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Implementation and Analysis Zhu-Takaoka Algorithm and Knuth-Morris-Pratt Algorithm for Dictionary of Computer Application Based on Android Handrizal Handrizal; Andri Budiman; Desy Rahayu Ardani
IJISTECH (International Journal of Information System and Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (661.504 KB) | DOI: 10.30645/ijistech.v1i1.2

Abstract

The string matching algorithm is the one of the most important parts in the various processes related to data and text types, which is the word search on computer dictionary. Computers have a basic role in the field of education, especially in teaching and learning activities. So that the classical learning model, that is by using the book as learning resource can be boring. To make it easier for users who searching words, we made an offline dictionary application based on Android by applying Zhu-Takaoka algorithm and Knuth-Morris-Pratt algorithm. The performance of Zhu-Takaoka is doing a search starts from the end of pattern that is tailored to the text, but in Knuth-Morris-Pratt algorithm starts from the beginning of pattern till match which the pattern used is word searched. The result of this research indicates that the Zhu-Takaoka algorithm is faster than the Knuth-Morris-Pratt algorithm which showed the running time of each algorithm.
Implementation and Analysis Zhu-Takaoka Algorithm and Knuth-Morris-Pratt Algorithm for Dictionary of Computer Application Based on Android Handrizal Handrizal; Andri Budiman; Desy Rahayu Ardani
IJISTECH (International Journal of Information System and Technology) Vol 1, No 1 (2017): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v1i1.2

Abstract

The string matching algorithm is the one of the most important parts in the various processes related to data and text types, which is the word search on computer dictionary. Computers have a basic role in the field of education, especially in teaching and learning activities. So that the classical learning model, that is by using the book as learning resource can be boring. To make it easier for users who searching words, we made an offline dictionary application based on Android by applying Zhu-Takaoka algorithm and Knuth-Morris-Pratt algorithm. The performance of Zhu-Takaoka is doing a search starts from the end of pattern that is tailored to the text, but in Knuth-Morris-Pratt algorithm starts from the beginning of pattern till match which the pattern used is word searched. The result of this research indicates that the Zhu-Takaoka algorithm is faster than the Knuth-Morris-Pratt algorithm which showed the running time of each algorithm.
JARINGAN SARAF TIRUAN DALAM MEMPREDIKSI SUKUK NEGARA RITEL BERDASARKAN KELOMPOK PROFESI DENGAN BACKPROPOGATION DALAM MENDORONG LAJU PERTUMBUHAN EKONOMI Agus Perdana Windarto; Solikhun Solikhun; Handrizal Handrizal; M Fauzan
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 4, No 2 (2017)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v4i2.90

