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All Journal International Journal of Electrical and Computer Engineering KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal of Computing Science and Applied Mathematics Jurnal Teknologi Informasi dan Pendidikan Indonesian Journal of Electrical Engineering and Computer Science NUCLEUS: Jurnal Sains dan Teknologi Jurnal ComunitA Servizio
Prasetyo, Tegar Arifin
Information Technology, Faculty Of Vocational Studies, Institut Teknologi Del
Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation

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Pembuatan Website Kelompok Maduma Tani Samuel Sibuea; Fritz Marpaung; Lawy Xenna; Tegar Arifin; Rudy Chandra; Asido Saragih
JURNAL Comunità Servizio : Jurnal Terkait Kegiatan Pengabdian kepada Masyarakat, terkhusus bidang Teknologi, Kewirausahaan dan Sosial Kemasyarakatan Vol. 5 No. 2 (2023): OKTOBER
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM), Univesitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/cs.v5i2.5010

Abstract

Sipituhuta Village is one of the villages in Pollung District which has commodities in the agricultural sector. In 2016 a farmer group called the Maduma Tani Group was established as a means for sustainable agriculture to increase income. This farmer group provides farming tools that can be borrowed by farmers. However, the lack of information about the availability of farming tools and education on agricultural processing causes the process of borrowing tools and seeking agricultural processing education is still manual. The use of the website is one of the solutions in the field of information technology that helps increase farmers' knowledge in solving agricultural problems they face and borrowing farming tools in Sipituhuta Village. The development of this website uses the prototyping method, where this method is very suitable for building small-scale and customized websites that are created based on certain requests and needs. Website development using the PHP programming language, Laravel framework, and MySQL Database Management System (DBMS). Some of the features that have been successfully developed include lending tools, viewing history of tool lending, viewing education, viewing farming projects, viewing notifications. The result of this activity is that farmers in Sipituhuta Village can easily find information about agriculture and borrow farming tools. Website testing is done using the black box method. The test results show that the website that was built has been successfully running according to its function.
Development of DelTalk (an English learning application) using Agile Method Tegar Arifin Prasetyo; Monalisa Pasaribu; Tiurma Lumban Gaol; Togu Novriansyah Turnip; Juli Yanti Damanik; Andree Panjaitan; Mei Pane; Nathan Fernando Lumban Tobing; Lilis Marito Pardosi; Timothy Timothy; Yohana Sihombing
Jurnal Teknologi Informasi dan Pendidikan Vol 16 No 1 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i1.662

Abstract

English has become a world language that must be mastered by many people because English has dominated the era of communication to connect and transfer knowledge to the entire world. When it comes to the development of mobile applications for language learning, previous research has tended to emphasize testing on various technologies such as multimedia, virtual and augmented reality, conversational agents and artificial intelligence-based systems. This research, therefore, aimed to develop a mobile-based English learning application that provided English learning in the form of stories called the Deltalk. This mobile-based English learning application provides features in which the users can practice their speaking in English. This app was developed by integrating ASR (Automatic Speech Recognition) technology provided by NOVO Learning. The ASR was integrated with Deltalk through the API (Application Programming Interface) and Websocket. Deltalk development adapted two agile frameworks, including Scrum and Lean Software Development by performing MVP process one time.
Design and Implementation of the Shortest Path Navigation in Samosir District using Branch and Bound Algorithm Rudy Chandra; Tegar Arifin Prasetyo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5585

Abstract

Samosir has a large area and several tourist attractions, making it difficult for visitors to explore the island. Unknowing the route can make the journey less fun and waste time. In general, tourists seek to know the fastest way to a tourist location to save time and money while on vacation. As a result, we require an application that will offer directions to the shortest path. This research aims to develop a web-based application that may display a map of the shortest travel to a tourist site. This website will display a map that marks the route from the origin point to the destination point. The Branch and Bound algorithm is used to determine the shortest path. The Python libraries OSMnx, Folium, and NetworkX modify paths and show a route map with OpenStreetMap. The error value of the distance between the branch, the bound algorithm, and Google Maps is used to obtain the RMSE accuracy value. The RMSE value is 3.02 and the MAPE value is 0.0023 indicating that the application produced already has a good implementation prototype. Furthermore, there is no significant distinction between the appearance of maps that implement OpenStreetMap and Google Maps.
Evaluating the efficacy of univariate LSTM approach for COVID-19 data prediction in Indonesia Tegar Arifin Prasetyo; Joshua Pratama Silitonga; Matthew Alfredo; Risky Saputra Siahaan; Roberd Saragih; Dewi Handayani; Rudy Chandra
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1353-1366

Abstract

The coronavirus disease 2019 (COVID-19) pandemic, originating in 2020, has emerged as a critical global issue due to its rapid and widespread transmission. Indonesia, among the affected nations, has taken measures to address the situation, including the development of a deep learning model for predicting future COVID-19 infection and spread. This predictive tool serves as a valuable reference for the government and stakeholders, aiding them in making informed decisions and implementing appropriate measures to contain the virus. The deep learning model employs the long short-term memory (LSTM) algorithm, chosen for its ability to recognize temporal patterns in the country’s COVID-19 data. The model creation process involves data collection, preprocessing, model architecture planning, modeling, training, and evaluation. Two LSTM models were developed: a univariate and a multivariate model. Following thorough training and evaluation, the univariate model emerged as the superior choice, boasting evaluation metrics of 16.72 for mean absolute percentage error (MAPE) and 66.36 for root mean squared error (RMSE). This model was then deployed on a publicly accessible website, presenting visualizations of past COVID-19 data and predictions of future cases through line graphs. This user-friendly platform enables the public to access and analyze the data easily.
Refining tomato disease recognition: hyperparameter tuning on ResNet-101 architecture for precise leaf-based classification Tegar Arifin Prasetyo; Tiurma Lumban Gaol; Nico Felix Sipahutar; Tessalonika Siahaan; Trito Exaudi Manik; Rudy Chandra
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1204-1213

