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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Proceeding Information Technology JOIV : International Journal on Informatics Visualization JATI (Jurnal Mahasiswa Teknik Informatika) Eduvest - Journal of Universal Studies Journal of Informatics and Advanced Computing
Ionia Veritawati
Pancasila University
Aerospace Engineering Computer Science & IT Engineering Health Professions Neuroscience Social Sciences

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Fractal Dimension Approach for Clustering of DNA Sequences Based on Internucleotide Distance Sadikin, Mujiono; Wasito, Ito; Veritawati, Ionia
Proceeding Information Technology 2013
Publisher : Proceeding Information Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstract – Recently, the volume of biological data increasesexponentially. Problem of utilization of this kind of data is notonly concerning to the volume but also to its various format andstorage distribution. To solve this kind of problems, someapproaches require new methods, algorithms or tools to assisthuman being in getting beneficial from the biological data. Thispaper presents the usage of fractal dimension approach based oninter nucleotide distance to cluster DNA sequences. Internucleotide distance is a numerical representation of DNAsequences which is transformed to time series signal spectrum.Higuchi Fractal Dimension (HFD) is one of methods to estimatefractal dimension which it can be utilized to reduce time seriesdimension. HFD estimation then is applied to the signal spectrumand it is treated as input to clustering method. The result of thisclustering shows that HFD approach can be considered as analternative method for dimensional reduction purposes.Compared with previous study result as ground truth, the HFDapproach clustering provides some similarities in certain degree.Tested with two kinds of data test sample, this approach results 6and 7 group similarities of 10 groups. Keywords: DNA Sequences, Fractal, Inter Nucleotide Distances
Artificial intelligence-based learning model to improve the talents of higher education students towards the digitalization era Wahjusaputri, Sintha; Bunyamin, Bunyamin; Indah Nastiti, Tashia; Sopandi, Evi; Subagyo, Tatang; Veritawati, Ionia
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3611-3620

Abstract

Artificial intelligence (AI) technology is a hallmark of the 4.0 revolution. The two main issues in Indonesia are infrastructure that needs to be equipped with technology and intelligence-based curriculum integrated with business and industry programs, and lecturers as educators who do not want to use and develop AI technology in applying guided learning models. This research aims to create a learning model based on AI that will help college students develop their talents while maintaining the Pancasila principles in the age of digitization. This study contains four stages: data collection, data analysis, research analysis outcomes, and validation of research analysis results. This research developed an AI-based learning model for use in higher education consisting of four dimensions: input, process, output, and outcome. The input dimension includes components such as students, lecturers, organizations, and infrastructure ready to adopt AI-based learning models. The process dimension consists of the elements that influence the operation of the AI-based learning model system and the functionality provided by the learning model. The output dimension includes characteristics that may be directly measured and process feedback. Finally, the outcome comprises the predicted outputs from the AI-based learning model.
ANALISIS POLA PEMBELIAN KONSUMEN MENGGUNAKAN ALGORITMA APRIORI UNTUK MENENTUKAN STRATEGI PEMASARAN PRODUK DI TOKO RETAIL X Safitry, Dwy Laila; Rosianti, Noviana; Divayaning, Erin; Zidan, Husein; Arnecia, Zahra Jane; Paryudi, Iman; Veritawati, Ionia; Nursari, Sri Rezeki Candra
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12429

