J-SAKTI (Jurnal Sains Komputer dan Informatika)
JSAKTI adalah jurnal yang diterbitkan oleh LPPM STIKOM Tunas Bangsa Pematangsiantar yang bertujuan untuk mewadahi penelitian di bidang Manajemen Informatika. JSAKTI (Jurnal Sains Komputer dan Informatika) adalah wadah informasi berupa hasil penelitian, studi kepustakaan, gagasan, aplikasi teori dan kajian analisis kritis dibidang Ilmu Komputer terbit 2 kali setahun.
Articles
473 Documents
<![CDATA[Penerapan K-Nearest Neighbor Berbasis Genetic Algorithm Untuk Penentuan Pemberian Kredit ]]>
<![CDATA[Ester Arisawati]]>
<![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.v1i1.24
<![CDATA[Consumer financing is financing activities for the procurement of goods based on the needs of consumers with payment in installments. While the Financing Company is a business entity specifically set up to conduct leasing, factoring, consumer finance, or business credit card. The finance company will approve the proposed consumer credit after a credit analysis of the feasibility of providing consumer financing, if approved and not disetujui.Dalam analysis process for consumers, there are some that are not accurate, therefore consumers can not afford to pay in a timely manner resulting in bad debts , To solve the problem we need a model that is able to classify and predict consumer data is problematic and not problematic. In this research, testing ie k-Nearest Neighbor and k-Nearest Neighbor optimized genetic algorithm is applied to the data consumer that gets better the consumer credit financing is problematic or not. From the test results by measuring the performance of the three algorithms using Cross Validation testing methods, Confusion Matrix and ROC curves, it is known that the k-Nearest Neighbor algorithm optimized Genetic Algorithm has the AUC value and highest accuracy.]]>
<![CDATA[Perancangan Website Dinas Pendidikan Pemuda Dan Olah Raga (Studi Kasus Dinas Pendidikan Pemuda Dan Olah Raga Kabupaten Kebumen) ]]>
<![CDATA[Ari Waluyo]]>;
<![CDATA[El Vionna Laellyn Nurul Fatich]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 2 (2017): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v1i2.42
<![CDATA[The research have goal to design the Dinas Pendidikan, Pemuda dan Olah Raga website using PHP programming language and MySQL database at Dinas Pendidikan, Pemuda dan Olah Raga in Kebumen. Reseach method have used in this research is qualitative with descriptive method. Data collection technique is observation, interview, and literature review which have connection with main problem. The system development method which used is SDLC (System Development Life Circle). From the result of research have problems such as the menu provided too much and the information presented is not grouped properly. It made the user still feel difficulty in finding the needed information. There are recommendations which give to solving the problem are: 1) grouping the menus to easier finding informations, 2) re-design website that can show the information with categories, and 3) make the user-friendly website design.]]>
<![CDATA[Analisa Pembangunan Aplikasi Pengolahan Data Akademik Berbasis Web ]]>
<![CDATA[Anisya Anisya]]>;
<![CDATA[Bayu Febriadi]]>;
<![CDATA[Wahyu Hidayat]]>
<![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.v2i1.58
<![CDATA[Vocational High School (SMK) is one form of a formal education unit that provides vocational education as a continuation of (Junior High School) SMP / MTs and equal. One of them is SMK N 1 Koto Baru. In the processing of academic data using Microsoft Excel and Microsoft Word applications, the number of students approximately 550 students are divided into 9 departments so it takes a long time in the processing of academic data. This study aims to analyze the development of SMK N 1 Koto Baru to process academic data such as attendance, assessment of daily exams, duties, and final exams. The development of this system uses PHP programming language and MySQL database. The results obtained from this study in the form of student report cards per academic year.]]>
<![CDATA[Analisis Dan Pemodelan Posisi Access Point Pada Jaringan Wi-Fi Menggunakan Metode Simulate Annealing ]]>
<![CDATA[Anjar Wanto]]>;
<![CDATA[Jaya T Hardinata]]>;
<![CDATA[Herlan F Silaban]]>;
<![CDATA[Widodo Saputra]]>
<![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.v1i1.35
<![CDATA[Laying the position of the access point on the Wi-Fi network in a room is needed to optimize the signal strength received from the transmitter to the receiver. The parameters that determine the performance of the access point is the value of the signal strength. Strong or weak a signal access point will be affected by distance and barriers that exist between the access point and a client that accesses the access point. This study has been performed several simulations in multiple rooms are placed the access point to the receiver. The parameters used to measure the signal strength using inSSIDer applications that generate value RSSI (Received Signal Strength Indication) of a transmitter to the receiver and barriers (barriers) that may influence the strength of the signal. From this research strength of the signal received by the receiver not only in pengaruhui by the distance between accespoint to the recipient, but rather influenced by barriers (barriers) which is in a room. From the results of the research are expected to be able to obtain appropriate modeling to optimize access point placement position using the Simulate annealing method.]]>
<![CDATA[Penyandian File Word Berdasarkan Algoritma Rivest Code 5 (RC5) ]]>
<![CDATA[Widodo Arif Prabowo]]>;
<![CDATA[Annisa Fitri Harahap]]>;
<![CDATA[Ridha Ismadiah]]>
<![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.v2i1.55
