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Henry Novianus Palit
Program Studi Informatika
Computer Science & IT

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Feature Selection pada Phishing Detection dengan Menggunakan Parallel Genetic Algorithm dan Ensemble Learning Alles Sandro Oktavio Gandadireja; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Phishing sites could become a threat, which retrieves personal information without the user knowing this action. Every site has numerous records, which will be converted to features. Not all features extracted are relevant. Feature selection becomes the main topic of this case. This research uses Genetic Algorithm, using Ensemble Learning as fitness function. This process requires a lot of time, parallelization then used to improve the execution time of the system. The results show that with feature selection, an improvement could be obtained. Parallelization also helps improving execution time up to 2 times faster. Using this system, it is possible to improve the effectiveness of phishing detection.
Aplikasi Pendukung Diagnosis COVID-19 Yang Menganalisis Hasil X-Ray Paru-Paru Dengan Model EfficientNet Ananta Kusuma Pangkasidhi; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 9, No 2 (2021)
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In December 2019, a new type of corona virus was detected that had symptoms of pneumonia in the seafood market in Wuhan City, Hubei Province, China. The virus then spread throughout the world, which in March 2020, WHO announced the status of the epidemic as a pandemic. WHO finally named this virus as COVID-19. COVID-19 has infected more than 105 million people worldwide, and deaths that have reached more than 2.3 million worldwide. In Indonesia alone there have been more than 1 million cases of COVID-19 and more than 30 thousand deaths in February 2021 . Based on number of cases, patient must be handled responsively. One of the supporting diagnosis for COVID-19 is Chest X-Ray. Chest X-Ray becomes one of the mandatory steps for patients to confirm and determine the treatment(s) to medicate the patients appropriately.In this study using the Deep Learning EfficientNet architecture to classify people affected by COVID-19, pneumonia, and normal from Chest X-Ray. The test results are measured by Accuracy, F1-Score, recall, precision, and specificity. With this research it is expected to be able to detect as quickly as possible so that it reduces the spread of COVID-19 and is more cost-effective because Chest X-Ray is cheaper, faster, and less radiation than CT-Scan. The result is that the accuracy in this study reaches 96 percent, and the F1-Score, Recall, Precision, Specificity is above 95 percent.
Pengaruh Sampling Method dan Feature Extraction untuk Meningkatkan Detection Rate pada Minority Class pada Intrusion Detection System yang Disusun dari Support Vector Machine, Decision Tree, dan Naïve Bayes Janthake Decuellar; Henry Novianus Palit; Justinus Andjarwirawan
Jurnal Infra Vol 9, No 2 (2021)
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Intrusion detection system (IDS) has started to rely on machine learning to perform misuse detection or anomaly detection. As misuse detection, machine learning must be able to detect various types of intrusions, including those that are rare. However, machine learning has weaknesses, especially when faced with imbalanced datasets. Various methods are used to make machine learning able to perform the classification correctly even though the data provided is imbalanced. One of them in this study tries to implement Principal Component Analysis as feature extraction, Tomek Links as under-sampling and ADASYN as over-sampling on datasets. There are two types of datasets used in this research, namely KDD-99 and UNSW-NB15.The results obtained from research on the KDD’99 dataset are, Support Vector Machine can identify more intrusions than before and True Positive Rate of Decision Tree model for minority classes is increased between 0.03% to 4.762%. The results obtained from research on UNSW-NB15 dataset, accuracies for Support Vector Machine and Naïve Bayes models are increased between 0.045% to 1.513%.
Implementasi Sistem Inventori pada Prodi Informatika Universitas Kristen Petra Richard Putra Sugijanto; Henry Novianus Palit; Leo Willyanto Santoso
Jurnal Infra Vol 8, No 2 (2020)
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Petra Christian University Informatics Study Program is one of the educational institutions which one of the activities to carry out an inventory of items which includes submission, purchase, recording, and distribution / delivery of items both for the purposes of supporting teaching and learning activities and for the needs of employees in carrying out their work in serving students and lecturers, and its reporting. So far there has not been an inventory system, especially in laboratories used by Informatics Study Programs. The data collection and reporting process is still done manually which requires a long time in completing each work. Errors sometimes occur in the calculation and recording of items. Items are often moved so that they forget where they are. Seeing the problems that occur, then made a computerized inventory system to simplify and speed up the data collection process, and the process of reporting inventoryThe software developed is a web-based inventory system. This system is also adjusted to the results of the analysis of the existing system with several additional features to adjust the needs of the laboratory. The web system was developed using the serveride PHP programming language as well as several supporting libraries such as clientide css, javascript in the form of bootstrap, datatables, and jQuery.The final results of software development include the movement of items that occur in laboratories, such as input data of items, lending, returning and moving items.
