J-SAKTI (Jurnal Sains Komputer dan Informatika)
J-SAKTI adalah jurnal yang diterbitkan oleh LPPM STIKOM Tunas Bangsa yang berfokus di bidang Manajemen Informatika. Pengiriman artikel tidak dipungut biaya, kemudian artikel yang diterima akan diterbitkan secara online dan dapat diakses secara gratis. Topik dari J-SAKTI adalah sebagai berikut (namun tidak terbatas pada topik berikut) : Artificial Intelegence, Digital Signal Processing, Human Computer Interaction, IT Governance, Networking Technology, Optical Communication Technology, New Media Technology, Information Search Engine, Multimedia, Computer Vision, Information System, Business Intelligence, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems, Software Engineering, Programming Methodology and Paradigm, Data Engineering, Information Management, Knowledge Based Management System, Game Technology.
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499 Documents
<![CDATA[Pengembangan Model Sistem Pendukung Keputusan Dengan Kombinasi Metode Fuzzy Tahani Dan Topsis Dalam Penilaian Kinerja Instruktur ]]>
<![CDATA[Safrizal, Safrizal]]>;
<![CDATA[Susianto, Susianto]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v3i2.143
<![CDATA[The instructor is the main academic implementer in the Institute for Aviation Education and Training (LPP). One of the factors that influence the success of LPP Aviation in improving student quality is the commitment and performance of instructors. One method used is to conduct an instructor performance appraisal process. The large number of Instructors in LPP Aviation is a separate issue in the assessment process, considering the process is based on subjectivity and has a great chance of making mistakes in the decision making, namely the selection of instructors who do not meet the desired standards and are not in accordance with the determination of instructor performance evaluation priorities. For this reason, a decision support system is needed in conducting the instructor's performance appraisal process. The Multi Attribute Decision Making (MADM) model has been widely used by decision makers to solve decision making problems with a variety of methods that can be used to find the best solution, but from these methods can still be developed with the aim of providing maximum decision results. In this research a decision support system model will be built with a combination of two methods, namely the Fuzzy Resistant method and TOPSIS which aims to manipulate the success data of instructors who are ambiguous by conducting a search for appropriate and accurate data for the criteria used in the assessment process LPP Aviation instructor performance by using Fuzzy-Resistant to get priority criteria in the form of rules, then ranking will be done by using TOPSIS in getting the quality of teaching conducted by LPP Aviation Instructors as the best instructor selection. The results of the flight instructor's performance evaluation with a combination of the Fuzzy Resistant method and TOPSIS, are based on 250 data tested samples, therefore, the accuracy value is 93%.]]>
<![CDATA[Kombinasi Multi Factor Evalution Process (MFEP) Dan Equal Weight Dalam Penentuan Tingkat Kesejahteraan Masyarakat ]]>
<![CDATA[Sudipa, I Gede Iwan]]>;
<![CDATA[Aryati, Komang Sri]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v5i1.300
<![CDATA[Community welfare reflects the equal distribution of social life in society. Various government assistance is provided to support the process of equal distribution of welfare. By knowing each community's level of welfare, aid can be provided on the right target principle. There are 21 assessment indicators used in determining the level of community welfare. In determining the level of community welfare, it is necessary to apply multicriteria decision-making techniques to determine the grouping of each category of community level. This study used a combination of the Multi-Factor Evaluation Process (MFEP) method to calculate the final evaluation value of 21 assessment indicators and determine the level of community welfare categories. Equal Weight method for determining the weight according to the number of assessment criteria with the same criterium importance. Combining the two methods above is to produce an alternative evaluation value and a category of community welfare level based on the final value of each alternative to the assessment indicator.]]>
<![CDATA[Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil ]]>
<![CDATA[Supriyatna, Adi]]>;
<![CDATA[Mustika, Wida Prima]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 2, No 2 (2018): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v2i2.78
