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
 18   19   20   21   22 
Penerapan Algoritma Genetika Untuk Mencari Optimasi Kombinasi Jalur Terpendek Dalam Kasus Travelling Salesman Problem Yusron Mubarok, Aldhiqo; Chotijah, Umi
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.424

Abstract

In delivering packages, goods, and in doing a business, location is a critical variable to control. The number of cases is often found in the arrival of late packages because the courier cannot find the fastest or most efficient route. Determining the most effective distance in a shipment of goods or packages determines customer satisfaction. In this case, the authors make an alternative to search for the shortest path optimization in the Travelling Salesman Problem (TSP) using genetic algorithm methods. With this method, the author wants to analyze and calculate the optimal or shortest route with the data set used. With the principle of a genetic algorithm that resembles the selection of living things with the population as part of each individual, each individual will represent by a fitness value. The application used to make this application is Matlab 2020a. The research results show that the optimal value of generation is 200 generations with the optimal crossover probability of 0.8, and the optimal mutation probability is 0.005. By finding the optimal value of each required variable, the graph of the shortest route will see. This value can be said to be best because the fitness obtained from these results is 0.036 indicating the most optimal value.
Otomatisasi Sistem Pengendalian dan Pemantauan Kadar Nutrisi Air menggunakan Teknologi NodeMCU ESP8266 pada Tanaman Hidroponik Marisa, Marisa; Carudin, Carudin; Ramdani, Ramdani
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.430

Abstract

The number of evictions of agricultural land to be used as buildings, offices and settlements has become narrow and agricultural land is reduced, so that farmers are now starting to grow a lot of crops using the hydroponic method, where this hydroponic method is a method of farming without soil elements. However, this hydroponic method requires intensive checking to monitor the condition of nutrient levels in the water so that plants grow well. This is a serious problem among hydroponic farmers because if the nutrient levels in the water do not match the needs of the type of plant, it will cause the death of the plant. Lettuce hydroponic plants require a water nutrient dose (PPM) of 560 – 840. If the PPM value exceeds the ideal value in the nutrient solution, it will result in reduced water absorption by lettuce plants so that the food formation process (photosynthesis) is disrupted. Meanwhile, if the PPM/EC value is smaller than the ideal value, the lettuce growth process will be hampered. Therefore, an automation control and monitoring system was made using the Deep Flow Technique method in adjusting the nutrient dose based on the concentration value by converting the PPM value on hydroponic plants according to the age of the plant. the system that is made can control the volume of nutrients well so as to achieve ideal nutritional conditions.
Analisis Sentimen dan Emosi Vaksin Sinovac pada Twitter menggunakan Naïve Bayes dan Valence Shifter Akbar, Bagus Muhammad; Akbar, Ahmad Taufiq; Husaini, Rochmat
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.433

Abstract

The Sinovac vaccine is among the Covid-19 news in the world in early 2021. That information has led to public responses between the pros and cons. Through Twitter media, the public responds to the issue of the Sinovac; therefore, their opinions on Twitter can analyze to count the percentage of sentiment and emotion towards the Sinovac. This analysis hopes to provide a wise and objective reference, although the pros and cons information is still emerging. This study uses Rstudio for sentiment analysis through Twitter opinion classification using Naïve Bayes and the Valence Shifter Lexicon method to analyze emotions, also using the Naïve Bayes. The Data is 2000 English-language Twitter comments limited to the latest and most popular tweet based on the Sinovac keyword since February 1, 2021, from all Twitter users worldwide. The results showed that Naïve Bayes recognized 1433 (71.65%) positive sentiments, 403 (20.15%) negative sentiments, and 164 (8.2%) neutral sentiments. Meanwhile, Valence Shifter Lexicon recognized 903 (45.15%) positive sentiment, 437 (21.85%) negative sentiment, and 660 (33%) neutral sentiments. The Naïve Bayes also succeeded in recognizing emotions with the highest number 1727 (86.35%) mixed emotions and 141 (7.05%) joy emotion.
Pengukuran Tingkat Kesiapan Implementasi E-Learning di Politeknik Negeri Jakarta Warsuta, Bambang; Muharram, Asep Taufik; Yusdisti, Iga; Jasmine, Syahda Afallia
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.434

