Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

7.076

P-Index

This Author published in this journals

All Journal Media Statistika JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Seminar Nasional Informatika (SEMNASIF) JOURNAL OF APPLIED INFORMATICS AND COMPUTING PINTER : Jurnal Pendidikan Teknik Informatika dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) bit-Tech Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Informasi dan Teknologi JATI (Jurnal Mahasiswa Teknik Informatika) G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems ESTIMASI: Journal of Statistics and Its Application Jurnal Statistika dan Matematika (Statmat) Journal of Advanced in Information and Industrial Technology (JAIIT) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Journal of Technology and Informatics (JoTI) International Journal of Data Science, Engineering, and Analytics (IJDASEA) International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of Information Systems and Technology Research Journal of International Conference Proceedings Jurnal Teknik Terapan (J-TETA) Journal of Data Mining and Information Systems Parameter: Jurnal Matematika, Statistika dan Terapannya Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal PETISI (Pendidikan Teknologi Informasi) Joong-Ki Jurnal Pengabdian Masyarakat SENSASI

Kartika Maulida Hindrayani

Universitas Pembangunan Nasional Veteran Jawa Timur

Author-ID : 1333222

Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

Published : 61 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

Penerapan Cross Validation sebagai Analisis Sentimen Pelayanan Publik Kereta Api Lokal Daop 8 Menggunakan Metode Multinomial Naïve Bayes Risnaldy Novendra Irawan; Kartika Maulida Hindrayani; Mohammad Idhom
G-Tech: Jurnal Teknologi Terapan Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i2.4117

Dalam menyediakan layanan yang efisien dan berkualitas untuk Masyarakat pada sektor transportasi kereta api wilayah daerah operasional 8 Surabaya, perlu dilakukan langkah untuk memenuhi harapan pengguna kereta api subsidi. Penelitian ini bertujuan untuk mengetahui pengaruh cross validation terhadap metode Multinomial Naïve Bayes dalam analisis sentimen menggunakan metode 10-fold cross validation. Langkah-langkah preprocessing data dilakukan sehingga didapatkan data sebanyak 1123 komentar dengan dua kelas yaitu kelas positif sebanyak 778 komentar dan negatif sebanyak 345 komentar. Analisis dilakukan sebanyak 2 kali dengan proses validasi 10-fold cross validation dan pengujian Multinomial Naïve Bayes. Berdasarkan hasil pengujian Multinomial Naïve Bayes menggunakan data uji sebanyak 225 data, didapatkan 14 data positif dan 160 data negatif yang ditinjau dari performa pengujian terbaik pada parameter nilai validasi fold = 1. Hasil akhir didapatkan nilai akurasi 77%, presisi 81%, recall 77%, dan f1 score 71%, yang mengungkapkan bahwa model efektif dalam mengklasifikasi komentar negatif dari kesluruhan data uji.

Identifikasi Penyakit Daun Jeruk Siam Menggunakan Convolutional Neural Network (CNN) dengan Arsitektur EfficientNet Burhan Syarif Acarya; Amri Muhaimin; Kartika Maulida Hindrayani
G-Tech: Jurnal Teknologi Terapan Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i2.4120

Jeruk siam menjadi salah satu komoditas hortikultura yang memegang peranan utama dalam sektor pertanian Indonesia dengan jumlah produksi yang mencapai 2 juta ton setiap tahunnya. Namun, produksi jeruk siam rentan terhadap serangan hama dan penyakit, terutama pada bagian daun. Penyakit yang umum terjadi termasuk Blackspot Leaf, Canker Leaf, Greening Leaf, Powdery Mildew, dan Citrus Leafminer. Pada umunya identifikasi penyakit pada tanaman jeruk dilakukan secara manual sehingga penentuan penyakit cenderung subyektif. Oleh karena itu, diperlukan solusi otomatis dalam mendeteksi penyakit pada daun jeruk. Tujuan penelitian yaitu untuk mengidentifikasi penyakit yang menyerang daun jeruk menggunakan metode deep learning yaitu CNN dengan arsitektur EfficientNetB3. Dataset yang digunakan adalah citra penyakit daun jeruk yang diambil langsung dari kebun jeruk yang dibagi menjadi 6 kelas seperti pada penyakit yang disebutkan di atas. Hasil penelitian menggunakan skenario epoch 10 dengan optimizer Adam memperoleh hasil akurasi terbaik yaitu 0,98 (98%).

