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J-SAKTI (Jurnal Sains Komputer dan Informatika)
Published by Sekolah Tinggi Ilmu Komputer Tunas Bangsa
ISSN : 25489771     EISSN : 25497200     DOI : http://dx.doi.org/10.30645/j-sakti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy
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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 499 Documents
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Analisis Sensitivitas Prioritas Kriteria Pada Metode Analytical Hierarchy Process (Kasus Penentuan Pemberian Kredit) Wiguna, I Komang Arya Ganda; Semadi, Ketut Ngurah; Sudipa, I Gede Iwan; Septiawan, I Kadek Jerry
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.420

Abstract

The criteria affect a priority decision to find out the most important criteria in the Analytical Hierarchy Process (AHP) seen from the priority weights generated by the calculation. However, the analysis of the importance of priorities is to find out how important changes in the weight of the criteria can change the order results of alternative rankings and how critical the alternative values on the criteria are in influencing the ranking results. This study uses an example of providing credit with six criteria, namely Collateral (C1), Business Status (C2), Total Dependents (C3), Loan Amount (C4), Ability to Pay (C5) and Loan Term (C6). The test results from the three processes of sensitivity analysis with changes in the weight of the criteria show criteria C2 with a sensitivity value of 1.13284, Criterion C1 with a sensitivity value of 0.34874 and Criterion C5 with a sensitivity value of 1.078735. The highest percentage of alternative changes shows criteria C2, C4 and C5 with a percentage of 16.67%
Analisis Sentimen Terhadap Cryptocurrency Berbasis Python TextBlob Menggunakan Algoritma Naïve Bayes Azhar, Rizaldi; Surahman, Adi; Juliane, Christina
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.443

Abstract

Cryptocurrency users are now increasing as the market becomes more and more attractive. In 2019 recorded around 139 million account users verified id cryptocurrency. Recently, it was enlivened by the emergence of #crypto on Twitter and had become a world trending topic. This gives rise to many opinions and opinions from twitter users. With so many twitter users' opinions on the hashtag, it is very difficult to know whether positive, negative or neutral sentiments are manual. This requires machine learning to be able to automate labeling, be it positive, neutral or negative sentiments. Machine learning used is by utilizing Python TextBlob. The results of automatic labeling using Python TextBlob from a total of 1032 tweets obtained 632 tweets or 61.24% containing positive sentiments, 296 neutral sentiments or 28.68% tweets and 104 negative sentiments or 10.07%. The test results using the Naïve Bayes algorithm with each testing data and training data are 0.2 and 0.8. From this test, the accuracy value is 71.98%, precision is 83.04%, recall is 60.88% and f1_score is 65.07%.
E-Recruitment Menggunakan Metode Simple Additive Weighting dan Algoritma K-Nearest Neighbor Janubiya, Tasya Khaerani; Andryana, Septi; Sholihati, Ira Diana
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.434

Abstract

Along with the increasing number of PT Midi Utama Indonesia Tbk outlets, the company's human resource needs are also increasing. Therefore, the recruitment of new employees is very important to support the company's operations. In order to select prospective new employees to fill various positions needed by the company. Recruitment of new employees has not been carried out professionally. This is because there is no systematic method to assess the suitability of new employees. The application of a decision support system uses a combination of the Simple Additive Weighting (SAW) method and the K-Nearest Neighbor (K-NN) algorithm. This method determines the weight value and ranking results of each candidate. Then, the company conducts the process of selecting candidate data based on the value closest to the old prospective employee to determine the final classification results. In this case, prospective new employees who qualify as employees are based on predetermined criteria. Then this decision support application is built using the PHP programming language and MySQL database. The conclusion in this study by combining the SAW and K-NN methods in the recruitment process is very helpful because the administrative and assessment processes are carried out online. So that decision makers can make choices quickly and accurately.
Implementasi Multilayer Perceptron Untuk Memprediksi Harapan Hidup Pada Pasien Penyakit Kardiovaskular Sabilla, Wilda Imama; Vista, Candra Bella; Hormansyah, Dhebys Suryani
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.425

Abstract

Cardiovascular disease is one of the leading causes of death in the world. The risk of death is important to predict to determine treatment or behavior and lifestyle changes in cardiovascular patients. Medical record data of cardiovascular patients can be used as input in predicting life expectancy. This study offers the construction of a life expectancy prediction system for cardiovascular patients. Prediction using multilayer perceptron method by testing various scenarios. In addition, feature selection methods, namely correlation based filter (CBF), linear discriminant analysis (LDA), and principal component analysis (PCA) are applied to obtain relevant features to improve classification performance. Based on the experiments conducted, the average accuracy using CBF and LDA feature selection is 84% and 84.7%, respectively. In the best trial, CBF is able to produce accuracy, precision, recall, and f-measure with value of 91.7% 85% 89.5% and 87.2%. Based on these results, it can be concluded that this prediction system is able to provide fairly accurate results
Sistem Pendukung Keputusan Pemberian Vaksin HPV Untuk Mencegah Kanker Serviks Pada Wanita Dengan Metode TOPSIS Sefrika, S
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.439

Abstract

One thing that can be done to prevent cervical cancer in women is to vaccinate against HPV. However, further research needs to be done on the priority scale of vaccine recipients so that the goal of service cancer prevention can be carried out. The aim of the study was to determine the administration of the HPV vaccine to women to prevent cervical cancer. The research method used is the TOPSIS method. TOPSIS uses alternative criteria so as to get ideal results from the various options offered. The results showed a value of 1.22 for criteria C4, a value of 0.83 for criteria C1, a value of 0.53 for criteria C2 and a value of 0.37 for criteria C3. Suggestions for giving vaccines should be carried out according to priorities, namely sexually active women (C4), married women (C1), adolescents (C2) and children (C3).
Analisis Sentimen Identifikasi Opini Terhadap Produk, Layanan dan Kebijakan Perusahaan Menggunakan Algoritma TF-IDF dan SentiStrength Aziz, Abdul; Fauziah, F
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.430

