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Jurnal Teknologi Terpadu
Published by STT Terpadu Nurul Fikri
ISSN : 24770043     EISSN : 24607908     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 266 Documents
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Strategi Implementasi SIEM untuk Mengurangi Risiko terhadap Kebocoran Informasi Anggara, Taufik Rendi
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.756

Abstract

More than 100 instances of information leakage brought on by unauthorized access occurred in 2022. This study used case studies in conjunction with system development. Early Warning Systems (EWS) are intended to give current information on event violations. When the worker goes to the console, EWS will warn and ask for verification. In Centralised Log Management (CLM), data logs were filtered with a policy-based Correlation setup approach. Network Security devices are configured for Rule-Based Correlations, and log data will be forwarded to CLM. In the case of an occurrence, logs are crucial to the inquiry. We used the CLM model to secure log data. EWS can filter harmful activity and malicious events from all current devices using this CLM. EWS will send any malicious activities or events it detects through telegram and email. Applying CLM and EWS with IT risk measurement can assist in reducing the risk of information leakage and offer quick information for breaches or incidents, according to this study. Evaluation, which lasted for two weeks, produced outcomes including less unauthorized activity, outstanding performance in the notification system that may assist in verifying access to the proper privileges for accessing the device, and simple detection of unauthorized access and file modifications, among other things.
Pengaruh Keseimbangan Data terhadap Akurasi Model Support Vector Machine pada Data Set Donor Darah Widyanto, Agung; Kusrini; Kusnawi
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.771

Abstract

In classification, unbalanced data is expected. Unbalanced data has an inequality ratio between the majority and minority classes. Models trained with unbalanced data tend to predict the minority class as the majority class. This study aims to determine the effect of data balance on the accuracy of the Support Vector Machine (SVM) classification model. The data set used is the blood donor data set downloaded from the repository belonging to the University of California, Irvine (UCI). The Waikato Environment for Knowledge Analysis (WEKA) tool was chosen to present the results of training development and model testing. The research framework scheme is used as a reference for knowledge flow. In scenario 1, data pre-processing includes handling missing values using mean-impulse and normalizing MinMax scaling. With a data set that has an inequality ratio of 1:3, the SVM classifier gets an accuracy performance of 76.7%. In scenario 2, post-pre-processing is done by balancing the data using the Synthetic Minority Oversampling Technique (SMOTE). SVM classifier gets 69.8% accuracy performance. Model performance is evaluated using confusion metrics. The gap in recall values for each class is very high in scenario 1 (2.8% and 99.8%). Things are different in scenario 2 (75.6% and 64%). The test results of 748 samples obtained an accuracy of 76.7% for the scenario-1 model and 93.2% for the scenario-2 model. This proves that the balance of data influences the accuracy of the SVM classification model.
Implementasi Metode Clarke and Wright Savings dalam Penyelesaian Vehicle Routing Problem di PT. Adiguna Gasindo Munir, Misbahul; Kurniawan, Muchamad; M, Moch. Kalam; Setyawati, Indah
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.876

Abstract

A vehicle routing problem (VRP) is a problem in finding the most optimal route with the addition of a constraint. PT. Adiguna Gasindo is one of the LPG gas agents who needs help in shipping to agents, the problem is that there is a limit to the amount of LPG cargo that can be transported. In this research, we will solve the LPG delivery problem by optimizing distance and cost. The Clarke and Wright Savings Method, commonly known as the Saving Matrix, will be implemented to complete VRP. In this study, the distance approaches are the nearest insert and nearest neighbor. The test scenarios were carried out using three types of vehicles with different capacities, namely small (225 kg), medium (275 kg), and large (480 kg). The results obtained will be compared with the actual results (routes done) due to validation. From the results of 90 different scenarios, the results obtained by vehicles with large loads are those of vehicles that get the most optimal route in terms of distance and cost. The saving matrix will be more optimal if it is done by adding the nearest insert or nearest neighbor technique.
Analisis dan Perancangan Antarmuka Aplikasi Wisata Menggunakan Metode User Centered Design (UCD) Purbo, Yevi Septiray; Utomo, Fandy Setyo; Purwati, Yuli
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.977

