Article Per Year (5 Year)
p-Index From 2021 - 2026
5.246
P-Index
This Author published in this journals
All Journal Information System Diploma Program - Informatics Management JAKSTIK Journal Jurnal Ilmiah KOMPUTASI Knowledge Engineering and Data Science Petir ComTech: Computer, Mathematics and Engineering Applications IJIES (International Journal of Innovation in Enterprise System) Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Applied Engineering and Technological Science (JAETS) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Ilmu Teknik dan Komputer EKOMABIS: Jurnal Ekonomi Manajemen Bisnis Jurnal Ilmu Komputer dan Informatika Journal of Social Research Jurnal Computer and Technology Prosiding SeNTIK STI&K Folia Medica Indonesiana Jurnal Teknik Silitek
Ire Puspa Wardhani
STMIK Jakarta STI&K
Humanities Biochemistry, Genetics & Molecular Biology 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 Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Neuroscience Social Sciences

Published : 101 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 101 Documents
Search

 7   8   9   10   11 
RANCANGAN DAN IMPLEMENTASI CHATBOT LAYANAN INFORMASI PENDAFTARAN PASCASARJANA DI PERGURUAN TINGGI Elang M Sony Ariestono; Aqwam Rosadi Kardian; Ire Puspa Wardhani
Prosiding Seminar SeNTIK Vol. 7 No. 1 (2023): Prosiding SeNTIK 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

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

Abstract

Pemanfaatan Teknologi chatbot yang dapat membantu pengguna memperoleh informasi pendaftaran program Pascasarjana. Tujuan dari penelitian ini adalah memanfaatkan Teknologi Chatbot untuk Pendaftaran mahasiswa Pascasarjana dengan melakukan Perancangan yang1 dapat diimplementasikan dengan menggunakan tools Dialogflow dengan metode Natural Language Processing (NLP) dan WhatsApp API. Berdasarkan tahapan pengujian yang telah dilakukan menunjukkan bahwa hasilnya aplikasi chatbot mampu menjawab pertanyaan-pertanyaan terkait pendaftaran Pascasarjana dengan akurasi sebesar 97,82% dengan menggunakan data sebanyak 17 kalimat pertanyaan tentang pendaftaran Pascasarjana. .Diharapkan hasil penelitian ini dapat membuat sebuah chatbot yang hasilnya dapat memudahkan para pendaftar, dikhususkan1 pada infomasi program Pascasarjana, dalam menjawab pertanyaan-pertanyaan terkait seleksi masuk program Pascasarjana
IMPLEMENTASI PENGUKURAN SKALA LIKERT PADA APLIKASI EDUKASI BAHAYA TOXIC PARENT BERBASIS WEB Hendajani, Fivtatianti; Wardhani, Ire Puspa; Pramaishella, Deva Putri
Journal Computer and Technology Vol. 3 No. 1 (2025): Juli 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v3i1.338

Abstract

Kesehatan mental termasuk menjadi salah satu faktor kesehatan seorang anak dalam menjalani aktivitas kesehariannya, apabila mental anak dalam keadaan baik-baik saja, hal tersebut juga akan memengaruhi kesehatan fisik. Kenyataannya, saat ini banyak dari sebagian anak mengalami tekanan batin saat berada di rumah. Perlakuan tersebut tidak bersifat fisik atau berupa kekerasan, melainkan lebih menekankan pada tekanan psikologis atau emosional. Secara tak sadar orang tua memberikan beban serta memberikan perilaku tidak adil kepada si anak. Dalam ranah psikologi, orang tua dengan sifat-sifat tersebut disebut sebagai Toxic Parents atau orang tua yang memberikan dampak negatif secara emosional. Calon orang tua yang akan mempunyai anak mestinya wajib mendapatkan edukasi tentang bagaimana menjadi orang tua yang baik untuk kedepannya. Karena jika tidak mendapat ilmu edukasi tersebut, kedepannya akan menjadi bahaya dan ketakutan anak akan perilaku orang taunya yang toxic akan berdampak ke mental si anak. Aplikasi edukasi toxic parent berbasis web adalah aplikasi yang dapat membantu pengguna, calon orang tua untuk mendapat pengetahuan tentang bagaimana cara mendidik anak dengan memperhatikan kesehatan mental anak. Penilaian kualitas aplikasi edukasi toxic parent yang telah dirancang dilakukan menggunakan skala Likert, dan menghasilkan persentase sebesar 81,8%. Dari nilai tersebut dapat menjadi patokan bahwa hasil penelitian dan perancangan tersebut dapat memudahkan pengguna serta dapat menjadikan aplikasi edukasi toxic parent menjadi portal utama sebagai sumber asli informasi pengetahuan tentang toxic parent.
PENGEMBANGAN APLIKASI PENYUSUNAN RUTE PERJALANAN WISATA JAKARTA BERBASIS WEBSITE DENGAN METODE ALGORITMA ANT COLONY Wardhani, Ire Puspa; Anggraini, Nenny; Widayati, Susi; Sabrina, Wafa
Journal Computer and Technology Vol. 3 No. 1 (2025): Juli 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v3i1.354

