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J-SAKTI (Jurnal Sains Komputer dan Informatika)
Published by STIKOM Tunas Pematang Siantar
ISSN : 25489771     EISSN : 25497200     DOI : -
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : -
Articles 499 Documents
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Analisis Pola Transaksi Pelanggan Menggunakan Algoritme Apriori Styawati, S; Nurkholis, Andi; Anjumi, Krisma Nur
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.362

Abstract

Diengva is a shop that sells various kinds of goods such as household items, household appliances, accessories, flower buckets, clothes, bags, shoes, cosmetics, and others. The large number of purchase transaction data in diengva can be used to analyze customer behavior in purchasing goods. Apriori algorithm is one of the algorithms in the field of data mining for extracting association rules. This study applies the apriori algorithm to find customer buying patterns in diengva store sales transaction data using rapid miner. The rules resulting from the application of the apriori algorithm can be used as a basis for stocking items that meet the minimum support and minimum confidence values. Items that meet these rules are eyelashes, eyelash glue, soft lens, and soft lens water. The confidence value of the relationship between two items can be high so that the results of these rules can be used as the basis for stocking.
Prediksi Kepribadian Berdasarkan Media Sosial Twitter Menggunakan Metode Naïve Bayes Classifier A, Muhammad Ichsanudin; Irawan, Agung Susilo Yuda; solehudin, Arip
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.394

Abstract

Analysis of a person's personality is very helpful as an assessment in various matters such as recruitment, career, health. The methods commonly used in personality analysis are interviews, observations, and questionnaire surveys. This study tries to provide a solution by simply using social media, namely twitter, by analyzing twitter user information data called tweets, this is to add to the method of personality analysis. The method used in this personality prediction research is to classify a tweet into 5 personality forms. The personality method used by the researcher is the Big Five Personality which consists of openness, conscientiousness, extraversion, agreeableness, and neuroticism with classification calculations using Naive Bayes. The result of this research is an accuracy of 42% with the highest class, namely Agreeableness.
Penerapan Metode Waterfall Untuk Perancangan Sistem Informasi Pengolahan Nilai Pada SD Nature Islam Badrul, Mohammad; sari, Novita
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.385

Abstract

SD Nature Islam is one of the educational institutions located in the Tangerang Banten area. Its activities are certainly inseparable from the activities of the teaching and learning process. The results of these teaching and learning activities are in the form of grades that are reported in a student learning progress report book or report card every semester. Nature Islam Elementary School uses the 2013 curriculum which is of course based on the Basic Competencies formulated in the curriculum. Thus, it requires teachers and staff to develop perfect assessment techniques. The use of computers is very useful and helps work become better, faster, and more efficient. The use of computers in particular will be very beneficial. in processing report cards at SD Nature Islam. However, in terms of processing report cards, they still use pen counts and calculators. This will take time and teacher labor in the process. For that we need a system that can play an important role to help the field in question run well. Good value data processing will produce report cards as a good evaluation result. To get results from processing good grades data, one of them is by utilizing existing and currently developing technology or in other words making a computerized student value data processing system using one of the methods to develop information systems, namely the waterfall method, in the form of applications web based.
Sistem Pakar Diagnosa Penyakit dan Hama Tanaman Pepaya Menggunakan Metode Forward Chaining dan Naïve Bayes Prayoga, Aldo Rio; Wahyuddin, M. Iwan; Andrianingsih, A
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.376

Abstract

Papaya is an agricultural product that can be grown anywhere. This causes papayas to be susceptible to pests and diseases, which can cause delays in the harvest period. So we need an expert system application that can help diagnose pests and diseases in papaya so that it can make it easier for papaya plant cultivators. The research has a goal to create an expert system application that can provide information on papaya plant diseases and can make it easier to diagnose diseases that exist in papaya and can be accessed easily anywhere by the public. This system is designed using Forward Chaining and Naïvei Bayes Methods. This expert system application is expected to make it easier for users to diagnose diseases and pests on papaya plants without having to require experts directly, based on the discussion and results in this research, the accuracy value of this expert system application has an accuracy value of 95% in diagnosing diseases and pests on papaya plants.
Aplikasi Pengolahan Data Penjualan Pembangkit Listrik Tenaga Surya Menggunakan Model View Controler Berbasis Framework Codelgniter Dan White Box Testing Rafli, R; Fauziah, F; Aldisa, Rima Tamara
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.367

Abstract

Solar power plants are engaged in providing services and selling solar cells. The design of the sales data processing application uses a database and generates archiving data reports on the sales data report maker. To meet the needs of inputting sales data, there is a special section that handles the admin section, the cashier section, but this work system already uses a web-based data processing application. The method used in data processing applications is in the form of observation, interviews, and documentation. While the application design method uses document flow charts, data flow diagrams, and use cases. Supporting software in making data processing applications using the php database programming language used mysql. The design of the product sales data application produces a database design, namely the goods data and sales table. Black box test results show the features in the application run accordingly and the white box test results in the login menu generate the same region and path value of 7 for the value of Cyclomatic Complexity=7 , Region=7 and Independent Path=7, meaning that the logic used in the program code is appropriate and running and in accordance with the research objectives that the input process of stock goods and transactions can be done optimally.
Implementasi Link State Routing Dengan Algoritma Dijkstra Pada Jaringan GM Purinet Kosambi Menggunakan Metode NDLC Firdiansyah, Adri; Carudin, C; Purnamasari, Intan
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.399

