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Djoni Haryadi Setiabudi
Program studi Teknik Informatika, Universitas Kristen Petra surabaya
Computer Science & IT

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Sistem Pakar Untuk Mendiagnosa Infeksi Mikroorganisme Pada Anak Menggunakan Metode Forward Chaining William Tupan; Djoni Haryadi Setiabudi; Andreas Handojo
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Infectious diseases caused by microorganisms such as viruses, bacteria, fungi, and worms are very vulnerable to attack children, this is caused by a lack of self-awareness to maintain personal and environmental hygiene and the immune system that exists in children's bodies that have not been fully developed.  Lack of knowledge makes parents also unable to recognize the symptoms of diseases suffered by children that arise due to infection with these microorganisms.This expert system was created to diagnose diseases in children caused by microorganisms such as viruses, bacteria, fungi, and worms.  From this expert system information can be obtained about the name of the disease, how to handle it and the level of confidence in the diagnosis.  This expert system uses the Forward Chaining method and the Certainty Factor method.The results of this system test show that the system is able to determine the disease, how to handle it, and is able to display the level of confidence in the system diagnosis, based on the symptoms previously selected by the user.
Analisis Sentimen Ulasan Restoran Menggunakan Metode Support Vector Machine Yoel Julianto; Djoni Haryadi Setiabudi; Silvia Rostianingsih
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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Reviews on restaurants on the internet have a huge impact on a restaurant. Reviews provided help other customers to evaluate the business or services provided from a  restaurant. Customers can leave positive or negative reviews. The large number of reviews from customers makes it difficult for restaurants to know if their restaurant has move positive or negative reviews. In this undergraduate thesis an application will be made to determine whether a restaurant has positive or negative reviews.Application that is equipped with text mining features will help restaurant in evaluate their restaurant. The steps taken are preprocessing which consist of case folding, tokenization, stopword removal, and stemming. Then the process of converting text data into vector using TF-IDF. Furthermore the data will be trained using Support Vector Machine which later will generate a model that will be used to make predictions from input data. The data which be used as training are Indonesian-language reviews from various restaurants.From this research conducted the result showed an accuracy of 93% and f1-score of 93%. To increase accuracy and f1-score values, classification model require TF-IDF parameters min_df  0.05, max_df  0.75, norm l2, n-gram (1, 2), linear SVM kernel with C 1. Besides TF-IDF and SVM parameters, the number of datasets can also increase confusion matrix and f1-score values.
Sistem Nomor Antrian Bantuan Sosial di BRILink Berbasis Web Studi Kasus BRILink Mingalvo Desa Hutumuri, Ambon Vitalona Crysantini Paays; Andreas Handojo; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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BRILink Mingalvo is located in Hutumuri Village, South Leitimur District, Ambon City. BRILink Mingalvo is a BRI agent that can assist the public in making withdrawal transactions, payments, and social assistance collection without the community having to go to BRI which is a long distance from where they live. At BRILink people who get social assistance must come first and queue to make transactions, of course this is inefficient and a waste of time for people who have to do other activities. Therefore, a queue application is required for social assistance collection on BRILink. An app that can be accessed by social assistance recipients wherever they are.This web-based application is created using the HTML, PHP, and MySQL database programming languages. The First create source code in sublime text 3, and continued by creating a database on MySQL. After the program is completed, Testing on users and admins for the application.The end result of the development of this application is that it can easily retrieve queue numbers, can view transactions in progress, and in the admin can add a social assistance retrieval schedule for the user.
Sistem Pakar Deteksi Penyakit Ikan Lohan Menggunakan Metode Forward Chaining Richard Alexander; Djoni Haryadi Setiabudi; Alexander Setiawan
Jurnal Infra Vol 10, No 1 (2022)
Publisher : Universitas Kristen Petra

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Flowerhorn care has different handling, where this can affects how to cultivate and how to treat it. Where if the treatment given is not good, the quality of the fish produced also decreases, which can greatly affect the selling price of the fish.The problem that the author want to solve is by utilizing an android application that functions to diagnose diseases that exist in flowerhorn by using an expert system based on the Forward Chaining Method to diagnose the symptoms that arise in flowerhorn fish.The test was carried out on a collection of interview data in the form of disease symptoms and the application made was able to diagnose flowerhorn with the results of the method test being able to achieve an accuracy value of 80%.