Abstract

Jakarta merupakan kota yang memiliki trafik padat, masalah rute perjalanan di Jakarta menjadi perhatian tersendiri bagi pengguna jalan. Pencarian jalur terpendek dalam jaringan transportasi di Jakarta seperti mengurangi kemacetan lalu lintas, rekomendasi rute terpendek untuk perjalanan dinas dan pengiriman barang atau mencapai lokasi wisata. Penelitian tentang Aplikasi penyusunan rute perjalanan wisata dengan metode algoritma ant colony ini merupakan penelitian yang ingin menyelesaikan permasalahan lamanya waktu menyusun rute perjalan wisata. Data yang diperoleh dari pengumpulan data melalui wawancara dengan pengusahan tour dan travel yaitu diperlukannya waktu minimal satu hari untuk menyusun rute perjalanan wisata. Sebagai salah satu solusi perlu aplikasi berbasis web yang dapat menyusun rute perjalanan wisata berdasarkan jarak terpendek. Aplikasi ini merupakan aplikasi berbasis website, dengan input data objek wisata. Metode pengembangan aplikasi penggunakan RAD dan algoritma ant colony untuk proses penyusunan rute perjalanan wisata terpendek yang terdiri atas 2 (dua) user. Output berupa aplikasi penyusunan rute perjalanan wisatayang menyusun rute perjalanan wisata terpendek.
OPTIMIZATION OF FASHION RETAIL CUSTOMER DATA MANAGEMENT THROUGH EXPLORATORY DATA ANALYSIS AND RECENCY, FREQUENCY, MONETARY Yusuf, Yusuf; Basri, Lody Saladin; Hastomo, Widi; Wardhani, Ire Puspa
Prosiding Seminar SeNTIK Vol. 8 No. 1 (2024): Prosiding SeNTIK 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

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

Abstract

This study was conducted to analyze revenue patterns, product segmentation, and customer retention in the H&M retail business using Kaggle competition data "H&M Personalized Fashion Recommendations." The urgency of this study lies in the need to understand revenue fluctuations and customer behavior in order to optimize business strategies. The data used includes transactions, articles, and customer profiles from 2018 to 2020. The analysis methods applied include exploratory data analysis (EDA) analysis and customer segmentation using the RFM (recency, frequency, and monetary) model to identify customer groups based on purchasing behavior. The results of the study show that the highest revenue occurs in the middle of the year, with a sharp decline in growth in mid-2018. Low-recency customers contribute more to revenue, while product segmentation shows the need for stock adjustments, especially for baby/children and divided products. This study successfully identified key factors that influence revenue and customer retention and provided strategic recommendations for inventory improvement and market segmentation. These results are important for H&M to improve operational efficiency and improve marketing strategies in the future.
Application of the Naïve Bayes Classifier Algorithm to Analyze Sentiment for the Covid-19 Vaccine on Twitter in Jakarta Ire Puspa Wardhani; Yudi Irawan Chandra; Ferri Yusra
International Journal of Innovation in Enterprise System Vol. 7 No. 1 (2023): International Journal of Innovation in Enterprise System
Publisher : School of Industrial and System Engineering, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/ijies.v7i01.171