<![CDATA[Warts is a skin health problem that is generally characterized by the appearance of small, rough-textured lumps on the skin surface caused by a virus that is human papilloma virus (HPV). One technique of treatment of wart disease is immunotherapy, this method is a treatment by boosting the immune system to overcome the disease of warts. Naive bayes and Support Vector Machine (SVM) is a method of data mining algorithm used to classify. The aim of this study was to compare the Naive bayes algorithm with Support Vector Machine (SVM) in predicting the success of immunotherapy treatment method in the treatment of wart disease. Tests conducted using the method of Naive bayes and Support Vector Machine (SVM) using the R programming language, then the results are used to do the comparison. The results of this study revealed that the Naive bayes method has superior prediction capability compared to Support Vector Machine (SVM) because Naive bayes can predict all class instances correctly with the accuracy level of 1.]]>
<![CDATA[Metode Hybrid Particle Swarm Optimization - Neural Network Backpropagation Untuk Prediksi Hasil Pertandingan Sepak Bola ]]>
<![CDATA[Lubis, Muhammad Ridwan]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 1 (2017): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v1i1.30
<![CDATA[Hybrid is using two methods to a problem with the aim to improve their approach towards the specified target data. Hybrid PSO-ANN one optimal algorithm to solve such predictions in football matches. The process begins with determining the outcome of test dataset with the neural network architecture, specify the input parameters, the value of weight up to the value of hidden layer and output layer. Then the optimization of the results of the first test on a training dataset optimized by Particle Swarm Optimization. Testing will continue over using back propagation neural network until the maximum iteration and the results of the initial approach the target value. Furthermore, from the output obtained to search the value of the average error.]]>
<![CDATA[Penerapan Clustering Dengan Fuzzy C-Means Dalam Mendiagnosa Radang Asam Urat ]]>
<![CDATA[Syahrin, Elvin]]>;
<![CDATA[Juliawan, Dicky]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v4i2.255
<![CDATA[Inflammation of uric acid is a disease that occurs due to excess uric acid in the blood, which then accumulates and accumulates in the form of crystals in the joints. The high-accuracy uric acid inflammation test must be done several times to treat the inflammation of uric acid in the body. Several indicators in the body can be a starting point for treating gout inflammation. Also, errors, the limitations of medical staff in handling huge amounts of data manually are a problem. One solution for this is to use a computer as a mathematical calculation in the Fuzzy C-Means grouping method. The criteria specified are joint pain, swollen joints, stiff joints, sprained feet and lumps in the joints. The grouping consisted of groups with gout inflammation and non-gout inflammation. Testing was carried out on 14 data.]]>
<![CDATA[Software Development Sistem Informasi Kursus Mengemudi (Kasus: Kursus Mengemudi Widi Mandiri) ]]>
<![CDATA[Nugroho, Nurhasan]]>;
<![CDATA[Rahmanto, Yuri]]>;
<![CDATA[Rusliyawati, R]]>;
<![CDATA[Alita, Debby]]>;
<![CDATA[Handika, H]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v5i1.325
<![CDATA[Widi Mandiri is an institution that provides training courses for driving four-wheeled vehicles. In managing data, Widi Mandiri uses records in certain forms or books from participant registration, scheduling and all business processes. With the existing system, there are several obstacles that hinder the conduct of business at Widi Mandiri. For that we need a driving course information system that helps in the management of all business activities at Widi Mandiri. The system development is carried out by using the extreme programming (XP) system development approach. The research has produced a system that can manage driving course data from registration of course participants, booking courses and cars to scheduling according to the schedule of course participants and instructors. Based on usability testing, the average value was 85.8%, and was in the good category]]>
<![CDATA[Sistem Informasi Pengarsipan Instrumen Akreditasi Perguruan Tinggi ]]>
<![CDATA[Febriadi, Bayu]]>;
<![CDATA[Wiza, Fana]]>;
<![CDATA[Putra, Pandu Pratama]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v3i1.110