Abstract

Analisis pola pembelian konsumen telah menjadi kunci keberhasilan dalam industri retail modern yang semakin kompetitif. Meskipun demikian, banyak toko retail masih menghadapi tantangan dalam menganalisis data transaksi mereka secara efektif, yang dapat menghambat optimalisasi strategi pemasaran dan manajemen inventori. Untuk mengatasi permasalahan ini, penelitian ini mengusulkan implementasi algoritma Apriori guna melakukan market basket analysis pada data transaksi Toko retail X. Toko retail X merupakan sebuah platform e-commerce yang menjual berbagai hadiah dan peralatan rumah tangga. Melalui penerapan algoritma Apriori, penelitian ini berhasil mengidentifikasi beberapa association rule yang kuat antar produk, seperti kombinasi set Regency Teacup and Saucer, set Jumbo Bag, dan tea party set. Hasil analisis ini dapat dimanfaatkan untuk mengoptimalkan strategi pemasaran, termasuk penawaran bundling, dan rekomendasi produk yang lebih tepat sasaran, sehingga berpotensi meningkatkan penjualan dan tingkat kepuasan pelanggan
Development of Mobile and Spatial Based Smart Community Applications to Improve the Community Economy Veritawati, Ionia; Pribadi, Adi Wahyu; Murtako, Amir; Riono, Bambang
Eduvest - Journal of Universal Studies Vol. 5 No. 2 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i2.1734

Abstract

The economy in Depok Community is a problem, where the community needs support from the surrounding community and stakeholders in developing its economy. In planning, Depok is planned to become a smart city. Smart community is part of a smart city with a concept that includes technology-people-innovation in developing society. For this reason, this research developed the Smart Community concept which uses mobile and spatial-based technology to help improve the economy of its citizens, including MSME business actors in the sub-district area, especially in Cilodong Sub-district in this case study. The application development method uses the water fall methodology and an object-oriented approach. The results obtained, the application developed can be used by citizens to share information and communicate to help the citizens' economy, one of which is online marketing, and assisting stakeholders in monitoring and providing support in economic matters.
Clustering Daftar Harga Rumah di Jakarta Dengan Algoritma K-Means Faradilla, Zyhan; Veritawati, Ionia
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 2 (2022): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v3i2.4663

Abstract

Abstrak—Harga rumah di setiap daerah berbeda-beda sesuai dengan daerah dan kategorinya masing-masing. Khususnya harga rumah yang berada di kota misalnya Jakarta. Di Jakarta sendiri memiliki harga rumah yang berbeda sesuai dengan kategorinya. Banyak masyarakat yang tidak mengetahui apakah harga rumah tersebut termasuk murah atau mahal. Maka diberikan solusi untuk mengkategorikan harga rumah yang ada di Jakarta dengan clustering menggunakan algoritma K-Means. Algoritma KMeans dapat membantu untuk mengkategorikan harga rumah di Jakarta dengan 8 atribut yang digunakan terdapat nomor data, nama rumah, harga dari rumah, jumlah luas bangunan, jumlah luas tanah, jumlah kamar tidur, jumlah kamar mandi, dan jumlah kapasitas mobil dalam garasi. Dengan dilakukan penelitian menggunakan algoritma K-Means pada k = 5 didapatkan class data harga termurah pada class 0 sampai yang termahal pada class 4. Dan hasil validitas dari silhoutte score yaitu 0,626.
Prediksi Harga Smartphone berdasarkan Spesifikasi menggunakan K-Nearest Neighbors: Prediksi Harga Smartphone berdasarkan Spesifikasi menggunakan K-Nearest Neighbors Fitra Ningrum, Dea; Putri Ramadhani, Shabrina; Paryudi, Iman; Veritawati, Ionia; Rezeki Candra Nursari, Sri
Journal of Informatics and Advanced Computing (JIAC) Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v4i2.6293

Abstract

Di era teknologi informasi yang terus berkembang, pasar ponsel pintar menjadi salah satu pasar konsumen yang paling dinamis dan beragam. Pembeli seringkali dihadapkan pada banyak pilihan dalam memilih smartphone baru yang sesuai dengan kebutuhan dan budgetnya. Penelitian ini bertujuan untuk memprediksi harga smartphone berdasarkan spesifikasi. Metodologi yang digunakan adalah algoritma K-Nearest Neighbor dengan menggunakan Euclidean distance, membagi dataset menjadi 70% data latih dan 30% data uji. Model ini telah diuji sebanyak 2 kali, pengujian pertama menggunakan k sebesar 1 dan menghasilkan akurasi sebesar 57%, sedangkan pengujian kedua menggunakan nilai k sebesar 3 dan memperoleh akurasi sebesar 65%.
Pemilihan Promosi Perawatan Kecantikan Berdasarkan Pola Pemesanan Pelanggan dengan Menggunakan Algoritma FP-Growth Faradilla, Zyhan; veritawati, ionia
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i1.8319

