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All Journal Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Informatics for Educators and Professional : Journal of Informatics Network Engineering Research Operation [NERO] KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Indonesian Journal of Applied Informatics Jurnal ICT : Information Communication & Technology Jurnal Sistem Informasi Kaputama (JSIK) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Perangkat Lunak JSR : Jaringan Sistem Informasi Robotik JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknik Informatika (JUTIF) Jurnal Mahasiswa Sistem Informasi (JMSI) International Journal of Social Science Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jurnal Janitra Informatika dan Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) INFORMATIKA Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Mahasiswa Ilmu Komputer TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Manajemen Kreatif Jurnal JURSIMA Jurnal Ekonomi Manajemen Akuntansi BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat NERO (Networking Engineering Research Operation) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sistem Informasi dan Manajemen INTERNAL (Information System Journal) Intechno Journal : Information Technology Journal
Yudhistira Arie Wijaya
STMIK IKMI Cirebon
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PENERAPAN X-MEANS CLUSTERING TERHADAP HASIL KUESIONER WEBSITE VIRTUAL TOUR STMIK IKMI CIREBON SYSTEM USABILITY SCALE (SUS) Manzis, Zian; Kurniawan, Rudi; Arie Wijaya, Yudhistira
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 3 (2024): JATI Vol. 8 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i3.9575

Abstract

Dengan pesatnya perkembangan teknologi informasi, banyak layanan dan produk berupa aplikasi berbasis website yang digunakan untuk menunjang aktivitas sehari-hari, Perkembangan teknologi informasi memberikan dampak positif bagi penggunanya karena memudahkan mereka dalam melakukan berbagai aktivitas, Suatu website dikatakan berhasil jika tingkat kegunaannya memenuhi kriteria suatu metode tertentu, kegunaan website juga menjadi salah satu faktor yang menentukan apakah suatu website mudah digunakan oleh pengguna. Penelitian ini berfokus pada analisis data survei SUS untuk memahami dan meningkatkan kegunaan website. Dengan menerapkan pendekatan inovatif menggunakan algoritma X-Means, penelitian ini bertujuan mencari cluster terbaik sesuai parameter dari Metode Clustering X-Mean. Tujuannya adalah untuk mendapatkan pemahaman mendalam tentang kekuatan dan kelemahan tertentu yang dapat dioptimalkan. Dengan mengintegrasikan metode survei SUS dan algoritma X-Means. Dengan menerapkan pengelompokan X-Means pada hasil survei SUS, penulis mengidentifikasi kelompok pengguna dengan karakteristik berbeda. Algoritma X-Means dapat diterapkan untuk mengelompokkan pengguna berdasarkan preferensi mereka untuk berbagai aspek kepuasan dan kegunaan. Hal ini memberikan wawasan yang lebih mendalam mengenai kebutuhan dan harapan pengguna, memungkinkan pengembang untuk menyesuaikan peningkatan dan pengembangan sesuai preferensi masing-masing kelompok. Hasil yang penulis dapatkan dari permasalahan di atas cluster terbaik adalah cluster 0 menggunakan parameter algoritma X-Means dengan jarak rata-rata cluster (Avarage Cluster Distance) sebesar 1.093 dan DBI sebesar 0.296. pertanyaan 10 responden cenderung bertolak belakang antara cluster 0 dan cluster 1 yang artinya disini terjadi perbedaan pendapat pada pertanyaan yang terpilih di atas tersebut, sedangkan pertanyaan lainnya yaitu pertanyaan 1, pertanyaan 2, pertanyaan 3, pertanyaan 5, pertanyaan 7, pertanyaan 8, responden cluster 0 dan cluster 1 lebih sependapat ketika menjawab pertanyaan tersebut
ANALISIS DATA PENERIMAAN PESERTA DIDIK BARU MENGGUNAKAN CROSS VALIDATION DAN ALGORITMA DECISION TREE DI SMA NEGERI 1 BANDUNG Andriyani, Wini; Kurniawan, Rudi; Arie Wijaya, Yudhistira
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 3 (2024): JATI Vol. 8 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i3.9603