Development of Brand Awareness Through Social Media Marketing of UMKM Fried Chicken in Medokan Ayu Surabaya Kartika Maulida Hindrayani; Tresna Maulana F; Imelda Widya Ningrum; Aisyah Kirana Putri Isyanto
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4139

The development of information technology has many benefits for partner actors to make processes automatic in increasing productivity and marketing. Marketing management in today's technological world requires a strategy for disseminating information and expanding marketing targets. Skills in using social media as a digital marketing tool can increase consumers or customers' ability to recognize and remember a product being promoted. This will also increase brand awareness. The method used is a development method with observation steps in the field, identifying partner’s problems and weaknesses, offering solutions to partners, designing training materials, implementing training material designs and integrating materials. The results of the development of brand awareness using social media, we use Instagram Platform and Google Review. Hopefully this will raise awareness of the UMKM Fried Chicken with its franchise located in Medokan Ayu. Good relations, complete explanations and clear communication with partners will support marketing development through brand awareness through social media.

ANALISIS SENTIMEN KEPUASAN PELAYANAN TRANSPORTASI ONLINE GOJEK MENGGUNAKAN ALGORITMA EXTREME LEARNING MACHINE Riskiyah, Ameliyah; Fahrudin, Tresna Maulana; Hindrayani, Kartika Maulida
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.714

With the rapid advancement of technology, online transportation has become the main solution for many people in Indonesia to travel easily and efficiently. Companies such as GOJEK are constantly innovating to improve their services, resulting in many responses and reviews from users. This research aims to analyze customer satisfaction with these online transportation services by analyzing the sentiment of user opinions on the Twitter platform. Sentiment analysis plays a very important role in decision making by classifying user reviews. Data was retrieved through a crawling process using specific keywords related to each service. The data preprocessing process includes case folding, tokenizing, normalization, stemming, filtering, and convert negation. This aims to clean and prepare the data so that it can be processed using the algorithm better. This process includes removing irrelevant elements from the text data, converting the text into a consistent or more standardized form, reducing the number of features in the data by stemming, and converting the text into numbers or vectors so that it can be processed by the algorithm. Feature extraction is performed using the Word2Vec model to convert text into a numerical vector representation that can later be processed by ELM. Converts words into numeric vectors in a high-dimensional space, where words that have the same context in the text are close to each other in that space. The ELM (Extreme Learning Machine) algorithm is used as a classification model due to its high training speed and good generalization ability. Model evaluation is done using confusion matrix which measures classification performance through accuracy, precision, recall matrix. The results of this study show that the ELM algorithm with Word2Vec feature extraction is able to classify user sentiment with a high level of accuracy. This research provides insight into user satisfaction with online transportation services and can be a reference for companies to improve their service quality

IMPLEMENTASI PEMBELAJARAN PADA PROGRAM STUDI INDEPENDEN BIDANG MACHINE LEARNING DI PT DICODING AKADEMI INDONESIA Meisya Vira Amelia; Kartika Maulida Hindrayani
Jurnal Pengabdian Masyarakat SENSASI Vol. 4 No. 2 (2024): Jurnal Pengabdian Masyarakat SENSASI
Publisher : Faculty of Economics and Bussiness, UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/sensasi.v4i2.78

Merdeka Belajar – Kampus Merdeka merupakan bagian dari kebijakan Merdeka Belajar oleh Kementerian Pendidikan, Budaya, Riset, dan Teknologi yang memberikan seluruh mahasiswa untuk mengasah kemampuan sesuai bakat dan minat dengan terjun langsung ke dunia kerja sebagai langkah persiapan karir. Dari berbagai pilihan program yang disediakan oleh pihak Merdeka Belajar – Kampus Merdeka, peneliti memilih untuk mengikuti kegiatan Magang dan Studi Independen Bersertifikat (MSIB), khususnya adalah kegiatan studi independen yang diadakan oleh PT Dicoding Akademi Indonesia, yaitu Bangkit Academy. Penelitian implementasi pembelajaran pada Bangkit Academy dilakukan dengan metode kualitatif deskriptif. Hasil penelitian menunjukkan bahwa implementasi pembelajaran pada Bangkit Academy sudah dilakukan dengan baik. Dimulai dari metode self-paced learning yang diterapkan untuk meningkatkan motivasi belajar peserta, banyaknya akses materi yang diberikan, ragam perancangan soal agar menarik, dan diakhiri dengan proyek akhir secara kelompok untuk mengaplikasikan seluruh pengetahuan yang didapatkan menjadi aplikasi yang berguna. Selain itu juga fasilitas yang diberikan berupa pendampingan dari mentor Bangkit Academy dilakukan dengan baik dan instruktur yang dihadirkan merupakan orang-orang yang telah berpengalaman.