Abstract

The epidemic of a new disease caused by the coronavirus (2019-nCoV), commonly referred to asCOVID-19, has been declared a global virus epidemic by the World Health Organization (WHO).President Joko Widodo has officially ratified Presidential Decree No. 99 of 2020 concerning theprovision of vaccines and the implementation of vaccination activities. Twitter is a social mediaplatform that allows users to share information and opinions directly with fellow users. Tweets givencan be in any form, either positively or negatively, so one of the methods used is sentiment analysis.Sentiment analysis helps determine an opinion or comment on an issue, whether the response ispositive or negative. The Naïve Bayes algorithm is used in sentiment analysis because it is suitablefor tweets or text data that is not too long or short text. The initial stage of sentiment analysis is textpre-processing which consists of Cleaning, case folding, tokenizing, and stopword removal. Then thedata is labeled manually. The analysis results are visualized as bar charts, pie charts, and word clouds.Then the word weighting is carried out using the term frequency-inverse document (TF-IDF), andclassification is carried out using the Naïve Bayes classifier. From the test results, the accuracy valueof the confusion matrix is 82% from 2600 tweet data with 80% training data composition and 20%test data.
CORRELATION OF F2-ISOPROSTANE WITH INTERLEUKIN-6 AND INTERLEUKIN-10 IN TRANSFUSION-DEPENDENT THALASSEMIA PATIENTS : A CROSS-SECTIONAL STUDY Muhlisa, Nurul; Hernaningsih, Yetti; Wardhani, Puspa; Andarsini, Mia Ratwita; Ali Hasan, Zulfikar
Folia Medica Indonesiana Vol. 61, No. 2
Publisher : Folia Medica Indonesiana

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

Abstract

Transfusion-dependent thalassemia (TDT)[-7pc]AU: Please Provide authors affiliations. is a condition in which patients require lifelong regular blood transfusions. However, regular blood transfusions carry a major risk of iron overload, which accumulates in the body and can trigger oxidative stress and chronic inflammation. Oxidative stress is characterized by an increase in reactive oxygen species (ROS), which can be assessed through the measurement of F2-Isoprostanes (8-iso-PGF2α). Excessive ROS affects cytokine production by inducing an inflammatory response, such as IL-6 and IL-10. This study aims to analyze the correlation between F2-isoprostane with Interleukin-6 and Interleukin-10 levels in TDT patients. This research was an observational analytical study with a cross-sectional design that involved 33 patient samples at Dr. Soetomo General Academic Hospital, Surabaya, from July to August 2025. The variables studied included F2-Isoprostane, IL-6, and IL-10 levels. F2-Isoprostane and IL-10 levels were measured using the Enzyme-Linked Immunosorbent Assay (ELISA) method (Isoprostane assay kit ELISA No. E-EL 47 0041 Elabscience and Human IL-10 kit ELISA No. E-EL-H6154 Elabscience). IL-6 levels were measured using the Chemiluminescence Immunoassay (CLIA) method (CLIA MAGLUMI IL-6 kit, Snibe). Data were analyzed by the Spearman correlation test. The results showed that the correlation coefficient (r) and significance values between F2-Isoprostane and IL-6 (p = 0.887; r = 0.026) indicated a very weak positive correlation, while IL-10 (p = 0.904; r = –0.022), showed a very weak negative correlation that was not statistically significant. This study demonstrates that there is no correlation between F2-Isoprostane levels, as a marker of oxidative stress, and IL-6 or IL-10, as markers of inflammation.
Analysis of Human-Computer Interaction Satisfaction on The Employee Information System at The Department of Education, Bogor Regency (Sakedik) Using The Eucs Method Aryo Putra Hadiutama; Mahda Yulia Astary; Ire Puspa Wardhani
Journal of Social Research Vol. 4 No. 7 (2025): Journal of Social Research
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/josr.v4i7.2609

