cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muh Syaiful Romadhon
Contact Email
syaiful@nurulfikri.ac.id
Phone
+6221 - 786 3191
Journal Mail Official
lppm@nurulfikri.ac.id
Editorial Address
Jl. Raya Lenteng Agung No.20, RT.4/RW.1, Srengseng Sawah, Kec. Jagakarsa, Kota Jakarta Selatan, DKI Jakarta 12640 Location: Kota Jakarta Selatan, DKI Jakarta, Indonesia.
Location
Kota depok,
Jawa barat
INDONESIA
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
 23   24   25   26   27 
Optimasi Parameter DBSCAN menggunakan Metode Differential Evolution untuk Deteksi Anomali pada Data Transaksi Bank Ibadirachman, Rifqi Karunia; Chrisnanto, Yulison Herry; Sabrina, Puspita Nurul
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.v10i1.1189

Abstract

Anomalies in bank transaction data often indicate fraudulent activity or errors. This research aims to detect anomalies in bank transaction data by optimizing DBSCAN parameters using the Differential Evolution (DE) method because there are shortcomings, namely the difficulty of determining the right parameters to create the right cluster in order to detect anomalies in bank transaction data properly. The data used is transaction data from Bank XYZ with more than 1011 data records. The research stages include data collection, data preprocessing (data cleaning, normalization, and transformation), system design, algorithm implementation, and analysis and testing using the Silhouette score and Z-score methods. The DE method is used to automatically determine the optimal parameters of MinPts and Epsilon. The results show that the use of DE can produce optimal parameters, with increased anomaly detection accuracy using DBSCAN. Evaluation with Silhouette score shows an average accuracy of 0.7916 and using DBI reaches 0.19791 at the lowest, while Z-score and MSE measurements show high cluster density with anomaly detection accuracy reaching 98.41% and 0.555537. The DE approach to parameter selection is effective in improving the performance of DBSCAN in detecting anomalies in bank transaction data. Suggestions for future research are to increase the number of data records and conduct experiments on a wider variety of data attributes.
Perbandingan Klasifikasi Label Tunggal untuk Soal Ujian Fisika menggunakan Naïve Bayes dan K-Fold Cross Validation Herijanto, Christopher Kevin; Wahyuningsih, Yulia
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.v10i1.1210

Abstract

This research evaluates the use of the Naïve Bayes algorithm in classifying Physics questions with single labels. The main objective is to identify the best algorithm for classifying Physics questions to assist high school students with difficulty understanding them. The research method involves using a dataset containing Physics questions that need to be classified to facilitate learning for high school students. The Naïve Bayes algorithm is implemented using Google Colab to train the classification model using features extracted from the text of the Physics questions. Additionally, several other classification algorithms, such as Support Vector Machine (SVM), Logistic Regression, Decision Tree, and Random Forest, are tested, and their performance is compared. Experimental results show that Naïve Bayes provides competitive results in classifying single-label Physics questions. However, there are significant performance differences between Naïve Bayes and other algorithms, depending on the type and complexity of the classified Physics problems. In this study, SVM achieved higher accuracy, but Naïve Bayes excelled in training time. This research provides a deeper understanding of the strengths and weaknesses of Naïve Bayes in solving the task of classifying single-label Physics problems. These findings guide the development of more accurate classification models for application in the context of Physics learning.
Deteksi Citra Daun untuk Klasifikasi Penyakit Padi menggunakan Pendekatan Deep Learning dengan Model CNN Rijal, Muhammad; Yani, Andi Muhammad; Rahman, Abdul
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.v10i1.1224

