number of PT. XYZ's customers. Using the Five (5) Whys method, it was found the root cause analysis of the PT. XYZ is because of the number of industrial areas surrounding company is currently not much. Solutions that can be done in overcoming these problems are to apply market strategies such as market expansion, market development, diversification, or product development. In solving these problems, the SWOT Analysis method and research studies of previous studies are used. The results showed that market expansion was the chosen solution. This research approach can be used by companies that have similar problems