<![CDATA[At Lancang Kuning University, there were no facilities that could be used in the preparation of university accreditation instruments, while the need for accreditation data was greatly needed by the academics of the yellowish university in the preparation of accreditation instruments for universities and study programs so that they were still having difficulty filing and presenting form data information, plans strategic and operational and self-evaluation plan along with the documents needed during the visitation activity by the assessor of the National Accreditation Board of Higher Education (BAN-PT). With the use of information technology in the application of computerized based applications for filing and presenting accreditation data needs, it is expected to help the academic community more quickly and precisely in the data processing instrument for accreditation. It is expected that with the development of archiving applications and the presentation of accreditation instruments with the completion of the System Development Lyfe Cycle (SDLC) method in the problem analysis phase, the applications built can improve the quality of accreditation instruments in data processing that are well integrated and can be utilized at any time by the community the Lancang Kuning university.]]>
<![CDATA[Aplikasi Monitoring Proses Distribusi Makanan Beku Untuk Informasi Secara Realtime ]]>
<![CDATA[Susliansyah, Susliansyah]]>;
<![CDATA[Handayanna, Frisma]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 2, No 1 (2018): EDISI MARET ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v2i1.49
<![CDATA[The control of frozen food distribution process done by the logistic part in obtaining the data is still manual, using the form and excel, causing the admin difficulty in monitoring and controlling the distribution process or the delivery of frozen food to store or outlet. Problem solving is made an application using data collection method and RAD method, where the model of Rapid Application Development (RAD) has business modeling stage using kebutuah application admin and user, data modeling that explains the use of ERD and LRS from the database side, about usecase diagrams and activity diagrams from the application process side, application generation evolves about programming languages in application creation while testing and turnover describes the use of white box testing. The purpose of the application is made to facilitate the related division in processing the data distribution process, monitor and control the distribution process and obtain information distribution process in realtime.]]>
<![CDATA[Penerapan Teorema Bayes Dalam Mendiagnosa Gangguan Kepribadian Paranoid ]]>
<![CDATA[Dwiki Putri, Dini Ridha]]>;
<![CDATA[Fahlevi, Muhammad Reza]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v4i2.246
<![CDATA[Paranoid personality disorder is a condition of thought patterns and behavior that are unhealthy and different from normal people. Pervasive distrust or suspicion of other people and feel that other people are jealous of them, as a result people with this personality get limited association from their surroundings. The aim of this research is to diagnose patients with paranoid personality disorder more effectively and efficiently so that treatment can be done. The method used is Bayes' Theorem which can help analyze predetermined symptoms. The implementation of this research uses the PHP programming language and MySQL database. The level of accuracy in knowing the diagnosis on early symptoms is 84.11%, so it can be a recommendation to help psychologists diagnose paranoid personality disorders.]]>
<![CDATA[Sentimen Analisis Pengguna Twitter pada Event Flash Sale Menggunakan Algoritma K-NN, Random Forest, dan Naive Bayes ]]>
<![CDATA[Wandani, Aprilia]]>;
<![CDATA[Fauziah, F]]>;
<![CDATA[Andrianingsih, A]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v5i2.365
<![CDATA[There is a sales system called Flash Sale in e-commerce. Basically the concept of a Flash Sale is to offer a lower price and a predetermined time and number of products. The sales system is only held at certain moments, by making cheaper product sales but with a limited time and number of products it will make sales increase because buyer interest will be higher. But apart from all the advantages of course there will be pros and cons. Sentiment analysis on Twitter was chosen because Twitter itself is a social media that allows users to be free to comment or write opinions about anything, including opinions about flash sale events that exist in e-commerce today. Thus, this research exists to find out the opinions of existing Twitter users regarding the Flash Sale event held by e-commerce. By using the methodology of three classification algorithms, Naive Bayes, K-Nearest Neighbor and Random Forest in classifying the data to determine the accuracy of the sentiment value of Twitter users in the Flash Sale event. This research takes two data samples from the keywords "flash sale" and "flash sale shopee", the results accuracy of the implementation of the three classification algorithms are 83.53% Naive Bayes, 82.94% K-NN, 80.59% Random Forest for the keyword "flash sale” and 81.48% Naive Bayes, 77.78% K-NN, 74.07% Random Forest for the keyword “flash sale shopee”. With this, the Naive Bayes Algorithm becomes a recommendation for classifying Sentiment Analysis data with greater accuracy and more stability to be used for large and small data.]]>