Abstract

Agriculture is a vital sector related to food security. Rice is one of the productions that currently ranks third behind wheat and corn. However, in 2023, rice production in Indonesia will decrease 2022 by 1.12 million tons of GKG, and Diseases in plants are one of the causes of the reduced quantity of agricultural products. This research aims to detect disease in rice plants using leaf images with three classification classes and a test matrix to measure the model built. This research uses the Convolutional Neural Network (CNN) method to classify rice plants based on leaf images with 3 test scenarios using the Jupyter Notebook text editor tool for system coding. Research results with training show that the CNN model can classify diseases in rice based on leaf images. Of the 3 test scenarios carried out, scenario 2 shows the best results with Epoch 50 with training values ​​from the last Epoch, namely training accuracy 0.9905 and training loss 0.0280 while validation accuracy 0.8000 and The validation loss is 0.9222 with the confusion matrix showing the suitability of predictions based on class with the classification report good recall, precision and f1-score values, namely 1.00.
Implementasi Bi-LSTM dengan Ekstraksi Fitur Word2Vec untuk Pengembangan Analisis Sentimen Aplikasi Identitas Kependudukan Digital Onsu, Romario; Sengkey, Daniel Febrian; Kambey, Feisy Diane
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.v10i1.1225

Abstract

The Indonesian government is striving to enhance digital public services, including the Digital Identity Application (IKD) launched in 2022 by the Directorate General of Population and Civil Registration. Since its launch, IKD has received various responses from the public. User reviews on Google Play Store indicate a decline in ratings from June to December 2023. Review analysis is essential to understand user satisfaction, identify issues, and guide application improvements. This study aims to perform sentiment analysis on IKD user reviews using Bidirectional Long Short-Term Memory (Bi-LSTM) and Word2Vec methods. Bi-LSTM and Word2Vec are used to develop sentiment analysis from previous research that still used Machine Learning methods. This research is expected to contribute to the development of sentiment analysis models using Deep Learning for the IKD application. Review data was collected from the Google Play Store using scraping techniques for the period January-December 2023 and categorized into positive and negative. The Bi-LSTM model was trained with Word2Vec CBOW and Skip-Gram variations with dimensions of 100, 200, and 300. The results show that the combination of Bi-LSTM and Word2Vec CBOW with a dimension of 200 and a data split ratio of 80/20 produced the highest accuracy of 96.06%, with a precision of 96.44%, recall of 95.64%, and an f1-score of 96.04%. All combinations of Bi-LSTM and Word2Vec outperformed other Machine Learning algorithms.
Pengaruh Jarak Objek Citra pada Model Deteksi dan Klasifikasi Botol Plastik menggunakan YOLO Rosanti, Nurvelly; Latifah, Retnani; Munir, Sirojul; Maududi, Izzuddin Al Qossam
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.v10i1.1247

Abstract

Plastic bottle waste must be separated based on shape and size to facilitate recycling. Sorting plastic bottles can use object detection technology to facilitate classification using images. Image distance capture affects the classification of bottle waste because large bottles will look small when seen from a distance and vice versa. This study aims to create a plastic bottle detection and classification model using the YOLOv8 algorithm with the same bottle shape but different sizes and measure the effect of image distance on the model. Bottles consist of three sizes: large bottles measuring 1500 ml, medium bottles measuring 600 ml, and small sizes 330 ml. Pictures for the bottle image dataset were shot between 80 and 100 centimeters away. Robotoflow was used to produce the dataset. Model performance evaluation used Mean Average Precision, and model testing used a confusion matrix. The test results for the same model with an image capture distance had an accuracy value of 100%. Testing of 80 cm distance images applied to the 100 cm model had an accuracy of 67%. Testing for 100 cm distance images applied to the 80 cm model was still quite good, with an accuracy of 91.6%. The results obtained show that the image distance affects the results of the model that has been built, so use an image that matches the distance applied to the model.
Pemanfaatan Data Ulasan Pengguna untuk Membangun Sistem Klasterisasi berdasarkan Pain Points menggunakan Algoritma K-Means Ulummuddin, Ikhya; Sari, Anggraini Puspita; Swari, Made Hanindia Prami
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.v10i1.1252

