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Penggunaan Metode Depth First Search (DFS) dan Breadth First Search (BFS) pada Strategi Game Kamen Rider Decade Versi 0.3 Prasetiyo, Budi; Hidayah, Maulidia Rahmah
Scientific Journal of Informatics Vol 1, No 2 (2014): November 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i2.4022

Pada permainan Game Kamen Rider Decade ini sangat membutuhkan strategi yang tepat jika ingin memenangkan dengan mudah permainan ini. Penelitian ini bertujuan untuk mengimplementasikan metode Dept First Search (DFS) dan Breadth First Search (BFS) pada Game Kamen Rider Decade, yang merupakan permainan dengan strategi penyelesaiannya menggunakan metode pencarian buta (blind search). Pengumpulan data dilakukan dengan pendekatan kualitatif dengan metode deskriptif, dimana pengujian dilakukan dengan memainkan 3 kali masing-masing dengan metode selalu BFS dan selalu DFS. Hasil menunjukan peluang lebih besar memenangkan permainan ini adalah dengan strategi selalu BFS. Dimana kemampuan BFS pada permainan ini dapat berguna untuk pertahanan terhadap musuh.Â

Kombinasi Steganografi Berbasis Bit Matching dan Kriptografi DES untuk Pengamanan Data Prasetiyo, Budi; Gernowo, Rahmat; Noranita, Beta
Scientific Journal of Informatics Vol 1, No 1 (2014): May 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i1.3643

Pada penelitian ini dilakukan kombinasi steganografi dan kriptografi untuk pengamanan data dengan tidak mengubah kualitas media cover. Metode steganografi yang digunakan dengan melakukan pencocokan bit pesan pada bit MSB citra. Proses pencocokan dilakukan secara divide and conquer. Hasil indeks posisi bit kemudian dienkripsi menggunakan algoritma kriptografi Data Encryption Standard (DES). Masukkan data berupa pesan teks, citra, dan kunci. Output yang dihasilkan berupa chiperteks posisi bit yang dapat digunakan untuk merahasiakan data. Untuk mengetahui isi pesan semula diperlukan kunci dan citra yang sama. Kombinasi yang dihasilkan dapat digunakan untuk pengamanan data. Kelebihan metode tersebut citra tidak mengalami perubahan kualitas dan kapasitas pesan yang disimpan dapat lebih besar dari citra. Hasil pengujian menunjukkan citra hitam putih maupun color dapat digunakan sebagai cover, kecuali citra 100% hitam dan 100% putih. Proses pencocokan pada warna citra yang bervariasi lebih cepat. Kerusakan pesan dengan penambahan noise salt and peper mulai terjadi pada nilai MSE 0,0067 dan gaussian mulai terjadi pada nilai MSE 0,00234.Â

The Comparison between Bayes and Certainty Factor Method of Expert System in Early Diagnosis of Dengue Infection Rachmawati, Eka Yuni; Prasetiyo, Budi; Arifudin, Riza
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.15740

The development of existing artificial intelligence technology has been widely applied in detecting diseases using expert systems. Dengue Infection is one of the diseases that is commonly suffered by the community and may cause in death. In this study, an expert diagnosis system for dengue infection is made by comparing between both Bayes method and Certainty Factor. The aims are to build an expert system using Bayes and Certainty Factor for early diagnosis of dengue infection and also to determine their level of accuracy. There are 80 data used in this study which are obtained from the medical records of Sekaran Health Center in Semarang City. The test results show that the level of accuracy obtained from 80 medical record data for Bayes method is 90% and the Certainty Factor method is 93,75%.

