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Henry Novianus Palit
Program Studi Informatika
Computer Science & IT

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Implementasi Enkripsi AES Cipher dan Discrete Wavelet Transform Dalam Metode Steganografi David Christ Antono; Henry Novianus Palit; Rudy Adipranata
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

The science of steganography leads to a branch of computer science that is about hiding data information in media that cannot be easily detected. There are many types of media for steganography. The most popular ones are digital images. Along with the development of the science of steganalysis, there is needs of a way to add security to the hidden data. With steganalysis, one can easily reveal existence of hidden data in media files. Therefore, this study seeks to answer the need for securing the data. The program is an application that is useful for securing hidden data. The function of this program is to encrypt data that will be hidden using the AES cipher method. By converting hidden data into ciphertext, even though hidden data can be taken its form is still in the form of text that cannot be read without using the key used to encrypt. This process involves data that will be hidden to be converted into ciphertext first and finally steganography will be performed using least significant bits. Not only that, the program will also compress stego image. From the results of the encryption, steganography and compression trials, the hidden image data can be retrieved using the key used during encryption. The hidden data does not experience loss of information because the process is carried out lossless. The hidden data has been compared with extracted data and produces unlimited PSNR values.
Aplikasi Sentiment Analysis Terhadap Pelaksanaan Pembelajaran Jarak Jauh Universitas Kristen Petra Dengan Metode Naive Bayes Classifier Kezia Sekarayu Setyawati; Andreas Handojo; Henry Novianus Palit
Jurnal Infra Vol 9, No 1 (2021)
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In maintaining student satisfaction during online learning period, Petra Christian University conducted a survey to know student’s response. The result then processed manually and takes a long time to gather an information. Therefore, a sentiment analysis application is needed which will help to collect information from survey in a shorter time by classifying sentiments and topics related to online learning. The method used to classify topics and sentiments is the Naive Bayes Classifier. Data will be prepared through preprocessing, by eliminating the same sentence, changing abbreviated words, stemming, and stop word removal.The classification model produced and used in this application can classify student survey data related to the implementation of online learning based on positive and negative sentiments, also based on the topic, material, lecturers, learning media, and supporting facilities. The accuracy of the classification model is 89% for sentiment classification and 80% for topic classification.
Evaluasi Kinerja Penggabungan Knowledge Graph Embedded-Based Question Answering dan TransP pada Data Freebase Fransisco Remon Liemena; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 2 (2020)
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Abstract

