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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Ilmu Komputer dan Informasi ELINVO (Electronics, Informatics, and Vocational Education) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INOVTEK Polbeng - Seri Informatika Jurnal Eksplora Informatika ILKOM Jurnal Ilmiah Didaktik : Jurnal Ilmiah PGSD STKIP Subang Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Panrannuangku Jurnal Pengabdian Masyarakat Archive: Jurnal Pengabdian Kepada Masyarakat Seminar Nasional Pengabdian Kepada Masyarakat Edukasia: Jurnal Pendidikan dan Pembelajaran Global Journal Basic Education Internet of Things and Artificial Intelligence Journal Teknovokasi : Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat Seminar Nasional Hasil Penelitian LP2M UNM Information Technology Education Journal Journal of Embedded Systems, Security and Intelligent Systems Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal of Deep Learning, Computer Vision and Digital Image Processing EduInovasi: Journal of Basic Educational Studies Journal of Progressive Information, Security, Computer and Embedded System Jurnal MediaTIK Journal of Computers, Informatics, and Vocational Education Journal of Engineering and Science Application Jurnal MEKOM: Media Komunikasi Pendidikan Kejuruan Media Elektrik Journal of Smart Education and Emerging Technology Journal of Emerging Research in Computer Science and Artificial Intelligence Journal of Education for Creativity and Innovation Jurnal Kendali Teknik dan Sains
Jumadi Mabe Parenreng
Department Of Informatics And Computer Engineering, Faculty Of Engineering Makassar State University
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Internet-based Design of Hydroponic Plants Monitoring and Automation Control Systems Parenreng, Jumadi Mabe; Andani, Andi Ferry Adlian Tri; Yahya, Muhammad; Adiba, Fhatiah
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i2.744

Abstract

Melons are one of the fruit types widely favored in the market due to their high content of vitamins, minerals, and water. Melon plants are challenging to cultivate when environmental conditions such as soil and air do not align with their characteristics. One way to address this is through hydroponic cultivation, which reduces the interaction of melon fruits with the air and environment. However, this method has a drawback in that the nutrient solution and water circulation of the plants must be continuously monitored. Therefore, a system is needed to automatically monitor and control the conditions of hydroponic plant growth with the assistance of IoT technology. This research proposes the Design and Implementation of a Monitoring and Automation System for Hydroponic Plant Control Based on the Internet of Things. The hydroponic system, specially designed for melon plants, is equipped with various sensors that can monitor soil nutrients in real time through mobile devices. Based on the test results, the TDS sensor yielded a result of 1313 PPM, the pH Water sensor showed 50.1, and the system also measured air temperature and humidity using DHT22, with air temperature at 29.5°C and humidity at 71.2%.
System for Determining Plant Types Based on Weather Characteristics and Soil pH Using Artificial Intelligence Akbar, Trisakti; Zain, Satria Gunawan; Kaswar, Andi Baso; Parenreng, Jumadi Mabe
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 2 (2025): Volume 5 Issue 2, 2025 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i2.902

Abstract

This research implements the Long Short-Term Memory (LSTM) algorithm for weather forecasting using minimum temperature, maximum temperature, average temperature, air humidity, rainfall, and solar radiation values over the past 30 days. The output consists of forecasts for average temperature, air humidity, rainfall, and solar radiation for the next 30 days. The LSTM model output and soil pH are used to determine plant types using the K-Nearest Neighbor (K-NN) algorithm. Based on the LSTM model testing results, the minimum temperature feature achieved a Mean Absolute Error (MAE) of 0.0078, a maximum temperature of 0.0054, an average temperature of 0.009, air humidity of 0.0099, rainfall of 0.0042, and solar radiation of 0.0208. For the K-NN model, an accuracy of 98% was obtained.
Visual Impaired Assistance for Object and Distance Detection Using Convolutional Neural Networks Parenreng, Jumadi Mabe; Andi Baso Kaswar; Ibnu Fikrie Syahputra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5491

Abstract

Vision is a very valuable gift from God; Most aspects of human needs in the body are dominated by vision. Based on data from the World Health Organization (WHO) there are around 180 million people in the world experiencing visual impairment, while the prevalence of blindness in Indonesia reaches 3 million people (1.5% of Indonesia's population), so we designed a system in the form of a prototype that could detect objects around the user and convey data in the form of sound to the user. This research discusses the application of a machine learning model using the Convolutional Neural Network method to detect objects optimally. The objects that have been collected will be trained on machine learning and produce a model to be embedded in the system's main machine, namely the Raspberry PI 4B. The training of the machine learning model was carried out several times by changing the compositions of several layers until a model with optimal accuracy was obtained; however, the size of the resulting model was quite large, so the researchers carried out SSDMobileNetV2 transfer learning to obtain the optimal model. The optimal model was obtained with a model precision of 92% and a model size of 18 MB. Object detection tests carried out under 3 test conditions resulted in an average object detection accuracy of 84.3%, and distance detection tests carried out under 10 conditions resulted in an average distance detection error of 2.1 cm. The results show that the system was accurate and effective.
Multimodal Biometric Recognition Based on Fusion of Electrocardiogram and Fingerprint Using CNN, LSTM, CNN-LSTM, and DNN Models Agustina, Winda; Nugrahadi, Dodon Turianto; Faisal, Mohammad Reza; Saragih, Triando Hamonangan; Farmadi, Andi; Budiman, Irwan; Parenreng, Jumadi Mabe; Alkaff, Muhammad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5098