Abstract

In design thinking, empathizing and defining stages are part of UX research. The goal is to analyze pain points or complaints experienced by users using qualitative data. However, this process is always done manually, which can be time-consuming and resource-intensive. The objective of this research is to develop a system for clustering qualitative data based on problem topics using K-Means clustering and several evaluation methods, namely silhouette score, Davies-Bouldin Index, and Calinski-Harabasz Index, implemented in Python programming language and run on Google Colaboratory. User review data for the Gojek app version 4.9.3 from November 2021 to January 2024, obtained from Kaggle and preprocessed, will be used as the object for system development. Based on testing for each cluster number, the results obtained are 14 clusters or problem topics with a silhouette score of 0.65, Davies-Bouldin Index of 0.35, and Calinski-Harabasz Index of 40.7, where each evaluation method has good accuracy. The system requires a computation time of 127.4 seconds. The K-Means algorithm is effective when clustered user review data based on complaint topics. UX researchers can utilize the system from this research to assist them in analyzing pain points more quickly and efficiently.
Pengembangan Aplikasi Game Pengenalan Jenis-jenis Virus Berbasis RPG Pradana, Dwifa Yuda; Vitianingsih, Anik Vega; Cahyono, Dwi; Wikaningrum, Anggit; Wati, Seftin Fitri Ana
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1249

Abstract

The global community has been significantly affected by the COVID-19 pandemic in terms of health, education, the economy, social matters, and culture. Digital devices are increasingly being used for entertainment to combat boredom amidst restrictions on physical activity. However, this behaviour can also reduce adherence to health protocols, which can lead to high cases of COVID-19. Education about viruses is increasingly emphasized, especially for adolescents, who are a key group in preventing the spread of viral infections. Consequently, the media is required to introduce the different kinds of viruses and their survival strategies. This study aims to create an RPG-based "V-Fight" game application for virus types' exposure among teens. The research used a software development methodology that applied the Multimedia Development Life Cycle (MDLC), which consists of Concept, Design, Material Collecting, Assembly, Testing, and Distribution. The validation test conducted on 35 respondents obtained a validity level of 76.38%. This indicates that the tested game has sufficient criteria to be considered a practical learning tool.
Transformasi Pelayanan Masyarakat melalui Website Kampung Malasigit sebagai Inovasi Berbasis TI Rumetna, Matheus Supriyanto; Hetharia, Charliany
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1393

Abstract

Malasigit Village is improving in terms of development and community services. The dissemination of information is still a significant problem; the information provided sometimes needs to reach the community. For example, health services related to the village community still need to be more efficient because sometimes the information provided by the assistant health center regarding health checks does not reach the village community. Another problem is related to the community's agricultural products; the condition that occurs is that agricultural products must be taken to be sold to the city, which is ± 30 km away and the understanding of village officials in the IT field, namely the use of computer devices and their applications. For this reason, village development is needed through IT, in this case, a website-based village information system to help village officials deliver transparent and efficient village information, providing service facilities/containers for farmers to promote their agricultural products to improve community services. This study uses the Waterfall method, website modelling using case diagrams and activity diagrams, which produce a home menu, profile, structure, facilities, news, information, gallery and contact.
Rancang Bangun Website Kampung Batu Lubang Pantai sebagai Destinasi Wisata dan Sarana Promosi Pariwisata Lina, Tirsa Ninia; Pormes, Frenny Silvia
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1416

