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INDONESIA
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Published by Universitas Medan Area
ISSN : 25496247     EISSN : 25496255     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
JURNAL TEKNIK INFORMATIKA, JITE (Journal of Informatics and Telecommunication Engineering) is a journal that contains articles / publications and research results of scientific work related to the field of science of Informatics Engineering such as Software Engineering, Database, Data Mining, Network, Telecommunication and Artificial Intelligence which published and managed by the Faculty of Informatics Engineering at the University of Medan Area .
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol. 8 No. 1 (2024): Issues July 2024" : 12 Documents clear
Analysis of Student Satisfaction Levels with Computer Laboratory Services with a Fuzzy Service Quality Approach Diana, Elviza; Kurniah, Reni
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.10762

Abstract

Quality of education provided Prof. University DR. Hazairin, SH Bengkulu, is a higher education institution that is committed to providing the best service to its students, including computer laboratory services. Computer laboratory services have an important role in supporting student learning and research, therefore, it is important to measure and analyze the level of student satisfaction with this service. In measuring the level of student satisfaction with computer laboratory services using the Fuzzy Service Quality approach method. This approach allows us to understand the complexity and diversity of students' views on service quality, which are often difficult to measure with conventional approaches. By using the Fuzzy Service Quality model, we can describe the level of student satisfaction more accurately, identify areas that need improvement, and increase the effectiveness and efficiency of computer laboratory services. Based on the research results, it was concluded that all aspects had a score above 3, which means student satisfaction with computer laboratory services has been met well. The highest score from all aspects is the cool and comfortable computer laboratory room and the lowest is 3.90 while the lowest is 2.77 for the Computer Laboratory service providing academic information and non-academic services in the form of a website (online). The reliability aspect (reliability of lecturers, and academic staff) has the highest reliable value of 0.916. Based on the results of Servqual and Logical Fuzzy data analysis, a high GAP value was found in students' perceptions and expectations regarding computer laboratory services providing academic information and non-academic services in the form of websites (online).
Automated Detection of Ancient Indonesian Coins for Historical Numismatic Investigations Rosalina, Rosalina
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11241

Abstract

This study focuses on cultural heritage preservation, employing the YOLOv8 model for detecting and classifying ancient Indonesian coins. Motivated by challenges in accurately identifying coins with diverse physical conditions, YOLOv8, introduced in January 2023, presents a groundbreaking advancement in computer vision. Meticulous testing on a curated dataset demonstrates the model's capacity to recognize unique features across various coin variations, marking a substantial stride in cultural heritage preservation. Contributing significantly to computer vision and cultural heritage studies, the research emphasizes key metrics in model evaluation—accuracy, recall, and precision. The rigorous assessment underscores the YOLOv8 system's efficiency and reliability in classifying ancient Indonesian coins, with experimentation yielding a commendable 91% accuracy. Beyond technical contributions, the study extends understanding of YOLOv8's capabilities, paving new avenues for object recognition in cultural preservation. This research serves as a milestone, advancing the integration of cutting-edge technology to safeguard and comprehend the rich cultural heritage embodied in ancient Indonesian coins.
High Gain Plannar Series Array 8x2 Element Microstrip Antenna Using Spiral Stub For 5G Communication System Suryadi, Suryadi; Alam, Syah; Surjati, Indra; Ningsih, Yuli Kurnia
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11267

