Article Per Year (5 Year)
p-Index From 2020 - 2025
2.926
P-Index
This Author published in this journals
All Journal Jurnal Ilmu dan Teknologi Kelautan Tropis Lontar Komputer: Jurnal Ilmiah Teknologi Informasi ILMU KELAUTAN: Indonesian Journal of Marine Sciences Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) JURNAL SUMBER DAYA AIR Charity : Jurnal Pengabdian Masyarakat Indonesian Community Journal eProceedings of Engineering
Didit Adytia
Telkom University
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Public Health Social Sciences Other

Published : 30 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 30 Documents
Search

 1   2   3 
Pembangunan Dan Pengujian Protokol Mqtt & Websocket Untuk Aplikasi Iot Rumah Cerdas Berbasis Android Muhammad Adzhar Amrullah; Kemas Muslim Lhaksmana; Didit Adytia
eProceedings of Engineering Vol 5, No 2 (2018): Agustus 2018
Publisher : eProceedings of Engineering

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

Abstract

Abstrak Teknologi berkembang dengan pesat pada era sekarang, dengan seiring perkembangan teknologi tersebut maka ada dampak yang ditimbulkan pada dunia industri maupun pada masyarakat. Salah satu teknologinya adalah Internet of Things (IoT) yang dapat menghubungkan beberapa perangkat pada jaringan Internet. Dengan adanya konsep tersebut perangkat rumah dapat dikendalikan dan dipantau dari jarak jauh menggunakan telepon pintar. Mengingat efisiensi waktu yang sangat penting hal ini perlu dilakukan untuk meningkatkan kualitas hidup manusia. Dalam pembangunannya penulis memilih perangkat lampu, pengunci pintu dan sensor suhu ruangan untuk dikendalikan dan dipantau melalui telepon pintar berbasis Android yang terhubung ke dalam jaringan Internet, pada bagian perangkat rumah dihubungkan dengan mikrokontroller NodeMCU yang berfungsi sebagai kendali perangkat dari sebuah pesan telepon pintar dan berfungsi menghubungkan perangkat rumah ke dalam jaringan Internet melalui jaringan nirkabel, adapun dalam pembangunan ini penulis membandingkan waktu pengiriman pesan melalui protokol Message Queuing Telemetry Transport (MQTT) dan WebSocket, hal ini dilakukan upaya mengetahui prosedur pengiriman pesan yang lebih cepat, dengan adanya hal tersebut tentu perlu didapat sebuah layanan Server yang mampu melayani sebuah prosedur pengiriman pesan tersebut melalui jaringan Internet. Hasil dari tugas akhir ini adalah sebuah pembangunan aplikasi IoT untuk rumah cerdas berbasis Android, dan menunjukan hasil pengujian waktu pengiriman pesan melalui protokol MQTT lebih cepat daripada protokol WebSocket. Kata kunci : IoT, rumah cerdas, android, NodeMCU, MQTT, websocket. Abstract Technology is growing rapidly in the present era, with the development of such technology there is an impact on the industry and the community. One of the technologies is the Internet of Things (IoT) that can connect multiple devices on the Internet network. With the concept that home devices can be controlled and monitored remotely using a smart phone. Given the time efficiency is very important this needs to be done to improve the quality of human life. In its development the authors chose the device lights, door locks and indoor temperature sensors to be controlled and monitored through an Android-based smart phone connected to the Internet network, in the home device section is connected to NodeMCU microcontroller that serves as the device control of a smart phone message and works connecting the home device into the Internet via a wireless network, As for the development of this author compare the time of message delivery with Message Queuing Telemetry Transport (MQTT) and WebSocket, this is done to know the procedure of sending a message faster, with the provisions of things that are required for server service capable of serving a messaging procedure over the Internet. The result of this final project is the development of the IoT application for smart home based on Android, and shows the test of message delivery time through MQTT protocol faster than with WebSocket protocol. Keywords: IoT, smart home, android, NodeMCU, MQTT, websocket
Implementasi Staggered Grid Pada Persamaan Air Dangkal Untuk Simulasi Gelombang Tsunami Akibat Longsor Bawah Laut Arkan Priya Anggana Hadna; Didit Adytia; Dede Tarwidi
eProceedings of Engineering Vol 5, No 3 (2018): Desember 2018
Publisher : eProceedings of Engineering