Abstract

The rapid advancement of information technology has encouraged government institutions to adopt electronic-based systems to enhance public service delivery. The Department of Education of Bogor Regency has developed the Personnel Information System (SAKEDIK) to streamline personnel data management. This study aims to evaluate user satisfaction with the SAKEDIK system using the End User Computing Satisfaction (EUCS) method, which assesses five dimensions: content, accuracy, format, ease of use, and timeliness. Data were gathered through questionnaires distributed to 97 respondents and analyzed using the Customer Satisfaction Index (CSI). The results show that overall user satisfaction falls within the "moderately satisfied" category. The information quality dimension received a "very satisfied" rating, while the system quality dimension was rated as "satisfied." These findings suggest that while the SAKEDIK system performs well in terms of content and accuracy, there is room for improvement in other areas, particularly in system usability and timeliness. This study provides insights that can guide future enhancements of the SAKEDIK system to improve user satisfaction and contribute to better public service management.
OPTIMISASI INTERAKSI MANUSIA DAN KOMPUTER UNTUK MEMPERCEPAT PROSES ENKRIPSI VIGENERE CHIPER DENGAN MD5 DAN PENYISIPAN PESAN PADA GAMBAR STEGANOGRAFI Asep Suryanta; Yohanes Dwi Cahyono; Ire Puspa Wardhani
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.v9i1.12132

Abstract

Keamanan informasi merupakan aspek krusial dalam pengelolaan data di era digital, dan teknologi kriptografi serta steganografi memainkan peran penting dalam menjaga kerahasiaan dan integritas data. Salah satu teknik enkripsi yang banyak digunakan adalah Vigenère Cipher, yang dapat dipadukan dengan algoritma hash MD5 untuk meningkatkan tingkat keamanannya. Namun, proses enkripsi menggunakan Vigenère Cipher dengan MD5 dan penyisipan pesan ke dalam gambar menggunakan steganografi sering kali memerlukan waktu yang signifikan, terutama saat operator harus menangani sejumlah besar pesan. Penelitian ini bertujuan untuk mengoptimalkan interaksi manusia-komputer (HCI) guna mempercepat proses enkripsi Vigenère Cipher dengan MD5 dan penyisipan pesan ke dalam gambar melalui teknik steganografi. Dengan merancang antarmuka yang lebih intuitif dan efisien, penelitian ini memungkinkan operator untuk mempercepat tugas mereka dalam proses enkripsi dan penyisipan pesan ke dalam gambar sehingga mengurangi potensi kesalahan, serta meningkatkan produktivitas secara keseluruhan
Recurrent Session Approach to Generative Association Rule based Recommendation Armanda, Tubagus Arief; Wardhani, Ire Puspa; Akhriza, Tubagus M.; Admira, Tubagus M. Adrie
Knowledge Engineering and Data Science
Publisher : citeus

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

Abstract

This article introduces a generative association rule (AR)-based recommendation system (RS) using a recurrent neural network approach implemented when a user searches for an item in a browsing session. It is proposed to overcome the limitations of the traditional AR-based RS which implements query-based sessions that are not adaptive to input series, thus failing to generate recommendations. The dataset used is accurate retail transaction data from online stores in Europe. The contribution of the proposed method is a next-item prediction model using LSTM, but what is trained to develop the model is an associative rule string, not a string of items in a purchase transaction. The proposed model predicts the next item generatively, while the traditional method discriminatively. As a result, for an array of items that the user has viewed in a browsing session, the model can always recommend the following items when traditional methods cannot. In addition, the results of user-centered validation of several metrics show that although the level of accuracy (similarity) of recommended products and products seen by users is only 20%, other metrics reach above 70%, such as novelty, diversity, attractiveness and enjoyability.
Stacked LSTM-GRU Long-Term Forecasting Model for Indonesian Islamic Banks Sujatna, Yayat; Karno, Adhitio Satyo Bayangkari; Hastomo, Widi; Yuningsih, Nia; Arif, Dody; Handayani, Sri Setya; Kardian, Aqwam Rosadi; Wardhani, Ire Puspa; Rere, L.M Rasdi
Knowledge Engineering and Data Science
Publisher : citeus