Abstract

Tomatoes plants are widely recognized as versatile vegetables globally. This study aims to develop a high-precision web interface for classifying various leaf diseases in tomatoes. Utilizing a convolutional neural network (CNN) algorithm using the residual network-101 (ResNet-101) architecture, this tool aids farmers in accurately identifying leaf diseases in tomatoes, thereby reducing the risk of crop failure. The dataset comprises 6,800 images, categorized into four classes: early blight, spider mites two spotted, tomato yellow leaf curl virus, and healthy tomatoes, each containing 1,700 images. Hyperparameter tuning was conducted as part of an experiment aimed at enhancing the performance of the model. Experiments involved varying epoch values (10, 25, 30, 50, 60, 75, 100, and 110), a fixed batch size of 4, different learning rates (0.1, 0.01, 0.001, 0.0001), and num workers (4, 8, 16). The results demonstrated an accuracy of 99% with 100 epochs, a batch size of 4, a learning rate of 0.001, and 16 num workers. Consequently, this research contributes to a deeper understanding of disease management in tomato plants, ensuring optimal quality and quantity of the harvest.
Penerapan Website untuk Digitalisasi dan Pengembangan Bisnis di Usaha Pemandian Air Panas Karunia Sipoholon Rudy Chandra; Tegar Arifin Prasetyo; Tahan HJ Sihombing; Juan Carlos Munthe; Christian Benedict Lumbantoruan; Dame Sisri Haryati Katarina Rumapea; Herbeth Augustinus Napitupulu
JURNAL Comunità Servizio : Jurnal Terkait Kegiatan Pengabdian kepada Masyarakat, terkhusus bidang Teknologi, Kewirausahaan dan Sosial Kemasyarakatan Vol. 6 No. 1 (2024): APRIL
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM), Univesitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/cs.v6i1.5297

Abstract

Traveling is an activity that people do to unwind from their daily routines. There are many types of travel destinations, and one of them is a natural hot spring located in Situmeang Habinsaran Village, Sipoholon District, North Tapanuli. Besides being a tourist destination, natural hot springs are believed to have the ability to cure various skin diseases and promote healthier skin. The owner of the Karunia hot spring business is one of the entrepreneurs who provide hot spring baths, accommodations/homestays, and a restaurant. This business opportunity has become more competitive with many similar ventures opening up. Marketing and promoting this natural attraction continues. As time goes by, the promotion and business systems need to be enhanced by using information technology to improve. A website is one of the means for promotion and branding, enabling the digitization of the established business. Building a website is applied for promotional purposes and to enhance credibility with the public, making them more familiar with the hot spring tourism in Sipoholon, especially Karunia hot spring. The website also serves as a centralized platform for financial management, cash flow, and business operations, which have previously been done manually. The goal of creating this website is for partners to increase income and improve business branding
Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm Rudy Chandra; Tegar Arifin Prasetyo; Heni Ernita Lumbangaol; Veny Siahaan; Johan Immanuel Sianipar
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.v9i1.1296

Abstract

Caladium is a popular ornamental plant and has business potential. However, difficulties in recognizing the type of Caladium often occur because of the similarities in shape, pattern, and color of the leaves between the different kinds of Caladium. To overcome this problem, research will use machine learning with the Convolutional Neural Network (CNN) algorithm to build a mobile application that can accurately classify four types of Caladiums. The data set used is 1200 data with four classes; each class has 300 data. The best model is found with the parameter epoch 100, learning rate 0.001, and batch size 64. The model is then implemented in a mobile application with two menus, "Take a photo" and "Choose an image," which will display the classification output and confidence values of the four types of Caladiums. Testing with 30 test data per class achieves 0.975 accuracy on both menus. On the “Take a photo” menu, precision is 0.974, recall is 0.9725, and f1-score is 0.965. Meanwhile, on the “Choose an image” menu a precision and recall value is 0.975, and f1-score value of 0.97.
Co-Authors Andree Panjaitan Asido Saragih Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Dewi Handayani Ester Saulina Hutabarat Evan Richardo Sianipar Fritz Marpaung Goklas Henry Agus Panjaitan Heni Ernita Lumbangaol Henny Flora Panjaitan Herbeth Augustinus Napitupulu Johan Immanuel Sianipar Joshua Pratama Silitonga Juan Carlos Munthe Juli Yanti Damanik Lawy Xenna Lilis Marito Pardosi Matthew Alfredo Mei Pane Muhammad Isnaini Hadiyul Umam Muhammad Luthfi Hamzah Muhammad Rizki Nathan Fernando Lumban Tobing Nazaruddin Nazaruddin Nico Felix Sipahutar Pasaribu, Monalisa Poibe Leny Naomi Risky Saputra Siahaan Roberd Saragih Romauli Sianipar Rudy Chandra Rudy Chandra Samuel Sibuea Sarbaini Sarbaini SIAGIAN, WESLY MAILANDER Tahan HJ Sihombing Tahan HJ Sihombing Tessalonika Siahaan Timothy Timothy Tiurma Lumban Gaol Togu Novriansyah Turnip Trito Exaudi Manik Veny Siahaan Victor Lambok Desrony Yohana Sihombing Yohanssen Pratama