Abstract

Setiap tahun, SMA Negeri 1 Bandung menerima calon peserta didik baru melalui tiga jalur pendaftaran: penelusuran minat, Prestasi Akademik (PA), dan ujian tertulis. Namun, proses seleksi dalam Penerimaan Peserta Didik Baru (PPDB) menghadapi kendala dalam menetapkan kriteria kelulusan. Untuk mengatasi masalah ini, diperlukan prediksi data guna meningkatkan kualitas penerimaan siswa. Tujuan penelitian ini adalah menganalisis data PPDB untuk menyederhanakan proses seleksi calon siswa dengan menerapkan teknik data mining, khususnya algoritma Decision Tree. Metode ini menghasilkan pohon keputusan yang membantu mengidentifikasi siswa yang lolos dan tidak lolos dengan lebih efisien. Hasil penelitian menggunakan aplikasi RapidMiner Studio menunjukkan bahwa dari 282 data, sebanyak 86 data tidak lolos dan 191 data lolos, dengan tingkat akurasi mencapai 98.24%, precision 97.45%, dan recall 94.51%. Pemahaman faktor-faktor yang mempengaruhi keberhasilan akademik siswa juga dapat membantu pengembangan strategi pendidikan yang lebih efektif. Melalui teknik Cross-Validation, validitas model Decision Tree diuji untuk memastikan kinerjanya yang tinggi dalam berbagai lingkungan. Dengan demikian, penelitian ini berpotensi memberikan kontribusi yang signifikan terhadap kebijakan penerimaan siswa baru yang efisien dan berkualitas di SMA Negeri 1 Bandung.
ALGORITMA NAIVE BAYES UNTUK MENINGKATKAN MODEL KLASIFIKASI PENERIMA PROGRAM INDONESIA PINTAR DI SDN 2 PURWAWINANGUN Darussalam, Luthvi Nurfauzi; Kurniawan, Rudi; Wijaya, Yudhistira Arie; Suprapti, Tati
Jurnal Informatika dan Teknik Elektro Terapan Vol 13, No 1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i1.5882

Abstract

Penelitian ini bertujuan meningkatkan keakuratan klasifikasi penerima Program Indonesia Pintar (PIP) di SDN 2 Purwawinangun, Kabupaten Kuningan. Metode yang lambat dan kurang akurat digantikan dengan algoritma Naive Bayes untuk menganalisis data siswa berdasarkan kriteria tertentu. Proses penelitian meliputi pengumpulan data sekunder, preprocessing data, dan implementasi algoritma Naive Bayes. Hasilnya, model ini mencapai akurasi 96,47% dalam menentukan kelayakan penerima PIP, dengan mempertimbangkan atribut seperti latar belakang sosial ekonomi dan kinerja akademik siswa. Temuan menunjukkan bahwa algoritma ini efisien dalam mengolah dataset kompleks dibandingkan metode manual. Namun, kinerja model sangat bergantung pada kualitas data awal, sehingga data yang tidak lengkap dapat mempengaruhi hasil.Penelitian merekomendasikan penerapan metode ini di sekolah lain dan integrasi algoritma tambahan, seperti Decision Tree, untuk validasi hasil. Dengan pendekatan ini, seleksi penerima PIP menjadi lebih tepat sasaran, efisien, dan transparan.
Analisis Bibliometrik: Pemetaan Penelitian Machine Learning dalam E-commerce Berdasarkan Data dari Scopus (2019-2024) Yudhistira Arie Wijaya; Dadang Sudrajat
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

This study explores the application of machine learning in e-commerce using descriptive and visual bibliometric analysis methods. Data were collected from the Scopus database for the period 2019–2024 through five stages: defining search keywords, initial search results, refinement of the search results, compiling statistics on the initial data, and data analysis. The findings indicate a significant increase in publications from 2020 to 2023, peaking in 2023, followed by a decline in 2024. IEEE Access and the International Journal of Advanced Computer Science and Applications are the main sources of publications, with India and China standing out as the countries with the highest number of publications. International research collaboration shows significant growth, and co-word analysis identifies “machine learning” as a central topic closely linked with “electronic commerce” and “learning systems." Citation trends reveal that highly cited publications have a significant impact. These findings provide comprehensive insights into the development and contributions of research in machine learning for e-commerce, with important implications for researchers and industry practitioners in addressing new challenges and opportunities.
Analisis Internet Network Performance Menggunakan Parameter Quality of Service Pada Jaringan STMIK IKMI Cirebon Martanto; Dian Ade Kurnia; Fathurrohman; Irfan Ali; Yudhistira Arie Wijaya
Prosiding SISFOTEK Vol 8 No 1 (2024): SISFOTEK VIII 2024
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