Abstract

Sistem komunikasi 5G membutuhkan antena sebagai perangkat penerima yang memiliki kinerja tinggi termasuk bandwidth yang lebar dan gain yang tinggi. Antena mikrostrip mempunyai kelebihan seperti biaya yang murah, cocok untuk frekuensi tinggi dan mudah diintegrasikan dengan perangkat lain. Salah satu kelemahan antena mikrostrip adalah gain yang rendah. Oleh karena itu, antena mikrostrip dengan gain tinggi sangat dibutuhkan untuk mendukung sistem komunikasi 5G. Penelitian ini memberikan solusi dengan mengusulkan antena mikrostrip dengan gain tinggi yang beroperasi pada frekuensi resonansi 3,5 GHz untuk sistem komunikasi 5G. Antena usulan dikembangkan dalam lima tahap dimulai dari satu elemen, susunan seri dua elemen, susunan seri 4 elemen, susunan seri 8 elemen dan susunan seri plannar 8x2 elemen. Teknik susunan seri plannar dan menggunakan spiral stub pada line feed serta slit diusulkan untuk meningkatkan gain antena mikrostrip. Dalam tulisan ini, simulasi dan pengukuran dari antena usulan ditampilkan dan dibandingkan secara komprehensif untuk menunjukkan peningkatan kinerja dari setiap tahap pengembangan model usulan. Berdasarkan hasil pengukuran, antena yang dirancang memiliki gain maksimum sebesar 13,08 dB pada frekuensi resonansi 3,5 GHz. Gain antena masing-masing meningkat 118 % dibandingkan dengan antena elemen tunggal. Oleh karena itu, antena usulan ini dapat direkomendasikan untuk digunakan sebagai antena penerima sistem komunikasi 5G
4G Network Design and Performance Evaluation in Kroya, Cilacap: A Comparative Study of 700 MHz SU-MIMO and MU-MIMO Isnaeni, Novita Ayu; Buchari, Erlin Herlina; Ariansyah, Ahmad; Kaban, Esra Andio; Wibowo, Prasetyo Adi; Alfin Hikmaturokhman; Pramono, Subuh
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11339

Abstract

Penelitian ini merancang jaringan 4G menggunakan frekuensi 700 Mhz dengan bandwidth 20 Mhz di kawasan Kroya, Cilacap seluas 31,636 km2. Model propagasi yang digunakan adalah Okumura-Hatta. Simulasi prediksi coverage menggunakan Software Atoll 3,4 yang menggunakan frekuensi 700 Mhz. didapatkan jumlah Base Tranceiver Station (BTS) sebanyak 25. Berdasarkan jumlah Base Tranceiver Station (BTS) tersebut, maka dilanjutkan dengan mensimulasikan dengan parameter-parameter penelitian yang telah ditentukan. Rata-rata tingkat sinyal (Coverage by Signal) pada SU-MIMO dan MU-MIMO didapatkan nilai sebesar -91,35 dBm dan -91,62 dBm. Rata-rata tingkat sinyal dan rata-rata kekuatan sinyal efektif pada Single-User Multiple Input Multiple Output (SU-MIMO) -123,8 dBm sedangkan pada Multiple Input Multiple Output (MU-MIMO) sebesar -120,71 dBm, rata-rata rasio C/(I+N) pada SU-MIMO sebesar 3,79 dB sedangkan pada MU-MIMO 3,28 dB tidak menunjukkan perbedaan yang signifikan. SU-MIMO mendukung throughput tinggi untuk satu pengguna yaitu sebesar 15,082 Kbps, sedangkan MU-MIMO menunjukkan stabilitas yang lebih baik dengan throughput yang lebih konsisten yaitu sebesar 13,638 Kbps.
Improving 2100 MHz Cellular Connectivity in Wonokerso, Sragen: Comprehensive Insights from MIMO Antenna Variation Analysis Muzzaki, Muhammad Raihan; Ayudya, Dila Ayudya; Afifah, Dinda Roshmalia Nur; Pinem, Ebeneser; Syahbana, Egia M.; Alfin Hikmaturokhman; Putri , Hasanah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11340

