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All Journal Jurnal Ilmiah Informatika Komputer Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika INTI Nusa Mandiri Infotek : Jurnal Informatika dan Teknologi SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Insan Journal of Innovative and Creativity

Ginabila

Universitas Bina Sarana Informatika

Author-ID : 1587610

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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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

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

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

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

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

Transformasi Sistem Electronic Assessment Management Menggunakan Metode RAD Pada Direktorat Peningkatan Mutu Tenaga Kesehatan Dany, Rahmad; Sriyadi, Sriyadi; Ginabila, Ginabila
Jurnal INSAN Journal of Information System Management Innovation Vol. 4 No. 1 (2024): Juni 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jinsan.v4i1.3613

Training Needs Assessment merupakan suatu proses yang dilakukan dalam penilaian kebutuhan pelatihan pada Direktorat Peningkatan Mutu Tenaga Kesehatan. Proses ini terkait dengan pengembangan sumber daya manusia yang ada di lingkungan Kementerian Kesehatan RI. Pada proses pengumpulan data dan penilaian TNA, ditmutunakes sering kali menghadapi sejumlah tantangan, seperti proses yang masih manual, ketidaksesuaian peserta, kurangnya data yang akurat, sulitnya mengidentifikasi prioritas kebutuhan pelatihan, serta kurangnya pemahaman admin dalam pengolahan data. Untuk itu, perancangan aplikasi ESEMA berbasis web menjadi solusi yang diusulkan. Aplikasi ini ditujukan guna memfasilitasi proses TNA tenaga kesehatan dengan lebih efektif dan efisien, sehingga dapat mengidentifikasi kebutuhan pelatihan yang diharapkan. Dalam prosesnya, Rapid Application Development menjadi metode pengembangan sistem yang digunakan dan dikombinasikan dengan bahasa pemrograman PHP. Dari transformasi sistem yang dilakukan, hasil yang diperoleh menyatakan bahwa aplikasi ESEMA sangat efektif dan mampu mengidentifikasi kebutuhan pelatihan, sehingga gap atau kesenjangan yang ada dapat dianalisa dengan baik.

KOMPARASI ALGORITMA DENGAN PENDEKATAN RANDOM UNDERSAMPLING UNTUK MENANGANI KETIDAKSEIMBANGAN KELAS PADA PREDIKSI CACAT SOFTWARE Ginabila, Ginabila; Fauzi, Ahamd
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

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 Fauzi, Ahmad; Ginabila, Ginabila
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

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.

ANALISIS SENTIMEN PERKEMBANGAN MOTOR LISTRIK MENGGUNAKAN SUPPORT VECTOR MACHINE DAN OPTIMASI PARTICLE SWARM OPTIMIZATION Ginabila, Ginabila; Fauzi, Ahmad; Pratiwi, Risca Lusiana; Fauziah, Siti; Alfianti, Zulia Imami
INTI Nusa Mandiri Vol. 19 No. 1 (2024): INTI Periode Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i1.5579

Innovation in electric motor technology such as increased range, speed, and battery endurance can attract interest from individuals fascinated by the latest advancements. Sentiment analysis enables a profound understanding of consumer perceptions towards electric motors. In this study, Support Vector Machine (SVM) is employed as a classification tool to evaluate opinions on current developments in electric motors. SVM seeks an optimal hyperplane that maximizes the distance between sentiment categories. The development of sentiment analysis methods utilizes SVM with Particle Swarm Optimization (PSO) to successfully achieve an accuracy of 80.33% and obtain a Good Classification category based on ROC Curve results. This research provides insights into consumer perceptions of electric motor technology, offering valuable feedback for manufacturers in the development of superior electric motor products. Leveraging sentiment analysis, manufacturers can enhance product improvements, increase quality, and expand functionality to meet the evolving market demands.

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

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.

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

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.

Co-Authors Abdul Hamid Ahmad Fauzi Ahmad Fauzi Ahmad Hafidzul Kahfi Akmal Dirgantara Akrom, Akrom Angga Kusuma Azis, Mochammad Abdul Dany, Rahmad Eko Yulianto Fauzi , Ahmad Fauzi Ahmad Muda Fauzi, Ahamd Hafidinulloh Fitrohan Imam Nawawi Imam Nawawi, Imam Indra Chaidir, Indra Isroni Isroni Jamhari Jamhari Mochammad Abdul Azis Muhammad Iqbal Prasetyo, Rizal Pratiwi, Risca Lusiana Rayhan Dharmawan Risca Lusiana Pratiwi Siti Fauziah Sriyadi Sriyadi, Sriyadi Zulia Imami Alfianti Zulia Imami Alfianti

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