In the past few years, data storage and analysis using graph keep increasing. One of the implementation of this is knowledge graph. There are many methods proposed on information extraction from knowledge graph, one of them is natural language question answering. However, all of the researches around question answering use direct query to find the answer. Knowledge Graph Embedding-based Question Answering (KEQA) is the latest method that implements deep learning and embedding to answer questions. Experiments demonstrate that KEQA outperforms other question answering methods. Despite having high accuracy, KEQA still uses simple and outdated embedding method.Knowledge graph embedding is one of the method for knowledge graph representation where the entities and relations are represented in vector (embedding) using deep learning. Many proposed embedding methods do not really consider the depth of a knowledge graph. TransP is a proposed method that consider the indirect relationship to represent a knowledge graph. Experimental results show that TransP outperforms other embedding methods in the task given. Based on this, KEQA will be built using TransP with the expectation that the accuracy of KEQA will increase.Based on the result of the experiment, TransP achieves Mean Rank of 5.390,25 and HIT10 of 28,5%. After that, KEQA with embedding can achieve up to 88,89% accuracy, and KEQA without embedding can achieve up to 88,89% accuracy. Experiment also shows that scoring parameters value with affect KEQA with embedding. In conclusion, TransP can increase the accuracy of KEQA.
Aplikasi Rekomendasi Tempat Makan berdasarkan Lokasi (Location Based Service) Stefanie Natasha Tjia; Djoni Haryadi Setiabudi; Henry Novianus Palit
Jurnal Infra Vol 8, No 1 (2020)
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The ease and affordability of transportation causes many people totravel or travel to another area or city. Salty people will needinformation about where to eat. From the quality and quantity, sothe application is needed to fulfill the information.The application that will be created is to provide a recommendationfor Places to Eat based on the closest distance from the coordinatesdetected by GPS from the user's mobile phone. In addition, thisapplication provides information about places to eat such asmenus, locations and also provides rating of eating and eatingplaces, which is useful to help users take a decision.Based on the results of tests that have been done, the applicationcan read GPS and provide recommendations based on the closestdistance to the user. Users can provide detailed meal ratings anddining places that are useful to help in making decisions inchoosing where to eat.
Aplikasi Android Untuk Backup dan Sinkronisasi File Menggunakan Amazon Web Services Simple Storage Service Brian Stanley; Henry Novianus Palit; Agustinus Noertjahyana
Jurnal Infra Vol 7, No 2 (2019)
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Cloud storage technology is a solution for the local storage which consumes lot of time for maintaining in the customer’s side. Amazon Web Service (AWS) provides S3, a storage that can be used for data backup purposes, but to use its features everytime users need to login through web browser. A solution to ease the use of S3 features is to utilize a mobile app that could automate the data backup and restore process.To solve the problem of unstable connection causing file transfers to start from the beginning each time, AWS provides an API that allows resumable uploads. TransferUtility from AWS will automatically issue a resume operation on the failed upload. Test results conclude that AWS S3 have a comparable connection to other cloud storage providers such as Google Drive, Dropbox, and OneDrive. The strength of S3 is its ability to automatically resume failed transfers caused by an unstable internet connection.
Implementasi Post-Boot Package Installation pada OpenStack untuk Image berbasis Linux Bobby Kwariawan; Henry Novianus Palit; Agustinus Noertjahyana
Jurnal Infra Vol 7, No 2 (2019)
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Cloud Computing technology is currently growing rapidly, so there have been a lot of companies plunged into using Cloud Computing Technology with the IaaS model (Infrastructure as a Service). OpenStack is one of the Cloud frameworks that is often used for Private Cloud Implementation. However, often Cloud users make configurable Virtual Machine Image as needed for different servers as templates to be easily deployed in the future. This can lead to waste of storage.Implementation of Package Installation Automation can reduce storage waste, by storing only 1 Virtual Machine Image then installing Package automatically using user-data features on cloud-init as needed, so Cloud users no longer need to manually install packages then save the Image results that were carried out by the package installation.Test results on OpenStack with Single-Node deployment show that this implementation can produce storage efficiency with an average of 79 % for Red Hat Enterprise Linux Image and 81 % for Ubuntu Image. But there are also inefficiencies in time with an average of 83 % for Red Hat Enterprise Linux and 71 % for Ubuntu Image.
Penerapan Recurrent Neural Network untuk Pembuatan Ringkasan Ekstraktif Otomatis pada Berita Berbahasa Indonesia Kristian Halim; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

