2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE)
The world immediately studied Corona virus Disease 2019 (COVID-19) and raced towards fmding the c... more The world immediately studied Corona virus Disease 2019 (COVID-19) and raced towards fmding the cure and developing an effective treatment. An aut omated approach is needed to discover drug candidates and provide those data to fa cilitate clinical trials in saving time and only fo cusing on the candidates which potentially become the cure for COVID-19. We propose the Drug Candidates for the Prevention of COVID-19 (DCPC) Database. DCPC Database provides a list of candidates of potential drugs for the prevention of COVID-19 based on disease-drug associations which are automatically discovered from biomedical literature. DCPC database is an integrative structural database, which involves a chemical database repository, such as PubChem and DrugBank to ensure that drug compound candidates have a standard representation of compounds. The database provides keyword-chosen categories and a determination of minimum supported articles for search, a list of drug candidates in the sorted table fo llowed by the detail for each candidate, and a download fe ature. The keyword category consists of three keywords, they are Chinese herbal compounds, Indian medicinal plants, and Indian medicinal plants & diabetic treatment herbs. Each candidate links to an article in the biomedical literature and to a page of the compound structure visualization. DCPC is freely available at https :/ /dcpc.brin.go.id/dcpc/ .
Jurnal Teknologi Informasi dan Ilmu Komputer, Jun 20, 2022
Tidak semua siswa sekolah bisa menangkap materi dengan kemampuan yang sama dikarenakan tingkat ke... more Tidak semua siswa sekolah bisa menangkap materi dengan kemampuan yang sama dikarenakan tingkat kecerdasan dan kemampuan belajar setiap anak berbeda-beda. Ada siswa yang kemampuan belajarnya rendah sehingga lambat dalam memahami materi yang biasa disebut sebagai slow learner. Siswa slow learner ini perlu perlakuan yg khusus supaya dapat memahami materi seperti siswa lainnya. Siswa slow learner yang tidak terdeteksi dapat memperlambat kegiatan belajar mengajar karena guru harus mengulang kembali menjelaskan materi untuk membuat siswa memahami materi tersebut. Penelitian ini bertujuan untuk mengklasifikasikan siswa slow learner dan non slow learner dan menghasilkan visualisasi dashboard yang dapat digunakan untuk membantu sekolah. Penelitian ini mengangkat studi kasus siswa kelas XI dan XII SMA Tunas Luhur yang berjumlah 89 siswa. Penelitian ini menggunakan algoritma naive bayes untuk klasifikasi dan cross validation 10 folds sebagai metode pengujian. Hasil pengujian didapatkan nilai akurasi 0.92857, precison 0.94736, recall 0.97297 , dan F-measure 0.96 serta hasil pengujian visualisasi dashboard menggunakan kuesioner System Usability Scale yang menghasilkan skor 71.75 atau acceptable. Algoritma naïve bayes berhasil mengklasifikasikan siswa slow learner dan non slow learner dengan baik, dan visualisasi dashboard bisa diterima dengan baik oleh pihak sekolah.
Bulletin of Electrical Engineering and Informatics
In the new-normal era, public services must make various adjustments to keep the community safe d... more In the new-normal era, public services must make various adjustments to keep the community safe during the COVID-19 pandemic. The Public Service Mall is an initiative to put several public services offices in a centralized location. However, it will create a crowd of people who want access to public service. This paper evaluates multi-tenant models with the rapid adaptation of cloud computing technology for all organizations' shapes and sizes, focusing on multi-tenants and multi-services, where each tenant might have multiple services to offer. We also proposed a multi-tenant architecture that can serve queues in several places to prevent the spread of COVID-19 due to the crowd of people in public places. The design of multi-tenants and multi-services applications should consider various aspects such as security, database, data communication, and user interface. We designed and built the "QuAntri'' business logic to simplify the process for multi-services in each te...
Seminar Nasional Open Source Software, ke-3, Bandung, 7 November 2009 : prosiding
Front-end Based Robust Speech Recognition Methods: A Review
The 2021 International Conference on Computer, Control, Informatics and Its Applications
Densely Connected Networks with Smoothed Labels Regularization for Tea Diseases Detections
The 2021 International Conference on Computer, Control, Informatics and Its Applications
WiFi-AC Based Telecommunication Infrastructure for Autonomous Vehicle in Limited Area
2021 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)
Desain dan implementasi Sistem Komunikasi Wireless
This research is aimed at designing and applying wireless communication system on SBC(Single Boar... more This research is aimed at designing and applying wireless communication system on SBC(Single Board Computer) for weather station communication system. The experiment and system testing use Alix3d2 as SBC and linux debian built by embedded linux community as embedded linux. This embedded linux itself is developed from uClinux, a linux processor without Memory Management Unit (MMU). Its library, uClibc is taken as a substitute of libc which is smaller for a native linux on minimalis system with a MMU processor. Beside the library, the proposed research also uses several native function of linux mixed by Busybox so that the size of application turn to be more reasonable and simpler. The result of the design is implemented on Alix3d2 board.
