Articles
<![CDATA[Pengenalan Aksara Jawa dengan Menggunakan Metode Area Based Feature Extraction dan Support Vector Machine ]]>
<![CDATA[Alfred Louis Wangsaputra]]>;
<![CDATA[Rudy Adipranata]]>;
<![CDATA[Alvin Nathaniel Tjondrowiguno]]>
<![CDATA[ Jurnal Infra Vol 7, No 1 (2019) ]]>
Publisher : <![CDATA[Jurnal Infra ]]>
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<![CDATA[Huruf Jawa merupakan salah satu dari budaya Indonesia yang beragam di pulau Jawa. Namun seiring dengan perkembangan teknologi, budaya huruf Jawa ini mulai ditinggalkan. Banyak generasi muda sekarang yang lebih tertarik untuk belajar bahasa asing daripada Bahasa Jawa. Walaupun orang Jawa tinggal di pulau Jawa tetapi masih banyak yang tidak mengerti huruf Jawa. Sangat disayangkan apabila suatu budaya yaitu huruf Jawa harus hilang karena tidak ada generasi muda yang mengerti huruf Jawa. Huruf Jawa memiliki tingkat kesulitan tersendiri untuk dipelajari karena bentuknya yang mirip antara satu huruf dengan huruf lainnya. Kesulitan dalam mempelajari huruf Jawa ini juga berpengaruh pada minat generasi muda untuk mempelajari huruf Jawa Selain itu, saat ini aplikasi mengenai huruf Jawa juga masih cenderung tidak terlalu banyak.Berdasarkan permasalahan tersebut, maka aplikasi pengenalan huruf Jawa ini dibuat dengan harapan dapat melestarikan budaya Indonesia sekaligus mempermudah pembelajaran huruf Jawa. Adapun penelitian sebelumnya yang juga merupakan pengenalan huruf Jawa tetapi dengan metode lain seperti Shape Based Feature Extraction sebagai metode ekstraksi fitur dan Probabilistic Neural Network, Elman Type, Feedforward Backpropagation sebagai metode pengenalan namun akurasinya masih relatif rendah. Proses dari pengenalan huruf Jawa ada 3 tahap, yaitu segmentasi, ekstraksi fitur, dan pengenalan. Input berupa gambar dokumen huruf Jawa yang akan di segmentasi. Proses segmentasi telah dibuat oleh penelitian sebelumnya dan hasilnya adalah gambar satu huruf Jawa. Proses fitur ekstraksi dilakukan dengan menggunakan metode Area Based Feature Extraction sehingga menghasilkan data fitur ekstraksi dari gambar satu huruf Jawa untuk digunakan dalam proses pengenalan. Proses pengenalan dilakukan dengan menggunakan metode Support Vector Machine. Output nya adalah teks digital dari huruf Jawa yang diklasifikasi.Hasil pengujian menunjukkan bahwa akurasi pengenalan huruf Jawa menggunakan metode Support Vector Machine mencapai 90.84%.]]>
<![CDATA[Penerapan Fuzzy Control untuk Pengereman Kereta dalam Simulation Game ]]>
<![CDATA[Reinaldo Julaidi]]>;
<![CDATA[Rolly Intan]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 7, No 1 (2019) ]]>
Publisher : <![CDATA[Jurnal Infra ]]>
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<![CDATA[Penelitian mengenai pengereman kereta telah banyak dilakukan. Sebagai contoh, Wahyudi melakukan penelitian perhitungan pengereman kereta berupa kecepatan dengan Fuzzy. Yulianti melakukan penelitian pengereman kereta berupa kecepatan dan jarak dengan Fuzzy, dan di simulasikan. Namun, penelitian yang dilakukan masih belum menyesuaikan dengan keadaan kereta sesungguhnya saat dilakukan pengereman.Karena itu, dalam skripsi ini akan dibuat sebuah game dengan genre Simulation Game dengan AI untuk mensimulasikan pengereman kereta. Pengereman kereta yang dilakukan menggunakan Fuzzy Control dimana akan melakukan pengererman berdasarkan setiap Fuzzy rules dengan menggunakan metode Mamdani dengan kecepatan, massa, dan jarak sebagai Fuzzy Input.Hasil pengujian menunjukkan bahwa kereta dapat berhenti di tujuan dengan melakukan pengereman yang dilakukan oleh Fuzzy Control dengan perlahan hingga berhenti di tujuan dengan menggunakan Fuzzy Inference Engine yang melakukan proses untuk menghasilkan setiap tindakan keputusan kekuatan pengereman kereta.]]>
<![CDATA[Pembuatan Aplikasi Segmentasi Dan Klasifikasi Jerawat Dengan Metode Region Growing Dan Self Organizing Map ]]>
<![CDATA[Ari Gunawan]]>;
<![CDATA[Rudy Adipranata]]>;
<![CDATA[Gregorius Satia Budhi]]>
<![CDATA[ Jurnal Infra Vol 5, No 1 (2017) ]]>
Publisher : <![CDATA[Jurnal Infra ]]>
