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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 52 Documents
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Search results for , issue "Vol 6, No 1 (2022): EDISI MARET" : 52 Documents clear
Analisis Konsumsi Energi Listrik Pelanggan Dan Biaya Pokok Produksi Penyediaan Energi Listrik dengan Machine Learning Nugraha, Raditya Hari; Yuwono, Eko; Prasetyohadi, Latif; B, Yanuardhi Arief; Patria, Harry
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.v6i1.424

Abstract

PT PLN (Persero) during the Covid-19 pandemic was one of the companies whose sales growth was affected by the decline in electricity consumption in several sectors. Another condition is that several power plant and substation construction projects have fulfilled the realization commitment to the RUPTL from PT PLN (Persero). This has resulted in PT PLN (Persero) being faced with an over supply condition between power capacity and customer usage load. Realization of sales growth until July 2021 was 4.44% (144,788 TWh). Energy consumption in July 2021 was 20.55 TWh where the growth of kWh sales in July 2021 comparing with July 2020 began to show a recovery of +1.82%. The factor that most affected business and industrial growth was the manufacturing sector in Indonesia experiencing a slowdown/contraction as reflected in the PMI (Purchasing Managers Index) which decreased from 53.5 to 40.1. Growth is strongly influenced by consumer behavior in responding to government regulations, especially related to controlling the spread of Covid-19 in Indonesia in the form of restrictions on social activities (PSBB, PPKM, or Lockdown) which have been effectively implemented since April 2020 until now. Based on the analysis of the customer's electrical energy consumption data per industrial sector, as well as using technical data on the availability of power per electrical sub-system and the cost of producing electrical energy in an area, an evaluation model will be obtained that can be used in selecting the criteria for prospective customers who will be given program offers "SEMAKIN PRODUKTIF". By using "SEMAKIN PRODUKTIF" program data modeling, it is hoped that prospective customers will be given program offers so that they can be an opportunity to increase sales growth of electrical energy which is targeted to grow 6% in December 2021
Analisis Sentimen Objek Wisata Bali Di Google Maps Menggunakan Algoritma Naive Bayes Utami, Dian Siti; Erfina, Adhitia
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.v6i1.456

Abstract

Bali is one of the most popular tourist destinations in Indonesia because it has a variety of tourist attractions. So this study aims to analyze a tourist review on Google Maps of the most recommended tourist attractions in Bali. The author considers that the review can be used as a data by scrapping data from the Data Miner Website. Then the data that has been extracted is analyzed by predicting a rapid miner using the Naïve Bayes Algorithm, which is considered to have a high enough level of accuracy so that it can determine 5 recommended Bali tourist attractions based on tourist reviews on Google Maps. The results of this study conclude that Nusa Pedina with an accuracy value of 94.64% is the most visited Bali tourist attraction because the accuracy value is superior to Garuda Wisnu Kencana with an accuracy value of 82.86%, edge with an accuracy value of 80%, Pandawa with an accuracy value by 82.86%. The accuracy value is 90.71%, Uluwutu Temple with an accuracy value of 85.54%.
Analisis Sentimen Aplikasi Novel Online Di Google Play Store Menggunakan Algoritma Support Vector Machine (SVM) Nurhafida, Selva Indah; Sembiring, Falentino
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.v6i1.447

Abstract

Following the COVID-19 outbreak, many people were forced to leave their employment due to layoffs in various companies, forcing them to seek other ways to pass the time. To pass the time, one of them reads novels online. Online novels are currently available through the android market's online novel platform, mainly the Google Play store. The best app has so far been awarded to the app with the most downloads and a star rating on the Google Play store. The Wattpad and Dreame apps have benefits and drawbacks, and there are several comments on the Google Play store site. Application reviews on the Google Play store can be used to determine if an app is good or poor, as well as to look for issues that people have with the app. Descriptive analysis obtained by rating a total of 4137 Wattpad user reviews revealed that 33.12 percent of users strongly dislike, 17.04 percent dislike, 15.71 percent neutral, 11.31 percent like, and 22.82 percent like, while applications Dreame received 10.94 percent users strongly dislike, 13.24 percent dislike, 27.86 percent neutral, 21.85 percent like, and 26.12 percent users strongly like from 3090 reviews. As a result of the rating, Dreame outperforms Wattpad
Klasifikasi Citra Bunga Dahlia Berdasarkan Warna Menggunakan Metode Otsu Thresholding Dan Naïve Bayes Syaeful, Achmad; Fadillah, Muhammad Ilham; Muftadi, Imam; Iskandar, Dadang
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.v6i1.470

