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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 39 Documents
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Search results for , issue "Vol 3, No 2 (2016): November 2016" : 39 Documents clear
Comparison Performance of Genetic Algorithm and Ant Colony Optimization in Course Scheduling Optimizing Ashari, Imam Ahmad; Muslim, Much Aziz; Alamsyah, Alamsyah
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.v3i2.7911

Abstract

Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization  algorithm in solving the case of course scheduling.
Decision Support Model for User Submission Approval Energy Partners Candidate Using Profile Matching Method and Analytical Hierarchy Process Moedjiono, Moedjiono; Kurnianda, Nia Rahma; Kusdaryono, Aries
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.v3i2.7916

Abstract

In the field of services, customer satisfaction is a very important factor and determine the success of an enterprise. In the field of outsourcing, customer satisfaction indicator is the labor required delivery in a timely manner and has a level of quality in accordance with the terms proposed by the customer. To provide the best talent to customers, team recruitment and selection must perform a series of tests with a variety of methods to match the criteria of office given by the user with the criteria owned candidates and in order to support growth in graduation rates force a partner at the stage of user approval. For this purpose, the authors conducted a study with the method of observation, interviews, document reviews the candidate recruitment process, so as to provide recommendations for candidates with the highest quality delivery to the user at the stage of approval. The author put forward a model of decision support that is supported by the method of profile matching and Analytical Hierarchy Process (AHP) in problem solving. The final results of this study can be used to support a decision in order to improve the effectiveness of the delivery of quality candidates, increase customer satisfaction, lower costs and improve gross operational margin of the company.
Assessment The Method of Fuzzy Logic to Determine The Quality of Service Expedition in Jabodetabek Area Pamuji, Agus
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.v3i2.7906

Abstract

Search application services that was designed, could be the based on the difficulty to find out, and to select expedition services which have provided.  In these case, when someone who wants to send the packages to a particular destination. Each shipper will see the name of courier services, the speed the god arrive at the destination, prices, and customer services. This application is designed with fuzzy logic method that can be based on the selection of criteria, and specific category. The using and fuzzy logic method implementation can to help and ensure the selection of expedition service that based in variable or criteria are price, speed, location, and services. The result of this research will to display of application that was supported with database systems such as expedition services information and location, and then table of price is available.
The Implementation of Grey Forecasting Model for Forecast Result’s Food Crop Agricultural Muqtadir, Asfan; Suryono, Suryono; Gunawan, Vincensius
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.v3i2.7912

Abstract

The increasing of the needs of  food crops raised several issues related to land use. The  problems of land used caused by the lack of information related to productivity and eligibility used of land. The goal of this research is to implementation a model of Grey forecasting GM(1,1) to forecast agricultural production, especially in food crops. GM(1,1) is used to built a model with limited data samples and generate good forecasts for short libertine forecasts. This research uses data from the production of food crops for the 2004-2013 it can be calculated by using the model of GM (1,1). The results showed the model GM (1,1) can produce highly accurate forecasts, from the experimental results for pattern trends generate value ARPE 5.74% or accuracy of forecasts reached 94.26% in crop production.
Comparison of Patterns Shapes and Patterns Texture for Identification of Malaria Parasites in Microscopic Image Kusanti, Jani; Santosa, Yusuf Zain
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.v3i2.7917

Abstract

Identification of malaria parasites in red blood cells has been done, with the aim of as tools to identify experts microscopic parasites more quickly. This study aimed to compare the level of accuracy in the results to identify and classify parasites based on the pattern shape and texture patterns. The comparison is based on the characteristics of the pattern used, the steps being taken in this study is the image quality improvement process, the process of segmentation with Otsu method, feature extraction process on the image data to be tested. The process of pattern recognition and pattern shapes texture. The last step is to test the identification and classification of plasmodium falciparum parasite into 12 classes using methods Learning Vector Quantization (LVQ). The results of this study indicate that the pattern forms can provide a higher level of accuracy compared to LVQ texture pattern. LVQ with input shape pattern successfully identified 91% of image data correctly and input texture successfully identified 48% of image data properly.
Decision Support Systems with AHP and SAW Method for Determination of Cattle with Superior Seeds Josaputri, Clarissa Amanda; Sugiharti, Endang; Arifudin, Riza
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.v3i2.7908