Perbandingan Analisis Faktor Penentu Penjualan PT. X Menggunakan LASSO Regression dan Gradient Boosted Regression Tree Jessica Athalia; Henry Novianus Palit; Silvia Rostianingsih
Jurnal Infra Vol 9, No 1 (2021)
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Abstract

Information becomes a crucial asset for an organization. However, employees of PT. X are facing difficulty in analyzing data because it has to be processed one by one. Moreover, analyzing data in an operational database is not recommended as it can interfere with the performance of the operational database. Then, when the Board of Directors want to know the reason behind its sales’ performance, they conclude it based on their mere assumption. This research implemented a data warehouse with the help of ETL tools. Then, sales transactions of PT. X were analyzed to get information about factors that affect company’s revenue. Factor models were formed for brands which sales were not good enough these past few years. Factors which are examined are sales price, stock availability, on time delivery of goods, quantity of returns, month of transaction, and cost price. The analysis was carried with two methods, LASSO regression and Gradient Boosted Regression Tree. These models were measured by Root Mean Squared Error, R-squared, and Variance Inflation Factor to know which model performs better. Result of the research shows LASSO regression and Gradient Boosted Regression Tree succeed in performing feature selection for sales transactions of PT. X. Yet, the factor model from Gradient Boosted Regression Tree gives a better result than LASSO regression. Last, a program was made for the company in the need of future analysis using Gradient Boosted Regression Tree.
Analisis Kinerja Genetic Algorithm yang diakselerasi untuk Travelling Salesman Problem pada Platform Multicore CPU dan CUDA Alexander Thomas Kurniawan Pratomo; Henry Novianus Palit; Darian Gunamardi
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Advancement in technology brings about both new challenges and opportunities. One of which is the opportunity to accelerate an algorithm which usually took a very long time to finish. Genetic algorithm is one such algorithm that can be accelerated using these advancements. Certain ways to accelerate this algorithm is done by tuning the parameters, but these methods are usually unable to retain the quality that is obtained from previous, non-accelerated method. This research applies parallel computing using the multicore technology of CPU and GPU to accelerate genetic algorithm without any changes to the parameters. The purpose of the research is to analyze the differences in performance of the algorithm upon being accelerated with the technologies. The technologies used are CUDA platform and OpenMP API for GPU and CPU respectively. Aside from the technology itself, choosing the algorithm segments on which the implementation is done will also greatly affect the performance of the algorithm. According the testing results, Genetic Algorithm can be accelerated with parallelization using either OpenMP with CPU or CUDA with GPU.
Sistem Proteksi Kebocoran Gas LPG Berbasis Arduino dan Aplikasi Mobile Robertus Yunico Prasetiyo; Henry Novianus Palit; Resmana Lim
Jurnal Infra Vol 7, No 2 (2019)
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Abstract

Until now there are still many people who do not know how to improve, and how to care for them. LPG in homes. Therefore we need a tool that can tell through the application if there is an accurate and fast LPG gas leak.Arduino and applications are made using LPG gas based on PPM levels in LPG tubes, and can also use LPG tube temperature and humidity that change suddenly in a certain period of time. If a leak occurs, the gas application will immediately notify you of the LPG leak.Based on the results of testing that has been done, Arduino can protect gas leaks through PPM levels and can also protect gas leakage through temperature and humidity. Arduino can also directly turn off LPG gas by turning the regulator knob to the off position. Arduino and applications can run properly according to their functions. The application can also provide notifications in the event of a gas leak.
