Article Per Year (5 Year)
p-Index From 2020 - 2025
3.79
P-Index
This Author published in this journals
All Journal Syntax Jurnal Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Sistem dan Informatika JIKO (Jurnal Informatika dan Komputer) Informatika Pertanian Jurnal Sains dan Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Informatika Universitas Pamulang J-SAKTI (Jurnal Sains Komputer dan Informatika) EDUMATIC: Jurnal Pendidikan Informatika JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknologi Informatika dan Komputer Jurnal Ilmiah Wahana Pendidikan International Journal of Basic and Applied Science J-SAKTI (Jurnal Sains Komputer dan Informatika) CEBONG Journal Jurnal Informatika Polinema (JIP)
Budi Arif Dermawan
Universitas Singaperbangsa Karawang
Religion Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

Published : 29 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Jurnal Informatika Universitas Pamulang

 1 
Klasifikasi Ulasan Pengguna Zoom Cloud Meetings Menggunakan Metode Information Gain dan Naïve Bayes Classifier Rohanah, Aan; Dermawan, Budi Arif; Purnamasari, Intan
Jurnal Informatika Universitas Pamulang Vol 6, No 2 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i2.10728

Abstract

During the Covid-19 pandemic, ZOOM Cloud Meetings video conference application was felt to be of benefit. This is due to limited direct physical contact and all activities are carried out virtually from home. So that during the pandemic the ZOOM Cloud Meetings application was widely downloaded by various groups of people, and reaped various responses from users who complained on the Google Play Store. Complaints from user reviews can contain valuable information for application development. To obtain this information, user reviews of applications are classified based on the ISO 9126 category. ISO 9126 is one of the standards for evaluating software based on user satisfaction. The ISO standards used are functionality, efficiency, reliability, maintainability, portability, and usability. This study uses the CRISP-DM research methodology and for modeling in the classification applies the Naïve Bayes Classifier and Information Gain. Information Gain is used for word conversion and data transformation from categorical to numeric and to reduce data dimensions. Naïve Bayes is able to predict data to enter the classification class. Testing of the model applies manual and automatic k-fold cross validation testing. The results of the classification of the model in manual testing produce the best accuracy of 79% and the k-fold cross validation test is 80.51%. The existence of this accuracy value is expected to be a reference for developing the ZOOM Cloud Meetings application.
Sentimen Analisis Komentar Toxic pada Grup Facebook Game Online Menggunakan Klasifikasi Naïve Bayes Renaldy Permana Sidiq; Budi Arif Dermawan; Yuyun Umaidah
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6571

Abstract

Toxic comments are comments made by social media users that contain expressions of hatred, condescension, threatening, and insulting. Social media users who are on average still teenagers with a nature that still cannot be controlled completely becomes a matter of great concern when they comment, their comments can be studied as text processing. Sentiment analysis can be used as a solution to identifying toxic comments by dividing them into two classifications. Where the data used amounted to 1,500 taken from social media Facebook in the private group Arena of Valor community. The dataset is divided into 2 classes: toxic and non-toxic. This research uses Naive Bayes with TF-IDF transformation and Information Gain feature selection and use distribution ratio 80:20. It will be compared the results of the evaluation where Naive Bayes without transformation, using TF-IDF transformation, and TF-IDF using Information Gain feature selection. The results of the comparison of evaluations from confusion matrix that have been carried out obtained the best classification model is to use the ratio of training and testing data 80:20 with TF-IDF transformation resulting in an accuracy of 75%, precision of 63%, recall of 67%, and F-measure of 64%.
Penerapan Fuzzy Inference System untuk Sistem Pemantauan Kualitas Air pada Budidaya Cheerax Quadricarinatus Budi Arif Dermawan; Adhi Rizal; Anis Fitri Nur Masruriyah
Jurnal Informatika Universitas Pamulang Vol 8, No 1 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i1.29214

Abstract

Cheerax quadricarinatus (Redclaw) becomes a fishery commodity that has high selling value with various advantages in terms of cultivation. In the Redclaw cultivation process, water quality is one of the indicators that require attention. Flawed water quality affects the conditions when the lobsters molt. In addition, shoddy water quality also impacts the slow growth rate and high mortality during ontogeny. The level of water quality is influenced by the parameters of Temperature, Potential of Hydrogen (pH), Ammonia, and Total Dissolved Solid (TDS). The level of water quality requires monitoring in real-time with the aim of being able to find out the latest conditions according to the category of aquaculture pond. Water quality monitoring is carried out by implementing a Fuzzy Inference System in a Water Quality Monitoring System based on a Wireless Sensor Network (WSN) and the Internet of Things (IoT). The water quality monitoring system is running well, marked by all sensors being able to send parameter values and the monitoring dashboard being able to display all parameter values along with water quality and condition values. The water quality level results show that the pond's cultivation habitat is in a suitable category, indicated by a water quality value of more than 90%. The level of water quality can be represented as suitability for Redclaw habitat to increase growth.
Co-Authors Adhi Rizal Agung Siswoyo Aini Lailla Asri, Nur Alfafisabil, Wahyu Alfanda Novebrian Maharadja Aliffia Kulsumarwati Alrasyid , Wildan Anggara, Jerry Anis Fitri Nur Masruriyah Apriade Voutama Betha Nurina Sari Carudin Cika Oktavia Daffa Rafif Agustian Dwi Ely Kurniawan Eddy Ryansyah Erliza Hambali Fuza Putra Arwanda Haerudin Hannie, Hannie Hengki Tamando Sihotang Ibnu Adam, Riza Ikhsal, Muhammad Fachry Intan Purnamasari Iqbal Maulana Iqbal Maulana Isy Karima Fauzia LILIK BUDIPRASETYO Loemongga Oktaria Sihombing Muhammad Hilmi Syarif Nana Mulyana Maghfur Natcha Kwintarini Suparman Nur Padilah, Tesa Nurul Afifah Arifuddin Permatasari, Ismi Aprilianti Putri Dwi Rahayu Putri, Dyas Rahma Rasenda, Rasenda Renaldy Permana Sidiq Rijal Abdulhakim Riza Ibnu Adam, Riza Ibnu Rizky A, Galih Prakoso Rohanah, Aan Sofi Defiyanti Sukarno Wijaya, Nanda Susilawati Susilawati Syafi'i, Muhammad Tesa Nur Padilah Tesa Nur Padilah Wahyu Alfafisabil Yuyun Umaidah