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Luky Agus Hermanto
Jurusan Teknik Informatika, Fakultas Teknologi Informasi, Institut Teknologi Adhi Tama Surabaya
Computer Science & IT

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Klasifikasi Kualitas Pisau Potong Tembakau (CUT CELL) Menggunakan Metode Radial Basis Function (RBF) Fungki Apriyanto; Hari Agus Sujono; Luky Agus Hermanto
INTEGER: Journal of Information Technology Vol 1, No 2 (2016): September 2016
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2016.v1i2.62

Abstract

Indonesia is one of countries that produces several types of tobacco. Almost 80% tobacco produces is used of cigarette industry. Tobacco leaves slicing into small cuts is one of the process of cigarette production. The cutting process of tobacco requires Cut Cell which is able to cut tobacco into small pieces. Contol is required in the process of making cut cell to set the quality of the blade. The quality control often has problem in determining the Cut Cell quality. The problem is the length of time needed in determining the quality. In this fast paced era, the Quality Control is demanded to be able to determine the cut cell quality quickly and accurately. To support this need from the Quality Control, a system that can be used to determine the cut cell quality which has fast output result. The research process is started with collecting the system needs, followed by system designing, then system making, and system test. The system designing is initiated by preparing the test data and training data which are going to be used for the making and testing of the system. RADIAL BASIS FUNCTION consist of several calculation processes. The first  process is the process of center search of each variable using K-MEANS method. Aftar the center is found, the deviation standard of each variable is calculated. The second process is setting the GAUSSIAN matrix of every group found. The third process is the process of new weight and bias values search by doing pseudo-inverse GAUSSIAN matrix multiplication. The forth process is classification in which this process sets out the classication result by multiplying the value of GAUSSIAN matrix and new weight and bias applying network output formula. The experiment done to 75 experiment data which are compared to manual data as the reference result 12 different data, thus it can be concluded that the accuracy level of this system is 84 %.
Saran Aksi Saham Dengan Pendekatan Fundamental Dan Teknikal Menggunakan Metode Learning Vector Quantization Neural Network I Made Gery Inggrayana; Wahyu Widodo; Luky Agus Hermanto
INTEGER: Journal of Information Technology Vol 1, No 2 (2016): September 2016
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2016.v1i2.60

Abstract

Stock is one instrument that is traded in the capital market. Investment in the form of shares can also offer enormous profit, even though it is highly risky in the investment especially on weekly stock trade.; Based on this reason, a system is developed to help take action in transactions whether to buy, sell or hold the stock. This analysis system uses technical and fundamental approach by applying Learning Vector Quantization (LVQ). This research uses five inputs taken from technical analysis, namely: Open Price, High Price, Low Price, Close Price, and Volume. One more input from the fundamental approach is Last Price. This system test indicated 72% accuracy on the transaction actions.
Co-Authors Fungki Apriyanto Hari Agus Sujono I Made Gery Inggrayana Wahyu Widodo