Abstract

Lampung has many tourist attractions and natural areas that attract the attention of tourists, both domestic and foreign. However, there are still challenges in optimizing Lampung's tourism potential. One of the challenges is limited access to information regarding tourist destinations, accommodation and available activities. Apart from that, coordination between tourists and related parties such as destination managers and tourism services also need to be improved. To overcome this problem, a prototype of the VACALAM (Vacation Lampung) application was designed using Figma with the User-Centered Design (UCD) method. This research aims to increase user comfort and satisfaction in using the Vacalam application and encourage tourists to visit Lampung. In this application there are several features including ticket booking features, tour lists, trending tours, and a list of events in Lampung. The results of this research are user interface designs that follow good design principles, including simplicity, consistency, and readability. The use of colors, typography, and icons are also considered to improve the clarity and visual appearance of the application. The good user interface design and user experience have been tested using the System Usability Scale (SUS), with a final score of 71.75. These results provide guidance for other application developers in designing engaging and responsive user interfaces and user experiences using Figma.
Rancang Bangun Website Lelang Mobil menggunakan Framework Codeigniter 3 pada PT.ABC Surya, Alfin Adi; Haromain, Imam
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.1031

Abstract

An auction is a public sale of goods by oral or written bidding to achieve the highest price. PT.ABC is an auction company engaged in car auctions. PT.ABC is still using conventional methods for auction activities. The conventional system has several disadvantages, including manual recording, vulnerability to loss, and bidders being required to come to the location to buy auction items. This research builds a car auction website to improve the efficiency of the auction business. The application was built using the CodeIgniter 3 Framework using the MySQL database and web socket technology, Socket.IO. The software development method uses the waterfall method. Data collection was carried out by interview and observation at PT.ABC obtained data on the needs of the online auction system, the flow of car auction activities, and the things participants need to take part in the auction. Application development used a modeling concept, namely UML. The application was tested using a user acceptance test with 5 respondents for the admin and 24 people for the front-end. Evaluation results show that the application is very feasible to use and helps the process of running a business, with results from the questionnaire for the admin website at 93% and the front-end website at 91.67%.
Klasifikasi Motif Songket Palembang menggunakan Support Vector Machine berdasarkan Histogram of Oriented Gradients Yohannes, Yohannes; Al Rivan, Muhammad Ezar; Devella, Siska; Meiriyama, Meiriyama
Jurnal Teknologi Terpadu Vol 9 No 2 (2023): Desember, 2023
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v9i2.1032

Abstract

Songket Palembang is one of the intangible cultural heritages with the domain of traditional craftsmanship and crafts. Songket Palembang has several motifs, including Chinese Flowers, Cantik Manis, and Pulir. Preservation efforts are carried out by providing an understanding of Palembang Songket patterns. This study classified Palembang Songket patterns based on shape features using the Histogram of Oriented Gradient (HOG) method. Based on the test results of 45 test data images, the HOG method can become a feature in the image classification of Palembang Songket patterns, namely Chinese Flowers, Cantik Manis, and Pulir. The Support Vector Machine (SVM) method is a classification method that can recognize Palembang Songket patterns with RBF, Linear, and Polynomial kernels. The results showed that the RBF kernel was the best kernel that produced an average accuracy value of 88.1%, a precision of 84.1%, a recall of 82.2%, and an f1-score of 82.6%, and the three Palembang Songket patterns tested, it was found that the Palembang Songket patterns that were easiest to classify well were the Cantik Manis patterns for all types of SVM kernels.
Klasifikasi Penyakit Daun Pisang menggunakan Convolutional Neural Network (CNN) Pratama, M Duta; Gustriansyah, Rendra; Purnamasari, Evi
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1167

Abstract

Bananas are a fruit with promising economic value in Indonesia. They are an essential commodity for farmers, but diseases affecting banana plants can harm their livelihoods. Banana diseases initially attack the leaves, and in the early stages, they are difficult to differentiate with the naked eye due to farmers’ limited knowledge of pathogens. This research utilized the Convolutional Neural Network (CNN) method with transfer learning assistance using Google Colab to facilitate the classification of banana leaf diseases. The trained model experienced overfitting, so regularization was applied using dropout. The best model achieved an accuracy of 92%, precision of 92%, sensitivity of 91%, and an F1-score of 91% at a 70:20:10 ratio on epoch 80, as evaluated and validated using a confusion matrix. This study produced a reliable model for classifying banana leaf disease.
Penerapan Metode Combined Compromise Solution (CoCoSo) dalam Pemilihan Franchise Minuman Marito, Julita; Nainggolan, Wahyuni Betris; Mahendra, Gede Surya
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1183