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

Abstract

Abstrak Gelombang tsunami tidak hanya ditimbulkan oleh adanya gempa bumi atau letusan gunung berapi bawah laut tetapi juga dapat diakibatkan oleh adanya longsor bawah laut. Makalah ini memfokuskan pada simulasi numerik gelombang tsunami yang dipicu oleh longsor bawah laut. Persamaan gerak untuk gelombang air direpresentasikan oleh persamaan air dangkal. Sedangkan untuk longsor bawah laut dimodelkan dengan cara menurunkan persamaan gerak benda padat yang meluncur pada bidang miring. Solusi dari persamaan air dangkal dicari secara numerik dengan mengimplementasikan metode volume hingga skema staggered grid. Solusi dari persamaan air dangkal yang diselesaikan dengan metode staggered grid kemudian divalidasi dengan hasil eksperimen kasus run-up yang telah dilakukan oleh (Synolakis, 1986). Hasil simulasi numerik gelombang tsunami yang diakibatkan oleh kemunculan longsor bawah laut menunjukkan kecocokan yang cukup tinggi dengan hasil simulasi yang telah dilakukan oleh (Lynet & Liu, 2002) dengan menggunakan metode boundary integral equation model (BIEM). Kata kunci : longsor bawah laut, persamaan air dangkal, simulasi numerik, staggered grid, tsunami Abstract Tsunami wave is not only caused by an earthquake or underwater volcanic eruption but can also be caused by an underwater landslide. This paper focuses on the numerical simulation of tsunami waves triggered by an underwater landslide. The equation of motion for water waves is represented by shallow water equations. Meanwhile, underwater landslide is modeled by deriving the equation of motion of a solid object that slide down on the sloping bottom. Solution of shallow water equations is numerically determined by implementing finite volume method with staggered grid scheme. The solution of shallow water equation which is solved by the staggered grid method is validated with experimental results for run-up case that have been performed by (Synolakis, 1986). Numerical results of tsunami simulation show a good agreement with the simulation results presented by (Lynet & Liu, 2002) which used the boundary integral equation model (BIEM) method. Keywords: numerical simulation, shallow water equation, staggered grid, tsunami, underwater landslide
Simulasi Dam Break Dengan Menggunakan Persamaan Air Dangkal Dengan Implementasi Skema Lax-wendroff Finite Volume Method Radika Rafif Gibran; Didit Adytia; Dede Tarwidi
eProceedings of Engineering Vol 5, No 3 (2018): Desember 2018
Publisher : eProceedings of Engineering

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

Abstract

Abstrak Dam adalah sebuah konstruksi yang dibangun untuk menahan laju air menjadi waduk, danau, atau tempat rekreasi, tidak jarang dam digunakan untuk mengaliri air ke sebuah pembangkit listrik tenaga air. Dam sendiri sebagai bangunan yang berupa tanah, batu, dan beton, dam dianggap sebagai bangunan yang berbahaya, karena dampak besar yang ditimbulkan jika dam itu hancur. Tugas Akhir ini akan membahas tentang simulasi Shallow Water Equations (SWE) dengan implementasi Skema LaxWendroff dalam satu dimensi menggunakan Dam Break sebagai studi kasus, metode numerik ini adalah salah satu solusi untuk persamaan diferensial parsial hiperbolik. Pada tugas akhir ini akan disimulasikan skema tersebut dan akan dilihat seberapa besar keakurasian dari skema tersebut untuk studi kasus seperti Dam Break. Kata kunci : Shallow Water Equation, Lax-Wendroff, Dam Break. Abstract Dam is a construction that is built to withstand the rate of water into reservoirs, lakes, or recreational places, not infrequently the dam is used to drain water to a hydroelectric power plant. Dam itself as a building in the form of land, stone, and concrete, the dam is considered a dangerous building, because of the large impact caused if the dam is destroyed. This Final Project will discuss about the Shallow Water Equations (SWE) simulation with the implementation of the Lax-Wendroff Scheme in one dimension using Dam Break as a case study, this numerical method is one solution for hyperbolic partial differential equations. In this final project, the scheme will be simulated and it will be seen how much accuracy of the scheme is for case studies such as Dam Break. Keywords: Shallow Water Equation, Lax-Wendroff, Dam Break.
Simulasi Numerik Propagasi Gelombang Soliter Pada Bentuk Pantai Komposit Indira Citra Widya; Didit Adytia
eProceedings of Engineering Vol 6, No 3 (2019): Desember 2019
Publisher : eProceedings of Engineering