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<![CDATA[Acne vulgaris is a common skin disease found in men of all ages and sexes. Acnes have different types according to their severity.In this research, an application were developed to detect, do segmentation, and process the classification an acne object in human’s face. The process begins with the insertion of several seed points on a photo. Each of those seed points were developed further into a region that mask the whole acne using Region Growing Method. Afterward, the regions were grouped together with other acne of similiar features using Self Organizing Map.According to the experiment’s result, the Region Growing Method gives a satisfying result to do a segmentation on an acne object. But it should be pointed out that every different acne object requires different threshold to achieve an ideal result. Self Organizing Map gives an undesirable result, as the input photos with different skin colors and lightning conditions affect the accuraccy of the result.]]>
<![CDATA[Implementasi Fuzzy Logic dan Ellie: Buddy AI Pada Companion Dalam Game Survival Horror ]]>
<![CDATA[Winsen Wonady]]>;
<![CDATA[Kristo Radion Purba]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 5, No 2 (2017) ]]>
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<![CDATA[The development of the game is now very rapidly growing. As the game develops, making AI (Artificial Inteligence) in the game even more advanced. There are many types of AI that are usually used in the game including AI NPC Companion is AI that will accompany players during the game. Game will be developed using Unity Application and using C # language programming language. In the game players will be accompanied by NPCs who use Fuzzy Logic combined with Ellie: Buddy AI as AI controller. In the game players will also face zombies and bandits as enemies that will use rulebase as AI nya. The end result of this game is a survival horror game genre with NPC Companion feature. The testing done at the end of the segment is testing of the application, testing of NPC, testing of Enemies, testing of players and Comparison between NPC Companion and AI bandit.The final result of testing is that the game can run smoothly, AI NPC and Enemy can run with Well, and Control player can be used well, At the end result of comparison NPC found can do action more varied compared to AI bandit.]]>
<![CDATA[Sistem Pendeteksian Lahan Parkir Kosong pada Static Image dengan Image Processing ]]>
<![CDATA[Albert Liem]]>;
<![CDATA[Iwan Njoto Sandjaja]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 5, No 2 (2017) ]]>
Publisher : <![CDATA[Jurnal Infra ]]>
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<![CDATA[In this paper we will explain about vacant parking space detection system through image processing. This program was made with Visual Studio using C++ programming language and OpenCV library. Image processing itself has a vast research area and some of its methods will be used to create a parking space detection system. In this program, the input consists of the video feed of the parking lot, the said video is processed and analyzed with thresholding classification and SVM classification, resulting in an indicator to show if certain parking slot is vacant or not.]]>
<![CDATA[Perancangan Modul Penggajian Berbasis Odoo ]]>
<![CDATA[Vincent K. Edison Koeswanto]]>;
<![CDATA[Yulia Yulia]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 4, No 1 (2016) ]]>
Publisher : <![CDATA[Jurnal Infra ]]>
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<![CDATA[Human Resource Module is one of the modules owned by Odoo. One of the feature of this module is payroll. However, the features is not in accordance with the needs of companies in Indonesia in general. This causes the payroll system in Odoo not suitable to be implemented directly in the company.To solve these problems, author develop the payroll system in Human Resource module in Odoo. The development of this system is preceded by designing and analyze the payroll system at PT X. It also conducted a review of the Act and other regulations relating to payroll system in Indonesia.The end result of this development are additional features and adjustment on payroll. The testing is done by implementing this system in company X.]]>
<![CDATA[Aplikasi Pengenalan Wajah Menggunakan Hough Transform Based Feature Extraction ]]>
<![CDATA[Septian Triadi]]>;
<![CDATA[Leo Willyanto Santoso]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 5, No 2 (2017) ]]>
