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All Journal Jurnal Informatika dan Teknik Elektro Terapan Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro Journal of Computer System and Informatics (JoSYC) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) JEITECH (JOURNAL OF ELECTRICAL ENGINEERING AND INFORMATION TECHNOLOGY)
Akbar, Lalu A. Syamsul Irfan
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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WEBSITE INTERFACE MONITORING CLIENT ACTIVITIES USING MIKROTIK ON UBUNTU SERVER 18.04 LTS Akbar, Lalu A. Syamsul Irfan; Putra, Rayasa Puringgar Prasadha; Ariessaputra, Suthami
DIELEKTRIKA Vol 10 No 1 (2023): DIELEKTRIKA
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/dielektrika.v10i1.332

Abstract

Internet network is beneficial to be able to support the needs of the learning process. However, a large number of internet users, for example, who access university data, can cause weaknesses in a system, making it very vulnerable to data theft, damage, and leakage of confidential documents. The obstacle faced is that the internet is getting slower due to many users using the internet network and not knowing the amount of bandwidth usage. A system is needed to determine the bandwidth usage for each client. This system To simplify the process of monitoring the internet network. It can view client browsing history and block website domains so that internet users in the world of education have positive characteristics and the internet is not slow. In this system, the admin will monitor the use of internet clients connected to the campus environment through the user name and password obtained for each student. The results of this research are the creation of an internet monitoring system for a proxy to monitor the maximum amount of bandwidth usage for each client, view the client's browsing history, and block website domains and client IPs. The admin can observe the internet network and monitor client activity that uses the internet network in the campus environment using the monitoring application.
KLASIFIKASI GENUS TANAMAN ANGGREK MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN) DENGAN MENGGUNAKAN ARSITEKTUR VGG 16 Zulkipli; Akbar, Lalu A. Syamsul Irfan; Kanata, Bulkis
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 4 (2024): EDISI 22
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i4.4982

Abstract

Indonesia is one of the countries that has very diverse orchid genetic resources. Orchid species are found in several islands in Indonesia such as Java, Sumatra, Kalimantan, Sulawesi, Nusa Tenggara, Bali, Maluku and Papua and have types of orchids with varying flower characters. Orchids are one of the most popular ornamental plants and have a beautiful charm. The beauty and value of orchids are in their flowers. However, some orchids have the same color and appearance even though they belong to different species. In fact, many people think that one orchid species with other species that have similar shapes are the same species. Therefore, a system is needed that can make it easier to recognize orchid species. The method used is the Convolutional Neural Network with VGG 16 Architecture to classify orchid flower types, where the dataset used is divided into 3 scenarios, namely scenario 1 using orchid petal images, scenario 2 using orchid leaf tree images, and scenario 3 using combined images of orchid flower petals and leaves. From the three scenarios, the results of the model with high accuracy in scenario 3 were 99.47%. This shows that the model built is able to predict well.
IMPLEMENTASI ROUTING STATIC MULTI HOP PADA PERANGKAT LORA Astarina, Raditia; Akbar, Lalu A. Syamsul Irfan; Budiman, Djul Fikry
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.5228