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

Abstract

The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of LSTM and GRU. Each model performs the training process in four epochs (200, 500, 750, and 1000). The results of observations in this study show that long-term predictions (28 days ahead) using four stacks of LSTM-GRU and daily training accumulation techniques produce better accuracy than the general method (using multiple outputs). From the observations we have made for predictions for the next 28 days, the model with the LGLG stack arrangement (LSTM-GRU-LSTM-GRU) produces the best accuracy at epoch 750 with an MSE LSTM-GRU 63.43762863. This study will undoubtedly continue in order to achieve even better precision, either by utilizing a new design or by further improving the technology we are now employing.
Co-Authors Abdul Hakim Aditya Pranata Admira, Tubagus M. Adrie Agung Slamet Riyad Agung Slamet Riyadi Agung Slamet Riyadi Ahmad Bahrudin Akhmad Haryanto Akhriza, Tubagus M. Akhwan Khairul Alam Alby Maulana Sidik Aldi Marwoto Aldy Wirawan Andi Herawati Andi Maulana Ibrohim Andi Perdana Anggar Prasetyo Anggar Prasetyo Annisa Indrayanti Annisa Mutia Putri Annissa Mutia Putri Aqwam Rosadi Kardian Arif Mughni Arif, Dody Armanda, Tubagus Arief Aryo Putra Hadiutama Asep Suryanta Basri, Lody Saladin Bayangkari Karno, Adhitio Satyo Bolivia Dwi Agustiani Cherry Mariz Wibowo Cherry Mariz Wibowo Damayanti, Arika Dapit Dapit Defrizal Defrizal Defrizal Defrizal Devi Devi Devita Rizky Nur Septiani Devita Rizky Nur Septiani Dewi Nur Cahyani Diah Fitaloka Dila Andriyani Dyta Nigtyas Dyta Nigtyas Ega Rudy Graha Ega Rudy Graha Eko Tri Asmoro Elang M Sony Ariestono Fencing Prasetyo Ferri Yusra Ferri Yusra Fipit Aprilyanthi Firhan Okvalino Firhan Okvalino Fitriyanto Rizky Anjasmoro H. Soetirto Sadikin, Drs., MA. H. Soetirto Sadikin, Drs., MA. Handayani, Sri Setya Hasan, Zulfikar Ali hendajani, fivtatianti HENRI SAPUTRA Herlina Herlina Herman Herman Idham Adriansyah Indah Permatasari Cahyaningtyas Indrayanti, Annisa Irfan Irfan Caniago Juwita Juwita Kardian, Aqwam Rosadi Kellek Kurniawan Kenya Puspita Lindri Lussiana Lussiana Lussiana Lussiana Lussiana, ETP Mahda Yulia Astary Maria Sri Wulandari Maria Ulfah Mia Ratwita Andarsini Miftachul Fuad MM SKom Fivtatianti Hendajani Mohamad Afhdal Jauhari Mohamad Chotibul Umam Mohamad Chotibul Umam Mohamad Saefudin Mohammad Afdhal Jauhari Muhammad Badruzaman Muhammad Riefdan Muhammad Riefdan Muhlisa, Nurul Munich Heindari Ekasari Munich Heindari Ekasari Nenny Anggraini Nia Yuningsih Noor Cholis Nur Ali Akbar Nurkholifah Nurkholifah Nurritu Praworo Pramaishella, Deva Putri Prihandoko . Pujiono Pujiono Purwo Hadi Santoso Rere, L.M Rasdi Rijayanih Rijayanih Risandi Aldino Rita Riyanti Pipit Riyadi, Agung Slamet Rojoko Rojoko Roviqoh, Vella Sabrina, Wafa Salim, Sofyan Nur Sarifuddin Madenda Shandy Juniantoro Siti Wirdayatih Soegijanto Soegijanto Sukiswo Sunny Arief Sudiro Supeni Siskawati Supeni Siskawati Susi Widayati Tondi Febriyana Wahyu Hidayat Widi Hastomo Wisnu Sutrisno Wiwiek Pujiningsih Wulan Kurniawati Yayat Sujatna, Yayat Yetti Hernaningsih Yohanes Dwi Cahyono Yokiansyah Sasbriantoyo Yudi Irawan Chandra Yusuf Yusuf