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All Journal TEKNIK INFORMATIKA JURNAL SISTEM INFORMASI BISNIS Voteteknika (Vocational Teknik Elektronika dan Informatika) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Riau Journal of Computer Science JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Penelitian Pendidikan IPA (JPPIPA) Indonesian Journal of Artificial Intelligence and Data Mining Rang Teknik Journal ILKOM Jurnal Ilmiah MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Journal of Information Technology and Computer Engineering Jambura Journal of Informatics ComTech: Computer, Mathematics and Engineering Applications Jusikom: Jurnal Sistem Informasi Ilmu Komputer bit-Tech Dinasti International Journal of Education Management and Social Science Systematics Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Informatika Ekonomi Bisnis Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Ilmiah Manajemen Kesatuan Dinasti International Journal of Digital Business Management JUKI : Jurnal Komputer dan Informatika Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Journal of Applied Computer Science and Technology (JACOST) Journal of Computer Scine and Information Technology Bulletin of Computer Science Research Jurnal Penelitian Inovatif Jurnal Ipteks Terapan : research of applied science and education Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Sistim Informasi dan Teknologi Jurnal Administrasi Sosial dan Humaniora (JASIORA) Innovative: Journal Of Social Science Research e-Jurnal Apresiasi Ekonomi Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) SmartComp Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Sarjon Defit
Universitas Putra Indonesia YPTK Padang
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Machine Learning Predicts the Level of Disease Spread Saputra, Dhio; Wisky, Irzal Arief; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 4 (2024): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i4.7070

Abstract

The aim of the research is predictive analysis of the spread of disease. Variable analysis at the population level in a region and the total disease events detected in the community. These variables can show the accuracy and certainty of the status of the resulting analysis. The concept of Machine Learning analysis is proposed to develop previous analysis models. The methods used include the K-Means cluster, Naïve Bayes, and Decision Tree (DT). There are two stages in the analysis process: pre-processing and classification. The discussion presented by K-Means provides a classification analysis pattern. The patterns obtained will be passed on to the classification process using Naïve Bayes and DT. Naïve Bayes results provide quite significant results with an accuracy rate of 83.33%. DT can also describe the results of information and knowledge analysis in the form of decision trees. DT produces decision trees that can provide knowledge and information analysis. The DT results provide an accuracy rate of 91.76% so these results can be used as consideration in decision making. The resulting information and knowledge can be used as a guide in making policies for handling health in the community.
Prediction of Graduation Accuracy Using the K-Means Clustering Algorithm and Classification Decision Tree Rahmawati, Sri; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 4 (2024): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i4.7073

Abstract

Becoming a scholar at the right time for students is a very meaningful award for them if it is supported by seriousness and perseverance in their studies. Here, sample data was taken from 131 randomly taken in testing. Where there are still students who are not detected by the study program in completing their lectures, so research is carried out on clustering and classification with decision trees in determining the level of accuracy of lectures by clustering data, determining the initial centroid value and the centroid point. The results found were that there were 78 people grouped in cluster 0 and 53 people grouped in cluster 1, where those with potential for punctuality for their studies were in cluster 0 so they were students who could finish within the specified time. Meanwhile, students grouped in cluster 1 illustrate that these students need coaching and guidance both in the study program and with their supervisors. In the classification taken from the results of data clustering, two classes were obtained, namely class a and class b, with 73 and 58 data respectively, so that the results between clustering and classification did not differ too much in the data to predict the accuracy of a student's graduation.
Rought Set: Effective Method for Determining Scholarship Recipients Andin, Silfia; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 4 (2024): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i4.7088

Abstract

Every year, higher education institutions receive a KIP Tuition scholarship quota that has been determined by Ristek Dikti through LLDIKTI which is given during the new student admissions process. The process of determining recipients is carried out manually resulting in inaccurate scholarship recipients being selected and the selection results may not be the same based on those who participated in making the decision. This research is motivated by the need for an algorithm for determining prospective scholarship recipients that is appropriate and effective because the recipient selection process often takes a long time because many high school and equivalent students register so that they exceed the quota limit while the quota given is limited. This research aims to use a system for scholarship recipients and provide rules and knowledge, namely rough set Theory and adapted to the Rosetta application, using prospective student data during the selection process for new students who apply for the KIP Kuliah scholarship in the 2020/2021 academic year. The resulting decision is the KIP Opportunity which consists of 4 (four) attributes, including parents' income, housing status, dependents, and parental status. The results of this research using sample data from 12 people produced 6 (six) rules and knowledge of 26 rules. This research is very supportive in identifying the eligibility of KIP Kuliah recipients.
Texture and Flag Color Extraction in Backpropagation Neural Network Architecture Rizki, Syafrika Deni; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 5 (2024): May
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i5.7146