Abstract

This research discusses 4G-LTE cellular network coverage planning in Wonokerso, Sragen, Central Java, at the 2100MHz frequency by comparing MU-MIMO and SU-MIMO. The growing demand for connectivity is driving a thoughtfulapproach to network development. MU-MIMO uses multiple antennas to increase throughput, while SU-MIMO relieson one antenna per user. The analysis results show that the average signal level (coverage by signal level) for SUMIMO and MU-MIMO in signal strength is -87.88 dBm and -87.77 dBm, respectively. The standard deviation for SUMIMO and MU-MIMO is 9.84 dBm and 14.34 dBm, respectively. In the effective SU-MIMO and MU-MIMO signals, the signal strength gets the same value of -119.36 dBm. The standard deviation for SU-MIMO and MU-MIMO is 7.3 dBmand 7.28 dBm, respectively. On average, the C/(I+N) SU-MIMO and MU-MIMO ratios for signal strength get values of7.75 dB and 7.41 dB, respectively. The standard deviation for SU-MIMO and MU-MIMO is 5.5 dB and 5.15 dB,respectively. And for SU-MIMO and MU-MIMO signal throughput, the signal strength gets a value of 30,455.75 kbpsand 24,731.04 kbps, respectively. The standard deviation for SU-MIMO and MU-MIMO is 28,192.34 kbps and 17,057.9kbps, respectively. Overall, SU-MIMO tends to provide lower but more consistent signal levels, whereas MU-MIMOexhibits a slightly higher average signal level with greater variation
EVALUATION OF STUDENTS' E-LEARNING LEARNING OUTCOMES USING THE COURSE COMPLETION METHOD Jemakmun, Jemakmun makmun; Rahmatullah, M.Taufik; Roni, Mukran
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11639

Abstract

The current development of internet technology has changed the direction of the learning system at both elementary and tertiary levels by means of online, blended learning, and e-learning. This research aims to determine and analyze the learning outcomes of students using course completion during lectures using the eLearning method. The research subjects are Bina Darma University students. Data collection was carried out in this research through observation and taking primary data from the e-learning system. The instruments in this research include the independent variable (X), which is report completion, and the dependent variable (Y), which is elearning learning outcomes. The resulting research results are: 1. There is a positive influence from the activity task variable on the student learning outcome variable, which is known to be active in carrying out the tasks in e-learning. 2. There is a positive influence from the material variable on the student learning outcome variable, which is known to be active in opening the material. provided in e-learning. Multiple linear regression tests result from the course completion variable on student learning outcomes. It can be concluded that there is a positive influence on the learning outcomes of variable Y from variable X. Students can also share information or opinions on various matters relating to the subject matter or assignments given by the lecturer. Apart from that, lecturers can place learning materials and assignments that students must complete in certain places in e-learning for students to access.
Analyzing Food Prices in North Sumatra Province in 2022 – 2024 Using the Linear Regression Method Faza, Sharfina; Firjatullah, Muhammad; Azhar, Muhammad Fauzan; Hidayatullah, Rafly Artha; Lubis, Arif Ridho
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11788

Abstract

The food price data used was obtained from literature studies which include main food ingredients such as rice, beef, chicken, eggs, red onions, red chili pepper and cooking oil. The linear regression method is used to model the relationship between the independent variable (year) and the dependent variable (food prices), with the aim of predicting future food prices based on historical data. Although linear regression can provide fairly accurate food price estimates, improvements in prediction models can be achieved by incorporating other analysis methods such as time series analysis or machine learning. The implications of this research highlight the importance of effective policy planning to maintain food price stability and ensure sufficient food availability for the community. Future research could involve more in-depth analysis of the factors influencing food prices, as well as the development of more sophisticated prediction models to support decision-making in agriculture and food. This research aims to analyze food prices in the Northern region of Sumatra Province during the period 2022 to 2024 using the linear regression method. The results show that rice, meat, chicken meat, chicken eggs, shallots, red chilies and edible oils all increased, but only chicken meat, shallots and edible oils also experienced a decrease.
Comparison of ARIMA and LSTM Models in Stock Price Forecasting: A Case Study of GOTO.JK Adam, Hikmah Adwin; Raditiansyah, Farhan; Imani, Muhammad Rayyan; Fawwaz, Mohammad Faris; Julham, Julham; Lubis, Arif Ridho
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11841