Indonesian Sign Language (BISINDO) Classification Using Xception Transfer Learning Architecture Amelia, Meisya Vira; Saputra, Wahyu Syaifullah Jauharis; Hindrayani, Kartika Maulida; Riyantoko, Prismahardi Aji
International Journal of Advances in Data and Information Systems Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i2.1392

Human communication generally relied on speech. However, this was not applicable to the deaf people, who depended on sign language for daily interactions. Unfortunately, not everyone had the ability to understand sign language. In higher education environments, the lack of individuals proficient in sign language often created inequality in the learning process for deaf students. This limitation could be addressed by fostering a more inclusive environment, one of which was through the implementation of a sign language translation system. Therefore, this study aimed to develop a machine learning model capable of detecting and translating Indonesian Sign Language (BISINDO) alphabet gestures. The model was built using the Xception transfer learning method from Convolutional Neural Networks (CNN). The dataset consisted of 26 BISINDO alphabet gestures with a total of 650 images. The model was evaluated using K-Fold cross-validation and achieved an F1-score of 94% during testing.

Perancangan Aplikasi EMKASADA untuk Penjadwalan Kegiatan Perkuliahan Program Studi Sains Data UPN Veteran Jawa Timur Pakpahan, Vera Febrianti; Afidria, Zulfa Febi; Bhalqis, Anissa Andiar; Hindrayani, Kartika Maulida; Trimono
Journal of Technology and Informatics (JoTI) Vol. 7 No. 1 (2025): Vol. 7 No.1 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i1.835

The development of information technology has encouraged innovation in various fields, including education. Lecture scheduling is one important aspect that requires special attention to ensure efficient and effective use of resources. The EMKASADA application improves efficiency in lecture scheduling by automating the process of preparing schedules, thus reducing the time and manual effort in managing schedules. With features such as dashboards, lecturer data, courses, days, sessions, rooms, lecturers, and automatic scheduling, this system is able to speed up the schedule preparation process and optimize the allocation of available resources. In terms of effectiveness, the EMKASADA application ensures that scheduling is more optimal by minimizing the possibility of clashes between lecturer schedules, courses, and rooms. With the waterfall method approach, the system is developed in a structured and systematic manner, following the stages from requirements analysis to maintenance. Testing was conducted using the black box testing method to ensure all application features, such as dashboards, lecturer data, courses, days, sessions, rooms, lecturers, and scheduling, function properly. The test results show that the features in the EMKASADA application function properly and are able to increase efficiency in scheduling lectures.

Business Intelligence for Educational Institution : A Literature Review Maulida Hindrayani, Kartika
IJCONSIST JOURNALS Vol 2 No 1 (2020): September
Publisher : International Journal of Computer, Network Security and Information System

Educational institution is one of the organizations that should manage data to improve decision making. Students, department, research, and community services, are the data that should be managed in education. Those data could help in accreditation, marketing, and operational process. Business Intelligence (BI) helps visualize a huge amount of data. Executives will easily understand what the data try to imply in graphics. In this research, literature review about BI in educational organization will be conducted.

Determining Students Preparation for College Entrance Examinations in Indonesia From Twitter Data Using Exploratory Data Analysis Maulida Hindrayani, Kartika; Maulana F, Tresna; Aji R, Prismahardi; Kartini
IJCONSIST JOURNALS Vol 2 No 02 (2021): March
Publisher : International Journal of Computer, Network Security and Information System

Nowadays, educational data can be learned not only for those in Education but also in Information Technology. This happened because education and technology can no longer be separated. Senior high school graduates will take College Entrance Examination to be admitted to public institutions in Indonesia. Sometimes, they share their progress, target, and complain on social media. In this research, we collected data from Twitter. We explore the data to determine student's preparation using Exploratory Data Analysis. The results are positive words in both English and Indonesia, word count, word cloud, and geographical data plot.