Abstract

A flag is a rectangular or triangular piece of cloth or paper used as a symbol of the state, association, body, etc. or as a sign. It is often also used to symbolize a country to show its sovereignty. Along with the large number of countries, the country's flag also has many varieties and colors. The use of computers as a human aid is expected to the extent that the computer's ability can replace the limitations that humans have. Humans can recognize an object by using their eyes and brain, but if the eyes and brain cannot work properly it will hamper human work. In this research, training will be conducted on the Back Propagation Neural Network Architecture. Characteristic data for image recognition is obtained by extracting texture features and RGB color features. So that the network can recognize the flags by matching the feature data obtained from the training carried out. Characteristic data obtained from 24 data consisting of 16 training images and 8 testing images. From the results of the image network training can be identified properly, the accuracy rate of object identification is 87.50%. GUI users are able to identify flag images based on RGB text and color features.
Development of the Rough Set Method to Determine Lecturer Scholarship Opportunities Surmayanti; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 5 (2024): May
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i5.7147

Abstract

Currently, all groups can experience the development of artificial intelligence, this happens because artificial intelligence has experienced very significant changes. Artificial Intelligence (AI) consists of several branches, one of which is machine learning. Machine Learning (ML) technology is a branch of AI that is very interesting because it is a machine that can learn like humans. The method used here is the rough set method. In this research, a case will be raised to determine scholarship opportunities for lecturers based on predetermined criteria. To solve the problem above, machine learning was used using the Rough Set method, using Rosetta software. By the regulations determined by the scholarship provider, in this case, the institution concerned where the lecturer is registered as teaching staff to obtain a scholarship, criteria are needed to determine who will be selected to receive the scholarship. The distribution of scholarships is carried out to improve lecturer performance, as an achievement as well as an appreciation for the lecturer concerned for his long service to the institution.
Customized Convolutional Neural Network for Glaucoma Detection in Retinal Fundus Images Islami, Fajrul; Sumijan; Defit, Sarjon
Jurnal Penelitian Pendidikan IPA Vol 10 No 8 (2024): August
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i8.7614

Abstract

Glaucoma is one of the leading causes of permanent blindness and remains a current challenge in the field of ophthalmology. This research aims to present a comprehensive investigation into the development and evaluation of new technology for glaucoma detection in retinal fundus images. The development and evaluation are presented on a customized architecture, using the Convolutional Neural Network (CNN) method. The proposed CNN architecture is designed to address the complex characteristics of glaucoma changes in the identification process. The research dataset consists of 506 retinal images categorized into 117 glaucoma images, 19 suspected glaucoma images, and 370 healthy images. Through our in-depth exploration, we conducted a careful analysis to uncover patterns and fundamental trends related to glaucoma-related features. During the training phase, the proposed CNN achieved outstanding average accuracy, sensitivity, and specificity values of 92.88%, 94.66%, and 89.31%, respectively. In the unseen test dataset, the model demonstrated competitive performance with an accuracy of 80.87%, sensitivity of 85.65%, and specificity of 71.26%. These findings emphasize the potential of the model as a reliable tool for glaucoma detection. The results indicate that the proposed method utilizing a customized CNN architecture is designed for glaucoma detection in retinal fundus images. The presented output results also hold promise for clinical relevance and can be considered an improvement in the care of retinal fundus patients.
Implementasi Algoritma Apriori dalam Data Mining untuk Optimalisasi Stok Obat di Apotik Parinduri, Rezti Deawinda; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal KomtekInfo Vol. 11 No. 3 (2024): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v11i3.544

