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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 564 Documents
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Performance Test of Openflow Agent on Openflow Software-Based Mikrotik RB750 Switch Kartadie, Rikie
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7987

Abstract

A network is usually developed by several devices such as router, switch etc. Every device forwards data package manipulation with complicated protocol planted in its hardware. An operator is responsible for running configuration either to manage rules or application applied in the network. Human error may occur when device configuration run manually by operator. Some famous vendors, one of them is MikroTik, has also been implementing this OpenFlow on its operation. It provides the implementation of SDN/OpenFlow architecture with affordable cost. The second phase research result showed that switch OF software-based MikroTik resulted higher latency value than both mininet and switch OF software-based OpenWRT. The average gap value of switch OF software-based MikroTik is 2012 kbps lower than the value of switch OF software-based OpenWRT. The average gap value of throughput bandwidth protocol UDP switch OF software-based MikroTik is 3.6176 kBps lower than switch OF software-based OpenWRT and it is 8.68 kBps lower than mininet. The average gap throughput jitter protokol UDP of switch OF software-based MiktoTik is 0.0103ms lower than switch OF software-based OpenWRT and 0.0093ms lower than mininet. 
The Effect of Best First and Spreadsubsample on Selection of a Feature Wrapper With Naïve Bayes Classifier for The Classification of the Ratio of Inpatients Wijaya, M Rizky; Saptono, Ristu; Doewes, Afrizal
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7910

Abstract

Diabetes can lead to mortality and disability, so patients should be inpatient again to undergo treatment again to be saved. On previous research about feature selection with greedy stepwise forward fail to predict classification ratio inpatient of patient with the result of recall and precision 0 on data training 60%, 75%, 80%, and 90% and there is suggestion to handle unbalanced class data problem by comparison of data readmitted 6293 and the otherwise 64141. The research purposed to know the effect of choosing the best model using best first instead of greedy stepwise forward and data sampling with spreadsubsample to resolve unbalanced class data problem. The data used was patient data from 130 American Hospital in 1999 until 2008 with 70434 data. The method that used was best first search and spreadsubsample. The result of this research are precision found 0.4 and 0.333 on training dataset 75% and 90% with best first method, while spreadsubsample method found that value of precision and recall is more significantly increased. Spreadsubsample has more effect with the result of precision and recall rather than using best first method.
Comparative Analysis of Simple Additive Weighting Method and Weighted Product Method to New Employee Recruitment Decision Support System (DSS) at PT. Warta Media Nusantara Setyawan, Agus; Arini, Florentina Yuni; Akhlis, Isa
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.8458

Abstract

Issue handling of inadvertence situations in the decision-making process of recruiting new employees at PT. Warta Media Nusantara that use criteria value of interviews, field test, a psychological test and medical check-up requires Multi Attribute Decision Making (MADM) as an auxiliary method of decision-making on the prospective eligible employee to be accepted in the company. There are various MADM methods, such as Simple Additive Weighting (SAW) method and Weighted Product (WP) method. Both of these methods are known as the most common method used in handling MADM issues, so in this study both methods are applied to the DSS and analyzed the differences in terms of obtained results and the execution time required for each method. The results of the study of the application of SAW and WP methods in the recruitment of new employees DSS there are some differences in the results of the candidates rank order and the differences in execution time of each method. The differences in rank order of these methods are due to the effects of alternative values, weighting criteria, and the calculation method. WP method is able to provide more rigorous result than SAW method, while the difference in execution time of SAW and WP methods explains that the execution time of SAW method relatively quick because SAW calculation method has a simpler process than the process of WP calculation methods 
Implementation of Decision Tree and Dempster Shafer on Expert System for Lung Disease Diagnosis Alfatah, Abdul Muis; Arifudin, Riza; Muslim, Much Aziz
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.13440

Abstract

The expert system is a computer system that contains set of rules to solve problems like an expert. The lungs are one of the vulnerable respiratory organs. The purpose of this research is to implement decision tree and dempster shafer method on lung disease diagnosis and measure the accuracy of the system. The symptom was searched using forward chaining decision tree and the diagnosis was calculated using dempster shafer method. Dempster Shafer method calculates the possibility of a lung disease based on the density of probability value that possessed by each symptom. This research used 65 data obtained from medical record of Puskesmas Tegowanu Grobogan Regency. General symptoms and types of disease are used as a variable. Based on the results of the study, it can be concluded that the results of the diagnosis using dempster shafer method has an 83.08% accuracy.
Abstract Keyword Searching with Knuth Morris Pratt Algorithm Ependi, Usman; Oktaviani, Nia
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.9797

