Garuda - Garba Rujukan Digital

Analysis Sentiment Based on IMDB Aspects from Movie Reviews using SVM Ramadhan, Nur Ghaniaviyanto; Ramadhan, Teguh Ikhlas
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 1 (2021): Article Research Volume 6 Issue 1: January 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i1.11204

A movie is a spectacle that can be done at a relaxed time. Currently, there are many movies that can be watched via the internet or cinema. Movies that are watched on the internet are sometimes charged to watch so that potential viewers before watching a movie will read comments from users who have watched the movie. The website that is often used to view movie comments today is IMDB. Movie comments are many and varied on the IMDB website, we can see comments based on the star rating aspect. This causes users to have difficulty analyzing other users' comments. So, this study aims to analyze the sentiment of opinions from several comments from IMDB website users using the star rating aspect and will be classified using the support vector machine method (SVM). Sentiment analysis is a classification process to understand the opinions, interactions, and emotions of a document or text. SVM is very efficient for many applications in science and engineering, especially for classification (pattern recognition) problems. In addition to the SVM method, the TF-IDF technique is also used to change the shape of the document into several words. The results obtained by applying the SVM model are 79% accuracy, 75% precision, and 87% recall. The SVM classification is also superior to other methods, namely logistic regression.

Implementasi Metode User Centered Design (UCD) dengan Framework Kanban dalam Membangun Desain Interaksi Rudi Hartono; Teguh Ikhlas Ramadhan
Jurnal Algoritma Vol 19 No 2 (2022): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.19-2.1203

Interaction design is now widespread in product and service development. Various software developers are competing to create applications that can provide a pleasant experience for their users. This has an impact on user loyalty in using an application which is a challenge for developers to continuously improve quality and provide user experience so that it can be easily and easily understood how the flow of the application flows properly. The purpose of this research is how to apply the User Centered Design (UCD) method with the Kanban framework in designing an interaction design that suits user needs so that users can easily understand and use the application. In achieving the objectives of the research, the User-Centered Design (UCD) method was applied where this method focuses on a design by directly involving users in system development activities. In addition, a framework was created using a kanban as a monitoring process during the research. The conclusion of this study is that the application of interaction design using the UCD method and the Kanban framework can create an easy-to-use interaction design.

Implementasi Metode User Centered Design (UCD) dengan Framework Kanban dalam Membangun Desain Interaksi Rudi Hartono; Teguh Ikhlas Ramadhan
Jurnal Algoritma Vol 19 No 2 (2022): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.19-2.1203

Interaction design is now widespread in product and service development. Various software developers are competing to create applications that can provide a pleasant experience for their users. This has an impact on user loyalty in using an application which is a challenge for developers to continuously improve quality and provide user experience so that it can be easily and easily understood how the flow of the application flows properly. The purpose of this research is how to apply the User Centered Design (UCD) method with the Kanban framework in designing an interaction design that suits user needs so that users can easily understand and use the application. In achieving the objectives of the research, the User-Centered Design (UCD) method was applied where this method focuses on a design by directly involving users in system development activities. In addition, a framework was created using a kanban as a monitoring process during the research. The conclusion of this study is that the application of interaction design using the UCD method and the Kanban framework can create an easy-to-use interaction design.

Implementation of Neural Machine Translation for English-Sundanese Language using Long Short Term Memory (LSTM) Ramadhan, Teguh Ikhlas; Ramadhan, Nur Ghaniaviyanto; Supriatman, Agus
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2614

In this modern era, machine translation has been used all over the world for solving humankind’s problems such as it deals with language. Machine translation is almost used by people who want to translate their native language into their foreign language. The international language being used is the English language. Machine translation is the task to translate a source language to another language. The input of it is a word or a sentence from the source language and it will be translated into another language. The input of it is a word or a sentence from the source language and it will be translated into another language. There are many purposes for using machine translation such as learning another language, communicating, finding a certain or better word to use, and even writing something in a book or another article. Several methods have been conducted to do the machine translation task such as the statistical approach and the neural approach In terms of Sundanese machine translation, there are several methods or several approaches that other researchers have conducted. However the study about Sundanese machine translation, none of the research conducted the English into Sundanese language. In this study using the encoder and decoder LSTM architecture achieve a good result regarding building a model for machine translation task. The performance of this model has achieved 0.99 accuracies in both training and testing as well as less than 0.1 loss value to both training and testing data. This model also achieves more than 0.8 average BLEU score for both training and testing data.

