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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jupiter Jurnal INKOM PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal technoscientia Jurnal Pseudocode Jurnal Intelektualita: Keislaman, Sosial, dan Sains POSITIF Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) SMATIKA KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) Jurnal Ilmiah KOMPUTASI Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research JURNAL MEDIA INFORMATIKA BUDIDARMA Syntax Literate: Jurnal Ilmiah Indonesia CogITo Smart Journal Jurnal Ilmiah Matrik INOVTEK Polbeng - Seri Informatika Jusikom : Jurnal Sistem Komputer Musirawas JURNAL INSTEK (Informatika Sains dan Teknologi) IRJE (Indonesian Research Journal in Education) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Informatika Universitas Pamulang Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Informasi MURA Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Media Sisfo J-SAKTI (Jurnal Sains Komputer dan Informatika) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Informatika Global EDUMATIC: Jurnal Pendidikan Informatika JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Tekno Kompak Jurnal Mantik Jurnal Muara Ilmu Ekonomi dan Bisnis Journal of Information Systems and Informatics Zonasi: Jurnal Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) Scientific Journal of Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknologi Informatika dan Komputer JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Djtechno: Jurnal Teknologi Informasi KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian kepada Masyarakat Bina Darma Jurnal Locus Penelitian dan Pengabdian Jurnal Bina Komputer Jurnal Pengabdian Masyarakat Information Technology (JPM ITech) Jurnal Ilmiah Ilmu Terapan Universitas Jambi International Journal of Advanced Science Computing and Engineering Innovative: Journal Of Social Science Research Bulletin of Social Informatics Theory and Application Jurnal Teknologi Informasi Mura Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Journal on Mathematics Education Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI) Smatika Jurnal : STIKI Informatika Jurnal
Edi Surya Negara
Universitas Bina Darma
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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PELATIHAN PEMBUATAN BLOG SEBAGAI LOGBOOK MAHASISWA MAGANG DI UNIVERSITAS BINA DARMA Azhiman, Fauzan; Negara, Edi Surya; Putra, Ade; Dasmen, Rahmat Novrianda; Rasmila, Rasmila; Raihan, Muhammad
Jurnal Pengabdian Masyarakat Information Technology Vol. 2 No. 2 (2023): Jurnal Pengabdian Masyarakat Information Technology - September 2023
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jpm_itech.v2i2.2645

Abstract

Logbook merupakan sebuah hal yang terpenting sebagai catatan atau dokumentasi dalam suatu kegiatan, tentunya tujuan dengan pelatihan pembuatan blog melalui wordprss menjadi sebuah logbook magang pada mahasiswa universitas bina darma untuk meningkatkan kualitas pengalaman magang serta sebagai hal yang menarik untuk pelaporan secara online. Metode yang dilaksanakan merupan Action Reaseach melalui beberapa teknis didalamnya yang ada yaitu melibatkan serangkaian workshop yang mencakup aspek teknis pembuatan blog dan manajemen konten. PkM dari pelatihan ini ditemukan bahwa mahasiswa magang yang menerapkan blog sebagai logbook mereka memiliki kecenderungan yang lebih baik dalam mencatat pengalaman dan pemahaman mereka. Blog memberi mereka ruang untuk mengekspresikan refleksi pribadi, mempromosikan pemahaman mereka tentang konteks pekerjaan, dan berbagi wawasan dengan sesama mahasiswa magang. Selain itu, blog ini juga membantu dalam mempermudah supervisi dan evaluasi oleh dosen pembimbing magang.
Komparasi Metode Klasifikasi terhadap Data Penderita Penyakit Diabetes Menggunakan Python 3 Pratiwi, Ayu Okta; Kurniawan, Tri Basuki; Negara, Edi Surya; Kunang, Yesi Novaria
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 4 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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