Abstract

The growth of Startup companies is soaring in this era of digital economy, not a few also use LAN within the scope of their company to conduct data transactions between divisions in the company. This study aims to analyze the performance of the Link State routing protocol with Dijkstra's Algorithm using qualitative method and the Network Development Life Cycle (NDLC) methodology. Qualitative method aims to test the quality of a system to assess its performance. The research object that will be selected is GM Purinet Kosambi for the reason it has all the requirement needed for this research to continue. Because the performance of Link State Routing is not yet known by many people if it is implemented and used as a superior routing protocol in a Startup business that uses a Computer Network in it, the author is interested in researching it. The results of this study indicate that the performance of Link State Routing is very good according to the parameter of Quality of Service (QOS) and can prevent and solve existing problems as well as preventable problems such as network disconnections and detection of disturbances that commonly occur in computer networks.
Klasifikasi Alat Musik Tradisional dengan Metode Machine Learning dengan Librosa dan Tensorflow pada Python Anggeli, Puja; Suroso, S; Agung, M. Zakuan
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.390

Abstract

The development of artificial intelligence technology AI (Artificial Intelligence) has been widely applied in various fields of daily life. AI (Artificial Intelligence) is divided into several branches, one of which is Machine Learning. Machine Learning is developed based on statistics, mathematics and data mining so that machines can learn by analyzing data without needing to be reprogrammed. With the development of the music world, not many people and the current generation know about traditional music from their respective regions. Traditional musical instruments produce sound art that has its own characteristics and uniqueness which is passed down from generation to generation. Therefore, to simplify the process of recognizing each musical instrument, a system was created that can classify traditional musical instruments using machine learning. The methods used in this research are librosa and tensorflow, where tensorflow is used for numerical computing and large-scale machine learning projects that have the best performance in classifying. In this study using Python 3.6 as a programming language and using PyCharm as a Integrated Development Environment (IDE). From the results, the system accuracy as expected after being tested several times, namely 91%.
Aplikasi Mobile Augmented Reality Pada Proses Terjadinya Gerhana Matahari Ismail, Taufiq; Muda, Lalu Iskandar
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.358

Abstract

One of the interesting cosmic phenomena to study in astronomy is solar eclipses because they are so rare that observations are recommended. This study developed a mobile application as a medium to explain the process of a solar eclipse using Augmented Reality with equipment such as a telescope, sun glasses, and pinhole. The application was built in collaboration with the Andromeda Study Group and the Ahmad Dahlan University Center for Astronomy Studies. The method used in this research is the Multimedia Development Life Cycle (MDLC) which consists of six stages, namely concept, design, material collection, assembly, testing, and distribution. This study produces a mobile application for the introduction of a solar eclipse using Augmented Reality to help people understand the process of a solar eclipse digitally or in 3D. Applications that have been made in this study are then tested using the blackbox test and material feasibility test. The blackbox test produces a value of 100% so that the application built can function properly. The feasibility test produces a value of 100% so that it is declared that the application is suitable for use.
Analisis Sentimen Terhadap Kebijakan Pemerintah Tentang Larangan Mudik Hari Raya Idulfitri di Indonesia Tahun 2021 Menggunkan Metode Naïve Bayes Aziz, Abdul; Fauziah, F; Fitri, Iskandar
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.381

Abstract

Social media as a place to access and disseminate information has grown very rapidly, one of which is Twitter. Twitter, as a place for information flow, is a rich source for seeking public opinion and sentiment analysis. Twitter in this study was used as a source to obtain data about the 2021 homecoming in Indonesia. The purpose of this study is to determine public satisfaction with government policies regarding the ban on going home in Indonesia in 2021. The data to be processed is Indonesian-language tweets, the keywords are #mudik and #diarangmudik, the length of data collection is 1 week, with lots of data generated as many as 1000. Sentiment analysis in this study using the Naïve Bayes Classification method. The steps in this study are first crawling Twitter data which is then stored in csv format, second preprocessing which consists of tokenizer, case folding, cleansing and stop removal, third Naive Bayes classification which will be carried out after going through the Pre-processing stage, where the results of the classification tweets tend to be positive or negative or neutral. The results of this study obtained an accuracy of 56.52% with each positive sentiment value of 62.28%, negative sentiment as much as 46.72% and neutral sentiment as much as 66.50%.
Analisa Pemilihan Kursus Daring Pada Karyawan PT. Gramedia Asri Media dengan Metode Analytical Hierarchy Process Jaelani, Ahmad; Purnamasari, Indah
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.372

Abstract

PT. Gramedia Asri Media established the Gramedia Digital Technical Department which implements remote work so that it is possible for employees working in various places to stay connected and collaborate. However, with the limited space and time for employees and the difficulty of meeting at one time to get various trainings, then MOOC is expected to be the answer to the need for workers to get proper training and in accordance with the technical capabilities required by the company. MOOC (Massive Open Online Courses) is an example of technological development of the learning process that offers flexibility in time and place. Currently, there are many alternative MOOC providers with various criteria, so it is necessary to choose the one that is most suitable for its users. One method of making decisions based on many criteria is AHP (Analytical Hierarchy Process). This study uses 5 criteria, namely Teacher Credibility, Certificate, Price, Course Topics and Course Time and 4 alternatives, namely Coursera, EdX, Udemy and Codecademy, where the course topic is obtained as the priority with a priority weight of 0.2289 then followed by Course time with a priority weight of 0.2238 Price with priority weight 0.2133, Credibility of teachers with priority weight 0.1833, Certificate with priority weight 0.1508. While the alternative with the priority is Udemy with a priority weight of 0.4379 followed by Coursera with a priority weight of 0.2234, Codecademy with a priority weight of 0.1989 and lastly Edx with a priority weight of 0.1723.

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