Abstract

Politeknik Negeri Jakarta (PNJ) is anticipated to be an Asia-Class Polytechnic. The strategic issue of PNJ development to be transformed into an Asia-Class Polytechnic is the implementation of “Digital Transformation” for learning and servicing. One of the forms of this digital transformation is e-learning. The success of e-learning is influenced by how much the institution has prepared to utilize information technology in the learning process. This research uses an action research design with a questionnaire instrument based on an established model. Aydin and Tasci Model, adapted for an educational institution, is utilized for the preparedness evaluation. The measurement scale used in the model is a Likert scale (1-5). Aydin and Tasci divided the scale into four assessment intervals, which is not ready, needs much work (index 1-2,59); not ready, needs some work (index 2,6-3,39); ready, but needs a few improvements (index 3,4-4,19); ready go ahead (index 4,2-5). The result with a score of 4,16 indicates that PNJ is ready to implement e-learning with slight improvement, which is related to self-development and innovation.
Penerapan Computer Vision Menggunakan Metode Deep Learning pada Perspektif Generasi Ulul Albab Arifin, Imamul; Haidi, Reydiko Fakhran; Dzalhaqi, Muhammad
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.436

Abstract

Machine learning is one of the applications of artificial intelligence. The use of machine learning in computer vision is closely related to deep learning where computer scientists get inspiration about deep learning technology from the environment. The purpose of the research in this manuscript is to know and understand deep learning technology along with simple examples in processing image objects and to know and understand artificial intelligence technology from the perspective of the ulul albab generation so that it can provide comprehensive benefits for the world. The research conducted in this paper is a type of qualitative research with library research using various books and other reading literature such as journals and special websites so as to produce information on the topic under study. Artificial intelligence technology will always develop and lead to increasingly sophisticated directions, but technology also has a negative impact. The Ulul Albab generation must be able to struggle to have a positive impact on society because the Ulul Albab generation is the hope for the progress of Islamic civilization in various sectors of science and technology.
Pengembangan Absensi berbasis Mobile Aplikasi pada Badan Kepegawaian dan Pengembangan Sumber Daya Manusia Kabupaten Bone Usman, Syahrul; Jeffry, Jeffry; Aziz, Firman
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.437

Abstract

Since being designated a global pandemic by the world health agency (WHO), the Corona Virus Disease (Covid-19) outbreak has become a scourge worldwide; various standard transmission control procedures have been set by WHO to break the chain of transmission.  Bone District Government through the Circular of the Regional Secretary No. 800/1919/VI/BKPSDM/2020 dated June 4, 2020, regarding the work system of State Civil Apparatus Employees (ASN) in the new standard order regulates employee attendance using manual attendance and not using fingerprint attendance machines, and this will undoubtedly affect the recording of the performance of each ASN where the attendance data is already connected to the e-performance application that is applied to the Bone district. The purpose of this research is to create an online attendance application based on Android Mobile to be an alternative way of being absent by using the data communication method using the Representational State Transfer (Rest) web service architecture and utilizing the HTTP protocol with JavaScript Object Notation (JSON) format and the Java programming language as a language. Mobile Application programming. The results of this study are a mobile-based attendance application that has been tested for web service performance using the Apache JMeter application to ensure this application is ready to be used simultaneously by many ASN.
Implementasi Skyline Query pada Sistem Rekomendasi Pemilihan Tempat Kuliner di Kota Depok, Bogor, dan Tangerang Asqia, Misna; Munir, Sirojul
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.440

Abstract

In recent years, creative economic businesses in the form of culinary stalls have sprung up in various regions in Indonesia. A digital platform application for recommendations for picking regional superior culinary tours is likely to be highly beneficial to tourists in selecting the desired culinary location based on their tastes. There are three aspects as standards for culinary enterprises: product aspects, service aspects, and management aspects; these aspects can be a reference in one's preferences in choosing or determining a rating from a culinary business. This study uses the skyline query method to implement recommendations for selecting places to eat based on tourist preferences on four aspects of criteria: food, atmosphere, service, and health. The survey results through questionnaires from 169 respondents from Depok, Bogor, and Tangerang obtained 85.63% of respondents choosing places to eat based on service aspects, 77.42% health aspects, 73.99% atmosphere aspects, and 67.82% food aspects. The results of implementing the skyline query algorithm on a MySQL relational database system and a web-based application prototype obtained 100% of the functional applications running well.
Sistem Pengenalan Benih Padi menggunakan Metode Light Convolutional Neural Network pada Raspberry PI 4 B Hermawan, Indra; Arnaldy , Defiana; Agustin, Maria; Widyono, M. Farishanif; Nathanael, David; Mulyani, Meutia Tri
Jurnal Teknologi Terpadu Vol 7 No 2: Desember, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i2.443