<![CDATA[Nowadays, important data in the form of word files have been widely used. But there are still few who apply security techniques to the important files. Files that are confidential or important, if they fall into the hands of others may be misused or manipulated for certain purposes. The existence of document security applications built on cryptographic algorithms is one solution to solve the above problems. Cryptographic techniques secure a data or important files by encoding the data into a cipher that is difficult to understand again by others. The RC5 algorithm is one of the cryptographic technique algorithms that can be used to encode text from word files based on the RC5 algorithm so that it can improve the expression of important and confidential word files.]]>
<![CDATA[Analisis Sentimen Pada Media Sosial Twitter Menggunakan Naive Bayes Classifier Dengan Ekstrasi Fitur N-Gram ]]>
<![CDATA[Agung Nugroho]]>
<![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.v2i2.83
<![CDATA[Social media is currently an online media that is widely accessed in the world. Microblogging services such as Twitter allow users to write about various things they experience or write reviews of a product, service, public figures and so on. This can be used to take opinion or sentiment towards an entity that is being discussed on social media such as Twitter. This study utilizes these data to determine public opinion or sentiment regarding public perceptions of the issue of rising electricity tariffs. Opinion taking is based on three classes namely positive, negative and neutral. Users often use non-standard word abbreviations or spelling, this can complicate the process and accuracy of classification results. In this study the authors apply text-preprocessing in handling these problems. For feature extraction, n-gram and classification methods are used using the Naive Bayes classifier. From the results of the research that has been done, the most negative sentiments are formed in response to the issue of the increase in basic electricity tariffs. In addition, from the results of testing with the method of cross validation and confusion matrix it is known that the accuracy of the naïve Bayes method reaches 89.67% before applying n-gram, and the accuracy rate increases 2.33% after applying n-gram characters to 92.00%. It is proven that the application of the n-gram extraction feature can increase the accuracy of the naïve Bayes method.]]>
<![CDATA[Metode Hybrid Particle Swarm Optimization - Neural Network Backpropagation Untuk Prediksi Hasil Pertandingan Sepak Bola ]]>
<![CDATA[Muhammad Ridwan Lubis]]>
<![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[Rekomendasi Pemberian Beasiswa Bantuan Siswa Miskin Menggunakan Algoritma TOPSIS ]]>
<![CDATA[Muhammad Safii]]>;
<![CDATA[Surya Ningsih]]>
<![CDATA[ J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 2 (2017): EDISI SEPTEMBER ]]>
Publisher : <![CDATA[STIKOM Tunas Bangsa Pematangsiantar ]]>
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DOI: 10.30645/j-sakti.v1i2.39
<![CDATA[Poor Student Assistance is a National Program that aims to assist poor students to go to school and gain access to appropriate educational services, prevent dropping out of school, help students meet the needs of learning activities, support the Nine Years Education Program (even to upper secondary) school programs sourced from the State Budget. Several outcomes from the evaluation and study of BSM Program implementation show the weakness of this program, that is related to the accuracy of targeting of BSM where there are still many non-poor households that receive BSM and the number of inadequate. The target of BSM Program beneficiaries is still weak where many BSM recipients are not from poor households and many students from poor households / households do not receive BSM benefits and are still manuals of the methods used in establishing BSM recipients. In this research used decision support system with Technique for Order Performance by Similarity to Ideal Solution method. With this method can provide the right decision for the proper in scholarship grants for poor students.]]>
<![CDATA[Komparasi Algoritma Naive bayes dan SVM Untuk Memprediksi Keberhasilan Imunoterapi Pada Penyakit Kutil ]]>
<![CDATA[Adi Supriyatna]]>;
<![CDATA[Wida Prima Mustika]]>
<![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[Implementasi JST Dalam Menentukan Kelayakan Nasabah Pinjaman KUR Pada Bank Mandiri Mikro Serbelawan Dengan Metode Backpropogation ]]>
<![CDATA[Agus Perdana Windarto]]>
<![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.v1i1.25
<![CDATA[The purpose of this study was to develop a decision support system that can facilitate in determining the eligibility of borrowers KUR (Kredit Usaha Rakyat) through predictive use based on existing data and presents various alternative solutions in the selection of a feasibility customers in KUR loan. This study uses Artificial Neural Network applications using Backpropogation method. Criteria used as an assessment in this study is Collateral, Capacity, Loan Application Form, Income and Establishment Business License (Business License). The decision making process consists of two (2) phases where the first phase and pattern recognition, the second phase is forecast feasibility KUR customers. pattern recognition and predictive feasibility KUR customers using different data with the same process using training and testing. The conclusion by the two architectural models 5-2-1 and 5-3-1, obtained 93% accuracy with 0.0009995807 MSE is the 5-2-1 model architecture. This model is used to predict the feasibility of KUR customers with accuracy> 90% and MSE truth 0.0009566280.]]>