Analisis Sentimen Dari Keywords Yang Dimasukan Pengguna Di Twitter Indonesia Untuk Penunjang Pembelajaran Strategi Komunikasi Di Program Studi Ilmu Komunikasi Universitas Kristen Petra Dengan Metode Cnn-Bidirectional Lstm Andrianto Saputra Linardi Lie; Djoni Haryadi Setiabudi; Indar Sugiarto
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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To increase online media traffic, the first effort made by online media is to examine the trending phenomenon with the right marketing strategy. One of the methods that online media is used is a communication strategy that utilizes the sentiment analysis method. In reality, students of Communication Science Major at Petra Christian University are not optimally using sentiment analyst system because the sentiment analysis system for the Communication Studies Study Program (Netray) cannot be run by more than one student or is not used simultaneously and the price of the application is still not affordable if the students want to subscribe Netray. So a sentiment analysis system is needed to support the learning of the Communication Science Major at Petra Christian University. In previous related research, there was research that discussed the analysis of the #crowdfunding campaign on Twitter but there was not include sentiment analysis, there are only topological analysis, spatial analysis and others analysis. In addition, there are studies that use various deep learning methods of sentiment analysis, by researching CNN, DNN, RNN, Bi-Lstm, but none of them combine these methods. So it can be concluded that research will be made that analyzes sentiment analysis and combines deep learning methods. Sentiment analysis is the process of using text analytics to obtain various data sources from the internet and various social media platforms. Sentiment analysis can be utilized with artificial intelligence or with computing, because it is more efficient . Sentiment analysis can be complemented by methods from artificial intelligence systems, namely deep learning CNN-BILSTM. CNN-BILSTM is a combination of the two methods of CNN and bidirectional LSTM where CNN is the input layer and bidirectional LSTM is the layer that extracts features from the input. The dataset used in this application is retrieved from github by adopting the CC BY-NC (Common Creative Non Commercial) License. Data used in the deep learning model which contains a collection of Indonesian tweets containing neutral, positive, negative sentiments.From two testing this thesis using twitter as the online media. From the first test, 20 tweets were searched, the tweet contain "Shin tae yong” and yielded an accuracy of 30%. The second test was tested by 45 students of the Petra Christian University Communication Science Program at Petra Christian University Surabaya in the Q2.505 building where this application was tried and applied, after that the application was assessed with a satisfaction questionnaire which resulted in an average score of 4.01, so this application can meet the needs of the Petra Christian University Communication Science Program with the initial target of a satisfaction questionnaire of 3.75.
Adaptive Sparse Transformer untuk Meningkatkan ROUGE-1 Score pada Text Summarization Scientific Paper Andrew Firman Saputra; Liliana Liliana; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Technology advancement and internet causes lots of information that can be accessed at any time. Journal article is one of such many information that’s available that requires time to read thereof in need of automatic summary. Automatic Text Summarization (ATS) basically a process of making a new text that’s smaller than the original text without removing the meanings from the entire input text. The process of making automatic text summarization can be done in extractive and abstractive way. A summary that was made by an extractive method only able to generate a summary with a word that’s included in the original text, whereas summary that was made by an abstractive method can generate a summary that include word that does not exist in the original text. In the previous research in abstractive summarization is found is not optimal thereof need an improvement. The method used in this research is an abstractive summarization with Adaptive Sparse Transformer. Things that will be done in this research are scraping dataset arxiv machine learning, making the dataset, processing the data and trials on hyperparameter configuration in the model to see ROUGE-1 precision performance. The dataset used is Arxiv Scientific Paper dataset and Arxiv Scientific Paper+Machine Learning dataset. The results of this research showed that the method used capable to compete with state of the art methods with average R-1 precision score of 39.4 for Arxiv Scientific Paper+MachineLearning and 42.5 for Arxiv Scientific Paper.
Pengurangan Sampah Makanan dalam Bisnis Kuliner Menggunakan Konsep E-Marketplace pada Aplikasi Mobile Jessica Clarensia Suko; Djoni Haryadi Setiabudi; Justinus Andjarwirawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Food waste has a lot of negative impact on various aspects. The two biggest contributor of food waste are domestic food waste and food service food waste that come from foods that are unsold. There are a few mobile applications that help reducing food waste on a domestic level using food sharing between individuals, but it didn’t work effectively due to lack of trust. To resolve that, a mobile application with an e-marketplace concept will be created to reduce food waste that focuses on culinary businesses (food services) level. With e-marketplace concept, the individual who has the role to give the food to the consumers will be culinary businesses that used to make foods on day to day basis and have their own business reputation, so that hopefully it will increase the trust of the consumers on receiving leftover foods (unsold foods). The application was tested on two culinary businesses in Surabaya with the first culinary business being a small culinary business and not very well known by the public, while the second culinary business is a large and very well-known culinary business among the public. The result shows that the application can reduce food waste as much as 5% on the first culinary business, but the application has failed to reduce the food waste of the second culinary business. On the other hand, the application managed to increase the trust of the consumers on buying and accepting the leftover foods although there is culinary business that the consumers didn’t know before.