Abstract

Klinik perawatan kecantikan di Indonesia seperti Impressions Clinic yang menyediakan berbagai jenis perawatan memiliki permasalahan pada persaingan bisnis dan dalam menjalankan promosi masih menggunakan cara manual dengan langsung memilih jenis perawatan yang ada sehingga kurang efektif dalam strategi pemasarannya. Hal tersebut menyebabkan penurunan pendapatan karena berkurangnya pelanggan lama yang kembali ke Impressions Clinic. Untuk mempertahankan pelanggan, diperlukan strategi pemasaran yang lebih efektif, dengan melakukan promosi yang diambil dari jenis perawatan yang sering dipilih pelanggan menjadi satu paket perawatan. Algoritma FP-Growth digunakan untuk menentukan jenis perawatan yang sering dipilih pelanggan dengan mengatur nilai confidence minimum 75%, dan support minimum 2%, untuk mendapatkan hasil terbaik menggunakan aplikasi berbasis web. Hasil penelitian yang diperoleh yaitu jenis perawatan Thread Lift Mono 3O, Filler Treatment, Laneu Gold Mask, Laneu Glowing V Shape Mask, Botolinum toxin, Infusion Whitening dan PDO Thread Lift yang dapat dijadikan acuan dalam promosi jenis perawatan sebagai paket perawatan di Impressions Clinic.
Comparison of Classification Algorithms in Bamboo Distribution Mapping for Identification of Industrial Supporting Raw Materials Veritawati, Ionia; Maspiyanti, Febri; Mastra, Riadika; Fernando, Erick; Murtako, Amir
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3072

Abstract

This study aims to address the challenges in the widespread supply of bamboo raw materials and the lack of coordination between bamboo-producing regions, as well as to conduct a comprehensive inventory and mapping of bamboo resources. In addition, this study also explores the factors that influence the distribution and growth characteristics of bamboo, such as soil type, altitude, and rainfall. The main problems faced in the bamboo industry are the uneven distribution of raw materials and the lack of coordination between regions, which hinder the development of a strong and sustainable bamboo industry value chain. The lack of in-depth information on the ecological factors that influence bamboo growth also exacerbates this situation. The method used in this study involves mapping bamboo potential through aerial photography data collection, which is then analyzed using machine learning technology. The three algorithms used in the classification process are K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest. The study was conducted in an area rich in bamboo vegetation, especially Bojongmangu District in Bekasi, West Java, Indonesia. From the analysis results, the SVM algorithm showed the best performance with a classification accuracy ranging from 80% to 90%. These results indicate that this method is very effective in mapping bamboo vegetation areas with high precision. This study also identified other variables, such as soil type and altitude, that play a role in bamboo distribution. With this more holistic approach, the study is expected to provide deeper insights into bamboo ecology and improve sustainable bamboo resource management.
Co-Authors Arnecia, Zahra Jane Bunyamin Bunyamin Divayaning, Erin Erick Fernando B311087192 Evi Sopandi, Evi Faradilla, Zyhan Fitra Ningrum, Dea Indah Nastiti, Tashia Ito Wasito Maspiyanti, Febri Mastra, Riadika Mujiono Sadikin Murtako, Amir Paryudi, Iman Pribadi, Adi Wahyu Putri Ramadhani, Shabrina Riono, Bambang Rosianti, Noviana Safitry, Dwy Laila Sintha Wahjusaputri, Sintha Subagyo, Tatang Zidan, Husein