Article Per Year (5 Year)
p-Index From 2021 - 2026
7.973
P-Index
This Author published in this journals
All Journal Teknika Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan INTECOMS: Journal of Information Technology and Computer Science Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Kaputama (JIK) Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Applied Engineering and Technological Science (JAETS) Jurnal Teknik Elektro dan Komputasi (ELKOM) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Sistem Komputer & Kecerdasan Buatan Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Nasional (JPN) Indonesia Jurnal Cahaya Mandalika International Journal for Applied Information Management JUTECH : Journal Education and Technology AJAD : Jurnal Pengabdian kepada Masyarakat International Journal Software Engineering and Computer Science (IJSECS) Aptekmas : Jurnal Pengabdian Kepada Masyarakat KNOWLEDGE: Jurnal Inovasi Hasil Penelitian dan Pengembangan ABDINE Jurnal Pengabdian Masyarakat Journal of Artificial Intelligence and Digital Business CKI On Spot SmartComp Jurnal Pengabdian Nasional (JPN) Indonesia kawanad Journal Innovations Computer Science Informasi interaktif : jurnal informatika dan teknologi informasi
Betty Yel, Mesra
ST Ilmu Komputer Cipta Karya Informatika
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 59 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 59 Documents
Search

 2   3   4   5   6 
Media Interaktif Pembelajaran Berbasis Multimedia menggunakan Adobe Flash untuk TK dan PAUD Aryanti, Putri Gea; Lailany, Afyra Ar’bah; Amelia, Ika; Regita, Anggit Nur Hannaa; Setiawan, Kiki; Yel, Mesra Betty
AJAD : Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/ajad.v4i1.282

Abstract

Preschool (TK) or Early Childhood Education (PAUD) plays an essential role in shaping the foundation of knowledge, attitudes, and skills in children. The primary focus of early childhood education goes beyond stimulating, guiding, nurturing, and providing learning activities at school. Media learning, incredibly educational interactive media, becomes crucial in motivating and educating children. This study focuses on developing interactive multimedia-based learning media using Adobe Flash for TK and PAUD at TK Bamadita Rahman. Through interviews with the school principal and teachers, a needs analysis was conducted to evaluate the implementation of interactive learning media. The research addresses conventional learning challenges by designing an engaging, child-friendly interactive media application. The objectives include creating interactive media, serving as a reference for play-based learning activities, implementing interactive media, and assessing its effectiveness in TK and PAUD Bamadita Rahman. The study concludes that the learning application using Adobe Flash has been successfully designed, has the potential to cultivate an interest in animation among the younger generation, and enhances the efficiency of the teaching and learning process.
Sistem Inventory Barang Gudang Berbasis Web Studi Kasus Yayasan Indonesia Care Adzani, Adinda Mutiara; Mulya, Citra Pricylia Ananda; Ahluna, Faza; Febrianti, Syafira; Akbar, Yuma; Yel, Mesra Betty
AJAD : Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 1 (2024): APRIL 2024
Publisher : Divisi Riset, Lembaga Mitra Solusi Teknologi Informasi (L-MSTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59431/ajad.v4i1.284

Abstract

Along with the increasingly rapid development of technology, this can be characterized by increasingly sophisticated technology. Using computers as a tool in carrying out work in information technology is becoming increasingly common and developing in all fields. This research discusses implementing an equipment inventory information system at the Indonesia Care Foundation to increase the efficiency of managing equipment availability. This study includes requirements analysis, system design, and implementation of information technology-based solutions to monitor and manage equipment more effectively. Data collection methods involve interviews, observation, and documentation analysis. The research results show that implementing an inventory information system provides significant benefits, including increased recording accuracy, more efficient stock management, and better monitoring of equipment use and maintenance. This implementation's success positively contributes to operational efficiency and improves equipment management performance at the Foundation Indonesia Care.
Prediction of palm oil production using hybrid decision tree based on fuzzy inference system Tsukamoto Tundo, Tundo; Saifullah, Shoffan; Yel, Mesra Betty; Irawansah, Opi; Mubarak, Zulfikar Yusya; Saidah, Andi
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7773