Abstract

The need to analyze a product or policy becomes an important thing to measure the level of success. Twitter is currently one of the popular applications used by the public to give their impressions and opinions, both positive, negative and neutral opinions. Diverse public opinion on Twitter can be used as a reference material to get the level of community satisfaction on a product, service or policy. In this study, a sentiment analysis system was created using the TF-IDF and SentiStrength Algorithm. The steps in the research are, firstly, crawling Twitter data using the Twitter API, second preprocessing, thirdly doing spell correction, fourth Word weighting (TF-IDF) and lastly SentiStrength classification, where the results of the classification of tweets have positive, negative or neutral sentiments. In the test data taken using the keyword "child vaccines" as many as 1000 tweets, the results obtained were 54% positive sentiment, 20% negative sentiment and 26% neutral sentiment. Comparison with the same negative data analysis using a different algorithm, namely Naïve Bayes, results in positive sentiment of 55%, 16% and neutral 29%. Decision Tree got 61% positive results, 14% negative and 25% neutral.
Klasifikasi Penyakit Kulit Menggunakan Algoritma Naïve Bayes Berdasarkan Tekstur Warna Berbasis Android Furqan, Mhd.; Nasution, Yusuf Ramadhan; Fadillah, Rini
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.421

Abstract

The Skin is an important part of the human body which is used to protect organs from external disturbances (radiation, heat, sharp objects, etc.). the surface of the skin is divided into several textures, namely soft, rough, and supple. The skin also stores fat and is supple. The skin also stores fat and nerves which help in the process of human senses, the skin can also experience bacterial interference that can cause disease, the easiest thing to identify affected skin is through visuals (images). This research is to implement the naive bayes algorithma to classify android based skin diseases in helping the identification process of skin diseases based on visual form (color). Based on the results of the study that the classification of skin diseases (eczema, acne, chicken pox, etc). can be indentified through the naive bayes method and can obtain an accuracy of 75%.
Penerapan Metode Waterfall dalam Sistem Informasi Cuti Kepegawaian Madrasah Istiqlal Badrul, Mohammad; Janah, Luthfiyah Nuur
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.444

Abstract

Human resources in a company organization are very important to support the progress and quality of the company in achieving its goals. One of the keys to the success of an organization is employees, who have an important role in an organization, therefore human resource management in an organization is carried out properly in order to be able to achieve the shared goals of the organization. The administrative process for employee data that is currently running at Madrasah Istiqlal Jakarta is still being done manually, one of which is applying for employee leave. This manual system has many shortcomings, namely the use of a long time, incomplete reports required, and more prone to errors. The process of collecting personnel data manually will cause the available data to be incomplete or missing and take a long time. Therefore, a personnel information system is needed to overcome these problems. A good Personnel System will produce precise and accurate data so that it greatly influences the course of decision making. The waterfall method has a high speed of adaptation, can be made quickly and also because the waterfall method is suitable for software products whose needs are clear at the beginning, so there are minimal errors. The result of this research is a personnel information system that can assist employees in receiving information with an integrated database
Perbandingan Performa Algoritma Md5 Dan Sha-256 Dalam Membangkitkan Identitas File Saputra, Imam; Nasution, Surya Darma
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.435

Abstract

The ease of accessing the internet makes it very easy for humans to share various kinds of files. These files are very easy to download, so it is not uncommon for these files to become duplicates or the same files are stored on personal storage media. This of course will take up personal storage space owned. To avoid this, the steps that can be taken are to provide the identity of each file that represents the contents of the file. So that it can be known whether the contents of the file are the same or not. To generate the identity of a file, a special algorithm is needed that can represent the contents of the file. Algorithms that can be used to generate file identities are algorithms that fall into the hash function category. But in its development there are many algorithms in hash functions that can be used to generate file identities. The algorithms that are often used are the MD5 algorithm and the SHA-256 algorithm. The MD5 and SHA-256 algorithms have different algorithm structures so they have different performance when generating the identity of a file. By comparing the performance between the MD5 and SHA-256 algorithms, we will get an algorithm that has better performance when used to generate file identities.
Metode Analytical Hierarchy Process Dalam Menentukan Supplier WE Bakery Agustina, Bella; Ramanda, Kresna; Rusman, Arief; Sikumbang, Erma Delima; Sukmana, Sulaeman Hadi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.426

Abstract

Determining suppliers is important to support company performance, because determining the wrong supplier can cause harm to the company. Then the Analytical Hierarchy Process method is considered appropriate and appropriate for research related to problems in determining or selecting suppliers. By determining the right and optimal supplier using this AHP method, the company can select and evaluate suppliers so that the company can determine the appropriate criteria and alternative suppliers. Then the results are obtained that Arasari is considered the most appropriate to be a supplier with the highest weight gain priority of 0.427 or 42.7%, the second Lavanda Brownies of 0.291 or 29.1% and the third is Durian Orchid of 0.282 or 28.2%. While the results obtained through calculations using expert choice, explained that Arasari remained in first place with a value of 45.9% then Lavanda Brownies with a value of 29.7% and there was only a slight difference with Durian Orchid who obtained a percentage value of 24 4%. So based on these results, it can be seen that there is no difference in the order of global priorities for the total ranking goals obtained between manual data processing with the help of expert choice

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