The use of the internet for employees is a crucial need to support the completion of their work. STMIK IKMI Cirebon also provides internet facilities for its employees. However, the internet facilities provided are not yet optimal, as evidenced by frequent connection disruptions. This study aims to measure the performance of the internet connection at STMIK IKMI Cirebon. The method used is Quality of Service (QoS), which is a method to assess how well the installed network functions and its ability to define the attributes of the network services provided. QoS is necessary to calculate the parameters that determine the quality of an internet network. The steps in this study include recording network traffic using Wireshark, followed by calculating parameters such as bandwidth, packet loss, delay, throughput, and jitter. The study results indicate that during data upload from 08:00 to 12:05 at STMIK IKMI Cirebon, the throughput percentage achieved was 31% with an index of 1 "POOR," delay was 9.444 ms with an index of 4 "VERY GOOD," jitter was 8.444 ms with an index of 3 "GOOD," and packet loss was 0% with an index of 4 "VERY GOOD." During data download from 15:00 to 19:05, the throughput percentage achieved was 132% with an index of 4 "VERY GOOD," delay was 14.052 ms with an index of 4 "VERY GOOD," jitter was 13.052 ms with an index of 3 "GOOD," and packet loss received an index of 4 "VERY GOOD." Based on these results, it can be concluded that these values have met the TIPHON standard for both upload and download, indicating that the internet connection at STMIK IKMI Cirebon is still suitable for use
PENINGKATAN MODEL SEGMENTASI PENGGUNA TERMINAL TIPE B SUMBER KABUPATEN CIREBON DALAM PERBAIKAN SARANA DAN PRASARANA DENGAN ALGORITMA K-MEANS Kusmiyaty, Agesty; Kurniawan, Rudi; Arie Wijaya, Yudhistira; Hayati, Umi
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.v9i1.12466

Abstract

Terminal Sumber, sebuah terminal tipe B di Kabupaten Cirebon, menghadapi tantangan dalam memenuhi kebutuhan pengguna akibat pengelolaan sarana dan prasarana yang belum optimal. Tingkat kepuasan pengguna terhadap fasilitas, kebersihan, kualitas layanan, dan infrastruktur sering kali beragam, mencerminkan kebutuhan perbaikan yang terarah. Penelitian ini bertujuan untuk menganalisis kepuasan pengguna dengan memanfaatkan algoritma K-Means Clustering. Data kepuasan pengguna dikumpulkan melalui survei langsung, menghasilkan dua klaster berdasarkan nilai Davies Bouldin Index (DBI) optimal sebesar 0,547. Klaster 0 merepresentasikan pengguna dengan tingkat kepuasan lebih rendah, sedangkan klaster 1 memiliki tingkat kepuasan lebih tinggi. Hasil ini menunjukkan bahwa segmentasi pengguna dapat membantu pengelola terminal merancang strategi perbaikan layanan yang lebih spesifik dan efektif. Dengan demikian, penelitian ini berkontribusi dalam penerapan metode clustering untuk meningkatkan kualitas layanan transportasi umum, baik secara praktis maupun akademis
KLASIFIKASI MOTIF BATIK JAWA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (KNN) AKBAR, MUHAMAD DENI; Martanto, Martanto; Wijaya, Yudhistira Arie
JURSIMA Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.412

Abstract

Batik is one of Indonesia's beautiful and well-known heritages throughout the world, batik as a traditional heritage of the archipelago comes with a variety of motifs. Each region has different motifs and different philosophies. The number of Indonesian batik motifs spread from Aceh to Papua, so not everyone can distinguish batik motifs. This study aims to distinguish between Javanese batik motifs and non-Javanese batik motifs. The batik motifs taken by researchers as samples from the Java region were the Mega Mendung batik motif, Lasem batik motif, Sekar Jagad batik motif, Kawung batik motifs and motifs, and for non-Javanese researchers took samples of Cendrawasih batik motifs, Dayak batik motifs, and batik motifs. nutmeg, and Balinese batik motifs. The research method uses the K-Nearest Neighbors (KNN) algorithm which has stages of collecting image on batik motifs, knowing Javanese and non-Javanese batik motifs, pre-processing, feature extraction, image classification, and evaluation of motifs. Color feature extraction is carried out using gray level co-occurrence matrix (GLCM) methods. Based on the test results show that with the application of GLCM and KNN with an image size ratio of 200x200 with a ratio of k=5 the percentage of split image 80% test and 20% training is able to produce an accuracy of 65%.
Sistem Informasi Akuntansi Penjualan Bahan Pokok Berbasis Web Pada Housemart Cirebon Alya Fadia; Yudhistira Arie Wijaya
Jurnal Ekonomi Manajemen Akuntansi Vol. 29 No. 1 (2023): JURNAL EKONOMI MANAJEMEN AKUNTANSI
Publisher : sekolah Tinggi Ilmu Ekonomi Dharma Putra Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.04 KB) | DOI: 10.59725/ema.v29i1.65