PENGARUH BUDAYA ORGANISASI DAN GAYA KEPEMIMPINAN TERHADAP KEPUASAN KERJA DAN KINERJA KARYAWAN DI LINGKUNGAN KANTOR PUSAT UNIVERSITAS JEMBER Prasetiyo, Budi
BISMA: Jurnal Bisnis dan Manajemen Vol 11 No 1 (2017)
Publisher : Jurusan Manajemen Fakultas Ekonomi dan Bisnis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bisma.v11i1.6204

Abstract: Employee contribution becomes important when it is done with effective action and right behavior. Not only the amount of effort but also the direction of the business. The nature, effort or willingness to work as well as the various things that constitute organizational support is very important for the success of employee performance. In this study, the author tries to analyze the problems faced by the administrative staff of Jember University (UNEJ). Empirical tests were conducted on 115 administrative employees to obtain data on organizational culture and leadership style that has been enough to give hope to the administrative staff. Analyzer used in this research is Structural Equation Model (SEM). From the results of model testing, it can be concluded that organizational culture and leadership style have a positive effect on job satisfaction, leadership style positively affect the organizational culture. Organizational culture, leadership style, and job satisfaction have a positive effect on employee performance. To improve the performance of administrative employees, especially the dimensions of cost control and self-reliance initiatives, it requires a bureaucratic leadership style and autocratic leadership style in an open and process-oriented organizational culture system as an effort to improve employee job satisfaction.Keywords: Organizational Culture, Leadership Style, Job Satisfaction, and Employee Performance

Optimization Neuro Fuzzy Using Genetic Algorithm For Diagnose Typhoid Fever Fata, Muhamad Nasrul; Arifudin, Riza; Prasetiyo, Budi
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17097

Neuro Fuzzy is one method in the field of information technology used in diagnosing an disease. The application of Neuro Fuzzy is to identify disease. Genetic algorithms can be used to find solutions without paying attention to the subject matter specifically, one of which is an optimization problem. Typhoid or typhoid fever is a disease caused by Salmonella enterica bacteria, especially its derivatives. The diagnosis of typhoid fever is not an easy thing to do. This is because some of the indications experienced by patients also appear in other diseases. The number of patients with typhoid fever that requires accuracy in diagnosing typhoid fever based on indications caused. Based on this background this study aims to assist in the diagnosis of typhoid fever with 11 indication variables. This study uses medical record data for typhoid fever in 2017 Tidar Magelang Hospital. The method used is Neuro Fuzzy which optimizes the value of the degree of membership with genetic Algorithms. Then the value of the degree of neuro fuzzy membership is more optimal. The results of this optimization are the diagnosis of typhoid fever based on the variable of indications entered. From the research results obtained from the neuro fuzzy method get an 80% accuracy value and neuro fuzzy optimization results with genetic algorithms with a value of pc 0.5, pm 0.2 and max generation 25 the value of accuracy increases to 90%. Suggestions from this study, need to add more specific indication variables.

Kombinasi Steganografi Berbasis Bit Matching dan Kriptografi DES untuk Pengamanan Data Prasetiyo, Budi; Gernowo, Rahmat; Noranita, Beta
Scientific Journal of Informatics Vol 1, No 1 (2014): May 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i1.3643

Pada penelitian ini dilakukan kombinasi steganografi dan kriptografi untuk pengamanan data dengan tidak mengubah kualitas media cover. Metode steganografi yang digunakan dengan melakukan pencocokan bit pesan pada bit MSB citra. Proses pencocokan dilakukan secara divide and conquer. Hasil indeks posisi bit kemudian dienkripsi menggunakan algoritma kriptografi Data Encryption Standard (DES). Masukkan data berupa pesan teks, citra, dan kunci. Output yang dihasilkan berupa chiperteks posisi bit yang dapat digunakan untuk merahasiakan data. Untuk mengetahui isi pesan semula diperlukan kunci dan citra yang sama. Kombinasi yang dihasilkan dapat digunakan untuk pengamanan data. Kelebihan metode tersebut citra tidak mengalami perubahan kualitas dan kapasitas pesan yang disimpan dapat lebih besar dari citra. Hasil pengujian menunjukkan citra hitam putih maupun color dapat digunakan sebagai cover, kecuali citra 100% hitam dan 100% putih. Proses pencocokan pada warna citra yang bervariasi lebih cepat. Kerusakan pesan dengan penambahan noise salt and peper mulai terjadi pada nilai MSE 0,0067 dan gaussian mulai terjadi pada nilai MSE 0,00234.