Abstract

The renowned Indonesian company, PT Gojek Tokopedia Tbk, has a significant impact on the Indonesian economy by attracting investors to invest their shares. This study uses stock closing price data to forecast stock prices using ARIMA (AutoRegressive Intergrated Moving Average) and LSTM (Long Short-Term Memory) models, to predict using prediction by dividing the data into groups of 10 or 20 data with data sets to be trained as multiples. The analysis shows that ARIMA is superior to LSTM based on the comparison of average error and average percentage error, where the average error results in LSTM (3.843) and ARIMA (3.259), as well as the average error of LSTM (4.04%) and ARIMA (3.57%). The research supports the conclusion that ARIMA has a better performance in predicting the stock price of PT Gojek Tokopedia Tbk. These results provide important insights for investors and market participants, while the research supports the increased use of seasonal patterns in ARIMA forecasting for more accurate results in the future. Future research is recommended to explore additional factors and optimized models to further improve stock price prediction.
Machine Learning-Driven Detection of Malicious URL: Comparative Analysis of Random Forest and SVMs Adam, Hikmah Adwin; Nasution, Shaquil Fathza; Simanungkalit, Rikky Rifaldo; Diansyah, Ikhsan Hafid
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11844

Abstract

No longer a novelty, the internet has become the ubiquitous fabric of our lives, transforming how we interact, do business and disseminate information. However, its popularity has also attracted attackers who want to exploit it for personal gain. One tactic they use is to launch client-side attacks through malicious websites. Malicious websites are constantly evolving, and traditional methods such as blacklisting are no longer effective in identifying them. More sophisticated and adaptive solutions are needed to combat this threat. This research proposes an automatic malicious website detection method that utilizes URL properties and machine learning algorithms. This approach uses a combination of relevant URL features and a powerful machine learning model to accurately identify malicious websites. This research uses two popular machine learning algorithms: Random Forest (RF) and Support Vector Machines (SVM). Both models are trained on a dataset consisting of URL properties of malicious and Benign websites. The research results show that the proposed method is able to achieve a good level of accuracy in detecting malicious websites. Both RF and SVM show promising performance, with RF model achieved an accuracy of 86.15%, surpassing the SVM's performance of 85.38%. While overall performance is satisfactory, further optimization might be necessary, particularly to address potential class imbalance. Oversampling method could offer a more effective alternative to traditional undersampling methods and potentially improve performance across both website URLs categories
5G Implementation using Software Defined Radio (SDR) Ishak Ginting; Wibowo, Tody Ariefianto; Mahardika, Mohamad Fajar; Hikmaturokhman, Alfin
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 8 No. 1 (2024): Issues July 2024
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v8i1.11967

Abstract

Jaringan 5G merupakan perkembangan generasi selular 4G long term evolution (LTE), terdiri dari 3 entitas utama yaitu user equipment (UE), radio access network (RAN) dan Core network (CN). Uji coba implementasi jaringan 5G menggunakan Software defined Radio (SDR). Emulator user equipment sebagai entitas pengguna, menggunakan software open source srsUe dengan parameter seting user subscriber identity module (USIM) 51009. USIM merupakan gabungan kode mobile country code (MCC) 510 negara Indonesia dan mobile country code (MNC) 09 milik operator selular di Indonesia. GNodeB sebagai entitas base transceiver station (BTS) menggunakan software open source srsRAN dengan parameter seting enb_id sebagai identitas. Tracking area menggunakan parameter Tracking Area Code (TAC) 22. Physical cell identity (PCI) 7 ditentukan sebagai identitas cell arah downlink. Frekuensi kerja di 1824.5 Mhz atau dl_arfcn 368500 pada band 3. Entitas Core menggunakan software open source Open5GS dengan parameter seting TAC, MCC, dan MNC yang sesuai dengan paremeter seting gNodeB. Identitas Access mobility management function (AMF) ditentukan menggunakan alamat ip address. Implementasi jaringan 5G berhasil dilakukan menggunakan perangkat lunak sumber terbuka. Pengujian pada parameter jaringan selular komersil berhasil dilakukan dengan syarat parameter seting harus sama pada setiap entitas. Ini membuktikan open SDR ini dapat diterapkan pada jaringan komersil. Pengujian performansi ping test dari 5G Core ke arah user sukses dengan nilai rata-rata 39,58 ms, ping success rate 100% dan pinglost rate 0%. Pengujian user registration sukses dilakukan dengan hasil analisis berupa diagram message flow yang menunjukkan tahapan yang terjadi setelah initial ue message hingga user plan function (UPF).

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