Abstract

Di era digital yang semakin berkembang, teknologi Low Power Wide Area Network (LPWAN) seperti LoRa menjadi solusi utama untuk komunikasi nirkabel jarak jauh berdaya rendah. Penelitian ini mengkaji penerapan statistik routing multi-hop pada jaringan LoRa dan menganalisis pengaruh jarak antar node terhadap kinerja jaringan, seperti Packet Delivery Ratio (PDR) dan kekuatan sinyal (RSSI). Pengujian ini menggunakan metode uji coba yang telah dilakukan di jalur bypass yakni dengan menempatkan node 1 pada jarak 100 meter dari node 2 dan node 3 yang bertindak sebagai node perantara juga berada pada jarak 100 dari node 4 yang berfungsi sebagai receiver akhir. Jarak antar node kemudian diperpanjang dari 100 meter hingga 500 meter. Hasil pengukuran menunjukkan bahwa peningkatan jarak antar node dari 100 hingga 500 meter menurunkan kualitas komunikasi secara signifikan, dengan PDR turun dari 95% menjadi 45% dan error rate meningkat hingga 55%. Selain itu, jarak yang lebih jauh mempengaruhi kekuatan dan sinyal transmisi data, diperburuk oleh interferensi dan hambatan fisik. Strategi mitigasi seperti routing multi-hop dan jalur alternatif terbukti efektif dalam meningkatkan jangkauan, stabilitas, dan keberlanjutan komunikasi.
Prediksi Nilai Tukar Mata Uang Menggunakan Algoritma Long Short-Term Memory dan Random Forest Hidayat, Imam; Akbar, Lalu A. Syamsul Irfan; Rachman, Ahmad SjamSjiar
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6200

Abstract

Currency exchange rate is an exchange between two different currencies, which is a comparison of the value or price between the two currencies and this comparison is often called the exchange rate. Currency exchange rate movements are very complex and influenced by many factors, including economic, political, and social factors. In an effort to understand and predict these movements, many studies have been conducted using various methods of analysis and prediction. however, there is still no consensus on the best method to predict exchange rate movements. This study aims to compare the performance between the Long Short Term-Memory and Random Forest algorithms in predicting the exchange rate of the Rupiah (IDR) against the Singapore Dollar (SGD). By utilizing the historical data of currency exchange rate movements, the main data and the data of import and export values from the two countries as additional variables, After going through a series of stages ranging from data collection, preprocessing, to modeling, the evaluation results show that the Long Short Term-Memory algorithm has a better performance with a Root Mean Square Error (RMSE) of 152.28, Mean Absolute Percentage Error (MAPE) 1.25%, and 98.74% accuracy, while Random Forest has an RMSE of 284.3, a MAPE of 2.07%, and an accuracy of 97.93%. These results show that Long Short Term-Memory is superior in capturing complex exchange rate change patterns, making it a more effective choice in predicting currency exchange rates than Random Forest.
Perkiraan Suhu Menggunakan Algoritma Recurrent Neural Network Long Short Term Memory Zahidin, Ilham; Kanata, Bulkis; Akbar, Lalu A. Syamsul Irfan
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6242

Abstract

Air temperature is a critical variable in weather conditions that affects various aspects of human life, including health, agriculture, and the economy. In Indonesia, particularly in Mataram City, which is situated in a tropical region, significant temperature changes can impact sectors such as tourism, agriculture, and daily activities. Accurate temperature forecasting can aid the public, industries, and the government in making more informed decisions, both for short-term and long-term planning. However, weather in tropical regions like Mataram tends to be difficult to predict accurately due to its dynamic nature and the influence of multiple atmospheric factors. Conventional weather prediction methods often fail to capture the complex patterns in historical temperature data, necessitating more advanced methods to improve forecast accuracy. Recurrent Neural Networks (RNNs), particularly the Long Short-Term Memory (LSTM) variant, have proven to be highly effective tools for modeling complex time series data. This algorithm can retain long-term information and recognize patterns in data that change over time, making it well-suited for temperature prediction challenges. In this study, the RNN-LSTM algorithm is applied to forecast temperatures in Mataram City, aiming to improve forecast accuracy and produce results useful for various purposes. The temperature prediction model using the LSTM algorithm involves several steps: data collection, data normalization, splitting data into test and training sets, building the LSTM model by determining the number of epochs, layers, and batch size, and finally, evaluating the model with RMSE. Two parameters, epoch and batch size, influence the LSTM model’s forecasting results in this study. Epochs used in this study are 5, 10, 20, 30, 40, 50, and 100, with a fixed batch size of 32. The LSTM algorithm employs the RMSProp optimizer. The temperature prediction model using the LSTM method achieved the best average accuracy with a batch size of 32 and 50 epochs, yielding an RMSE value of 0.13 and a prediction accuracy of 99.96% in forecasting Mataram City’s temperature for the year 2023.
Development of an IoT-Based Smart Home Prototype Using the Blynk Application Adi Pramana, I Gusti Bagus; Akbar, Lalu A. Syamsul Irfan; Ramadhani, Cipta
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 7 No 1 (2025): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46574/motivection.v7i1.424