Neural Machine Tranlation Untuk Bahasa Sunda Loma – Sunda Halus Menggunakan Long Short Term Memory Sakinah, Marsela Arsya; Ramadhan, Teguh Ikhlas; Hartono, Rudi
Jurnal Komputer Antartika Vol. 2 No. 1 (2024): Maret 2024
Publisher : Antartika Media Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70052/jka.v2i1.244

Bahasa Sunda, dengan kompleksitas undak-usuk basa, memiliki peran penting dalam komunikasi di Jawa Barat, Indonesia. Mesin penerjemah Bahasa Sunda Loma ke Bahasa Sunda Halus menjadi tantangan karena penggunaan kata harus tepat sesuai konteksnya. Mesin ini penting sebagai alat pembelajaran Bahasa Sunda, mengingat banyaknya generasi yang kehilangan pemahaman terhadap bahasa daerah. Neural Machine Translation (NMT), terutama dengan model Long Short Term Memory (LSTM), menjadi solusi yang menjanjikan. Penelitian ini bertujuan mengimplementasikan LSTM dalam penerjemah Bahasa Sunda, tetapi penelitian terbaru masih kurang. Hasil penelitian menunjukkan bahwa optimizer ADAM pada dataset duplikat menghasilkan akurasi terbaik, meskipun masih ada evaluasi yang kurang baik. Mesin penerjemah ini diharapkan dapat membantu pelestarian Bahasa Sunda di era digital. Evaluasi BLEU score menunjukkan kualitas terjemahan yang rendah pada dataset asli dan dataset duplikat dengan optimizer RMS, sementara dengan optimizer ADAM menunjukkan peningkatan signifikan, terutama pada dataset duplikat. Meskipun demikian, masih ditemukan evaluasi yang kurang baik pada dataset yang diduplikat. Sundanese, with its intricate speech levels, holds a pivotal role in West Java's communication. Translating from Loma to Formal Sundanese poses challenges due to precise contextual word usage. Crucial for Sundanese language preservation, a Neural Machine Translation (NMT) system using Long Short Term Memory (LSTM) models emerges promising, yet current research is limited.This study aims to implement LSTM in Sundanese translation, focusing on the ADAM optimizer's efficacy on duplicate datasets. While ADAM yields the highest accuracy, some evaluations remain suboptimal. The translation engine's role is vital in preserving Sundanese in the digital era. BLEU score evaluations show low translation quality with RMS and significant improvements with ADAM, especially in duplicates. However, deficiencies persist, notably in duplicated datasets. This endeavor addresses the decline in regional language comprehension among younger generations, fostering Sundanese language education.

Evaluasi dan Implementasi Indobert Question Answering (QA) pada Domain Spesifik Menggunakan Mean Reciprocal Rank Ramadhan, Teguh Ikhlas; Supriatman, Agus; Kurniawan, Taufik Rahmat
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1542

Applications of artificial intelligence, such as Chat-GPT and Bard, have become common in various aspects of life today. One of the main aspects is the use of the Question Answering (QA) model to meet specific domain needs. However, in some cases, models like Bard may not be able to provide specific information, such as registration procedures at a particular company or lecturer schedules at a university. To overcome this challenge, an Indonesian QA model called IndoBERT-QA has been developed. This research aims to evaluate the capabilities of IndoBERT-QA in a specific domain context using the Mean Reciprocal Rank (MRR) evaluation method. The evaluation results show that the IndoBERT-QA model is able to achieve an MRR of 0.91 with an approach to creating a customized context for each question. These results indicate that this model has good performance in providing relevant answers. The benefit of this research is that it serves as a valuable reference for the development of QA systems that will be created by other parties in the same environment. By utilizing a well-tested and evaluated approach, this research provides a strong foundation for the development of a high-performance QA system in Indonesian, so that it can meet domain-specific needs. Besides that, this research also provides insights for further development. One approach that can be explored is the use of Information Retrieval or Passage Retrieval as an initial step in the QA process. This can help the model in getting more precise and relevant context, thereby allowing further improvement in the quality of the answers provided by the model. Index Terms-BERT, Mean Reciprocal Rank, Question Answering However, this research also provides insights for further development. One approach that can be explored is the use of Information Retrieval or Passage Retrieval as an initial step in the QA process. This can help the model in getting more precise and relevant context, thereby allowing further improvement in the quality of the answers provided by the model.