Abstract

Diabetes is a serious challenge in the world of health, with broad impacts. In an effort to overcome this problem, it is important to analyze the classification of diabetes data to provide valuable insights. This study focuses on the comparison of the two main classification methods, namely Naive Bayes and Support Vector Machine (SVM), in analyzing diabetes data. We use the Python 3 programming language for implementation. The initial study involved the characterization of the dataset, including parameters such as blood pressure and blood glucose levels, which were important factors in the analysis. The preprocessing process is carried out to ensure data quality by overcoming missing or invalid values. After that, the dataset is divided into training and testing subsets. The Naive Bayes and SVM methods are implemented using the scikit-learn library in Python 3. Both models are trained using a training subset and tested on a test subset. The test results show that both methods have good performance in classifying diabetes data, but SVM stands out with higher accuracy. SVM has the ability to handle complex data and find optimal decision boundaries. The Naive Bayes model achieves the highest accuracy of 78.13% on 70% training data and 30% testing data, while the SVM model achieves 79.63% on 90% training data and 10% testing data. Overall, this study provides an in-depth understanding of the effectiveness of both methods in the context of classifying data on diabetics.
Prototype Sistem Pelayanan Pengaduan Jalan Rusak Di Dinas Pekerjaan Umum Bina Marga Kabupaten Musi Rawas Menggunakan Metode Design Thinking Junisti, Alfina Wulan; Negara, Edi Surya
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.16062

Abstract

Pelayanan publik di era teknologi sekarang ini setiap aktivitas pelayanan diharapkan lebih mudah, efektif dan efisien dalam proses pelayanannya. Salah satu penerapan pelayanan publik yaitu pada infrastruktur jalan, sebagaimana UU No. 25 Tahun 2009 tentang Pelayanan Publik. Dinas Bina Marga Kabupaten Musi Rawas merupakan lembaga pemerintah yang menangani permasalahan perbaikan dan pembuatan jalan, Kabupaten Musi Rawas memiliki panjang ruas jalan 1.406,62 km2. Pembangunan jalan di Kabupaten Musi Rawas harus merata agar masyarakat tidak merasa ada diskriminasi. Untuk menyampaikan keluhan terkait kondisi jalan yang rusak masyarakat harus mengajukan proposal langsung ke Bina Marga hal tersebut dinilai kurang efektif. Maka dari itu, perlu adanya sebuah sistem yang dapat melaporkan kerusakan jalan yang dapat dimanfaatkan masyarakat untuk melaporkan kondisi kerusakan pada jalan, adapun metodologi yang digunakan pada penelitian ini ialah Design Thingking. Metode ini digunakan karena fokus dari penelitian ini adalah pengguna atau manusianya itu sendiri sebagai pengguna sistem, terdapat beberapa tahapan, antara lain memahami dan menentukan konteks pengguna, mengidentifikasi kebutuhan pengguna, membuat solusi desain, dan mengevaluasi desain. Evaluasi dapat dilakukan dengan menggunakan teknik System Usability Scale (SUS) yang dikembangkan oleh John Brooke.
Analysis of Behavioral Use of Academic Information Systems with the Implementation of UTAUT 2 Integration at the Muhammadi-Palembang Institute of Health Science and Technology Donan, Hendri; Negara, Edi Surya Negara Surya; Sutabri, Tata; Firdaus, Firdaus
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 12 No. 3 (2023): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i3.1978

Abstract

The utilization of Information Technology (IT) in higher education setting aims to enhance the quality of education, and this initiative is realized through the implementation of Information Technology at the Institute of Health Sciences and Technology Muhammadiyah Palembang (IKesT MP) in the form of an Academic Information System (SIMAKAD). SIMAKAD is a vital role as a tool to manage internal data and serves as an information hub for students. This research is conducted to evaluate the acceptance level of the UTAUT2 model and the impact of both the main and target variables within the UTAUT2 model. This research utilizes a quantitative method with 150 respondents, analyzed using SMART PLS 3.0 software." software. The research findings indicate that the acceptance level of the UTAUT2 model reaches 74%, signifying a high adoption rate. Variables like Perceived Value (p-Value: 0.019) and Habit (p-Value: 0.009) significantly influence Behavioral Intention, with a p-Value < 0.05, indicating that their hypotheses are accepted. On the other hand, variables such as Performance Expectancy (p-Value: 0.660), Effort Expectancy (p-Value: 0.417), Social Influence (p-Value: 0.652), and Facilitating Conditions (p-Value: 0.292) There is no substantial influence on Behavioral Intention as a result of using Information Technology (IT), indicating that their hypotheses have not been endorsed.. Additionally, the variable Hedonic Motivation (p-Value: 0.978) also does not can significantly impact one's inclination toward a  behavior Intention. However, variables Facilitating Conditions (p-Value: 0.000) and Behavioral Intention (p-Value: 0.000) have a positive impact on Use Behavior, indicating that their hypotheses are accepted. Conversely, the variable Habit (p-Value: 0.915) Does not exert a significant impact on Uss Behavior, resulting in the rejection of its hypothesis.
Analisis Tingkat Kepuasaan Pengguna Aplikasi Shoppe dan Facebook Menggunakan Metode E-Serqual yang Dimodifikasi pada Masyarakat Kota Prabumulih Sari, Yulia Permata; Negara, Edi Surya
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i12.17177