Penerapan Algoritma Kriptografi Kunci Publik Sebagai Pengamanan Sistem Distribusi Perangkat Lunak Lipirism
LIPIRISm@ adalah sebuah perangkat lunak yang telah dibuat oleh Pusat Penelitian Informatika – LIP... more LIPIRISm@ adalah sebuah perangkat lunak yang telah dibuat oleh Pusat Penelitian Informatika – LIPI yang digunakan oleh para praktisi iridologi untuk menganalisa kondisi organ dan sistem tubuh melalui iris mata seseorang. Pada tahun ini perangkat lunak LIPIRISm@ akan diluncurkan, namun tentunya untuk menjaga keaslian dan distribusi perangkat lunak ini maka diperlukan suatu sistem pengamanan yang baik agar tujuan dibuatnya perangkat lunak ini dapat terpenuhi. Pada tulisan ini akan dibahas beberapa model pengamanan perangkat lunak, dan yang dipilih adalah model pengamanan Sistem Registrasi Online dengan menerapkan Algoritma Kriptografi Kunci Publik pada perangkat lunak LIPIRISm@ dengan berbagai argumentasinya. Kata Kunci : Perangkat Lunak LIPIRISm@, Sistem Pengamanan, Sistem Registrasi Online.
Deep Convolutional Adversarial Network-Based Feature Learning for Tea Clones Identifications
2019 3rd International Conference on Informatics and Computational Sciences (ICICoS), 2019
Tea is a commodity has a strategic role in the Indonesian economy. The cultivation of tea plants ... more Tea is a commodity has a strategic role in the Indonesian economy. The cultivation of tea plants becomes very important in order to maintain the superior commodity, with respect to increase the production and/or improve the quality of tea. In a tea plantation management system, it is essential to identify the types of tea clones planted in the field. But, it requires human experts to distinguish one types of clones with another. The existence of an automatic clones identification is expected to make the identification easy, fast, accurate, and easily accessible for common farmers. In this work, we propose an unsupervised feature learning algorithm derived from Deep Convolutional Generative Adversarial Network (DCGAN) for automatic tea clone identification. The use of unsupervised learning enable us to utilize unlabeled data. Our experiments suggest the effectiveness of our method for tea clones detection task.
Generalized Filter-bank Features for Robust Speech Recognition Against Reverberation
2019 International Conference on Computer, Control, Informatics and its Applications (IC3INA), 2019
Traditionally, automatic speech recognition (ASR) uses a Hidden Markov Model with Gaussian Mixtur... more Traditionally, automatic speech recognition (ASR) uses a Hidden Markov Model with Gaussian Mixture Model (HMM-GMM) as acoustic model and hand-designed features such as Mel-frequency Cepstral Coefficient (MFCC) as acoustic features. It is usually assumed that the features are uncorrelated, making it possible to use diagonal covariances for the GMM. The assumption generally holds due to the use of Discrete Cosine Transformation (DCT) that de-correlates the speech spectra. However, DCT could cause some information loss, such as correlations between the feature components. Current ASR systems, which is based on Deep Neural Network (DNN) show to be better especially in reverberant conditions when more primitive features, such as filter-bank (FBANK), are used. This might be because DNN is better in modeling non-linear relations between the components of the features. But the use of short-time processing in FBANK may cause the lost of long-term correlations in a speech pattern. To tackle t...
Unjuk kerja sistem komputer adalah kemampuan komputer dalam menyajikan informasi yang diperlukan ... more Unjuk kerja sistem komputer adalah kemampuan komputer dalam menyajikan informasi yang diperlukan oleh pemakai. Faktor-faktor yang menentukan unjuk kerja komputer adalah sekumpulan perangkat keras dan perangkat lunak. Unjuk kerja komputer dapat diukur dengan berbagai cara. Unjuk kerja komputer ditentukan oleh perangkat keras yang terpasang dan perangkat lunak yang dijalankan pada perangkat keras tersebut. Pengukuran dilakukan untuk mengetahui kemampuan komputer dalam mengolah dan menghasilkan informasi yang diperlukan oleh pemakai. Cara pengukuran yang paling banyak digunakan yaitu dengan menggunakan metoda benchmarking. Geometri fraktal mempunyai karakter-karakter penting antara lain self similar, self affine, self inverse, dan self squaring. Yang jelas skala panjangnya tidak spesifik atau invariant. Berbeda dengan geometri euklidean, penyekalaan fraktal dicirikan oleh bilangan-bilangan pecahan atau tak bulat (noninteger), yang disebut dimensi fraktal (fractal dimensions). Ciri-ciri...