Exploratory Data Analysis and Machine Learning Algorithms to Classifying Stroke Disease Riyantoko, Prismahardi Aji; Fahrudin, Tresna Maulana; Hindrayani, Kartika Maulida; Idhom, Mohammad
IJCONSIST JOURNALS Vol 2 No 02 (2021): March
Publisher : International Journal of Computer, Network Security and Information System

This paper presents data stroke disease that combine exploratory data analysis and machine learning algorithms. Using exploratory data analysis we can found the patterns, anomaly, give assumptions using statistical and graphical method. Otherwise, machine learning algorithm can classify the dataset using model, and we can compare many model. EDA have showed the result if the age of patient was attacked stroke disease between 25 into 62 years old. Machine learning algorithm have showed the highest are Logistic Regression and Stochastic Gradient Descent around 94,61%. Overall, the model of machine learning can provide the best performed and accuracy.

Co-Authors Aang Kisnu Darmawan Abdul Mukti Achmad Dzulfiqar Alfiansyah Adhigiadany, Chelsea Ayu Afidria, Zulfa Febi Ahmad, Davin Anezta Aisyah Kirana Putri Isyanto Aji R, Prismahardi Altetiko, Faizal Johan Alya Mirza Safira Alzam, Muhammad Arsyad Amanda Aulia Amelia, Meisya Vira Amri Muhaimin Ardia Eva Ardiani Arkananta Handoyo Aulia Nur Fitriani Aviolla Terza Damaliana Azizah Zalfa Assyadida Azizah, Alisa Jihan Betty Dewi Puspasari Bhalqis, Anissa Andiar Brescia Ayundina Yuniarossy Budi, Aditya Septa Burhan Syarif Acarya Chelsea Ayu Adhigiadany Christina Halim Christina, Enzelica Vica Damaliana, Aviolla Terza Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Edelin Fortuna Elmaliyasari, Shifa Endang Tri Wahyurini Fahrudin, Tresna Maulana Fajar Ramadhani Fajria Ulumin Nafiah Fernando, Moch. Firman Hilya Zada Mardhatilla Al Haadiy Holly Patrycia I Gede Susrama Mas Diayasa idhom, Mohammad Imam Imanta Ginting Imelda Widya Ningrum Indira Zein Rizqin Isyanto, Aisyah Kirana Putri Kartini Kartini Kartini Kartini Khairunisa, Adenda Kristananda, Raja Valentino Lidya Musaffak, Awal Made Hanindia Prami Swari Maudi Adella Maulana F, Tresna Meisya Vira Amelia Meisya Vira Amelia Milla Akbarany Baktiar Putri Mohammad Idhom Mohammad Idhom Mohammad Idhom Muhammad Rafli Muhimmatul Arofah Nanda Kurnia Wardati Ni Luh Ayu Nariswari Dewi Ningrum, Imelda Widya Ningrum, Lisya Septyo Nur Aini Rakhmawati Pakpahan, Vera Febrianti Pratiwi, Nanda Aulia Prismahardi Aji Riyantoko Purwadwika, Reza Sadiya Putro, R. Kokoh H. rachmanto, Nugroho Fajar Radya Ardi Renaldy Al Ikhsan Reza Sadiya Purwadwika Rhomaningtias, Lina Riskiyah, Ameliyah Risnaldy Novendra Irawan Rizky Fatkhur Rohman Safira, Alya Mirza Safitri, Eristya Maya Saputra, Wahyu S. J. Selena Nurmanina Afandy Selly Rizkiyah Shindi Shella May Wara Shindi Shella May Wara Shindi Shella May Wara Sinthya Putri, Diana Steffany Marcellia Witanto Thoriqulhaq, Muhammad Tresna Maulana F Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono Trimono Trimono Trimono Trimono Trimono Trimono Trimono Trimono, Trimono Wahyu Syaifullah Jauharis Saputra Wahyu Syaifullah JS Wibowo, Muhammad Bagas Satrio Yosua Satria Bara Harmoni

Title

Found 61 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 61 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 61 Documents
Search