Abstract

Data Mining memainkan peran penting dalam mengelola dan menganalisis data besar untuk menemukan pola tersembunyi yang mendukung pengambilan keputusan strategis. Algoritma Apriori, yang dikenal untuk menemukan aturan asosiasi dalam data, menjadi alat yang sangat penting di berbagai sektor, termasuk sektor kesehatan. Dalam pengelolaan stok obat di apotek, terdapat tantangan signifikan seperti kelebihan stok, kekurangan stok, dan risiko kedaluwarsa obat, yang semuanya memerlukan solusi yang tepat dan canggih. Penelitian ini bertujuan untuk menerapkan Algoritma Apriori dalam Data Mining guna meningkatkan efektivitas pengelolaan stok obat, dengan fokus pada beberapa aspek kunci: pertama, memantau dan menganalisis pola pembelian obat secara mendalam; kedua, meningkatkan tata kelola stok melalui penerapan sistem monitoring otomatis yang terintegrasi dengan algoritma tersebut; dan ketiga, mengurangi tingkat kedaluwarsa obat melalui analisis data transaksi yang lebih komprehensif. Data transaksi yang digunakan dalam penelitian ini berasal dari PT Enseval Putera Megatrading Tbk. Cabang Padang, yang meliputi periode 3-7 Juni 2024. Data ini dianalisis menggunakan Microsoft Excel 2010 untuk pengolahan awal dan disimulasikan lebih lanjut dengan RapidMiner untuk memvalidasi hasil. Algoritma Apriori diterapkan untuk menentukan stok obat yang optimal melalui proses yang mencakup penentuan minimum support sebesar 3% dan confidence sebesar 40%, serta eliminasi itemset yang tidak relevan atau yang tidak memenuhi kriteria. Hasil dari analisis ini berhasil menemukan enam aturan asosiasi yang dapat digunakan untuk meramalkan stok obat secara lebih efektif dan efisien. Implementasi Algoritma Apriori diharapkan dapat secara signifikan meningkatkan efisiensi dalam manajemen stok obat, mengurangi risiko kelebihan atau kekurangan stok, serta meminimalkan masalah kedaluwarsa obat. Lebih dari itu, penelitian ini juga berkontribusi pada pengembangan pengetahuan ilmiah dalam bidang Data Mining dan manajemen stok obat, serta memberikan landasan yang kuat bagi penelitian lanjutan dan aplikasi praktis dalam konteks yang serupa. Dengan demikian, hasil penelitian ini tidak hanya memberikan solusi praktis untuk masalah pengelolaan stok obat, tetapi juga memperluas cakrawala pengetahuan dalam penggunaan teknik Data Mining untuk tujuan manajerial di bidang kesehatan.
The Role of Customer Trust as a Mediator in Building Loyalty to Agung Toyota After-Sales Service Rahmadani Hidayat; Sarjon Defit; Yulasmi
Jurnal Ilmiah Manajemen Kesatuan Vol. 13 No. 4 (2025): JIMKES Edisi Juli 2025
Publisher : LPPM Institut Bisnis dan Informatika Kesatuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37641/jimkes.v13i4.3477

Abstract

This study aims to analyze the role of customer trust as a mediator in building loyalty in Agung Toyota's after-sales service. Customer loyalty is an important aspect of business sustainability and service quality is considered a factor that influences it. However, in practice, the effect of service quality on customer loyalty is not always direct, but can be mediated by customer trust factors. This study uses a quantitative approach with a survey method. Data were collected by distributing questionnaires to 200 respondents who are Agung Toyota Pekanbaru Harapan Raya customers. The data analysis technique used is Structural Equation Modeling (SEM) with the help of SmartPLS software. The results of the study indicate that service quality has a positive and significant effect on customer trust. Furthermore, customer trust is proven to have a positive and significant effect on customer loyalty. Interestingly, service quality also has a direct effect on customer loyalty, but the effect becomes stronger when mediated by customer trust. This indicates that trust acts as a partial intervening variable in the relationship between service quality and customer loyalty. The implications of this study indicate that companies need to consistently improve the dimensions of service quality to build customer trust, which will ultimately increase their loyalty. By focusing on creating trust through superior service, companies can build long-term, profitable relationships with customers.
Sentiment Analysis in Platform X with the Support Vector Machine Method for Generation Z Sri Dewi, Apriandini; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal KomtekInfo Vol. 12 No. 4 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i4.659