Abstract

Kepuasaan dalam pengguna aplikasi shoppe dan facebook merupakan kebutuhan yang diinginkan oleh Masyarakat sekitar untuk mendapatkan produk yang mereka inginkan atau bisa juga disebut dengan loyalitas atas kepuasaan mereka. Berdasarkan hasil survey penelitian ini bisa dilihat dan dibandingkan berapa persen orang yang puas dengan pengguna shoppe dan pengguna facebook dari Tingkat brand , kualitas, harga dan lainnya. Metode e-serqual yang digunakan dalampenelitian ini untuk mengukur Tingkat kepuasaan dan loyalitas pada shoppe dan facebook dengan menggunakan kuesioner yang disebarkan. Dari hasil penelitian ini terdapat bahwa shoppe lebih unggul dari pada facebook dimana dalam perhitunganskala likert dengan metode e-serqual dan dibantu SPSS sehingga terdapat nilai yang hampir pengguna aplikasi itu lebih memilih shoppe dari pada Facebook dari tingkat Kepuasaan site organization. Realibility, User Friendliness, Personal Need sedangkan dari tingkat Loyality shoppe memiliki nilai yang positif dengan Responsivenees, User Friendliness, Eficiency.
Evaluasi Kepuasaan Penggunaan Sistem Akademik Menggunakan Metode WebQual 4.0 dan IPA Ari Hardiyantoro Susanto; Edi Surya Negara
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 01 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i01.810

Abstract

Musi Rawas University is one of the private tertiary institutions in the LLDIKTI Region II Sumbagsel area which is based in Lubuklinggau City, South Sumatra. Based on PDDIKTI data for the 2021/2022 academic year, Musi Rawas University has 11 Study Programs with a total of 1,706 students. Since the implementation of SIAKAD, Unmura has never evaluated both the quality aspect of its use and the performance of the system. This is of course important to do, because this SIAKAD will not only be applied in the present but will continue to be sustainable every year. In addition, the intended evaluation will have important value for management as an inside for the development and improvement of SIAKAD so that it can be better in the future. Performance evaluation of SIAKAD at Musi Rawas University. To do this, one of the analytical methods known as Webqual 4.0 and IPA (Importance Performance Analysis) will be applied. The results obtained from this study are the usability indicator of the correspondent's answer getting a satisfied response with a value of 75.4%, and the informant quality indicator of the correspondent's answer getting a satisfied response with a value of 77.4% and the interaction quality indicator of the correspondent's answer getting a satisfied response with a value of 63.4%.
COMPARING DEEP LEARNING AND MACHINE LEARNING FOR DETECTING FAKE NEWS ON SOCIAL MEDIA Andryani, Ria; Julian, Dedek; Syaputra, Rezki; Syazili, Ahmad; Rusli, Ahmad; Ramadan, Rahmat; Negara, Edi Surya
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.46370