Abstract

The research in this journal is motivated by the beverage franchise industry, which has become one of the most dynamic global business sectors. This article examines applying the Combined Compromise Solution (CoCoSo) method to the decision-making system (SPK) in selecting beverage franchises. The beverage franchise data that we use consists of 9 brands that are pretty famous among the public, such as Kopi Kenangan, Es Teh Indonesia, Teh Poci, Calais Tea, Puyo Puyo, Gulu Gulu, Kopi Kulo, Xi boba, Kopi Yor. In the process of data collection, we use observation and research. The data analysis process is carried out using the combined compromise solution method, one of the multi-criteria decision-making (MCDM) methods that can be used to select alternatives based on the calculation of criteria weights. This method can facilitate the determination of beverage franchises because it is more effective and efficient in calculating and ranking. Through the decision-making system that has been developed, the value of the beverage franchise can be generated based on predetermined criteria. Calculation of beverage franchises using CoCoSo shows the results of the calculation of the highest preference value obtained by the Puyo Puyo beverage franchise with a final value of 2.3436 and the lowest preference value obtained by the Kopi Kenangan beverage franchise with a final value of 1.3385.
Implementasi Metode Hybrid Filtering Technique pada Penentuan Rating Pestisida Ardimansyah, Ardimansyah; Husain, Husain; Herlinda, Herlinda; Kasmawaru, Kasmawaru; Nurdiansah, Nurdiansah; Marsa, Marsa
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1184

Abstract

Pesticides result from mixing organic chemicals that farmers use to protect their rice plants from disease. Farmers find it difficult to determine pesticide selection due to insufficient information.  So many pesticide products are available on the market, and their various advantages make it increasingly difficult for farmers to choose pesticides suitable for certain rice diseases. This research aims to provide farmers with recommendations on determining the best pesticide to eradicate rice diseases. The wrong choice of pesticide used can harm or reduce farmers' crop yields. This research used the Hybrid Filtering Technique combined with Content Based Filtering and Collaborative Filtering methods to search for weight values ​​and rating prediction values ​​using price criteria, pesticide ingredients, and form (liquid, solid, powder). The results of the calculation analysis of implementing the hybrid filtering technique method for each alternative criterion can simulate a ranking to recommend the best pesticide to eradicate the causes of rice disease. This research has concluded that the rating carried out by farmers who have used pesticides influences the determination of the rating value for each pesticide product. The system test results showed that the type of pesticide with the highest rating value was the enquity pesticide, with a value of 2,256.
Analisis Prediksi Kata Kunci Situs Web MonsterMAC dengan Metode Long Short-Term Memory (LSTM) Hanif Assalmi, Fityan; Syaifullah Jauharis Saputra, Wahyu; Muhaimin, Amri
Jurnal Teknologi Terpadu Vol 10 No 1 (2024): Juli, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i1.1187

Abstract

Amid increasingly fierce competition in the digital realm, many companies are striving to increase the number of visitors to their websites. One such competing company is MonsterMAC, a startup. This research aims to provide early warnings and analyze relevant keywords on the MonsterMAC website using the Long Short-Term Memory (LSTM) method. Visitor data from Google Analytics and keyword data from Google Trends for the period July 22, 2022, to July 15, 2023, have been collected and processed through several stages, such as preprocessing, model design, LSTM training, and testing, as well as visualization and interpretation of results. The modeling results show satisfactory performance, with MAE Train Real User = 0.0615, Vending Machine = 0.0218, IoT = 0.0284, Machine Learning = 0.0365, Digital Business = 0.0186, Business Intelligence = 0.0296. Furthermore, this research indicates that the number of visitors is predicted to increase but will also experience a sharp decline in the coming days. The use of the keyword "IoT" shows a significant increasing trend. Implementing the keyword "IoT" in SEO strategies has increased the number of visitors over the next seven days from 250 to 350. This research guides website owners in optimizing their content and SEO strategies to increase their visibility and competitiveness in a highly competitive digital environment. This research also emphasizes the importance of the LSTM method in keyword analysis and prediction to create more targeted SEO strategies.

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