Abstract

This research addresses the challenge of optimizing rule creation for palm oil production at PT Tapiana Nadenggan. It deals with the complexity of diverse agricultural variables, environmental factors, and the dynamic nature of palm oil production. The existing problem lies in the limitations of conventional decision tree models—J48, reduced error pruning (REP), and random—in capturing the nuanced relationships within the intricate palm oil production system. The study introduces hybrid decision tree models—specifically J48-REP, REP-Random, and Random-J48—to address this challenge via combination scenarios. This approach aims to refine and update the rule creation process, enabling the recognition of nuanced performance processes within the selected decision tree combinations. To comprehensively tackle this challenge and problem, the study employs Tsukamoto’s fuzzy inference system (FIS) for a sophisticated performance comparison. Despite the complexity, intriguing results emerge after the forecasting process, with the standalone J48 decision tree achieving 85.70% accuracy and the combined J48-REP excelling at 93.87%. This highlights the potential of decision tree combinations in overcoming the complexities inherent in forecasting palm oil production, contributing valuable insights for informed decision-making in the industry.
Analisis Sentimen Tanggapan Publik Mengenai E-Tilang Melalui Twitter Menggunakan Algoritma K-Nearest Neighbor Septiansyah, Ade; Yel, Mesra Betty; Akbar, Yuma
TEKNIKA Vol. 18 No. 2 (2024): Teknika Juli - Desember 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12773163

Abstract

Suatu kota harus memiliki sistem transportasi yang baik. Sistem tilang elektronik pemerintah untuk mengawasi lalu lintas disebut e-tilang. Banyak pelanggaran lalu lintas yang terjadi di jalan raya yang cenderung menyebabkan kecelakaan dan menambah kemacetan. Beberapa faktor penyebab pelanggaran lalu lintas termasuk ketidakpatuhan individu terhadap peraturan lalu lintas, misalnya larangan berhenti dan parkir di mana pun. Tujuan dari penelitian adalah untuk mengidentifikasi bagaimana pandangan masyarakat Indonesia tentang tilang elektronik dalam peneletian ini digambarkan melalui analisis sentimen tentang tilang elektronik dan mengelompokkan berbagai jenis komentar. Twitter adalah platform media sosial yang ideal untuk menyampaikan opini karena mudah digunakan, topik terkini, dan memungkinkan komentar. Setelah data dikumpulkan dari Twitter, preprocessing dilakukan untuk membersihkan data, tokenizing, case normalization, stopword, dan stemming. Selain itu, seleksi mengurangi noise dari label yang tidak relavan. Dataset terdiri dari 1.762 baris record tweets diklasifikasi menghasilkan dua kelas data kelas data positif dan kelas data negatif dengan total 1.342 data. Dalam studi ini, algoritma mesin pengklasifikasi K-Nearest Neighbor digunakan data yang sudah ada dari kelas data ini digunakan sebagai data pelatihan untuk mesin pengklasifikasi. Hasil evaluasi menunjukkan akurasi rata-rata 75,41%.
Analisa Sentimen Menggunakan Algoritma C4.5 Dan Naïve Bayes Dengan Topik Artificial Intelligence Pada Media Sosial Twitter (X) Prasetyo, Aji Dwi; Yel, Mesra Betty
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 5 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i5.11729

Abstract

Artificial intelligence (AI) atau yang biasa disebut dengan kecerdasan buatan manusia merupakan hal yang cukup ramai diperbincangkan dalam masyarakat saat ini dengan dampak yang positif yang signifikan dapat membantu meringankan pekerjaaan manusia. Namun disisi lain artificial intelligence juga memberikan dampak yang negatif yaitu dapat dapat mengambil alih pekerjaan manusia dan berpotensi menimbulkan kekacauan ekosistem informasi akibat dari propaganda yang berisi berita bohong dan disinformasi. Tujuan dari penelitian ini untuk mengetahui persepsi masyarakat terhadap dampak perkembangan artificial intelligence apakah positif atau negatif serta mencari nilai akurasi dari kinerja metode yang digunakan. Hasil dari penelitian ini dapat dijadikan referensi bagi pemerintah untuk mendukung pengambilan keputusan mengenai langkah yang dapat diambil dalam menghadapi dampak perkembangan artificial intelligence berdasarkan sudut pandang pada masyarakat luas. Algoritma yang digunakan adalah C4.5 dan Naïve bayes. Dari kedua metode ini digunakan sebagai hasil akhir akurasi dari penelitian ini dan menjadikan perbandingan nya antara satu sama lain.
Klasifikasi Jajanan Tradisional Jawa Tengah Dengan Metode Transfer Learning Dan MobileNetV2: Metode Transfer Learning Dan MobileNetV2 Aloisius Awang Hariman; Dadang Iskandar Mulyana; Mesra Betty Yel
Informasi Interaktif : Jurnal Informatika dan Teknologi Informasi Vol 8 No 1 (2023): JII Volume 8, Number 1, Januari 2023
Publisher : Program Studi Informatika Fakultas Teknik Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jii.v8i1.15

