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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknik Informatika UNIKA Santo Thomas Infotek : Jurnal Informatika dan Teknologi Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Ginabila Ginabila
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Analysis of Air Pollution Levels in DKI Jakarta Province Using the Mamdani Fuzzy Inference System Method Akmal Dirgantara; Ahmad Fauzi; Ginabila Ginabila
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.027 KB) | DOI: 10.31289/jite.v4i1.3804

Abstract

This study aims to measure the level of air pollution determined by pollutant gases contained in the air. Pollutants that measure air pollution are PM10 (Special Material), SO2 (Sulfur), NO2 (Nitrogen Oxide), CO (Carbon Monoxide, O3 (Ozone), and NO2 (Nitrogen Oxide), which are related to vehicle use and, according to the choice this pollutant threshold, we will discuss the level of air pollution with the fuzzy mamdani inference method. The results of the pollutant threshold study will then be applied to the rules / rules that are applied using the if-then rules and then the input variables are arranged using weighted averages, variable averages weighted will be determined higher into three levels: low, medium and high.Keywords Decision Tree, Feature Selection, Optimization of Lecturer Assistant Performance, Particle Swarm Optimization.
Information Retrieval & Perhitungan Kemiripan Dokumen pada Indonesian Heritage Library Menggunakan Vector Space Model Ginabila Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 5 No. 2 : Tahun 2020
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17605/jtiust.v5i2.987

Abstract

Kebutuhan user untuk mencari suatu kumpulan atau pangkalan informasi secara otomatis saat ini sudah menjadi hal yang sering dilakukan, untuk memenuhi kebutuhan user menemukan kembali informasi-informasi yang dibutuhkan tersebut maka information retrieval system digunakan. Pencarian dokumen yang dilakukan oleh user pada sebuah database dengan cara menginputkan nama dokumen, maka semua dokumen dengan judul yang hampir mendekati dokumen yang user maksud akan ditampilkan. Hal ini dikarenakan dalam sistem pencarian tersebut, sistem belum dapat mengukur mana dokumen yang paling sesuai yang harus ditampilkan dan yang dimaksud oleh user. Maka dengan masalah seperti ini penulis menggunakan information retrieval. Dalam penelitian ini akan dilakukan perhitungan kemiripan dokumen menggunakan metode Vector Space Model. Dalam metode ini data akan melalui proses token dan indexing sehingga tingkat ketepatan dokumen yang dimaksud oleh user untuk temu kembali informasi akan lebih sesuai.
Information Retrieval & Perhitungan Kemiripan Dokumen pada Indonesian Heritage Library Menggunakan Vector Space Model Ginabila Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 5 No. 2 : Tahun 2020
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (819.754 KB) | DOI: 10.17605/jtiust.v5i2.987

Abstract

Kebutuhan user untuk mencari suatu kumpulan atau pangkalan informasi secara otomatis saat ini sudah menjadi hal yang sering dilakukan, untuk memenuhi kebutuhan user menemukan kembali informasi-informasi yang dibutuhkan tersebut maka information retrieval system digunakan. Pencarian dokumen yang dilakukan oleh user pada sebuah database dengan cara menginputkan nama dokumen, maka semua dokumen dengan judul yang hampir mendekati dokumen yang user maksud akan ditampilkan. Hal ini dikarenakan dalam sistem pencarian tersebut, sistem belum dapat mengukur mana dokumen yang paling sesuai yang harus ditampilkan dan yang dimaksud oleh user. Maka dengan masalah seperti ini penulis menggunakan information retrieval. Dalam penelitian ini akan dilakukan perhitungan kemiripan dokumen menggunakan metode Vector Space Model. Dalam metode ini data akan melalui proses token dan indexing sehingga tingkat ketepatan dokumen yang dimaksud oleh user untuk temu kembali informasi akan lebih sesuai.
Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Mochammad Abdul Azis; Ahmad Fauzi; Ginabila Ginabila; Imam Nawawi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.
Klasifikasi Human Stress Menggunakan Adagrad Optimization untuk Arsitektur Deep Neural Network Mochammad Abdul Azis; Ahmad Fauzi; Ginabila Ginabila; Imam Nawawi
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 1 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

According to the World Health Organization, stress is a type of mental illness that affects human health and there is no one in this world who does not suffer from stress or depression. Stress is a term that is often used synonymously with negative life experiences or life events. . Analysis of data that has an unbalanced class results in inaccuracies in predicting human stress. This study shows that using the Deep Neural Network (DNN) Architecture model by optimizing several parameters, namely the optimizer, Learning rate and epoch. The best DNN Architect results are obtained with 4 Hidden Layers, Adagard Optimization, Learning rate 0.01 and the number of epochs 100. Accuracy, precision, recall and f-measure scores get 98.25%, 83.00%, 98.25%, 91.00%, respectively.
Pengembangan Aplikasi E-learning dengan Metode Rapid Application Development Ahmad Fauzi; Ginabila Ginabila; Mochammad Abdul Azis
Infotek: Jurnal Informatika dan Teknologi Vol 6, No 1 (2023): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v6i1.7414

Abstract

The development of the E-learning application is part of the solution for convenience in carrying out teaching and learning activities, the process of receiving and sending a digital document in the form of learning videos and ebooks is the most important part so that information can be accessed quickly and easily. Special methods are needed to build e-learning applications more quickly and according to needs. Requirements Planning plays a very important role in the software development process, project management in software development and one of the processes is to estimate that the software produced is according to a predetermined schedule and cost. The Rapid Application Development Method is a life cycle strategy aimed at To provide development that is much faster and get results with better quality, UML (Unified Modeling Language) is a language that has become a decent standard in designing, visualizing and documenting software.
Co-Authors Ahmad Fauzi Akmal Dirgantara Akrom Akrom Imam Nawawi Jamhari Jamhari Mochammad Abdul Azis