Sistem Pakar Diagnosa Penyakit Ikan Arwana dengan Menentukan Tingkat Kualitas Air Menggunakan Forward Chaining dan Simple Additive Weighting Kevin Christian; Djoni Haryadi Setiabudi; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

arwana fish always has its own charm for the people of Indonesia, as well as foreign countries. But every living thing must have been stricken with disease, including the arwana fish itself. Diseases in arwana are often not well identified by hobbyists and beginners because there are many parameters that must be considered. One of the problems in identifying arwana disease is the problem of the suitability of water parameters with arwana fish.            This expert system is equipped with Forward Chaining and Simple Additive Weighting methods. Forward Chaining allows the expert system to ask only the questions it needs. Simple Additive Weighting is used to determine the level of suitability of parameters in arwana fish. This method allows us to determine whether the water quality is suitable for the arwana fish by performing calculations based on the weight of the water parameters quickly.Tests were carried out by 2 experts on 20 arwana fish. The test results on the expert system for diagnosing arwana fish disease obtained an accuracy level of conformity with the expert with an accuracy value of 95%.
Sistem Pakar untuk Mendiagnosa Kerusakan pada Sepeda Motor Kawasaki KLX 150 Menggunakan Metode Forward Chaining dan Certainty Factor Maria Eve Angeline; Djoni Haryadi Setiabudi; Kartika Gunadi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

The Kawasaki KLX 150 is an all-road or dual sport motorcycle, which means it can be used on the road or off-road. Nowadayas dirt bike riders are not just crossers, ordinary people are starting to like dirt bikes to be used as daily vehicles. Dirt bikes have engines and various kinds of devices or parts that can be damaged or be problematic. The damage that often occurs on a dirt bike is considered trivial and not understood. Therefore, an expert system was created that can detect damage to the Kawasaki KLX 150 motorcycle, with the hope that this research can help replace the role of mechanics to diagnose damage based on the symptoms experienced. The expert system to diagnose damage to the Kawasaki KLX 150 will use the Forward Chaining method and the Certainty Factor method. The use of forward chaining method in this expert system is to collect facts obtained from users so that the system will produce conclusions. The use of Certainty Factor in this study is to provide a level of confidence from the results of system diagnosis in the form of metrics. From this expert system, it can provide information about the name of the damage, how to handle it and the level of confidence in the diagnosis. Application testing for the diagnosis of damage to the Kawasaki KLX 150, using real data with experts, resulted in a system accuracy of 90%. The application for the diagnosis of damage to the Kawasaki KLX 150 is also considered complete, accurate, appropriate and easy to use (user friendly) by the user.
Pewarnaan Otomatis Sketsa Gambar Menggunakan Metode Conditional GAN Untuk Mempercepat Proses Pewarnaan Regan Reinaldo Kalendesang; Liliana Liliana; Djoni Haryadi Setiabudi
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Anime is a Japanese animation that consists of many frames of images. Images that used to make an anime can be made using hand-drawn or using digital-drawn. It takes a lot of time to make an anime. In making anime for 1 second, it needs a total of 24 frames, this is why it takes a lot of time to make anime and also takes a lot of money. Each image also needs to be colored, this is also why making anime takes so much time. The method used in this research is GAN (Generative Adversarial Network) or should we call C-GAN (Conditional Generative Adversarial Network) to make coloring anime sketches easier. Dataset that is used in this research is a pair of sketch images and sketch images that have already been colored.
Co-Authors Abraham Imanuel Alexander Setiawan Alvin Nathaniel Tjondrowiguno Andreas Handojo Andrew Firman Saputra Andrianto Saputra Linardi Lie Cynthia Wijaya Hans Juwiantho Henry Novianus Palit Indar Sugiarto Jason Aldrian Jessica Clarensia Suko Justinus Andjarwirawan Kartika Gunadi Kevin Christian Liliana Liliana Maria Eve Angeline Regan Reinaldo Kalendesang Richard Alexander Silvia Rostianingsih Soni Marko Nathanniel Tannady Tania Sunyoto Vitalona Crysantini Paays William Tupan Wilson Mark Yoel Julianto