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All Journal Jurnal Ilmiah Informatika Komputer Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Mantik Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Infotek : Jurnal Informatika dan Teknologi
Ginabila Ginabila
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering 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.
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.
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.
Analisis Sentimen Terhadap Pemutar Musik Online Spotify Dengan Algoritma Naive Bayes dan Support Vector Machine Ginabila Ginabila; Ahmad Fauzi
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 6, No 2 (2023): Juli
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v6i2.180

Abstract

Abstrak: Manusia memiliki kebutuhan preferensi musik yang yang sangat beragam, oleh karena itu pemutar musik online menjadi salah satu solusi untuk memenuhi kebutuhan ini dengan menyediakan katalog musik yang luas. Analisis sentimen adalah proses untuk mengevaluasi dan mengklasifikasikan sentimen atau perasaan di balik teks atau data yang diberikan. Dalam konteks ini, analisis sentimen dilakukan pada pemutar musik online Spotify. Dua algoritma yang umum digunakan untuk analisis sentimen adalah Naive Bayes dan Support Vector Machine (SVM). Kedua algoritma ini dapat diterapkan dalam analisis sentimen pada pemutar musik online. Data teks seperti ulasan atau komentar pengguna dikumpulkan dan dilabeli dengan sentimen yang sesuai. Hasil dari penelitian menggunakan kedua algoritma ini menghasilkan nilai akurasi yang hampir sama baiknya. Algoritma Support Vector Machine menghasilkan tingkat akurasi sebesar 82,42%, sedangkan untuk Algoritma Naive Bayes mencapai 84,73%.Kata kunci: Analisis Sentimen, Naive Bayes, Support Vector MachineAbstract: Humans have diverse music preferences and online music players are a solution to meet these needs by providing a wide music catalog. Sentiment analysis is the process of evaluating and classifying sentiments or feelings behind given texts or data. In this context, sentiment analysis is performed on Spotify online music players. Two common algorithms used for sentiment analysis are Naive Bayes and Support Vector Machine (SVM). Both algorithms can be applied in sentiment analysis for online music players. Text data such as user reviews or comments are collected and labeled with corresponding sentiments. The results of the research using both algorithms yielded similar high accuracy. The Support Vector Machine algorithm achieved an accuracy rate of 82.42%, while the Naive Bayes algorithm reached 84.73%.Keywords: Sentiment Analysis, Naive Bayes, Support Vector Machine
Application of the Deep Neural Networks Model in Analyzing ChatGPT Application Sentiment Ahmad Fauzi; Indra Chaidir; Muhammad Iqbal; Ginabila Ginabila
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3432

Abstract

AI has been able to intelligently mimic human behavior and has been applied in various contexts, including healthcare for more efficient patient care. One of the prominent trends in AI is advanced language models such as ChatGPT developed by OpenAI. The effectiveness of ChatGPT in finding and fixing bugs in computer code is a subject of debate, depending on the task, training data, and system design. The popularity of social media platforms, particularly Twitter, as a data source for text analysis has increased interest in sentiment analysis. This study explores sentiment towards the ChatGPT application using a dataset of 50,000 tweets. Sentiment analysis is performed using a deep neural network (DNNs) approach to achieve optimal accuracy. Deep learning models are known to have high predictivity and efficient training time. Through this experiment, we aim to gain insight into how the public views ChatGPT in three sentiment categories: positive, negative, and neutral. DNN (Deep Neural Network) is proposed because of its good performance and can shorten the amount of training time. The results with the model used in this study, namely CNN and LSTM both achieve an accuracy value of more than 90%: Where CNN obtains an accuracy value of 91.12% and LSTM obtains an accuracy of 90.84%.
PENERAPAN METODE K-MEANS DALAM PENGKLASTERAN WILAYAH DI INDONESIA BERDASARKAN PEMBERIAN ASI EKSKLUSIF PADA BAYI Zulia Imami Alfianti; Ginabila Ginabila; Ahmad Fauzi
Jurnal Ilmiah Informatika Komputer Vol 29, No 3 (2024)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2024.v29i3.12781

Abstract

Breast milk is a fluid that comes out of a mother's breast glands which contains a variety of nutrients needed to support the development and growth of toddlers. Exclusive breast milk (ASI) is breastfeeding that is not accompanied by any other food or drink supplementation except medication. Currently, exclusive breastfeeding is influenced by many factors, namely working mothers, low maternal education, incessant advertising about the use of formula milk, breast milk not coming in and many other factors causing not all babies to receive exclusive breast milk. In this research, regional clustering will be carried out based on the percentage of exclusive breastfeeding for 6 month old babies from 34 provinces in Indonesia. Clustering was carried out to group 34 provinces in Indonesia into provinces with high, medium and low cases. The results of this research are that 31% of provinces have the highest percentage, 40% have a medium percentage and 29% have a low percentage.
Co-Authors Abdul Hamid Ahmad Fauzi Ahmad Hafidzul Kahfi Akmal Dirgantara Akrom, Akrom Imam Nawawi Indra Chaidir, Indra Jamhari Jamhari Mochammad Abdul Azis Muhammad Iqbal Zulia Imami Alfianti