Abstract

Housemart Cirebon is a trading company engaged in staple goods located on Jalan Cideng Indah, Cirebon Regency - West Java. Cirebon Housemart provides basic ingredients from national brands ranging from household needs, baby products, to body and beauty care products. At present the business activities carried out are somewhat less effective. Sales, promotions and orders are still done manually, this is less effective because there is no detailed information on what products are being sold to buyers. . Recording and checking of transaction data, customer data, goods data, is still done manually in written document archives, data loss is still very likely to occur. The development method used to design the system uses the prototype method. The results of this research are in the form of a web-based Housemart Cirebon Sales Information System that is capable of performing sales, ordering and data processing services at Cirebon Housemart so that it can increase the effectiveness and efficiency of performance and time. The hope is to be able to provide complete information regarding the ordering process, services and promotions so that it is even better at Housemart Cirebon.
ALGORITMA K-MEAN UNTUK OPTIMALISASI MODEL CLUSTERING DATA PENJUALAN TOKO ONLINE DI TIKTOK SHOP DALAM STRATEGI PEMASARAN Falih, Alfi Rizqi Falih; Kurniawan, Rudi; Arie Wijaya, Yudhistira; Anwar, Saeful
Jurnal Sistem Informasi Kaputama (JSIK) Vol. 9 No. 1 (2025): Volume 9, Nomor 1, Januari 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jsik.v9i1.929

Abstract

Penggunaan TikTokShop sebagai platform e-commerce berkembang pesat, memberikan peluang bagi pelaku usaha untuk menganalisis data penjualan dan memahami perilaku konsumen. Penelitian ini bertujuan mengoptimalkan model clustering dengan algoritma K-Means untuk mengelompokkan data penjualan TikTokShop dan mengidentifikasi segmen konsumen yang serupa, serta menentukan jumlah cluster optimal menggunakan Davies Bouldin Index. Metode KDD digunakan, dengan langkah-langkah pemilihan data, preprocessing, dan penerapan K-Means clustering dengan Euclidean distance. Hasil eksperimen menunjukkan jumlah cluster optimal adalah 15, dengan Davies Bouldin Index 0,001. Cluster_2 teridentifikasi sebagai yang terbaik, dengan perbedaan signifikan antara rata-rata jarak cluster keseluruhan dan cluster_2 sebesar 4129547026402010000. Karakteristik tiap cluster menunjukkan preferensi pelanggan berdasarkan produk, diskon, dan rata-rata jumlah item per pesanan antara 1 hingga 1,5 item. Temuan ini memberikan wawasan untuk pengembangan strategi pemasaran yang lebih tepat sasaran.
Perancangan Sistem Informasi Penjualan Thrifting Dikalangan Milenial Berbasis Web Laela Laela; Yudhistira Arie Wijaya
Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Vol. 1 No. 4 (2023): Oktober : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan
Publisher : Fakultas Teknik Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/wawasan.v1i4.1224