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

Abstract

ABSTRAK Propagasi dan runup gelombang tsunami telah menjadi topik riset yang sangat menarik sekaligus menantang bagi peneliti dibidang pemodelan tsunami. Model gelombang dan implementasi numerik yang akurat namun efisien secara komputasi sangat diperlukan untuk mendesain suatu perangkat lunak untuk sistem peringatan dini tsunami. Tsunami pada umumnya adalah gelombang panjang sehingga untuk mempelajari propagasi gelombang tsunami, biasanya gelombang tsunami diasumsikan sebagai gelombang soliter. Pada artikel ini, akan digunakan model gelombang nonlinear, non-dispersif Shallow Water Equations (SWE). Model ini diimplementasikan secara numerik dengan metode Finite Volume dengan skema numerik staggered grid. Model dan implementasi numerik ini akan digunakan untuk mempelajari propogasi gelombang tsunami pada bentuk pantai yang kompleks, yaitu bentuk komposit. Keakuratan dari implementasi numerik di validasi dengan data eksperimen dari laboratorium hidrodinamika. Terdapat tiga kasus yang dilakukan, yaitu propagasi gelombang soliter pada dasar rata, dan propagasi gelombang soliter tidak pecah dan pecah pada bentuk pantai komposit. Hasil perbandingan menunjukkan bahwa hasil implementasi numerik bersesuaian dengan hasil dari eksperimen. Kata kunci: Tsunami, gelombang soliter, finite volume, skema staggered grid, Shallow Water Equations ABSTRACT Propagation and runup of tsunami wave have been an interesting and challenging research topics for many researchers in a field of tsunami modelling. Wave model and its numerical implementation that is accurate as well as effisien in computation is needed in designing a software for tsunami early warning system. Tsunami in general, is categorized as a long wave, therefore to study the tsunami wave, the tsunami usually is assumed as a solitary wave. In this paper, we use the nonlinear, non-dispersive Shallow Water Equations (SWE) as the wave model. The model is implemented numerically by using finite volume method in a staggered grid scheme. The model and its numerical implementation is used to study the propagation of tsunami wave on a complex bathymetry, i.e. a composite beach. The accuracy of the numerical implementation is validated by comparing results of simulations with available experimental data from hydrodynamic laboratory. There are test three cases that are investigated, i.e. solitary wave propagation above a flat bottom, and propagation of non-breaking and breaking solitary wave above a composite beach. Results of comparison show a good agreement between numerical simulation with experimental data. Keywords: Tsunami, solitary wave, finite volume, staggered grid, Shallow Water Equations
Implementation of CRNN Method for Lung Cancer Detection based on Microarray Data Azka Khoirunnisa; - Adiwijaya; Didit Adytia
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1339

Abstract

Lung Cancer is one of the cancer types with the most significant mortality rate, mainly because of the disease's slow detection. Therefore, the early identification of this disease is crucial. However, the primary issue of microarray is the curse of dimensionality. This problem is related to the characteristic of microarray data, which has a small sample size yet many attributes. Moreover, this problem could lower the accuracy of cancer detection systems. Various machines and deep learning techniques have been researched to solve this problem. This paper implemented a deep learning method named Convolutional Recurrent Neural Network (CRNN) to build the Lung Cancer detection system. Convolutional neural networks (CNN) are used to extract features, and recurrent neural networks (RNN) are used to summarize the derived features. CNN and RNN methods are combined in CRNN to derive the advantages of each of the methods. Several previous research uses CRNN to build a Lung Cancer detection system using medical image biomarkers (MRI or CT scan). Thus, the researchers concluded that CRNN achieved higher accuracy than CNN and RNN independently. Moreover, CRNN was implemented in this research by using a microarray-based Lung Cancer dataset. Furthermore, different drop-out values are compared to determine the best drop-out value for the system. Thus, the result shows that CRNN gave a higher accuracy than CNN and RNN. The CRNN method achieved the highest accuracy of 91%, while the CNN and RNN methods achieved 83% and 71% accuracy, respectively.
Forecasting of GPU Prices Using Transformer Method Risyad Faisal Hadi; Siti Saadah; Diditq Adytia
eProceedings of Engineering Vol 10, No 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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

