Scientific Journal of Informatics
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.
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564 Documents
<![CDATA[Implementasi Logika Fuzzy Mamdani untuk Mendeteksi Kerentanan Daerah Banjir di Semarang Utara ]]>
<![CDATA[Arifin, Saiful]]>;
<![CDATA[Muslim, Much Aziz]]>;
<![CDATA[Sugiman, Sugiman]]>
<![CDATA[ Scientific Journal of Informatics Vol 2, No 2 (2015): November 2015 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v2i2.5086
<![CDATA[Kerentanan (Vuinerability) adalah keadaan atau kondisi yang dapat mengurangi kemampuan masyarakat untuk mempersiapkan diri menghadapi bahaya atau ancaman bencana. Logika Fuzzy adalah cara untuk memetakan suatu ke dalam suatu ruang output. Salah satu aplikasi logika Fuzzy adalah untuk menentukan kerentanan daerah banjir di Semarang Utara. Pengujian dilakukan dengan metode Mamdani Fuzzy Inference System. secara manual dan program menggunakan 5 defuzifikasi, yaitu Centroid, SOM (Smallest Of Maximum), LOM (Large Of Maximum), MOM (Mean Of Maximum), Bisector. Dari 2 contoh kasus diperoleh hasil pengujian dengan kesimpulan yang sama. ]]>
<![CDATA[Accuracy Measurements and Decision Making by Naïve Bayes and Forward Chaining Method to Identify the Malnutrition Causes and Symptoms ]]>
<![CDATA[Ibtasam, Muhammad]]>
<![CDATA[ Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v8i2.29317
<![CDATA[Malnutrition is characterized as muscle weakening and cognitive disparity caused by social, dietary, political, food security issues. It appears as many underlying symptoms like fatigue, weakness, micronutrient deficiencies, weight loss to apparent symptoms of muscle mass reduction. Every 1 in 5 children is malnourished in developing countries. Purpose: Policies and program formulation require prevalence facts to classify the most prevalent cause. Diagnostic tools and computer modeling have revolutionized the world of health sciences. Much algorithmic formulation can help to predict the prognosis of diseases based on the previous fact sheets. Methods/Study design/approach: Naïve Bayes provides the posterior probability value that gives an analysis of the member with the whole sample set. Forward chaining gives the logistic conclusion with IF and THEN approach. Result/Findings: Naïve Bayes provided high accuracy of 88% as compared to 85% forward chaining. Novelty/Originality/Value: In this study, the Naïve Bayes algorithm approach is coupled with the forward chaining system to provide a highly accurate measurement of the cause of malnutrition.]]>
<![CDATA[Comparison of PCA and 2DPCA Accuracy with K-Nearest Neighbor Classification in Face Image Recognition ]]>
<![CDATA[Sutarti, Sri]]>;
<![CDATA[Putra, Anggyi Trisnawan]]>;
<![CDATA[Sugiharti, Endang]]>
<![CDATA[ Scientific Journal of Informatics Vol 6, No 1 (2019): May 2019 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v6i1.18553
<![CDATA[Face recognition is a special pattern recognition for faces that compare input image with data in database. The image has a variety and has large dimensions, so that dimension reduction is needed, one of them is Principal Component Analysis (PCA) method. Dimensional transformation on image causes vector space dimension of image become large. At present, a feature extraction technique called Two-Dimensional Principal Component Analysis (2DPCA) is proposed to overcome weakness of PCA. Classification process in 2DPCA using K-Nearest Neighbor (KNN) method by counting euclidean distance. In PCA method, face matrix is changed into one-dimensional matrix to get covariance matrix. While in 2DPCA, covariance matrix is directly obtained from face image matrix. In this research, we conducted 4 trials with different amount of training data and testing data, where data is taken from ATT database. In 4 time testing, accuracy of 2DPCA+KNN method is higher than PCA+KNN method. Highest accuracy of 2DPCA+KNN method was obtained in 4th test with 96.88%. while the highest accuracy of PCA+KNN method was obtained in 4th test with 89.38%. More images used as training data compared to testing data, then the accuracy value tends to be greater.]]>
<![CDATA[An Identification of Tuberculosis (Tb) Disease in Humans using Naïve Bayesian Method ]]>
<![CDATA[Trihartati S., Agustin]]>;
<![CDATA[Adi, C. Kuntoro]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7918
<![CDATA[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%.]]>
<![CDATA[Application of Fuzzy Algorithms and Analytical Hierarchy Process Modification in Decision Support Systems for Lazis Scholarship UNNES ]]>
<![CDATA[Permadi, Dimas Bayu Satria]]>;
<![CDATA[Alamsyah, Alamsyah]]>
<![CDATA[ Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v7i1.21820
<![CDATA[Lazis scholarship is a scholarship given to underprivileged students and does not yet have a system that supports the decisions to be taken. AHP is one of the most popular decision making methods in solving problems. But, AHP has several weaknesses. So that it will be modified based on previous research and the addition of fuzzy algorithms to get a better decision support system method. The results of this research were A009 students with the final result priority index value of 0.004176516 getting the first position. And the addition and modification in in this research is better than the standard decision support system. Fuzzy c-means produce scores that are more variable than manual grouping. Using sorting and ranking will produce a pairwise comparison matrix that is definitely consistent and has an average faster processing time is 0.028396 seconds, whereas with the standard method is 0.284415 seconds. Modification of alternative priorities also have a relatively faster average implementation time of 0.3165 seconds than the standard calculation with 2.6003 seconds. And modifications to the FPIV, if  taking the top 25 ranking in the standard FPIV produces 3 the same value while in the modified FPIV there is 1 same value.]]>