Evaluasi dan Implementasi Indobert Question Answering (QA) pada Domain Spesifik Menggunakan Mean Reciprocal Rank Ramadhan, Teguh Ikhlas; Supriatman, Agus; Kurniawan, Taufik Rahmat
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1542

Applications of artificial intelligence, such as Chat-GPT and Bard, have become common in various aspects of life today. One of the main aspects is the use of the Question Answering (QA) model to meet specific domain needs. However, in some cases, models like Bard may not be able to provide specific information, such as registration procedures at a particular company or lecturer schedules at a university. To overcome this challenge, an Indonesian QA model called IndoBERT-QA has been developed. This research aims to evaluate the capabilities of IndoBERT-QA in a specific domain context using the Mean Reciprocal Rank (MRR) evaluation method. The evaluation results show that the IndoBERT-QA model is able to achieve an MRR of 0.91 with an approach to creating a customized context for each question. These results indicate that this model has good performance in providing relevant answers. The benefit of this research is that it serves as a valuable reference for the development of QA systems that will be created by other parties in the same environment. By utilizing a well-tested and evaluated approach, this research provides a strong foundation for the development of a high-performance QA system in Indonesian, so that it can meet domain-specific needs. Besides that, this research also provides insights for further development. One approach that can be explored is the use of Information Retrieval or Passage Retrieval as an initial step in the QA process. This can help the model in getting more precise and relevant context, thereby allowing further improvement in the quality of the answers provided by the model. Index Terms-BERT, Mean Reciprocal Rank, Question Answering However, this research also provides insights for further development. One approach that can be explored is the use of Information Retrieval or Passage Retrieval as an initial step in the QA process. This can help the model in getting more precise and relevant context, thereby allowing further improvement in the quality of the answers provided by the model.

Design of A Soil Moisture and pH Monitoring System for Tomato Plants Barki, Yori Saepul; Ramadhan, Teguh Ikhlas; Supriatman, Agus
Jurnal Prajaiswara Vol. 5 No. 3 (2024): Desember 2024
Publisher : Badan Pengembangan Sumber Daya Manusia (BPSDM) Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55351/prajaiswara.v5i3.125

In this era of globalization, many farmers are still less intensive in monitoring the growth period of their plants because tomato plants require an adaptation process to the environment and are very sensitive to soil moisture and soil pH. One of them is a Soil Humidity and pH Monitoring System to help farmers increase the harvest success rate of tomato plants. This monitoring system can provide quick information regarding soil moisture and pH conditions which can be monitored via gadget using the Telegram Bot. This soil control must have a pH of around 5-7 and humidity of around 60-80%. Detection of pH and humidity in soil using Soil Moisture and Soil pH sensors. This monitoring system is designed using Arduino Uno and NodeMCU as microcontrollers. With this pH and soil moisture monitoring system for tomato plants, soil conditions can be maintained and controlled easily because it can be done via Telegram Bot.

Passage Retrieval untuk Question Answering Bahasa Indonesia Menggunakan BERT dan FAISS Ramadhan, Teguh Ikhlas; Supriatman, Agus; Kurniawan, Taufik Rahmat
Jurnal Algoritma Vol 21 No 2 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-2.2100

This research develops a passage retrieval model for a Question Answering (QA) application in the Indonesian language, focusing on a specific domain. The model leverages BERT embedding techniques and the Faiss index to enhance the efficiency and accuracy of finding answers to user queries, with a particular focus on a text corpus related to Universitas Perjuangan Tasikmalaya. The evaluation was conducted on 80 questions, encompassing various informational aspects within the corpus. Results indicate an average execution time of 0.23 seconds per question and a total processing time of 18.8 seconds for all queries, achieving an accuracy rate of 43.75%. Accuracy was generally higher when the questions contained terms that exactly matched those in the corpus. While the initial findings are promising, the accuracy remains suboptimal and warrants further improvement. Potential areas for optimization include employing alternative embedding techniques, refining passage formation methods, and enhancing search performance using a cross-encoder. This research contributes to accelerating the retrieval process and improving the relevance of results for QA applications within specific domains.

Design of A Soil Moisture and pH Monitoring System for Tomato Plants Barki, Yori Saepul; Ramadhan, Teguh Ikhlas; Supriatman, Agus
Jurnal Prajaiswara Vol. 5 No. 3 (2024): Desember 2024
Publisher : Badan Pengembangan Sumber Daya Manusia (BPSDM) Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55351/prajaiswara.v5i3.125

In this era of globalization, many farmers are still less intensive in monitoring the growth period of their plants because tomato plants require an adaptation process to the environment and are very sensitive to soil moisture and soil pH. One of them is a Soil Humidity and pH Monitoring System to help farmers increase the harvest success rate of tomato plants. This monitoring system can provide quick information regarding soil moisture and pH conditions which can be monitored via gadget using the Telegram Bot. This soil control must have a pH of around 5-7 and humidity of around 60-80%. Detection of pH and humidity in soil using Soil Moisture and Soil pH sensors. This monitoring system is designed using Arduino Uno and NodeMCU as microcontrollers. With this pH and soil moisture monitoring system for tomato plants, soil conditions can be maintained and controlled easily because it can be done via Telegram Bot.

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