Abstract

Recently, Deep learning methods with Convolutional Neural Networks (CNNs) have been widely used for image classification tasks. CNN has an unrivaled advantage in extracting discriminatory image features. However, many existing CNN-based methods are designed to go deeper and more significant with more complex layers that make them challenging to implement on mobile devices or real-time devices that use microcontrollers like raspberry pi, Arduino, and immediately. This is overcome by using a Light Convolutional Neural Network (LCNN), so it needs to experiment to test the difference in LCNN performance on a personal computer and a raspberry pi four microcontrollers with a Raspbian operating system. Experiments will be carried out using several performance measures: accuracy, F-1 score, recall, precision, and time to get performance results from deep learning. As such, the results and model architecture will confirm performance differences across individual devices and show how the model performs on resource-constrained or real-time devices. Tests show that the performance of the raspberry pi, which is a tool with limited resources, does not affect the quality of image recognition but affects the recognition processing time because the raspberry pi requires a longer processing time to perform one data or photo recognition process. This will accumulate the time required for processing many data, so it can conclude that the raspberry pi and tools with limited resources are not very practical for conducting recognition training and carrying out a recognition process that contains a lot of data or photos in one process.
Pengenalan Gerakan Sikap Dasar Pencak Silat Bakti Negara berbasis Aplikasi Mobile menggunakan Neural Network Suantara, I Putu Julian Taruna; Fredlina, Ketut Queena; Sudiatmika, Ida Bagus Kresna
Jurnal Teknologi Terpadu Vol 8 No 1: Juli, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.445

Abstract

Research on introducing basic stance or poses recognition specializing in sports is scarce. Researchers have not yet found journals or articles that discuss the introduction of the fundamental view of Pencak Silat as in this research. The research results can be used by athletes, teaching staff or organizations, and even the government who want to take advantage of the results of this research in the form of an application to introduce the fundamental stance of Pencak Silat. To realize this application, researchers use Neural Network or artificial intelligence where the model of recognition is trained on the Teachable Machine, which produces recognition accuracy above 90%, then integrated with mobile application programs based on Android that have been built using Flutter. After being integrated whit the mobile application, This application recognition still produces accuracy above 90%, so it can be concluded this application can work very well.
Perancangan Mesin Abstrak Finite State Automata Untuk Aplikasi Sewa Tanah Desa Sany, Diny Syarifah; Suwandi, Suwandi
Jurnal Teknologi Terpadu Vol 8 No 1: Juli, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v8i1.448

Abstract

Village land rental is a government program with specific provisions to maximize the benefits of village assets. A village land rental application can be developed to facilitate village land rental activities, but there is no appropriate design model to build this type of application. The design model for village land rental applications can make it easier for developers to create land rental applications. Applications resulting from the suitable land lease model will maximize the performance of village land rental activities. Finite state automata (FSA) is an abstract machine that can be used and implemented into programming languages. The proposed FSA model is adapted to the village land lease activities. Data collection for research materials was taken from Girijaya Village, Cianjur Regency. Testing this model is carried out in two ways: scenario testing comparing the results of the FSA and actual activities. The second test is by implementing the proposed FSA into the PHP programming language and then testing respondents' feedback to assess the proposed FSA's accuracy. In the first test, by comparing the results of the FSA with actual activities, it was found that the designed FSA was following actual activities. For feedback testing, a questionnaire was carried out with ten respondents getting a score of 4.7 or equivalent according to to tend to be very suitable to be used as a reference in developing village land rental applications.

Page 20 of 27 | Total Record : 266

 18   19   20   21   22 

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