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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika 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 Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media

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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.
KOMPARASI ALGORITMA DENGAN PENDEKATAN RANDOM UNDERSAMPLING UNTUK MENANGANI KETIDAKSEIMBANGAN KELAS PADA PREDIKSI CACAT SOFTWARE Ginabila Ginabila; Ahamd Fauzi
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1063.258 KB) | DOI: 10.33480/pilar.v15i1.28

Abstract

Testing is a process that becomes a standard in producing quality software. In predictions of software defects, prediction errors are very bad. Incorrect and inappropriate data sets result in inaccurate prediction results will be affect the software itself. This study aims to overcome the problem of class imbalance with the software defect prediction data set, through the Random Undersampling (RUS) data level approach by taking several algorithms namely Naive Bayes (NB), J48 and Random Forest (RF) which aims to compare the accuracy level highest so that maximum results are obtained in the process of predicting software defects. From the results of this study it can be found that to overcome class imbalances using the Random Undersampling level data approach to predict software defects, the highest level of accuracy is obtained by the Random Forest algorithm with an accuracy rate of 71.932%.
INFORMATION RETRIEVAL SYSTEM PADA FILE PENCARIAN DOKUMEN TESIS BERBASIS TEXT MENGGUNAKAN METODE VECTOR SPACE MODEL Ahmad Fauzi; Ginabila Ginabila
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): PILAR Periode Maret 2019
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (938.599 KB) | DOI: 10.33480/pilar.v15i1.61

Abstract

Speed and density in the process of finding documents and information has become mandatory, contained in information systems, to facilitate the search process or find documents and information needed, it is called information retrieval or information retrieval system, implementation of the theory applied in this study using the model method vector space, the purpose of this study is to provide general exposure to the process of finding digital documents. With the token and indexing process so that the results of the masses are found in the database using keywords, so the system will search according to the keywords input into the system, and will be compared with the data contained in the database, so that it can produce the correct information.
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.
Komparasi Algoritma Logistic Regression dan Random Forest pada Prediksi Cacat Software Rizal Prasetyo; Imam Nawawi; Ahmad Fauzi; Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (665.169 KB) | DOI: 10.54367/jtiust.v6i2.1522

Abstract

Testing becomes the standard in producing quality software, testing can be assessed through certain measures and methods, one of the benchmarks for software quality is ISO, which was made by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) , In the prediction of software defects software defect prediction error is a very bad thing, the prediction results can have an effect on the software itself. This study compares the results of the Logistic Regression Algorithm and Random Forest before and after the resampling method is applied, the test results show that Random Forest with resampling produces a higher level of accuracy. From the test results above, it can be concluded that the Random Forest with resampling method is more effective in predicting software defects
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.
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.
Komparasi Algoritma Logistic Regression dan Random Forest pada Prediksi Cacat Software Rizal Prasetyo; Imam Nawawi; Ahmad Fauzi; Ginabila
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1522

Abstract

Testing becomes the standard in producing quality software, testing can be assessed through certain measures and methods, one of the benchmarks for software quality is ISO, which was made by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) , In the prediction of software defects software defect prediction error is a very bad thing, the prediction results can have an effect on the software itself. This study compares the results of the Logistic Regression Algorithm and Random Forest before and after the resampling method is applied, the test results show that Random Forest with resampling produces a higher level of accuracy. From the test results above, it can be concluded that the Random Forest with resampling method is more effective in predicting software defects
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.
Maintainability Prediction in Eclipse Mylyn Software Program Code Using Mamdani's Fuzzy Inference System Approach Mochammad Abdul Azis; Imam Nawawi; Ahmad Fauzi; Ginabila; Ahmad Hafidzul Kahfi; Abdul Hamid
Jurnal Mantik Vol. 5 No. 2 (2021): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol5.2021.1355.pp512-516

Abstract

Software quality can be assessed using certain measures and methods, as well as using software testing. ISO is used as one of the benchmarks of software quality that has been created by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). Software testing can use metrics to increase productivity, this software is very useful in simplifying the testing process by focusing the programmer on the code quality part of the program. The ability of software to be modified includes correction, improvement or adaptation to changes in the environment, requirements, and functional specifications. Metrics can be used to measure the quality level of a model's program code based on indicators from Chidamber Kemerer (CK) by performing Maintainability Predictions which are tested on the metrics bug prediction found in the eclipse mylyn application which consists of four properties, namely WMC, DIT, NOC, and , RFCs. To be able to help carry out the process of calculating software quality based on CK Metrics on mylyn eclips data using the Mamdani fuzzy inference system, it can prove the classification into Low, Medium, High forms. In this case, the defuzzification method is confirmed using the COA (centre of area) method to determine the final value obtained from the membership function formed from the composition process of all outputs.
Co-Authors Abdul Hamid Ahamd Fauzi Ahmad Fauzi Ahmad Fauzi Ahmad Hafidzul Kahfi Akmal Dirgantara Akrom, Akrom Anak Agung Gede Sugianthara Imam Nawawi Jamhari Jamhari Mochammad Abdul Azis Rizal Prasetyo