Abstract

This research was conducted to answer the problems of researchers for finding publication or papers that suitable with their topics. In this research was developed software for searching abstract keyword using Knuth Morris Pratt algorithm to answer the problems of researchers. Waterfall model used to develop abstract keywords searching software as tools development that has five phases, namely communication, planning, modeling, construction and deployment. The software was developed can display search results effectively and efficiently according to the enter search keywords, it can see while search results are shown is in case sensitive. The software is also tested; the testing process is conducted by functional observation with black box testing approach, Observation results while testing is conducted show the software running suitable with expected or 100% same with entered keyword, so worthy to be used as one of the tools of researchers searching articles.
Implementasi Adaptive Neuro-Fuzzy Inference System (Anfis) untuk Peramalan Pemakaian Air di Perusahaan Daerah Air Minum Tirta Moedal Semarang Arifudin, Riza; Sugiharti, Endang
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.6516

Abstract

Peramalan pemakaian air pada bulan januari 2015 sampai April 2015 dapat dilakukan menggunakan perhitungan matematika dengan bantuan ilmu komputer. Metode yang digunakan adalah Adaptive Neuro Fuzzy Inference System (ANFIS) dengan bantuan software MATLAB. Untuk pengujian program, dilakukan percobaan dengan memasukkan variabel klas = 2, maksimum epoh = 100, error = 10-6, rentang nilai learning rate = 0.6 sampai 0.9, dan rentang nilai momentum = 0.6 sampai 0.9. Simpulan yang diperoleh adalah bahwa implementasi metode Adaptive Neuro-Fuzzy Inference System dalam peramalan pemakaian air yang pertama adalah membuat rancangan flowchart, melakukan clustering data menggunakan fuzzy C-Mean, menentukan neuron tiap-tiap lapisan, mencari nilai parameter dengan menggunakan LSE rekursif, lalu penentuan perhitungan error menggunakan sum square error (SSE) dan membuat sistem peramalan pemakaian air dengan software MATLAB. Setelah dilakukan percobaan hasil yang menunjukkan SSE paling kecil adalah nilai learning rate 0.9 dan momentum 0.6 dengan SSE 0.0080107. Hasil peramalan pemakaian air pada bulan Januari adalah 3.836.138m3, bulan Februari adalah 3.595.188m3, bulan Maret adalah 3.596.416 m3, dan bulan April adalah 3.776.833 m3.
Comparison Between SAW and TOPSIS Methods in Selection of Broiler Chicken Meat Quality Adi, Pungky Tri Kisworo; Sugiharti, Endang; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14416

Abstract

Decision support system is a system that can assist semi-structured and unstructured decision making, in which no one knows exactly how decisions should be made. Broiler Chicken farm production is growing very rapidly along with the increasing market demand for Broiler Chicken. Broiler Chickens have fast growth in a relatively short time. The purpose of this research is the selection of chicken meat quality by applying comparison of SAW and TOPSIS method. The variables used are age, ration conversion, weight of chicken weight, and water consumption. The system is created using PHP framework Code Ignitier and database MySQL using waterfall method. That is analyze the user needs on the system, do the database design, by doing a coding and testing the system whether it is what is expected. The result of this research is the application of comparison between SAW and TOPSIS method each consist of 5 criteria. Comparison of these algorithms can facilitate the breeders in choosing a good quality broiler chicken meat.The results of the best farmer recommendation according to comparative method of SAW and TOPSIS. In SAW method of breeder 1 The biggest value is at V2 = 0,341, so alternative A2 is alternatives chosen as good alternative. Breeder 2 The biggest value is at V3 = 0.033, so alternative A3 is the alternative chosen as a good enough alternative. Breeder 3 The biggest value is at V1 = 0.005, so alternative A1 is the alternative chosen as an excellent alternative. Topsis Method of Breeders 1 is the largest value  at V2 = 9.98, so alternative A2 is the alternative chosen as a good alternative. Breeder 2 is the biggest value at V3 = 0.372, so alternative A3 is the alternative chosen as a good enough alternative. Breeder 3 is the biggest value at V3 = 0.982, so alternative A3 is the alternative chosen as a good enough alternative. This system uses only 5 criteria, it would be nice if you add other criteria that support the selection of broiler chicken meat quality.
Implementation of Analytic Network Process Method on Decision Support System of Determination of Scholarship Recipient at House of Lazis Charity UNNES Rahmanda, Primana Oky; Arifudin, Riza; Muslim, Much Aziz
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.11852