Abstract

Abstract— GPU or VGA (graphic processing unit) is a vital component of computers and laptops, used for tasks such as rendering videos, creating game environments, and compiling large amounts of code. The price of GPU/VGA has fluctuated significantly since the start of the COVID19 pandemic in 2020. This research aims to forecast future GPU prices using deep learning-based time series forecasting using the Transformer model. We use daily prices of NVIDIA RTX 3090 Founder Edition as a test case. We use historical GPU prices to forecast 8, 16, and 30 days. Moreover, we compare the results of the Transformer model with two other models, RNN and LSTM. We found that to forecast 30 days; the Transformer model gets a higher coefficient of correlation (CC) of 0.8743, a lower root mean squared error (RMSE) value of 34.68, and a lower mean absolute percentage error (MAPE) of 0.82 compared to the RNN and LSTM model. These results suggest that the Transformer model is an effective and efficient method for predicting GPU prices.Keywords— GPU, Transformer, Forecasting, Time Series Forecasting
Water Level Time Series Forecasting Using TCN Study Case in Surabaya Deni Saepudin; Egi Shidqi Rabbani; Dio Navialdy; Didit Adytia
JOIN (Jurnal Online Informatika) Vol 9 No 1 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i1.1312

Abstract

Climate change is causing water levels to rise, leading to detrimental effects like tidal flooding in coastal areas. Surabaya, the capital of East Java Province in Indonesia, is particularly vulnerable due to its low-lying location. According to the Meteorological, Climatological, and Geophysical Agency (BMKG), tidal flooding occurs annually in Surabaya as a result of rising water levels, highlighting the urgent need for water level forecasting models to mitigate these impacts. In this study, we employ the Temporal Convolutional Network (TCN) machine learning model for water level forecasting using data from a sea level station monitoring facility in Surabaya. We divided the training data into three scenarios: 3, 6, and 8 months to train TCN models for 14-day forecasts. The 8-month training scenario yielded the best results. Subsequently, we used the 8-month training data to forecast 1, 3, 7, and 14 days using TCN, Transformers, and the Recurrent Neural Network (RNN) models. TCN consistently outperformed other models, particularly excelling in 1-day forecasting with coefficient of determination () and RMSE values of 0.9950 and 0.0487, respectively.
Forecasting of GPU Prices Using Transformer Method Hadi, Risyad Faisal; Sa'adah, Siti; Adytia, Didit
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 1 (2023): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i1.1569

Abstract

GPU or VGA (graphic processing unit) is a vital component of computers and laptops, used for tasks such as rendering videos, creating game environments, and compiling large amounts of code. The price of GPU/VGA has fluctuated significantly since the start of the COVID-19 pandemic in 2020, due in part to the increased demand for GPUs for remote work and online activities. Furthermore, accurate GPU price forecasting can have broader implications beyond the computer hardware industry, with potential applications in investment decision-making, production planning, and pricing strategies for manufacturers. This research aims to forecast future GPU prices using deep learning-based time series forecasting using the Transformer model. We use daily prices of NVIDIA RTX 3090 Founder Edition as a test case. We use historical GPU prices to forecast 8, 16, and 30 days. Moreover, Transformer we compare the results of the Transformer model with two other models, RNN and LSTM. We found that to forecast 30 days; the Transformer model gets a higher coefficient of correlation (CC) of 0.8743, a lower root mean squared error (RMSE) value of 34.68, and a lower mean absolute percentage error (MAPE) of 0.82 compared to the RNN and LSTM model. These results suggest that the model is an effective and efficient method for predicting GPU prices.
Wave Downscaling Approach with TCN model, Case Study in Bengkulu, Indonesia Navialdy, Dio; Adytia, Didit
JOIN (Jurnal Online Informatika) Vol 9 No 2 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i2.1329