Abstract

Advances in information technology and the increasing use of social media have significantly influenced the behavior of Generation Z. The generation born between 1997 and 2012 is known to be very familiar with the digital world, but also faces challenges such as lack of in-person social interaction and the risk of mental health disorders. This study aims to identify and classify public sentiment towards Generation Z on social media, especially on platform X (formerly Twitter). The method used is the Support Vector Machine (SVM). This research was carried out through several stages, namely the collection of 1607 data in the form of text using crawling techniques, pre-processing of text (tokenization, case folding, removal of stopwords, stemming, and normalization), and feature extraction using the Term Frequency-Inverse Document Frequency (TF-IDF) method. The processed data is then classified into three sentiment categories: positive, negative, and neutral using SVM. Evaluation was carried out by measuring accuracy, recall value, and F1-score value through a confusion matrix. The results showed that the measurement of an accuracy value of 85%, a precision value of 85%, a value of recall of 95% and an F1-score value of 90% that SVM was able to classify sentiment with high accuracy and stability. In addition, SVM has been shown to be more effective than other methods studied in previous studies. The data analyzed shows that most sentiment towards Generation Z is negative, reflecting public concern about the behavior and mindset of this generation. This research is expected to be a reference for academics, practitioners, and policymakers in understanding public opinion and designing targeted policies for the younger generation. Keywords: Sentiment Analysis, Generation Z, Support Vector Machine, Social Media, Machine Learning.
Ekplorasi Timeline : Waktu Respon Pesan Terbaik WhatSapp Group “Gurauan kita STMIK Amik” Susandri susandri; Sarjon Defit; Fristi Riandari; Bosker Sinaga
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 20 No. 2 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v20i2.1149