Abstract

In the world of thrft shops, I isan activity of marketing used goods online or offline, most of these seles are related to the marketing of used goods. The rampant marketing of used goods is one of which is the 1994Squad sales platform. Based on the observations that have been made related to the marketing used on the 1994Squad platform, currently marketing is still carried out directly by conducting bazaar event activities of promoting products online through the Instagram platform, so that it is considered imperfect so hat the used goods marketing mechanism does not apply. Meanwhile, marketing sold through the Instagram platform can result in losses, fraud, over-consumption because users are tempted to buy goods just because the goods offered are cheapher. In addition, problems with marketing using a platform that includes income recapitulation for each purchase that is used are still manual which triggers several errors regarding the sum of income. Due to the occurrence of many problems with thrifting 1994Squad sales, a thrifting sales information system was created. The method used to create this website is in the form of a data collection which includes the interview method and sales system design, while the software development method uses the DSDM approach to the agile method which goes through several stages. In using this method, the steps that must be considered are analizing the problems that occur in 19994Squad sales, the next step is to carry out a needs analysis in marketing make a information system design, then implement or develop software testing. For programming laguages using PHP, Codeigniter, Javascript, and CSS. Using XAMPP as the database. This reseasing has several objectives including increasing efficiency in the sales process, making transctions easier, responsible website users making it easier to get the produt they want at a very friendly price and accessible in various media. The results of this information system designcan change the marketing of used gooda through the Instagram platform by faciliting the sales mechanism, searching for well-known brand products, besides that it can prevent errors in shipping goods and errors in data input on thrifting 1994Squad sales.
Co-Authors Abubakar Sidik Ade Irma Purnama Sari Ade Irma Purnamasari Ade Irma Purnamasari Adi Hermawan Aditiya Arif Firmansyah Adiyanto, Alfian Adjie Setyadj, Mochammad Agni, Vega Putra Dwi Ahmad Faqih Ahmad Jamalul Noor Ahmad Rifai Ikhsanudin AKBAR, MUHAMAD DENI Akhmad Taukhid Alfirda Sofyan, Zahra Aliya Anisa Rahma Alwan Azhar Alya Fadia An-naziz Safaat, Wafik Andi Ardiansyah Andriyani, Wini Anggara, Doni Anjar Permadi Aprianto, Wili Arya Hadi Wicaksana ASEP SAEFUDDIN Asmana, Asmana Astri Amelia Athaullah Abrar Bayan Beby Maryam Cintia Putri Prasetia Dadang Sudrajat Darma Irawan, Bobi Darussalam, Luthvi Nurfauzi Denni Pratama Denni Pratama Dermawan, Hibrizi Dzaky Dian Ade Kurnia Dian Ade Kurnia Dodi Solihudin Edi Tohidi Edi Wahyudin Falih, Alfi Rizqi Falih FANDI ACHMAD Fauzan, Muhamad Nur Fianita Rusadi Fianita Rusadi Firmansyach, Wildan Attariq Hajijin Amri Hamonangan, Ryan Hayati, Umi Hegarmanah Muhabatin Heliyanti Susana Herman Hermawan, Adi Hidayat, Zaids Syarif Ibnu Ubaedila Ikhwan Fahruddin, Yusuf Inawati, Windi Intan Wangi Nur Qibti Irfan Ali Irfan Ali Irma Agustina Jaelani Sidik Jayawarsa, A.A. Ketut Jurnal Konsera Khoeri, Yajid Komala, Wulan Kurnia, Dian Ade Kurniawan , Rudi Kusmiyaty, Agesty Laela Laela Leli Oktaviani Lukmanul Hakim Manzis, Zian Marta, Puji Pramudya Martanto Martanto . Martanto Martanto Masjunedi, Masjunedi Maulana, Tedy Mifta Almaripat Mita Amelia Moh Nurdayat Dayat MUHAMAD DENI AKBAR Muhamad Nur Fauzan Muhammad Aditya Rabbani Adit Mulyawan Nabila, Aynun Nana Suarna Nana Suarna Narasati, Riri Narasati Nashir, Mukhtar Nining Rahaningsih Nisa Dieanwati Nuris Nisa Dienwati Nuris Nur Amalia, Yustika Nurazijah, Wulan Nurdiawa, Odi Nurholipah, Titin Nurrahman, Rizki Odi Nurdiawa Odi Nurdiawan Pebriyanto, Ramdhan Pratama, Denni Puji Pramudya Marta Purnamasari, Ade Irma Restu Normalasari Rini Astuti Rini Astuti Rini Astuti Rio Febriyan Rizal Rizal Roni Saputra, Roni Rubangiya Rubangiya Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Saeful Anwar Saeful Anwar, Saeful Satria Turangga Septian Nugraha, Titan Septiani Gumilar, Tia Shifa Dwi Oktaviani Siti Sopiyah Suarna, Nana Sugianto, Nanda Putri Sulaeman, Muhammad Suteja Syach Putra, Yanuar Tati Suprapti Taufik Hidayat Tegar Lazuardi, Muhammad Thomas Agam Tiana Dewi Tri Anelia Trian Nurmansyah Triswanto, Triswanto Tuti Hartati Tuti Hartati Tuti Hartati Wahyudi Wahyudi Wartumi Wartumi Willy Prihartono Winayah, Winayah Windy Astuti Witriyani Witriyani Yudis Firmansyah Yufita, Ayura yulani, Yulani - Yulia, Yuli