Abstract

Perkembangan zaman di Indonesia telah membawa perubahan sejarah budaya, salah satunya adalah makanan atau jajanan tradisional. Jajanan tradisional merupakan makanan khas dari nenek moyang dan biasanya digunakan untuk acara atau sebuah tradisi, Masyarakat di Indonesia sudah cukup mengenal berbagai jenis jajanan tradisional dari daerah masing-masing namun untuk mengenal jajanan tradisional dari daerah lain dapat dibilang kurang memahami. Banyaknya jajanan tradisonal yang ada di Indonesia khususnya di pulau Jawa membuat peneliti tertarik untuk membuat program pengenalan jenis jajanan tradisional yang ada di Jawa Tengah berdasarkan dataset foto dengan 6 jenis jajanan tradisional yaitu Grontol, Lanting, Lumpia, Putu Ayu, Serabi Solo dan Wajik menggunakan metode Transfer Learning. Implementasi pengenalan citra ini dilakukan dengan memanfaatkan Pre-Trained model MobileNetV2 yang diambil fitur ektrasinya kemudian training CNN berjalan pada aplikasi Google Collaboratory dan Tensorflow. Dataset yang digunakan dalam pengujian sebanyak 1800 data training atau sebesar 80% dan 450 data testing atau sebesar 20% dengan melakukan pengujian sebanyak 50 kali dan batch size sebesar 32, maka diperoleh hasil akurasi sebesar 99,11% nilai loss sebesar 0.06. Keywords : jajanan tradisional, CNN, MobileNetV2, transfer learning, tensorflow
Optimasi Penerapan Metode Text Recognition Dalam Fitur Catatan Otomatis Berbasis Mobile Mulyana, Dadang Iskandar; Yel, Mesra Betty; Rahmanto, Muhammad Dzaky
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.634

Abstract

This study discusses the optimization of Machine Learning Kit Text Recognition in creating an automatic note feature based on mobile devices. Machine Learning Kit Text Recognition is used to recognize text captured from photos taken by users. In this study, a mobile application was developed to allow users to create automatic notes by taking pictures of documents or texts, which are then recognized and transformed into editable digital text. This feature can help users to create notes more quickly and easily, as well as avoid errors in manually typing the text. In addition, the test results show that Machine Learning Kit Text Recognition is capable of recognizing text with fairly high accuracy, effectively recognizing text from various texts and fonts, supporting uncommon languages, preserving user privacy, and being able to perform text recognition processes offline or with more efficient resources. Therefore, the automatic note feature can run well on mobile applications built using Machine Learning Kit Text Recognition technology.
Sentiment Analysis of Doctor’s Responses to Patient Inquiries in a Medical Chatbot: A Logistic Regression Approach Yel, Mesra Betty; Rodhiyah
International Journal for Applied Information Management Vol. 4 No. 2 (2024): Regular Issue: July 2024
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijaim.v4i2.80