Abstract

The advancement of Internet of Things (IoT) technology has enabled the development of smart home automation systems that enhance comfort, security, and energy efficiency. This study aims to design, develop, and evaluate an IoT-based smart home prototype utilizing the Blynk App for remote monitoring and control. The system consists of various components, including an ESP32 microcontroller, relays, and an LDR sensor, which facilitate both automatic and manual light control. A prototype development approach was employed, encompassing system design, implementation, and testing. The experimental results demonstrate that the smart home prototype operates efficiently, with an average response time of 73.4 ms, indicating fast and reliable system performance. The integration of Blynk Cloud security protocols further ensures secure device communication and real-time monitoring. This research provides a functional smart home prototype that can serve as a foundation for future smart home innovations. Moreover, the system's ability to optimize energy usage and improve user convenience highlights its potential impact on sustainable living and smart home advancements.
MONITORING SPEKTRUM FREKUENSI RADIO RUTIN DI STASIUN TETAP PADA SITE LOMBOK TENGAH MENGGUNAKAN PERANGKAT TCI SCORPIO CLIENT Azis, Imam Abdul; Akbar, Lalu A. Syamsul Irfan; Nababan, Sabar
JEITECH (JOURNAL OF ELECTRICAL ENGINEERING, INFORMATION TECHNOLOGY, CONTROL ENGINEERING, AND ROBOTIC) Vol. 3 No. 1 (2025): Edisi April 2025
Publisher : Depertment of Electrical Engineering University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Monitoring spektrum frekuensi radio secara rutin sangat penting untuk menjamin efisiensi penggunaan spektrum serta mencegah terjadinya interferensi antar layanan komunikasi. Penelitian ini membahas hasil pemantauan spektrum di stasiun tetap pada site Lombok Tengah menggunakan perangkat TCI Scorpio Client pada tanggal 27 Februari 2025. Tujuan utama dari studi ini adalah menganalisis tingkat pemanfaatan spektrum serta mengidentifikasi potensi interferensi berdasarkan pengukuran yang dilakukan pada hari tersebut. Data dikumpulkan melalui metode pengukuran langsung dengan perangkat TCI dan dianalisis menggunakan parameter Frequency Band Occupancy (FBO%) dan spektrum yang terpakai (occupied spectrum). Hasil monitoring menunjukkan bahwa tingkat pemanfaatan spektrum pada tanggal tersebut hanya sebesar 5,854% dari total lebar pita frekuensi yang tersedia, yaitu 61,425 MHz. Pita ketiga menunjukkan tingkat pemanfaatan tertinggi (27,273%), sedangkan pita keempat terendah (0,039%). Hasil ini mencerminkan kondisi spektrum pada saat pengukuran serta menandakan adanya peluang untuk optimalisasi, baik melalui redistribusi pengguna maupun evaluasi kebijakan alokasi frekuensi. Studi ini memberikan kontribusi bagi pengelolaan spektrum yang lebih efisien dan dapat menjadi dasar pemantauan jangka panjang untuk mengamati tren penggunaan spektrum.
Co-Authors Adi Pramana, I Gusti Bagus Ariessaputra, Suthami Astarina, Raditia Azis, Imam Abdul Bulkis Kanata Cipta Ramadhani Djul Fikry Budiman, Djul Fikry Ida Ayu Putu Sri Widnyani Jayawarsa, A.A. Ketut Nababan, Sabar Putra, Rayasa Puringgar Prasadha Rachman, Ahmad SjamSjiar Zahidin, Ilham