Abstract

The scholarship is one of the forms of giving/ rewarding funds to individuals or students to use for sustainability during their education. Scholarships are awarded as government or institutional efforts to ease the burden of students in meeting the need for increasingly expensive education costs. The mechanism for selecting scholarship recipients, the selection team of UNNES Charity House of Lazis still use the scoring of the scholarship scores manually based on the total sum of criteria assessment without considering the priority weighted value of each criterion. So that cause the disbursement of scholarship funds that are not on target. To solve the problem, it is necessary to apply a decision support system to help provide consideration of the award of the scholarship recipient. Decision support system used requires data as a guidance assessment in the form of data criteria and alternative data by implementing Analytic Network Process method. The ANP method is used to determine the criteria and alternate priority weight values and the results are rankings. The purpose of this research is to build and implement ANP method in decision support system of awarding of scholarship recipients. The criteria used include the work of parents, parent income, the amount/ grade of Single Tuition, grade point average cumulative. The results of this study indicate that the use of ANP method implementation can determine the scholarship recipients who declared feasible or not to receive the scholarship based on the ranking results of the priority weight of the alternative.
Prediction The Number of Dengue Hemorrhagic Fever Patients Using Fuzzy Tsukamoto Method at Public Health Service of Purbalingga Hikmawati, Zahra Shofia; Arifudin, Riza; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.10342

Abstract

DHF (Dengue Hemorrhagic Fever) is still a major health problem in Indonesia. One of the factors that led to an increase in dengue cases is uncertain climate that causes dengue fever is difficult to be predicted. Prediction is an important thing that is used to determine future events by identifying patterns of events in the past. When knowing the events that happen, it will make everyone to make better preparation for everything. This research is aimed at determining the accuracy of Tsukamoto Fuzzy method in the number of dengue patients in Puskesmas Purbalingga. Tsukamoto Fuzzy method can be used for prediction because it has the ability to examine and identify the pattern of historical data. Tsukamoto fuzzy that used to predict the number of dengue fever patients at Puskesmas Purbalingga has several stages. The first stage is the collection of climate data includes precipitation, humidity, water temperature and the data of dengue fever patients in Puskesmas Purbalingga. The next stage is processing the data that has been obtained. The last stage is to make predictions. Based on the results of the implementation by Tsukamoto Fuzzy method in predicting the number of dengue fever patients in Purbalingga for twelve months in 2016, it was obtained a percentage error (MAPE) of 8.13% or had an accuracy rate of 91.87 %. With the small value of MAPE and high accuracy, it shows that the system can predict well.
Metode K-Means untuk Optimasi Klasifikasi Tema Tugas Akhir Mahasiswa Menggunakan Support Vector Machine (SVM) Somantri, Oman; Wiyono, Slamet; Dairoh, Dairoh
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.5845

Abstract

Masih sulitnya dalam menentukan klasifikasi tema tugas akhir mahasiswa sering dialami oleh setiap perguruan tinggi. Algoritma SVM digunakan untuk mengklasifikasi jenis tema tugas akhir mahasiswa. SVM merupakan metode yang banyak digunakan untuk klasifikasi. K-Means Clustering merupakan metode pengelompokan paling sederhana yang mengelompokkan data kedalam k kelompok berdasar pada centroid masing-masing kelompok. Optimasi klasifikasi tema tugas akhir mahasiswa menggunakan SVM dan K-Means untuk meningkatkan tingkat akurasi. Hasil yang diperoleh memiliki tingkat akurasi yang lebih baik yaitu 86,21%.

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