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<![CDATA[The face recognition is one of the important areas in the field of research. Facial recognition can be used in commercial and legal fields. Thus the development of new techniques for characteristic extracting using hough transform is performed.Applications using pre-processing consist of histogran equalization, unsharp masking, and edge detection before processing using hough transform. Then use the block-wise hough transform to split the image into blocks of images.From the results of face recognition testing is influence by the variation of the pose. For lighting variations improvised using pre-processing so that different kinds of lighting can be recognized]]>
<![CDATA[Pembuatan Sistem Peramalan Penjualan Dengan Metode Weighted Moving Average dan Double Exponential Smoothing Pada UD Y ]]>
<![CDATA[Cindy Baktiar]]>;
<![CDATA[Adi Wibowo]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 3, No 1 (2015) ]]>
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<![CDATA[UD Y is a small business, that provides distribution of water pumps and the spareparts (capacitor, seal, fan) as well as manufacturing the accessories (valves, pvc tees and tanks). UD Y as a commercial industry, finds it hard to forecast the right amount of materials needed to produce their products. For that reason, for this thesis will be made a Sales Forecasting using the Weighted Moving Average and Double Exponential Smoothing methods to help UD Y to forecast the right amount of products that will be bought every month.This system was made using database MySQL with Hypertext Prepocessor (PHP) programming languageFrom the final testing of this program, system that has been made can show the sales forecast in UD Y so that system can help UD Y from making decision for the right amount of products stock.]]>
<![CDATA[Aplikasi Ekstraksi Fitur Citra Hufur Jawa Berdasarkan Morfologinya ]]>
<![CDATA[Meiliana Indrawijaya]]>;
<![CDATA[Liliana -]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 3, No 1 (2015) ]]>
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<![CDATA[Feature extraction is an important topic in the classification. Well detected features will be able to increase the level of accuracy for the recognition of an object. Javanese language is a language that is often used by people on the island of Java, Indonesia. Feature extraction of Javanese letter has its own difficulty level for Javanese letter consists of many types of letters and combinations. In this paper, developed an application that can extract a handwritten Javanese letter features.The process is carried out as follows: image that has been previously segmented, skeleton by using the method of Zhang Suen. The results of this skeletonizing will be used to extract image features, which consists of loops, straight lines and curves arch. Loop detection using flood-fill algorithm, line detection using Hough Transform and curve detection using Hough Transform with curve detection algorithm.The input is Javanese letters image that has been segmented previously. The output is the type and number of features that are recognized and can be saved in .csv format. This application is made to the programming language C# with Microsoft Visual Studio 2010 as the IDE.]]>
<![CDATA[Penerapan Algoritma Particle Swarm Optimization (PSO) untuk Optimisasi Pembangunan Negara dalam Turn Based Strategy Game ]]>
<![CDATA[Andre Setiawan]]>;
<![CDATA[Leo Willyanto Santoso]]>;
<![CDATA[Rudy Adipranata]]>
<![CDATA[ Jurnal Infra Vol 7, No 1 (2019) ]]>
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<![CDATA[Bermain Video Game merupakan salah satu hiburan yang menjadi pilihan untuk mengisi waktu luang. Salah satu genre game yang cukup digemari oleh pemain adalah Turn Based Strategy. Game Turn Based Strategy memerlukan AI yang dapat membuat keputusan dengan optimal. Pada penelitian ini, AI dapat membuat keputusan untuk menentukan jenis dan lokasi bangunan, sehingga pembangunan menjadi lebih optimal.Untuk dapat mengambil keputusan dengan optimal, dibuatlah sebuah sistem algoritma AI. Sistem algoritma AI yang digunakan adalah Particle Swarm Optimization dalam mengambil keputusan untuk menentukan jenis dan lokasi bangunan.Hasil pengujian menunjukkan bahwa algoritma Particle Swarm Optimization dapat dikembangkan untuk dapat menentukan keputusan dengan baik berdasarkan fitness yang berpengaruh pada penentuan jenis dan lokasi bangunan. Hasil pengujian juga menunjukkan bahwa dengan batas jumlah turn yang mencukupi, Particle Swarm Optimization dapat memberikan hasil yang lebih baik daripada metode random.]]>