Abstract

When conducting marine operations that rely on wave conditions, such as maritime trade, the fishing industry, and ocean energy, accurate wave downscaling is important, especially in coastal locations with complicated geometries. Traditional approaches for wave downscaling are usually obtained by performing nested simulations on a high-resolution local grid from global grid information. However, this approach requires high computation resources. In this paper, to downscale global wave height data into a high-resolution local wave height with less computation resources, we propose a machine learning-based approach to downscaling using the Temporal Convolutional Network (TCN) model. To train the model, we obtain the wave dataset using the SWAN model in a local domain. The global datasets are taken from the ECMWF Reanalysis (ERA-5) and used to train the model. We choose the coastal area of Bengkulu, Indonesia, as a case study. The  results of TCN are also compared with other models such as LSTM and Transformers. It showed that TCN demonstrated superior performance with a CC of 0.984, RMSE of 0.077, and MAPE of 4.638, outperforming the other models in terms of accuracy and computational efficiency. It proves that our TCN model can be alternative model to downscale in Bengkulu’s coastal area.
Menjembatani Teknologi dan Spiritualitas: Pengenalan Artificial Intelligence di Pondok Pesantren melalui Workshop Kolaboratif Sulistiyo, Mahmud Dwi; Adytia, Didit; Baizal, Z.K. Abdurahman; Mohamed, Raihani; Zamani, Nabila Wardah; Sharef, Nurfadhlina Mohd
I-Com: Indonesian Community Journal Vol 5 No 3 (2025): I-Com: Indonesian Community Journal (September 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i3.7799

Abstract

Pesantren sebagai lembaga pendidikan berbasis keagamaan memiliki tantangan dalam mengakses perkembangan teknologi terbaru seperti Artificial Intelligence (AI). Menjawab kebutuhan ini, tim pengabdian dari Telkom University menyelenggarakan workshop pengenalan AI dan mengundang sivitas Pondok Pesantren Modern Assuruur. Kegiatan ini bertujuan untuk meningkatkan literasi digital para santri melalui pengenalan konsep dasar AI dan pemanfaatannya dalam pembelajaran Al-Qur’an. Workshop dilakukan secara hybrid bersama narasumber dari Telkom University dan Universiti Putra Malaysia (UPM), mencakup pretest, materi inti, praktik aplikasi Tarteel, dan posttest. Hasil evaluasi menunjukkan peningkatan skor pemahaman peserta dari rata-rata 93,97 menjadi 98,10, disertai penurunan standar deviasi dari 14,50 menjadi 5,88. Kegiatan ini membuktikan bahwa pendekatan yang kontekstual dan aplikatif mampu meningkatkan pemahaman santri terhadap teknologi modern serta membuka peluang integrasi AI dalam pendidikan Islam.
Co-Authors Adiwijaya Alif Rizal Yonanta Alifa Puspa Yuninda Andonowati Andonowati Aniq Atiqi Rohmawati Annas Wahyu Ramadhan Arionmaro Asi Simaremare Arkan Priya Anggana Hadna Arnida Lailatul Latifah Azka Khoirunnisa Cornelius Stephanus Alfredo Dede Tarwidi Deni Saepudin Derry Destian Dio Navialdy E. van Groesen Egi Shidqi Rabbani Faishal Rasyid Fakhrurroja, Hanif Fhira Nhita Four Saputra BM Hadi, Risyad Faisal Huda Bachtiar I Putu Samskerta Indira Citra Widya Indra A Aditya Isman Kurniawan Kemas Muslim Lhaksmana Leo Sembiring Lukman Hardian Mahmud Dwi Sulistiyo Mohamed, Raihani Muhammad Adzhar Amrullah Muhammad Rafiuddin Navialdy, Dio Nopendri Nopendri Novalianda Jeriano Nugrahinggil Subasita Putu Harry Gunawan R. Fajrika hadnis Putra Radika Rafif Gibran Rasyadan Farouq Riam Badriana Risyad Faisal Hadi sa'adah, siti Semeidi Husrin Semeidi Husrin Seno Adi Putra Setyorini Setyorini Sharef, Nurfadhlina Mohd Siti Saadah Tatang Mulyana Tien Fabrianti Kusumasari Widianto Soekarnen Zamani, Nabila Wardah ZK Abdurahman Baizal