Penggunaan Metode Depth First Search (DFS) dan Breadth First Search (BFS) pada Strategi Game Kamen Rider Decade Versi 0.3 Prasetiyo, Budi; Hidayah, Maulidia Rahmah
Scientific Journal of Informatics Vol 1, No 2 (2014): November 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i2.4022

Pada permainan Game Kamen Rider Decade ini sangat membutuhkan strategi yang tepat jika ingin memenangkan dengan mudah permainan ini. Penelitian ini bertujuan untuk mengimplementasikan metode Dept First Search (DFS) dan Breadth First Search (BFS) pada Game Kamen Rider Decade, yang merupakan permainan dengan strategi penyelesaiannya menggunakan metode pencarian buta (blind search). Pengumpulan data dilakukan dengan pendekatan kualitatif dengan metode deskriptif, dimana pengujian dilakukan dengan memainkan 3 kali masing-masing dengan metode selalu BFS dan selalu DFS. Hasil menunjukan peluang lebih besar memenangkan permainan ini adalah dengan strategi selalu BFS. Dimana kemampuan BFS pada permainan ini dapat berguna untuk pertahanan terhadap musuh.

Expert System Diagnosis of Urinary System Diseases using Forward Chaining and Dempster Shafer Fitriana, Jevita Dwi; Prasetiyo, Budi; Arifudin, Riza
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.22400

Expert system is a computer system that can adopt human knowledge into a computer. Expert system can be used to solve problems commonly performed by experts, one of them is the diagnosis of urinary system diseases. Expert system for the diagnosis of the urinary system disease especially for the inflammation of the bladder and these pyelonephritis using the forward chaining and the dempster shafer method. Forward chaining is used to diagnose disease based on the rules and the dempster shafer is used to determine the value of confidence. The goal is to build an expert system using forward chaining and dempster shafer methods to diagnose early urinary system diseases and to determine the level of accuracy. The data used is the secondary data obtained from the UCI Machine Learning Repository as much as 120 data and 6 attributes. The result of the implementation of the forward chaining and the dempster shafer methods on this expert system of diagnosis of urinary system diseases generates an accuracy value of 87.5%.

Prediction of COVID-19 Using Recurrent Neural Network Model Alamsyah, Alamsyah; Prasetiyo, Budi; Hakim, M. Faris Al; Pradana, Fadli Dony
Scientific Journal of Informatics Vol 8, No 1 (2021): May 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i1.30070

The COVID-19 case that infected humans was first discovered in China at the end of 2019. Since then, COVID-19 has spread to almost all countries in the world. To overcome this problem, it takes a quick effort to identify humans infected with COVID-19 more quickly. One of the alternative diagnoses for potential COVID-19 disease is Recurrent Neural Network (RNN). In this paper, RNN is implemented using the Elman network and applied to the COVID-19 dataset from Kaggle. The dataset consists of 70% training data and 30% test data. The learning parameters used were the maximum epoch, learning late, and hidden nodes. The research results show the percentage of accuracy is 88.

Expert System Diagnosis of Urinary System Diseases using Forward Chaining and Dempster Shafer Fitriana, Jevita Dwi; Prasetiyo, Budi; Arifudin, Riza
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.22400

Expert system is a computer system that can adopt human knowledge into a computer. Expert system can be used to solve problems commonly performed by experts, one of them is the diagnosis of urinary system diseases. Expert system for the diagnosis of the urinary system disease especially for the inflammation of the bladder and these pyelonephritis using the forward chaining and the dempster shafer method. Forward chaining is used to diagnose disease based on the rules and the dempster shafer is used to determine the value of confidence. The goal is to build an expert system using forward chaining and dempster shafer methods to diagnose early urinary system diseases and to determine the level of accuracy. The data used is the secondary data obtained from the UCI Machine Learning Repository as much as 120 data and 6 attributes. The result of the implementation of the forward chaining and the dempster shafer methods on this expert system of diagnosis of urinary system diseases generates an accuracy value of 87.5%.

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