<![CDATA[Internalisasi Karakter Konservasi Lingkungan melalui Media Game Deservasi (Kader Konservasi) ]]>
<![CDATA[Setyawan, Fajar Arif]]>;
<![CDATA[Laelasari, Asmida Ulfa]]>
<![CDATA[ Scientific Journal of Informatics Vol 2, No 1 (2015): May 2015 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v2i1.4533
<![CDATA[Kepedulian terhadap lingkungan harus dimiliki oleh setiap manusia. Sikap peduli terhadap lingkungan dapat diwujudkan di antaranya dengan kebiasaan membuang sampah pada tempatnya, melestarikan lingkungan alam yang asri dan pemanfaatan sumber daya alam secara bijaksana. Munculnya berbagai permasalahan lingkungan yang disebabkan oleh kelalaian manusia perlu diatasi dan diantisipasi dengan penanaman nilai-nilai kepedulian terhadap lingkungan, bahkan perlu ditanamkan kepada setiap manusia sejak masa anak-anak. Media penanaman nilai-nilai kepedulian terhadap lingkungan kepada anak-anak perlu disesuaikan dengan ketertarikan mereka. Media game Deservasi yang dikembangkan dengan menggunakan Unity 3D akan menjadi media penanaman nilai- nilai kepedulian lingkungan yang efektif dan menyenangkan bagi anak-anak. Jenis genre game Deservasi adalah jenis permainan arcade game.]]>
<![CDATA[Collaboration Blockchain Technology and Gamification in iLearning systems ]]>
<![CDATA[Nevizond, Reza Filander]]>;
<![CDATA[Rahardja, Untung]]>;
<![CDATA[Lestari Santoso, Nuke Puji]]>;
<![CDATA[Purnama, Suryari]]>;
<![CDATA[Prihastiwi, Wahyu Yustika]]>
<![CDATA[ Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v8i2.31889
<![CDATA[Purpose: Currently, many fake certificates or diplomas are used to apply for jobs to get a better paying job. With that said, currently certificates cannot prove a person's expertise or skills. However, some students have implemented a Blockchain system in securing their certificates so that data manipulation is minimized, but only partially. Therefore, this research aims to motivate anyone, especially students in this Blockchain system and students will get incentives from all activities that are followed by racing in Blockchain gamification concept 4.0. Study design: This study uses the Pieces method to classify a problem (problem), opportunities (opportunities), and existing directions. Data collection techniques used primary data obtained by distributing questionnaires in the form of google form to respondents by involving students (n = 1129). Conclusions were analyzed with the SUS trial using a Likert scale with the cut and SUS method. Result: The results of this study are expected to Gamification in the system Blockchain can run optimally in implementation. The use of Gamification on the Alphabet Blockchain is included in the acceptable category. Value: The platform can check certificates that are not genuine.]]>
<![CDATA[Automatic License Plate Recognition: A Review with Indonesian Case Study ]]>
<![CDATA[Budianto, Aris]]>
<![CDATA[ Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v5i2.15804
<![CDATA[The Automatic License Plate Recognition (ALPR) has been becoming a new trend in transportation systems automation. The extraction of vehicle’s license plate can be done without human intervention. Despite such technology has been widely adopted in developed countries, developing countries remain a far-cry from implementing the sophisticated image and video recognition for some reasons. This paper discusses the challenges and possibilities of implementing Automatic License Plate Recognition within Indonesia’s circumstances. Previous knowledge suggested in the literature, and state of the art of the automatic recognition technology is amassed for consideration in future research and practice.]]>
<![CDATA[Edge Computing Implementation for Action Recognition Systems ]]>
<![CDATA[Pratama, Afis Asryullah]]>
<![CDATA[ Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v7i2.26433
<![CDATA[Nowadays the deep learning has been improved to many different sectors, including human action recognition system. This system mostly needs a high computing resource to work on. In its implementation, it will be built under cloud computing architecture which requires sensors used to send whole raw data to the cloud which puts a load in the networks. Therefore, edge computing system exists to overcome that weakness. This paper presents a method to recognize human action using deep learning with edge computing architecture. With RGB image as the input, this system will detect all persons in the frame using SSD-Mobilenet V2 model with various threshold values, then recognize every person’s action using our trained model with DetectNet architecture in various threshold too. The output of the system is detected person’s RoI and its recognized action action, which a lot smaller than the whole frame. As a result, our proposed system yields the best accuracy of human detection at 64.06% with a threshold at 0.15 and the best accuracy of action recognition at 37.8% with a threshold at 0.4.]]>
<![CDATA[Identification of Tuberculosis Patient Characteristics Using K-Means Clustering ]]>
<![CDATA[Sari, Betha Nur]]>
<![CDATA[ Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016 ]]>
Publisher : <![CDATA[Universitas Negeri Semarang ]]>
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DOI: 10.15294/sji.v3i2.7909
<![CDATA[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.]]>