Abstract

One of the critical issues resulting from the increasing penetration of social media is the spread of fake news. This can damage public information and influence mass opinion, leading to conflict. To overcome this problem, machine learning and deep learning-based approaches have been continuously developed to detect fake news on various social media platforms automatically. This article aims to compare the effectiveness of these two approaches in detecting fake news. The methods used include the implementation of traditional machine learning algorithms, such as Support Vector Machines (SVM) and Random Forest, as well as deep learning-based approaches, including Long Short-Term Memory and Self-Organizing Maps. Datasets containing real and fake news from various social media sources are used to train and evaluate these models. Model performance is measured based on accuracy, precision, recall, and F1-score. This study aims to determine which approach is more effective and identify challenges in implementing these algorithms in a dynamic social media environment. The results obtained show that the Random Forest algorithm achieves an accuracy level of 100%, surpassing other algorithms, including Long Short-Term Memory with an F-1 Score of 97%, Self-Organizing Map with an F-1 Score of 96%, and Support Vector Machine with an F-1 Score of 92%.
EARLY DETECTION OF ACADEMIC DEPRESSION USING SMARTPHONE-BASED MACHINE LEARNING MODELS Negara, Edi Surya; Hermawan, Latius; Mayrita, Hastari; Arisandy, Desy; Farozi, Mohamad; Ramadan, Rahmat; Ariana, Sunda; Andryani, Ria
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.46375

Abstract

Mental health in developing countries is a common and complex problem. The problem continues to increase and is closely related to low self-confidence, negative interpersonal relationships, and academic depression. This can affect students' ability to complete academic assignments on a university scale. An AI-based early detection application can potentially improve mental health services related to treatment access. This system can help identify users who may be depressed based on the language used, especially for those who are reluctant to seek professional solutions due to the negative stigma of mental health. This study uses a qualitative descriptive method involving observation, in-depth analysis of group conversations, and early detection of academic depression by identifying conversation patterns between students and counselors as the basis for developing a smartphone-based application. This study produced a dataset of 395 depression-level data entries used as training data to develop a machine-learning model. A prototype of an academic depression detection application has been developed as a mobile-based application.
Analisis Sentimen Ulasan Aplikasi Access by KAI Menggunakan Algoritma Naïve Bayes Ariansyah, Beni; Negara, Edi Surya
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.21-27

Abstract

The Access By KAI application, developed by PT Kereta Api Indonesia (Persero), allows users to purchase train tickets via mobile devices. This study aims to perform sentiment analysis on user reviews of the Access By KAI application using the naive Bayes algorithm. Data processing was carried out through stages such as case folding, cleaning, tokenizing, stopword removal, and stemming, and evaluation using metrics of accuracy, precision, recall, and F1-score showed that the naive Bayes algorithm provides satisfactory results. The study results indicate that the naive Bayes algorithm is able to classify reviews with an accuracy rate of up to 68% with a precision of 83% for the positive class, 59% for the negative class, and 79% for the neutral class; recall of 67% for the positive class, 93% for the negative class, and 42% for the neutral class. From these results, it is expected to help developers identify the aspects most complained about by users and improve service quality.
Agile-Based Integrated Community Information System With Marketplace Feature: Empirical Evaluation In The Papuan Student Community Of Sriwijaya (Kompas) TISJANDT, TIPRAN YIKWA; Negara, Edi Surya
Jurnal Ilmu Komputer dan Sistem Informasi |JIKSI| Vol. 6 No. 3 (2025): Jurnal Ilmu Komputer dan Sistem Informasi (JIKSI)
Publisher : Institute of Information Technology and Social Science (IITSS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61346/jiksi.v6i3.308