Abstract

WhatsApp merupakan salah satu aplikasi pesan instan yang banyak di gunakan saat ini. WhatsApp memungkinkan pengguna membuat grup. Sering pesan pada grup tidak terbaca dan terabaikan oleh anggota grup. Perlu dilakukan analisa waktu yang tepat sebuah pesan direspon anggota grup dengan cepat sehingga informasi dapat disampaikan dengan baik pada semua anggota. Penelitian ini melakukan explorasi WhatSapp Group “Gurauan kita STMIK Amik” untuk menentukan waktu terbaik menyampaikan pesan dengan metode timeline serta menganalisis anggota yg berjumlah 32 orang, emoji dan sentimen. Pada Analisis sentimen dari 1095 total pesan, sentimen positif 35.53% dan sentimen negatif 64.47%. Respon emoji dari anggota sebanyak 46% menggunakan pesan emoji diatas 50% dan 34% anggota menggunakan emoji dibawah 50% sedangkan 18 % anggota tidak pernah menggunakan emoji. Dalam penelitian ini dari proses timeline dapat disimpulkan waktu terbaik untuk mengirimkan pesan pada hari selasa dan jum’at pada jam 10, 13 sampai 15 siang dan jam 20 pada malam hari.
Co-Authors Abdul Azis Said Adawiyah, Quratih Adek Putri Adi Gunawan Adi Gunawan, Adi Adyanata Lubis Afriyadi, Iqbal Agus Perdana Windarto Agustin, Riris Ahmad Zaki Ahmad Zamsuri, Ahmad Akbar, Muhamad Rafi Akbar, Syifa Chairunnissa Deliva Am, Andri Nofiar Amran Sitohang Anam, M Khairul Andema, Henky Andin, Silfia Andri Nofiar Angga Putra Juledi Anthony Anggrawan Arda Yunianta ardialis Ariandi, Vicky Arif Budiman Arif Budiman Arika Juwita Z Asri Hidayad Ayunda, Afifah Trista Bastola, Ramesh Bosker Sinaga Breinda, Engla Bufra, Fanny Septiani Daeng Saputra Perdana Dahria, Muhammad Daniel Theodorus Dayla May Cytry Dendi Ferdinal Deno Yulfa Ardian Deti Karmanita Devita, Retno Dhena Marichy Putri Dila, Rahmah Dinda Permata Sukma Dwi Utari Iswavigra Dwiki Aulia Fakhri Efendi, Akmar Efendi, Muhamad Efrizoni, Lusiana Eka Praja Wiyata Mandala Elda, Yusma Elfiswandi Elfiswandi eriwandi Fadlul Hamdi Faisal Roza Fajrul Islami Fanny Septiani Bufra Fatimah, Noor Fauzan Azim Fauzana, Rahmi Fauzi Erwis Febri Aldi Febri Hadi Febrina, Yerri Kurnia Firdaus, Muhammad Bambang Fitriani, Yetti Fristi Riandari Fristi Riandari Fuad El Khair Gaja, Rizqi Nusabbih Hidayatullah Gunadi Widi Nurcahyo Guslendra, Guslendra Hadiyanto, Tegas Halifia Hendri Handika, Yola Tri Haris Kurniawan Hartati, Yuli Hasmaynelis Fitri Haviluddin Haviluddin Hazlita, H Hendrik, Billy Hendro Budiantoro Hengki Juliansa Henky Andema Hermanto Hidayad, Asri Hidayat, Rahmadani Honestya, Gabriela Huda, Ramzil Ikhbal Salam, Riyan Indah Savitri Hidayat Indhira, Sonia INTAN NUR FITRIYANI Ira Nia Sanita Irsyad, As'Ary Sahlul Irzal Arief Wisky Ismail Virgo Jefdy Kurniawan Jeri Wandana Juansen, Monsya Jufri, Fikri Ramadhan Juledi, Angga Putra Junadhi, Junadhi Kareem, Shahab Wahhab Khairul Azmi Kurniawan, Jefdy Kurniawan, Mhd Hary Leony Lidya Lidya, Leoni Lubis, Fitri Amelia Sari Lubis, Siti Sahara Lusiana Lusiana M Syahputra M. Ibnu Pati M. Iqbal Zuqron M. Syahputra Mardayatmi, Suci Mardian, Zurni Mardison Mardison Mardison Marfalino, Hari Meilinda Sari Meilinda Sari Melissa Triandini Menhard, Menhard Mhd Hary Kurniawan Miftahul Hasanah Miftahul Hasanah, Miftahul Mike Zaimy Monsya Juansen MUHAMMAD TAJUDDIN Muhammad Tajuddin Muhammad, L. J. Mulyanda, Sandy Mutiana Pratiwi Nadya Alinda Rahmi Nandan Limakrisna Nanik Istianingsih Nori Sahrun, Nori Novi Yanti Nurcahyo, Gunadi Nurcahyo, Gunadi Widi Nurdin, Yogi K Nurhadi Nurhidayat Nursyahrina Okfalisa, - Okmarizal, Bisma Olivia, Ladyka Febby Pandu Pratama Putra, Pandu Pratama Parinduri, Rezti Deawinda Pati, Muhammad Ibnu Pratiwi, Mutiana Pulungan, Akhiruddin Purnomo, Nopi Putra, Akmal Darman Putra, Rahman Arief Putra, Surya Dwi Putri, Adek Putri, Dhena Marichy Putri, Yozi Aulia Putut Wicaksono, Putut R Rahmiyanti Radillah, Teuku Rafika Sani Rafiska, Rian Rafnelly Rafki Rahmad Aditiya Rahmad Rahmad Rahmadani Hidayat Rahman Arief Putra Rahmi, Nadya Alinda Ramadhan, Mukhlis Ramadhanu, Agung Ramdani Bayu Putra Rani, Larissa Navia Refina Afindania, Pipin Resnawita, R Rezki - Rezki Rusydi Rian Kurniawan Rianti, Eva Rio Andika Malik Ritna Wahyuni Rizki Mubarak Roza Marmay Roza, Yesi Betriana Rusdianto Roestam Rustam, Camila S Sumijan Said, Abdul Azis Sandrawira Anggraini Sani, Rafikasani Saputra, Dhio Sari, Imrah Sari, Laynita Selfi Melisa Septiano, Renil Setiawan, Adil Sharon Shaza Alturky Siregar, Diffri Solihin Siswahyudianto Sitanggang, Sahat Sonang Slamet Riyadi Sofika Enggari Sovia, Rini Sri Dewi Sri Dewi Sri Dewi, Apriandini Sri Rahmawati Suci Mardayatmi Suhefi Oktarian Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Surmayanti Surya Dwi Putra Suryani, Vivi Susandri, Susandri Susriyanti, Susriyanti Syafri Arlis Syafrika Deni Rizki, Syafrika Deni Syaljumairi, Raemon Syofneri, Nandel Tamaza, Muhammad Abyanda Teri Ade Putra Tesa Vausia Sandiva Tukino, Tukino Veri, Jhon Veza, Okta Virgo, Ismail Vitriani, Vitriani Wahyu, Fungki Wanto, Anjar Wenni Afrodita Weri Sirait Y Yuhandri Yamin, Abdul Yamin Yemi, Leonardo Yerri Kurnia Febrina Yetti Fitriani Yogi K. Nurdin Yoni Aswan Yuda Irawan Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yulasmi Yulasmi, Yulasmi Yuli Hartati Yulihartati, Sandra Yunus, Yuhandri Yusma Elda Zakir, Supratman Zia Rahimi, Hadisha Zulvitri, Z