cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Yuni Wibawanti
Contact Email
stringinformatika@gmail.com
Phone
+6281617239740
Journal Mail Official
stringinformatika@gmail.com
Editorial Address
Prodi Teknik Informatika FTIK Universitas Indraprasta PGRI Jl. Raya Tengah Kelurahan Gedong , Pasar Rebo, Jakarta Timur
Location
Kota adm. jakarta selatan,
Dki jakarta
INDONESIA
STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Published by Universitas Indraprasta PGRI
ISSN : 25279661     EISSN : 25492837     DOI : http://dx.doi.org/10.30998/string.v4i3.6197
Core Subject : Science, Education,
Computer Science & IT Mathematics
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) focuses on the publication of the results of scientific research related to the science and technology. STRING publishes scholarly articles in Science and Technology Focus and Scope Covering: 1. Computing and Informatics 2. Industrial Engineering 3. Electrical Engineering 3. Mechanical Engineering 4. Applied Mathematical 5. Physics (Classical and modern) 6. Mathematics and Science
Arjuna Subject : Ilmu Komputer (semua kategori) - Teori Komputasi dan Matematika
Articles 14 Documents
 1   2 
Search results for , issue "Vol 8, No 2 (2023)" : 14 Documents clear
Inkubator Mesin Tetas Telur Otomatis Berbasis Mikrokontroler Arduino Azhar, Zul; Gani, Abdul Rafid Fakhrun; Gani, Abdul Rasyid Fakhrun; Nata, Zul Mahadi
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 8, No 2 (2023)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v8i2.16609

Abstract

The hen will naturally incubate the eggs to carry out the hatching process. However, natural hatching has a small percentage of success, and the egg incubation can only be conducted with a maximum number of 10 eggs. This study aims to design and implement an egg incubator to increase chicken production. This research uses the design method and experimental method. Testing tools are divided into 3 types, namely temperature testing, humidity testing, and egg-hatching testing. The research result is an automatic egg incubator using an Arduino microcontroller. The incubator uses several electronic components: Arduino, DHT 22 sensor, RTC DS 1307 module, heater, cooler fan, and humidifier. The temperature test is very good, with a temperature range of 38.50C-390C. The humidity test is very good, with a humidity range of 55%-60%. The egg-hatching test was classified as very good, with an efficiency value of 90%. Based on the tests, the egg incubator belongs to the very good category and can be applied to increase chicken production.
Klasifikasi Mutu Fisik Tempe Menggunakan Metode Convolutional Neural Network (CNN) Karo Karo, Ichwanul Muslim; Karo Karo, Justaman Arifin; Yunianto, Yunianto; Hariyanto, Hariyanto; Falah, Miftahul
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 8, No 2 (2023)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v8i2.17596

Abstract

The quality of tempeh has until now been determined through direct physical observation. The results of observations frequently show less consistency due to human visual limitations. Image processing is an alternative used to determining the quality of tempeh from the image aspect. Image processing has capabilities that are more sensitive, precise, and objective than human vision. Convolutional Neural Network (CNN) is a deep learning model that is able to identify image objects in such a way as to determine the type of the object. In some cases, CNN algorithm is used to identify the condition of an object quality. This research aims to identify the quality of tempeh from the image aspect to ensure whether the tempeh can be classified as the tempeh having good condition or the one starting to decompose. The image of tempeh is primary data obtained directly from one of the traditional markets in Medan. The number of images that were successfully obtained was 262. The resulted classification model went through seven phases: data preparation, preprocessing, data augmentation, dataset splitting, building a classification model with the CNN algorithm with the ReLU activation function, model testing, and evaluation. The results show that the model generated from 80% of the data has an accuracy of 98.71% and a loss rate of 0.0433%. In conclusion, this study shows that the loss rate will stabilize at this rate after 50 epochs.
Perbandingan Algoritma Binary Search dan Sequential Search untuk Pencarian Persediaan Stok Barang Berbasis Web Ramadhan, Hanzhalah; Fauziah, Fauziah; Lantana, Dhieka Avrilia
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 8, No 2 (2023)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v8i2.16475

Abstract

Inventory of goods is one of the most important assets of a company. So. there must be good internal handling for the large amount of data items in the warehouse. At this time, the existing system of goods reporting is still conducted manually. This can result in errors in data storage. Therefore, it is necessary to develop a website application for inventory that can help users to more easily store and find the items needed. The application is the one using binary search and sequential search algorithms for the process of searching for goods data to speed up data search. This study compares the binary search and sequential search algorithms. The testing process uses microtime to produce the fastest time. The results of the test carried out 50 times out of 500 data show binary search produced an average time of 0.0402524 ms and sequential search of 0.0519893 ms. Then, the next test uses the searching time complexity method with the best case with a binary search algorithm of 0.0125 ms and a sequential search of 0.11293 ms. The conclusion is that using the binary search algorithm has the fastest time compared to the sequential search algorithm.
Implementasi Aplikasi Reservasi Lapangan Futsal Berbasis Android pada King Soka Arena Wiyanto, Wiyanto; Nisa, Khilyatun; Nugroho, Agung; Ansor, Abdul Halim
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 8, No 2 (2023)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v8i2.16624

Abstract

The reservations of futsal courts at King Soka Arena are still carried out using conventional transactions, namely customers must come directly to King Soka Arena to see and ask for information on the schedule of courts still available for rent, then customers make transactions to order futsal courts at the available time and as desired. The research method used by the author is the Waterfall Method. In implementing this application, the author uses Android Operating System.  Considering the problems in the research object, this research is conducted to implement a Futsal Field reservation application, to make futsal court booking transactions at King Soka Arena effective and efficient, making it easier for customers to make Android-based futsal field reservations at the King Soka Arena. With the implementation of the futsal court ordering application at King Soka Arena. The customers only need to access it via an Android smartphone. The results of application testing using Black Box Testing show that the application functions well.

Page 2 of 2 | Total Record : 14

 1   2 

Filter by Year

2023 2023


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