Abstract

Papuan students in South Sumatra face challenges related to fragmented communication, limited information accessibility, and low participation in organizational activities. The absence of an integrated digital platform has reduced coordination efficiency within the Papuan Student Community of Sriwijaya (KOMPAS). This study aims to design and empirically evaluate an Agile-based integrated web information system incorporating digital governance and marketplace features to enhance organizational performance and engagement. The system was developed using the Agile methodology through five iterative sprints over a ten-month period involving 15 organizational stakeholders and 75 active members. The platform was implemented using Laravel and MySQL within a three-tier architecture framework. Evaluation procedures included functional testing, performance analysis, and usability assessment using the System Usability Scale (SUS). The results indicated an average page load time of 1.2 seconds (desktop) and 2.8 seconds (mobile), with a PageSpeed score of 94 and 85% unit test coverage. The system achieved a SUS score of 82.5, categorized as excellent usability. After one month of implementation, information accessibility increased from 24% to 76%, participation rose from 38% to 62%, and member engagement improved from 31% to 73%. The marketplace module recorded 23 transactions totaling Rp 8,500,000. These findings demonstrate that integrating digital governance mechanisms with marketplace functionality significantly enhances coordination, engagement, and economic participation in student-based community organizations.
Co-Authors AA Sudharmawan, AA Adam Prasetya Ade Putra Adi Wijaya Adila, Nia Aditya, Ferdi Agam, Padel Mohammad Ahmad Ghiffari Ahmad Syazili Akhiruddin, Deddy Rezano Amanda, Riyan Amin, Zulius Akbar Andreean Dharma Arisandi Andry Meylani andryani, ade Andryani, Ria Andryani, Ria Ari Hardiyantoro Susanto Ari Hardiyantoro Susanto Ariansyah, Beni Arjun, Jennifer Axel Natanael Salim Azhiman, Fauzan Bhagaskara, - Bhianta Wijaya Chairul Mukmin Cynthia Anisa Agatha Damayanti, Nita Rosa damayanti, selvia Dasmen, Rahmat Novrianda Deddy Rezano Akhiruddin Dedek Julian Dedi Irawan Dedy Syamsuar Dedy Syamsuar Dendi Triadi Dendi Triadi Deni Erlansyah Deris Stiawan Destarina, Nova Desy Arisandy Diana Donan, Hendri ENDRI ENDRI ERIENE DHEANDA evariani, evariani Fajarino, Aldo Farozi, Mohamad Fatoni Ferdiansyah Ferdiansyah Fernandy Jupiter Firdaus Firdaus H. Mukran Roni, H. Mukran Hastari Mayrita, Hastari Hendra Marta Yudha Herdiansyah, Izman Herdiansyah, M. Izman Herdiansyah, M. Izman Indah, Mayang Puspa Jemakmun, Jemakmun Julian, Dedek Juminovario Juminovario Junisti, Alfina Wulan KENI KENI Kiki Rizky Nova Wardani Kisworo, Marsudi Wahyu Kurniawan, Tri Basuki Latius Hermawan Linda Atika Linda Atika Liza Fahreni M Izman Herdiansyah Maria Ulfa Meilinda Meilinda Mery Sintia Mochammad Imron Awalludin Muhamad Akbar Muhammad Cahyono MUHAMMAD FAHMI Muhammad Izman Herdiansyah Muhammad Izman Herdiansyah Muhammad Marzuki Muhammad Marzuki Muhammad Qurhanul Rizqie Muhammad Raihan Muhammad Wahyudi Nanda Tri Haryati Nico Michael Bryan Novaria Kunang, Yesi Novita Anggraini Novrianda, Rahmat Nurhachita Nurhachita Nurhachita Nurhachita Oktariansyah Oktariansyah, Oktariansyah Pratiwi, Ayu Okta Prihambodo Hendro Saksono Purnama Dharmawan Puspita Dewi Setyadi Putra, Yusuf Andi Putri Armilia Prayesy Qisthiano, M Riski Rahmad Kartolo Rahmat Gernowo Raihan, Muhammad Ramadan, Rahmat Ramadani Ramayanti, Indri Rasmila, Rasmila REZA PAHLEVI Reza Pahlevi Reza Vidi Aditama Ria Andriani Ria Andryani Rianda, M. Rianda Rifan Fadilah Rivaldi, Ahmad Riyan Amanda Rizma Adlia Syakurah Robby Prabowo RR. Ella Evrita Hestiandari Rusli, Ahmad Saksono, Prihambodo Hendro Sari, Yulia Permata Saro, Dewi Novita Sunda Ariana, Sunda Supratman, Edi Suryayusra Syaputra, Rezki Tata Sutabri TISJANDT, TIPRAN YIKWA Tri Basuki Kurniawan Triadi , Dendi Triyunsari, Desra Usman Ependi Wawan Setiawan Widya Cholil Winata Nugraha Winoto Chandra Yandi, Jepri Yeni Widyanti Yepi Kusmeta Yesi Novaria Kunang Yessi Novaria Kunang Yuni Amrina Yuranda, Rezky Yusuf Andi Putra Yusuf, Abi daud Zulius Akbar Amin