Abstract

Kampung Batu Lubang Pantai is located in Makbon District, Sorong Regency, and is part of the marine tourism area in Southwest Papua. So far, tourists/visitors are primarily familiar with Tanjung Batu Lubang tourism, even though there are many other tourism potentials, such as beach tourism (Bainggik Beach, Bainggik Tengah, Klaswonik, Pasir Pendek, Kladimala, Tanjung Batu Lubang, Pasir Timbul), cultural attractions (A’len dance, Srar dance, Suling Tambur, traditional Moi Tribe houses), religious sites (Gospel Monument, Hill of the Cross), and local wisdom products (noken Banto, kal’uk head covers, kal’dala, kal’lagi, noken kwok ou ukisik, mats). This lack of awareness is due to the insufficient and incomplete dissemination of information, as well as the community’s limited understanding of IT utilization. The purpose of this research is to design and build a website for Kampung Batu Lubang Pantai to assist in spreading information related to village activities and tourist destinations, serving as a tourism promotion tool that can ultimately improve the welfare and economy of the community. The system development method uses the Waterfall model, which includes requirements, design, implementation, verification, and maintenance stages. The applications used include Balsamiq Mockups, draw.io, and Bracket Editor. The result of the research is a village website consisting of menus such as Beranda, Profil, Pemerintahan, Informasi, Galeri, Potensi, and Kontak. System testing using Black Box Testing showed that the menu functions were working well so that it could be handed over to the village.
Rencana Strategis Transformasi Teknologi Informasi pada Industri Kelapa Sawit Menggunakan Framework Zachman Solihin, Indra Permana; Triwahyono, Bambang; Wibisono, Mohamad Bayu; Munir, Sirojul
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1417

Abstract

This research aims to design and implement an effective Information Technology (IT) Transformation Strategic Plan to increase national palm oil productivity in the palm oil industry. IT strategies will be developed using the Zachman Framework, considering architectural aspects and business perspectives. This research was carried out from February to October 2024 at UPNVJ’s Data Science laboratory and company facilities in Jakarta and Central Kalimantan. This research contributes to integrating the Zachman Framework with a specific information technology transformation approach for the palm oil industry, which has not been widely applied in the previous literature. The implementation step involves an in-depth analysis of business needs and processes and the development of appropriate IT solutions. The research results are expected to result in significant transformations in palm oil industry operations, such as increased productivity, efficiency, and adaptation to market changes. The study also considers architectural dimensions and business perspectives in implementing effective IT solutions. Cooperation with key stakeholders, including palm oil producers, suppliers, and consumers, is highly valued. This study’s results are expected to guide other industries and the government in formulating policies supporting IT transformation in the national palm oil industry sector.

Page 25 of 27 | Total Record : 266

 23   24   25   26   27 

Filter by Year

2015 2025


Reset
Filter By Issues
All Issue Vol 11 No 1 (2025): Juli, 2025 Vol 10 No 2 (2024): Desember, 2024 Vol 10 No 1 (2024): Juli, 2024 Vol 9 No 2 (2023): Desember, 2023 Vol. 9 No. 1 (2023): Juli, 2023 Vol 9 No 1 (2023): Juli, 2023 Vol. 8 No. 2 (2022): December, 2022 Vol 8 No 2 (2022): Desember, 2022 Vol. 8 No. 1: July, 2022 Vol 8 No 1: Juli, 2022 Vol. 7 No. 2: December, 2021 Vol 7 No 2: Desember, 2021 Vol. 7 No. 1: Juli, 2021 Vol 7 No 1: Juli, 2021 Vol 6 No 2: Desember, 2020 Vol. 6 No. 2: Desember, 2020 Vol 6 No 1: Juli, 2020 Vol. 6 No. 1: Juli, 2020 Vol 5 No 2: Desember, 2019 Vol. 5 No. 2: Desember, 2019 Vol 5 No 1: Juli, 2019 Vol. 5 No. 1: Juli, 2019 Vol 4 No 2: Desember, 2018 Vol. 4 No. 2: Desember, 2018 Vol. 4 No. 1: Juli, 2018 Vol 4 No 1: Juli, 2018 Vol 3 No 2: Desember, 2017 Vol. 3 No. 2: Desember, 2017 Vol 3 No 1: Juli, 2017 Vol. 3 No. 1: Juli, 2017 Vol. 2 No. 2: Desember, 2016 Vol 2 No 2: Desember, 2016 Vol 2 No 1: Juli, 2016 Vol. 2 No. 1: Juli, 2016 Vol. 1 No. 2: Desember, 2015 Vol. 1 No. 1: Juli, 2015 Vol 1 No 1: Juli, 2015 More Issue