Abstract

Flowers are one of the organs of the plant body that function for generative propagation which has various forms and ways of working according to the type, but for plants that have seeds, these tools are usually important for plants that we know as flowers. Flowers are an important item in the object recognition process. The item recognition process in the computerized division is very important for determining the foundation and forefront of an image. It expects to get the spotlight it needs. The flower image in this study has a complicated picture which is very inconvenient because there are leaves and trees around the flower image. So, in this case concentrate on the proposed division involving Otsu Threshold as a strategy to isolate views and closer foundations. The division process is very firm to get shape highlights such as area, eccentricity, and perimeter. utilizing the computation of these elements will be sorted using the calculation of the Naïve Bayes algorithm by utilizing 120 flower images from 17 flower datasets. The dataset will be partitioned into test information and prepare information, and take advantage of cross-consensus (k=10). ensure that the settings using Naïve Bayes get a higher precision level of 99.168% with a relative absolute error of 9.0284%
Analisis Cyber Threat Injeksi Malware pada Suatu Dokumen Menggunakan Metode Mandiant’s Cyber Attack Lifecycle Model Mahmud, Rifqi; Prayudi, Yudi
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.v6i1.438

Abstract

The number of malware attacks that occur by embedding malicious code or exploits makes it important to know the flow of the malware attack that occurs so that we can understand where the attack started and what impacts can be caused by a malware attack that occurs, and how the flow of the attack using an analytical method Cyber Attack Lifecycle. This research was conducted to find out the flow of a malware attack, to find out where the attack started and to find out what impact the attack could have on the Mandiant's Cyber Attack Lifecycle Model. Mandiant's Cyber Attack Lifecycle Model was chosen as the analysis method because it has 8 stages that can cover the entire attack flow, namely initial recon, initial compromise, establish foothold, escalate privileges, internal recon, move laterally, maintain presence, and complete mission. Analysis of the attack was carried out from a document file which was indicated to contain malware in which the document file was sent by someone using Microsoft Excel document format and would be analyzed using Mandiant's Cyber Attack Lifecycle Model method to find out where the attack started and how the attack flow could occur. The results showed that the application of the Mandiant's Cyber Attack Lifecycle Model was successful in covering all the attack paths well, knowing the impact of the attack, and being able to find out where the attack started.
Rancang Bangun Sistem Penjualan Sate Taichan Berbasis Web Mulyadien, Muhamad Khandava; Kurniawan, Adi; Utami, Dwiarti Rahma; Enri, Ultach
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.v6i1.429

Abstract

An e-commerce Website is a Website to aims to sell one or more goods or services by using electronic media as a media for the transaction of goods/services. Taichandel is a food outlet that sells a variety of foods,  Aim of this research to solve the problem that occurs at the Taichandel because  the transaction of  this outlet still manual.  The metodh of this research using waterfall metodh, this metodh is used to  develop the software start with analytic, design, code until testing. The results of this research is  design system and system implementation with programming languages as html, php and database MySQL.  Benefit of this research is this information system can help the process of managing data related to the Taichandel Store and speed up the process of buying, selling and selling transactions  and also the owners  can check  the transaction reports because all store data is stored in the database so as to maximize sales evaluation and minimize loss of sales data.
Sistem Penunjang Keputusan Penerapan Metode Topsis Pada Peningkatan Kinerja Karyawan Alfaudzan, Adriansyah Muhamad; Gustian, Dudih
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.v6i1.461

Abstract

In determining the success of the company's work is influenced by human resource management (HR), one of the strategies in improving the quality of human resources work is to appreciate employee performance. The method used in determining this promotion is the topsis method, it is hoped that the assessment will be more precise because it is based on predetermined criteria and weights so that it will get more accurate results. For this reason, researchers try to help the problems mentioned above by developing a decision support system using the application of the TOPSIS method for this system. In this study we will know which employee performance is more accurate according to the company's determination, the results are in accordance with this study there are 5 candidates, 3 candidates who have high scores were selected, namely the first rank in the highest employee performance, the 1st is p1 with a preference value of 0.568796348, the second p2 with a preference value of 0.568579031, and the third rank p3 with the same preference value as p2.
Sistem Informasi Persediaan Barang Operasional Hotel Berbasis Web Aldo, Dasril; Nengsih, Yeyi Gusla; Wijaya, Trisno
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.v6i1.452

Abstract

Lovina Inn Hotel is a hotel that provides services to tourism guests in Batam City. At this time, in storing inventory data, it still uses a record book, so that when searching for inventory information, incoming and outgoing goods are still carried out in a recording form. The purpose of this study is to design an information system for operational goods inventory at the Lovina Inn hotel so that it makes it easier to manage data by not doing manual recording. With the application of a structured analysis model method for the creation of an Operational Inventory Information System, it can make it easier to build a system using the PHP language (Hypertext Preprocessor) and a database using MySQL. This application is designed to make it easier for the hotel to manage the incoming and outgoing stock of goods to the hotel operational inventory report
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%.

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