Recognizing Human Activities and Earthquake Vibration from Smartphone Accelerometers using LSTM Algorithm
2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA), 2018
Nowadays, most smartphones are equipped with accelerometer sensor, which can be used to record ac... more Nowadays, most smartphones are equipped with accelerometer sensor, which can be used to record acceleration caused by movements or vibration. It opens the opportunity to use them as a personal earthquake early warning system where people can use their smartphone to detect the incoming earthquake. However, to avoid false alarm, we must be able to recognize the source of sensor acceleration. One of the most common sources of vibration recorded by smartphone accelerometer is human activities. In this work, we used machine learning to distinguish the source of movement by observing the acceleration value caused by human activities and earthquakes. RNN-LSTM neural network is trained with labeled time series acceleration data and used to recognize the movement source. Our model show potential to differentiate between human activity and earthquake movement with training accuracy value of 97% and test loss value equal to 0.3.
Convolutional variational autoencoder-based feature learning for automatic tea clone recognition
It is common to have various clones from cross-seedlings or unintended planting by the farmers in... more It is common to have various clones from cross-seedlings or unintended planting by the farmers in a tea plantation. Since each tea clone has distinctive features such as quality, resistance to diseases, etc., visual inspections are usually conducted on the plantations to segment areas with different tea clones within the plantation to produce crops with consistent quality. However, this would be costly and time-consuming. In this work, we apply machine learning and develop an application to recognize tea clones automatically. We propose a convolutional variational autoencoder-based feature learning algorithm to produce robust features against data distortions. There are two main advantages of using this algorithm for feature learning. First, there is no need to design complex handcrafted features for classifications, usually conducted in machine learning. Second, the resulting features are more robust when tested with data taken from unideal conditions. The proposed method is evalua...
Perancangan Dan Implementasi Infrastruktur Jaringan Komputer Serta Cloud Strorage Server Berbasis Kendali Jarak Jauh (Studi Kasus DI Pt. Lapi Itb)
Dalam menjalankan bisnisnya, PT. LAPI ITB banyak melakukan kegiatan operasional di luar lingkunga... more Dalam menjalankan bisnisnya, PT. LAPI ITB banyak melakukan kegiatan operasional di luar lingkungan kantor, hal ini menimbulkan masalah, ketika beberapa data dan aplikasi hanya diperbolehkan untuk diakses pada jaringan lokal. Terlebih lagi dalam setiap pengelolaan proyeknya, tim PT. LAPI ITB yang berada terpisah di beberapa lokasi membutuhkan suatu metode sharing data yang bersifat everywhere and everytime. Tentu saja untuk menyelesaikan permasalahan ini dibutuhkan suatu perancangan dan implementasi infrastruktur jaringan komputer yang dikombinasikan dengan kendali jarak jauh serta layanan cloud storage. Kata kunci : Infrastruktur Jaringan, Cloud Storage, Kendali Jarak Jauh.
Development of Precision Farming Using Modular Multi Node Sensor
Integration between Wireless Sensor Network (WSN) and the Internet of Things (IoT) is widely used... more Integration between Wireless Sensor Network (WSN) and the Internet of Things (IoT) is widely used in many application to build a support system to overcome any problem. Indonesia as an agriculture country which needs that technology to solve agriculture problem such as land monitoring, water treatment, etc. Precision farming based on WSN and IoT is described in detail especially in multi-node sensor configuration and the master station. In this research, the WSN system consists of the multi-node sensor which contains several sensors for each node, a controller and wireless module. A master station is built with raspberry pi 3 (RPi3) as the main computer. All data from node sensor will be displayed to a graphical user interface (GUI) and saving data into internal databases. Communication between the master station and each node sensor through a wireless network based on X-bee board. The software operated in closed loop control to activate water treatment based threshold value from th...
With advances in information technology, various ways have been developed to detect diseases in p... more With advances in information technology, various ways have been developed to detect diseases in plants, one of which is by using Machine Learning. In machine learning, the choice of features affect the performance significantly. However, most features have limitations for plant diseases detection. For that reason, we propose the use of hybrid features for plant diseases detection in this paper. We append local descriptor and texture features, i.e. linear binary pattern (LBP) to color features. The hybrid features are then used as inputs for deep convolutional neural networks (DCNN) Support and VGG16 classifiers. Our evaluation on Based on our experiments, our proposed features achieved better performances than those of using color features only. Our results also suggest fast convergence of the proposed features as the good performance is achieved at low number of epoch.
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Papers by Ana Heryana