Abstract

Department of Animal Husbandry and Fisheries of Semarang District is an institution in charge of livestock and animal health. Basically the Animal Husbandry Department has provided standardization for quality livestock cattle with superior seeds that usually can be judged or measured by various criteria.They are weight, age and value of BCS (Body Condition Score).They needed a system that could help the Department of Livestock and Fisheries of Semarang District in determining the electoral process cattle with superior seeds.  In this research, the manufacture of Decision Support Systems in the determination cattle with superior seedsis using a combination of two methods is Analytical Hierarchy Process (AHP) and the Simple Addictive Weighting (SAW). In AHP will perform an importance value calculation criteria that will be paired up with an alternative to the SAW the next process is the sum of the weight from performance rating of all the attributes to each alternative, a ranking conducted to determine the result of cattle with superior seeds. Suggestions on this system, can be developed further by combining other methods to determine the recommendation that more effective.
Decision Support System to Choose Digital Single Lens Camera with Simple Additive Weighting Method Putri, Tri Pina; Rosa, Paulina H. Prima
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.v3i2.7913

Abstract

One of the technologies that evolve today is Digital Single Lens Reflex (DSLR) camera. The number of products makes users have difficulties to choose the appropriate camera based on their criteria. Users may utilize several ways to help them choosing the intended camera such as using magazine, internet, and other media. This paper discusses about a web based decision support system to choose cameras by using SAW (Simple Additive Weighting) method in order to make the decision process more effective and efficient. This system is expected to give recommendations about the camera which is appropriate with the user’s need and criteria based on the cost, the resolution, the feature, the ISO, and the censor. The system was implemented by using PHP and MySQL. Based on the result of questionnaire distributed to 20 respondents, 60% respondents agree that this decision support system can help users to choose the appropriate camera DSLR in accordance with the user’s need, 60% of respondents agree that this decision support system is more effective to choose DSLR camera and 75% of respondents agree that this system is more efficient. In addition, 60.55% of respondents agree that this system has met 5 Es Usability Framework.
An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method Trihartati S., Agustin; Adi, C. Kuntoro
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.v3i2.7918

Abstract

Tuberculosis (TB) is a disease that can cause a death if not recognized or not treated properly. To reduce the death rate of tuberculosis patients, the health experts need to diagnose that disease as early as possible. Based on the main indication data, laboratory test results and the  rontgen photo, Naïve Bayesian approach in data mining techniques could be optimized to diagnose tuberculosis. Naïve Bayes classifiers predict class membership probabilities with a class that has the highest probability value. The output of the system is an identification Tuberculosis type of the patients. Testing of the system using 237 data sample with variation of cross-validation in 3, 5, 7 and 9-fold cross validation gives an average accuracy 85,95%.
Identification of Tuberculosis Patient Characteristics Using K-Means Clustering Sari, Betha Nur
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.v3i2.7909

Abstract

In Indonesia, tuberculosis remains one of the major health problems unresolved. Indonesia is second ranked in the world as the country with the most tuberculosis cases. The purpose of this research is to study how K-means clustering applied to the treatment of tuberculosis patients data in order to identify the characteristics of tuberculosis patients. The results of K-means clustering validated by gene shaving and silhoutte coefficient. The experiment results indicate the optimum clusters value obtained from the K-mean clustering that has been validated by gene shaving and silhouette coefficient. K-means clustering divided four groups of tuberculosis patients based on their characteristics. There were divided at a category of disease (pulmonary TB, Extra Pulmonary TB and both), the age of the patient and the results of treatment of tuberculosis.

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