Simulasi Pembayaran Menggunakan RFID (Radio Frequency Identification) Pada Studi Kasus Layanan Mahasiswa Alvin Santoso; Henry Novianus Palit; Alexander Setiawan
Jurnal Infra Vol 7, No 2 (2019)
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Money is a tool for transactions. The growing of technology make payment methods is also more varied, for example with e-money. However, even there are methods like this, administrative Petra Christian University activities still use manual system so that make less practical. When e-money going to applied, there is a security aspect that must be considered. One of them is how to secure the balance that is on the card so that the balance cannot be duplicated.To make e-money payment on administrative Petra Christian University there will be make payment system with RFID (Radio Frequency Identification) with money in the card. There are 3 methods, AES, DES, 3DES with CBC and CFB mode in comparison of the speed encryption decryption, memory usage, and anti-duplication on the card. Besides there will be comparison of speed when doing top up/withdrawl balance/transaction when money stored in card and money stored in database.The test results found that there anti-duplication method successfully applied, encryption decrytion speed AES, DES, 3DES mode CBC more faster than CFB and memory usage same with all of method. Money in database have a faster process in top up/withdrawl balance while DES with CBC mode more faster in transaction.
Sistem Pakar Pendiagnosa Infeksi Saluran Pernafasan Akut (ISPA) dengan Metode Forward Chaining dan Certainty Factor Samuel Njoo; Kartika Gunadi; Henry Novianus Palit
Jurnal Infra Vol 9, No 2 (2021)
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Acute Respiratory Infection (ARI) is a group of diseases that are quite common in developing countries, including Indonesia. ARI consists of various diseases and has a very varied possibility of symptoms. If not detected and treated immediately, ARI can get even worse and can lead to death. With an expert system, users can quickly self-diagnose without worrying about the cost or time required. The knowledge possessed by the expert system also comes from doctors in their fields.The expert system will be built with the help of 2 (two) methods, namely the forward chaining as an inference method and the certainty factor as the calculation method. With the forward chaining method, the system can provide information such as what disease the user is suffering from directly after the user fills all the questions that will be asked by the system. In addition, with the certainty factor method, the system can provide information like how sure the system in providing diagnostic results and is intended in the form of a percentage, the user is also presented with several answer choices so each user's answer choices will have an impact on the final diagnosis result by the expert system.The system will be tested by 3 related experts and the accuracy of system diagnosis is 75%.
Sistem Rekomendasi Film Menggunakan Integrated Kohonen K-Means clustering Joshua Maximillian; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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With the development of the film industry, more and more films can be watched. But because there are too many films that can be watched that cause users to be confused in finding films that match what they like. So there is a movie recommendation system to help user. The movie recommendation system itself has various ways to produce movie recommendations that users might like.The movie recommendation system using Integrated Kohonen K-Means Clustering is one of the Data Mining methods that can be used in recommending films. Intergrated Kohonen K-Means Clustering compared to Kohonen Self Organizing Maps, and also K-Means Clustering in recommending films.According to the result of Integrated Kohonen K-Means Clustering to know how many K cluster that is optimal for K-Means Clustering use the Elbow Method. To know how good the cluster you produce use Silhouette Coefficient and the score -0.389 for the Integrated Kohonen K-Means Clustering. The Mean Reciprocal Rank produced by Integrated Kohonen K-Means Clustering which score is 0.362 is better than K-Means Clustering which score is 0.003 and Kohonen Self Organizing Maps which score is 0.002.
Co-Authors Agustinus Noertjahyana Alexander Setiawan Alexander Thomas Kurniawan Pratomo Alles Sandro Oktavio Gandadireja Alvin Nathaniel Tjondrowiguno Alvin Santoso Ananta Kusuma Pangkasidhi Andre Gunawan Andreas Handojo Anita Nathania Purbowo Antonius Tanuwijaya Billy Sugiharto Bobby Irawan Bobby Kwariawan Brian Stanley Daniel Widjojo Darian Gunamardi David Christ Antono Djoni Haryadi Setiabudi Edward Hosea Evandruce Filbert Eveline Cynthia Irawan Felicia Listyani Wijono Fransisco Remon Liemena Gordon Kusuma Kahono James Riady Janthake Decuellar Jessica Athalia Joshua Maximillian Justin Andjarwirawan Justinus Andjarwirawan Kartika Gunadi Kezia Sekarayu Setyawati Kezia Yedutun Kristian Halim Leo Willyanto Santoso Lily Puspa Dewi Martin Andersen Linggajaya Michael Levi Nico Kurniawan Resmana Lim Richard Putra Sugijanto Ricky Sunartio Robertus Yunico Prasetiyo Rolly Intan Rudy Adipranata Samuel Njoo Silvia Rostianingsih Stefanie Natasha Tjia Vania Putri Minarso Yulia Yulia