Technology advancement in modern world allow huge amount of information to flow everyday and news became one of the source to get that information. Because of this advancement, available information through news have been increased and so program is develop to make summary of news to reduce reading time using the neural network as the basis of this program.The method used for training the model is Recurrent Neural Network. The type of Recurrent Neural Network that being used is Gated Recurrent Unit that is run in 2 level, the word level and then the sentence level. As for making the Recurrent Neural Network model, some experiment can be carried out, like changing initial weight of the word embedding, change the pooling method, removing dropout layer, and some preprocessing for the dataset.The results shows that for the initial model, F1 – Score for ROUGE – 1, ROUGE – 2, and ROUGE – L can reach up to 80% when using extractive summary as the reference and up to 50% when using abstractive summary as the reference. The experiment shows that the best model is using training dataset as the initial word embedding weight, using average pooling and removing the dropout layer. The best experiment result gives F1 – Score 84.10 for ROUGE – 1, 83.10 for ROUGE – 2 and 83.31 for ROUGE – L using the extractive reference and 57.01 for ROUGE – 1, 51.17 for ROUGE – 2 and 55.10 for ROUGE – L using the abstrative reference.
Penerapan Microservices dan Amazon Elastic Container Service untuk Mendukung Scalability Antonius Tanuwijaya; Henry Novianus Palit; Agustinus Noertjahyana
Jurnal Infra Vol 9, No 2 (2021)
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The technology age under development provides the impact of increasing the number of users in a system may also increase the workload received by the server. This condition is experienced in PT. X, where the server cannot handle the growing workload over time, this makes the server overloaded and slow in response until it gets to the server condition is down and unreachable by the user. This research tried to provide solutions to the problems faced by PT. X by applying a system of microservices and Amazon Elastic Container Service. By applying microservices then all services will be split into independent and can ease the workload of the server. Moreover, with the combination of Amazon ECS then the process of scaling will be more effective only on the service that is experiencing an overload condition so that the process of scaling can adjust the conditions of the workload on the server at that time. The scaling process will allow the system to increase or decrease the number of tasks performed without a lack or excessive use of resources. Based on analysis of the implementation of microservices and the Amazon ECS on the PT. X system, It can be concluded that the scalable microservices system produces a lower average response time with a difference of 805.56% compared to unscalable microservices and 38% compared to monolithic, then the resulting deviation is 902.22% lower than unscalable microservices and 216.87% lower than monolithic, then the resulting throughput is higher by 22018.61 requests/minutes from unscalable microservices and 24524.16 requests/minutes from monolithic. For a maximum concurrent user comparison between a scalable microservices system, an unscalable microservices, and monolithic of 2000:1454:28. In addition, the CPU usage of scalable microservices systems is 20%-21% lower, especially at login, generate access tokens, and get schedules when compared to unscalable microservices systems, due to workload sharing system with replication tasks. Additionally, the use of resources can adjust to workload conditions dynamically and efficiently
Automatic Playlist Continuation Menggunakan Hybrid Recommender System Martin Andersen Linggajaya; Henry Novianus Palit; Alvin Nathaniel Tjondrowiguno
Jurnal Infra Vol 9, No 2 (2021)
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Abstract

One of the most popular ways to listen to music is using playlists. The playlist feature can be improved by giving track recommendations to be added to certain playlists. To support the development of this recommendation process, ACM and Spotify held the RecSys Challenge 2018 with the task of automatic playlist continuation. This research is a continuation from [6] that placed 3rd in the RecSys Challenge 2018. The method used consists of 2 phases: candidate selection using a hybrid recommender system called LightFM and ranking using XGBoost. The research gap being developed focuses on one of the calculations for co-occurrence features used in the ranking phase. The result of this research shows that co-occurrence of 3 tracks does not improve the performance of the model used. The model by [6] achieved scores of 0.5251, 0.5582, and 1.295 for R-precision, NDCG, and recommended song clicks respectively. Meanwhile, the model produced in this research achieved an R-precision of 0.5241, an NDCG of 0.5579, and recommend song clicks of 1.312.
Analisa Dampak Implementasi Odoo ERP: Studi Kasus Perusahaan Ready-Mixed Concrete PT. X Eveline Cynthia Irawan; Yulia Yulia; Henry Novianus Palit
Jurnal Infra Vol 8, No 1 (2020)
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Abstract

In this developing technological era, information technology has played an important role in the business world. However, PT. X is a ready-mixed concrete company that still does all the works manually. This causes the company to need more time to get the information needed because the company’s data are not integrated. In addition, there are human error problems that can occur due to employees’ negligence, such as forgetting to ask for proof of payment or forgetting to collect past due customer receivables. If the human errors are not immediately handled, they may cause problems in the company’s cash flow. This research tries to overcome the problems faced by PT. X by creating an Enterprise Resource Planning program. Among many ERP program platforms, Odoo was chosen as an ERP program that has many advantages, one of which is the ease in configuring and customizing the modules. An analysis of the ERP program is also carried out to measure the success of its implementation in the company by analyzing the suitability of business processes between the ERP program and the company's old business processes. Based on the analysis of the implementation of the ERP program at PT. X, it can be concluded that the ERP program has a positive impact on the company. Almost all business process designs in the Odoo program can meet the needs of the company well. Despite the limitations of Google Maps and financial data, the Odoo program can still run well.
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