Abstract

State Retail Sukuk is a Sharia Securities issued and its sale is regulated by the State, namely the Ministry of Finance (Depkeu). Where the government will choose the seller agent and consulting retail sukuk law. Selling agents must be obliged to have a commitment to the government in the development of the sukuk market and experience in selling Islamic financial products. The publication of this instrument is likened to a "mutualist symbiosis" between the Government and Society, both of which benefit equally. The government as the publisher benefits from the use of funds from the community, while the community benefits from investments made. This research contributes to the government and the Bank to be able to promote maximally for the next sukuk issuer. The data used is data from kemenkeu through website www.djppr.kemenkeu.go.id. The data are sukuk sales data with series 001 - 007 which are grouped into several categories namely geography, profession and age category. Algorithm used in this research is Artificial Neural Network with Backpropogation method. The input variables used are PNS (X1), Private Officer (X2), IRT (X3), Entrepreneur (X4), TNI / Polri (X5) and Others (X6) with architectural model of training and testing of 6 architectures 6-2-1, 6-5-1, 6-2-5-1 and 6-5-2-1. The output (output) generated is the best pattern of the ANN architecture. The best architectural model is 6-5-2-1 with epoch 37535, MSE 0.0009997295 and 100% accuracy rate. From this model will be conducted sensitivity analysis to see the variable that has the best performance and obtained variable Private Employees (X2) with a score of 0.3268. So obtained the results of the most investors predicted on the purchase of sukuk for the next 008 series based on the profession category is Private Employees. Keywords: Sukuk, JST, Backpropogation, Sensitivity Analysis and PredictionSukuk Ritel Negara adalah Surat berharga Syariah yang diterbitkan dan penjualannya diatur oleh Negara, yaitu Departemen Keuangan (depkeu). Dimana pemerintah akan memilih agen penjual dan konsultasi hukum sukuk ritel. Agen penjual haruslah wajib memiliki komitmen terhadap pemerintah dalam pengembangan pasar sukuk dan berpengalaman dalam menjual produk keuangan syariah. Penerbitan instrumen ini diibaratkan sebuah “simbiosis mutualis” antara Pemerintah dan Masyarakat, dimana keduanya sama-sama memperoleh keuntungan. Pemerintah selaku penerbit memperoleh keuntungan berupa  penggunaan dana dari masyarakat, sedangkan masyarakat memperoleh keuntungan dari investasi yang dilakukan. Penelitian ini memberikan kontribusi bagi pemerintah dan Bank untuk dapat melakukan promosi secara maksimal untuk penerbitat sukuk berikutnya. Data yang digunakan adalah data dari kemenkeu melalui website www.djppr.kemenkeu.go.id. Data tersebut adalah data penjualan sukuk dengan seri 001 – 007 yang dikelompokkan dalam beberapa kategori yakni geografis, profesi dan kategori umur. Algoritma yang digunakan pada penelitian ini adalah Jaringan Saraf Tiruan dengan metode Backpropogation. Variabel masukan (input) yang digunakan adalah PNS (X1), Pegawai Swasta (X2), IRT (X3), Wiraswasta (X4), TNI/Polri (X5) dan Lainnya (X6) dengan model arsitektur pelatihan dan pengujian sebanyak 6 arsitektur yakni 6-2-1, 6-5-1, 6-2-5-1 dan 6-5-2-1. Keluaran (output) yang dihasilkan adalah pola terbaik dari arsitektur JST. Model arsitektur terbaik adalah 6-5-2-1 dengan epoch 37535, MSE 0,0009997295 dan tingkat akurasi 100%. Dari model ini akan dilakukan analisis sensivitas untuk melihat variabel yang memiliki performa terbaik dan diperoleh variabel Pegawai Swasta (X2) dengan skor 0,3268. Sehingga didapat hasil prediksi investor terbanyak pada pembelian sukuk untuk seri 008 berikutnya berdasarkan kategori profesi adalah Pegawai Swasta.Kata Kunci: Sukuk, JST, Backpropogation, Analisis Sensivitas dan Prediksi
ALGORITMA BACKPROPAGATION DALAM MEMPREDIKSI JUMLAH KENDARAAN BERMOTOR YANG MEMBAYAR PAJAK MENURUT JENIS KENDARAAN DI KABUPATEN BATUBARA Enjelica Rumapea; Bintang Bestari; Joose Andar Laidin Manurung; Handrizal Handrizal; Solikhun Solikhun
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 2 No. 1 (2019): Jurnal RESISTOR Edisi April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v2i1.357

Abstract

Tax is a source of funds for the state to overcome various problems such as social problems, improving welfare, prosperity of its people. In the Batubara district itself, the number of receipts of Motor Vehicle Taxes and the development of the number of motorized vehicles have increased but not offset by awareness of taxpayers, this is reflected in the amount of arrears and considerable fines at the Coal Samsat Office. Looking at these problems, a method that is effective in estimating the number of vehicles paying taxes in the Batubara district is needed. The data used is data from the Regency Statistics Agency. Coal through the website www.batubarakab.bps.go.id. The data is the number of motorized vehicles that pay taxes in the Coal district in the period of 2012 to 2017. The algorithm used in this study is Artificial Neural Networks with the Backpropagation method. Input variables used are 2012 data (X1), 2013 data (X2), 2014 data (X3), 2015 data (X4), 2016 data (X5) and 2017 data as targets with models training and testing architecture of 4 architectures namely 4-4-1, 4-8-1, 4-16-1, 4-32-1. The resulting output is the best pattern of ANN architecture. The best architectural model is 4-8-1 with epoch 3681, MSE 0.009744 and 100% accuracy. So that the prediction of the number of motorized vehicles that pay taxes is obtained in Batubara district.