Abstract

This study addresses the challenge of improving doctor-patient communication in medical chatbot systems by integrating sentiment analysis to classify doctor responses as positive or negative. The primary objective was to develop a model that enhances the emotional intelligence and appropriateness of chatbot interactions using Logistic Regression. The model achieved 98.63% accuracy, 99.68% precision, 95.90% recall, and 97.75% F1-score, demonstrating its high reliability in classifying sentiments with minimal misclassifications. While the model performs well, further improvements could focus on reducing false negatives to increase recall. The implications of this research are significant for digital healthcare, as the model enables chatbots to provide more empathetic, context-aware responses, improving patient engagement and overall communication. The novelty of this study lies in applying sentiment analysis within medical chatbot systems, contributing to the growing field of emotional intelligence in digital healthcare. The findings highlight the potential of sentiment analysis to enhance patient interactions, making medical chatbots more effective and human-like. This study provides a solid foundation for further advancements in healthcare chatbots, demonstrating the potential of machine learning to improve the quality of doctor-patient communication in a digital context.
Forecasting Beef Production with Comparison of Linear Regression and DMA Methods Based on n-th Ordo 3 Tundo, Tundo; Yel, Mesra Betty; Nugroho, Agung Yuliyanto
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.24706

Abstract

Beef is considered a high-value commodity because it is an important food source of protein. Interest in beef is increasing along with increasing people's incomes and awareness of the importance of fulfilling nutrition. Demand for beef is expected to continue to increase. According to the Central Statistics Agency (CSA), beef production in Jakarta shows an increasing trend every year. In the last 10 years, beef production has increased significantly, but in 2020 there was a decrease in production of 7,240.68 tons due to the lockdown due to the corona virus outbreak. After that, in 2021, production reached 16,381.81 tons and will continue to increase in 2022 and 2023. Based on the above phenomenon, the aim of this research is to support the success and sustainability of the beef industry by ensuring that supply matches demand, resources are used optimally, and risks can be managed well. To predict beef production, an accurate method, model or approach is needed. One way to predict beef production in Jakarta is to use the Linear Regression and Double Moving Average (DMA) methodsThe way the Linear Regression and DMA methods work is to forecast based on concepts and properties. The concepts and properties of Linear Regression are models, functions, estimates and forecasting results, while DMA performs time series analysis based on moving averages. After analysis using MAPE, it was found that the algorithm that had the smallest error value was the linear regression algorithm with a percentage for the monthly period of 15% while for the year period it was 17% compared to DMA. So in this case it would be very appropriate to use the Linear Regression method from the error values obtained.
ANALISIS SENTIMEN PDI PERJUANGAN PASCA PILPRES 2024 DI JAKARTA TIMUR DENGAN NAÏVE BAYES Marsan, Alvin Cahya Pratama; Yel, Mesra Betty
KNOWLEDGE: Jurnal Inovasi Hasil Penelitian dan Pengembangan Vol. 5 No. 3 (2025)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/knowledge.v5i3.6782

Abstract

This study aims to determine the level of trust of the people of East Jakarta towards PDI Perjuangan after the 2024 Presidential General Election (Pilpres) and identify the tendency of sentiment formed, both positive, negative, and neutral. The background of this research is based on the complex dynamics of national politics, including the controversy over the candidacy of Gibran Rakabuming Raka as vice president, which caused pros and cons among the public and had the potential to influence public perception of PDI Perjuangan as the main supporting party. This study uses a quantitative approach with data collection techniques through a Likert scale questionnaire survey and essay questions distributed to respondents in the East Jakarta area. The data obtained is then processed through the text preprocessing stage, feature extraction using the Term Frequency–Inverse Document Frequency (TF-IDF) method, and analyzed using the Naïve Bayes algorithm with the help of the RapidMiner application. The results of the study show that the majority of public sentiment tends to be positive, followed by neutral and negative sentiments. This shows that PDI Perjuangan still has a strong support base in East Jakarta despite the controversial national political dynamics. The findings of this study not only provide a comprehensive picture of local political perceptions, but can also be used as a strategic reference in the preparation of political communication patterns, strengthening the party's image, and planning the legislative campaign of PDI Perjuangan in the 2029 elections. ABSTRAK Penelitian ini bertujuan untuk mengetahui tingkat kepercayaan masyarakat Jakarta Timur terhadap PDI Perjuangan pasca Pemilihan Umum Presiden (Pilpres) 2024 serta mengidentifikasi kecenderungan sentimen yang terbentuk, baik positif, negatif, maupun netral. Latar belakang penelitian ini didasari oleh dinamika politik nasional yang cukup kompleks, termasuk kontroversi pencalonan Gibran Rakabuming Raka sebagai wakil presiden, yang menimbulkan pro dan kontra di kalangan publik serta berpotensi memengaruhi persepsi masyarakat terhadap PDI Perjuangan sebagai partai pengusung utama. Penelitian ini menggunakan pendekatan kuantitatif dengan teknik pengumpulan data melalui survei kuesioner skala Likert dan pertanyaan esai yang disebarkan kepada responden di wilayah Jakarta Timur. Data yang diperoleh kemudian diproses melalui tahapan preprocessing teks, ekstraksi fitur dengan metode Term Frequency–Inverse Document Frequency (TF-IDF), serta dianalisis menggunakan algoritma Naïve Bayes dengan bantuan aplikasi RapidMiner. Hasil penelitian memperlihatkan bahwa mayoritas sentimen masyarakat cenderung positif, diikuti dengan sentimen netral dan negatif. Hal ini menunjukkan bahwa PDI Perjuangan masih memiliki basis dukungan yang cukup kuat di Jakarta Timur meskipun terdapat dinamika politik nasional yang kontroversial. Temuan penelitian ini tidak hanya memberikan gambaran komprehensif mengenai persepsi politik lokal, tetapi juga dapat dijadikan sebagai acuan strategis dalam penyusunan pola komunikasi politik, penguatan citra partai, serta perencanaan kampanye legislatif PDI Perjuangan pada Pemilu 2029.
Co-Authors Abdulloh Adzani, Adinda Mutiara Ahluna, Faza Ahmad Bustomi Zuhari Ahmad Bustomi Zuhari Ahmad Saepudin Akbar, Yuma Aldi Sitohang Almazar, Nufaisa Aloisius Awang Hariman Alwanto, Hilmi Amat Solihin Amelia, Ika Angel, Gadies Ari Ramadhan Arinal, Veri Aris Sufriman Aryanti, Putri Gea Azzizah, Putri Salfa Dhiyaa B, Muhamad Hasbi Toharudin Bobby Arvian James Candra Milad Ridha Eislam Dadang Iskandar Mulyana` Dewi Riyanti Wibowo Eka Maheswara Eri Novitasari F, Joe Renaldy Fadhil Khanifan Achmad Febrianti, Syafira Fernanda Adhipramana Ferry Fajar Pratama Franido, Richard Heny Nengsih Herdiyansyah herdi Hartanto Hutabarat, Joey Abdiner Parlindungan Ikhwanul Kurnia Rahman Imantara, Alaqsha Gilang Jodi Juliansah Kamali, Muhamad Fawaz Kastum Kastum Lailany, Afyra Ar’bah Mahyuddin K. M Nasution Mainia Mayasari Marsan, Alvin Cahya Pratama Maulida, Aulia Miftahul Huda Moerdyanto, Adjie Wongso Mubarak, Zulfikar Yusya Muhamad Ikbal Muhammad Dzaky Rahmanto Muhammad Faizal Lazuardi Muhammad Syahrul Fattah Ramadhan Mulya, Citra Pricylia Ananda Mutia Ramadhan Nandang Sutisna Nesti Lutfianti Nugroho, Agung Yuliyanto Nurfaishal, Muhammad Dzaky Nurhidayanti, Dian Oka Prasetiyo Okta Saputra Oky Tria Saputra7 Opi Irawansah, Opi Pakpahan, Gabriel Alezhandro Pane, Ropindo Pelix Prasetyo, Aji Dwi Putra, Adaffi Aditya Putri S, Dhiyah Labibah Nauli Rahmanto, Muhammad Dzaky Rasiban Regita, Anggit Nur Hannaa Richard Franido Rifai, Hanna Sabilla Rodhiyah Rosiana, Grace Lolita Sahrul Hidayat Saidah, Andi Saifullah, Shoffan Sari Agustia Ningtyas Sarimole, Frencis Matheos Septiansyah, Ade Setiawan, Kiki Sfenrianto Sfenrianto Sfenrianto, Sfenrianto Siahaan, Rizkyrino Ronaldhino Sinaga, Putri Cahyani Sopan Adrianto Sutisna Sutisna Tafonao, Rekardius Tri Wahyudi Tundo, Tundo Untung Wahyudi Wahyu Hidayat Wijayanto, Willy Yusuf, Musalim Zaeny Miftah