Abstract

Biometric authentication offers a promising solution for enhancing the security of digital systems by leveraging individuals' unique physiological characteristics. This study proposes a multimodal authentication system using deep learning approaches to integrate fingerprint images and electrocardiogram (ECG) signals. The datasets employed include FVC2004 for fingerprint data and ECG-ID for ECG signals. Four deep learning architectures—Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and Deep Neural Network (DNN)—are evaluated to compare their effectiveness in recognizing individual identity based on fused multimodal features. Feature extraction techniques include grayscale conversion, binarization, edge detection, minutiae extraction for fingerprint images, and R-peak–based segmentation for ECG signals. The extracted features are combined using a feature-level fusion strategy to form a unified representation. Experimental results indicate that the CNN model achieves the highest classification accuracy at 96.25%, followed by LSTM and DNN at 93.75%, while CNN-LSTM performs the lowest at 11.25%. Minutiae-based features consistently yield superior results across different models, highlighting the importance of local feature descriptors in fingerprint-based identification tasks. This research advances biometric authentication by demonstrating the effectiveness of feature-level fusion and CNN architecture for accurate and robust identity recognition. The proposed system shows strong potential for secure and adaptive biometric authentication in modern digital applications.
An approach of battery adaptation in wireless sensor network with resource aware in extreme environmental area Parenreng, Jumadi Mabe; Shiraj, Muhammad Reza; Zain, Satria Gunawan; Wahid, Abdul
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1812-1821

Abstract

A wireless sensor network (WSN) is a distributed wireless system that employs sensor nodes to perform various tasks, including sensing, monitoring, data transmission, and delivering information to users via internet communication. Resource availability in WSNs is a critical factor influencing data delivery performance. One of the main challenges is the rapid depletion of resources, particularly batteries, which play a pivotal role in the system’s operational sustainability. This study evaluates the impact of battery adaptation through four testing scenarios. The results show that implementing battery adaptation significantly extends system lifespan compared to scenarios without adaptation. In the scenario without both a classification algorithm and adaptation, the system lasts approximately 270 minutes. When battery adaptation is applied without a classification algorithm, the lifespan increases to 330 minutes and 30 seconds. In contrast, the scenario using a classification algorithm without adaptation yields a lifespan of about 185 minutes, while combining the classification algorithm with adaptation extends it to approximately 252 minutes. The findings demonstrate that battery adaptation enhances the longevity and resource efficiency of WSN systems. However, the use of a classification algorithm tends to reduce operational time compared to scenarios that do not employ such algorithms.
Sistem Penentuan Mahasiswa Berprestasi menggunakan metode Analytic Hierarchy Process (Studi Kasus : Fakultas Teknik UNM) Jariah, Rezki Nurul; Fadiah, Nur; Surianto, Dewi Fatmarani; Parenreng, Jumadi M; Adiba, Fhatiah
Eksplora Informatika Vol 14 No 1 (2024): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1096

Abstract

Penentuan mahasiswa berprestasi merupakan langkah krusial dalam meningkatkan mutu pendidikan, namun menentukan kriteria yang sesuai dan mengukur kinerja mahasiswa secara adil dan efektif merupakan suatu tantangan. Oleh karena itu, penelitian ini bertujuan untuk mengeksplorasi serta mengimplementasikan sistem pendukung keputusan berbasis Analytical Hierarchy Process (AHP) dalam menentukan mahasiswa berprestasi di lingkungan akademik, berdasarkan empat kriteria utama yaitu nilai IPK, jumlah prestasi yang dicapai, partisipasi dalam organisasi, dan total SKS yang telah dilulusi. Hasil penelitian ini menunjukkan bahwa sistem yang dibangun mampu menentukan mahasiswa berprestasi dengan menggunakan bobot standar. Bobot tersebut dihitung berdasarkan nilai IPK minimal 3.5, jumlah prestasi minimal 2, jumlah organisasi minimal 1, dan jumlah SKS yang dilulusi minimal 85. Hasil pengujian diperoleh bahwa Metode AHP dapat diimplementasikan dalam penentuan mahasiswa berprestasi dengan tingkat usabilitas mencapai 91,63% yakni pada kategori sangat layak. Dengan demikian, penelitian ini tidak hanya mengidentifikasi masalah dalam penentuan mahasiswa berprestasi, tetapi juga memberikan solusi konkret melalui penggunaan AHP, membuktikan efektivitasnya dalam meningkatkan keakuratan dalam seleksi mahasiswa berprestasi di lingkungan akademik.
Clustering and Modeling of Daily Weather Pattern Distribution in Makassar City Using Hybrid DBSCAN-Gaussian Mixture Model Risaldi, Muhammad; Safitri, Ayu; Nur Risal, Andi Akram; Surianto, Dewi Fatmarani; Andayani, Dyah Darma; Edy, Marwan Ramdhany; Firdaus, Firdaus; Parenreng, Jumadi M
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5254

Abstract

Dynamic and irregular daily weather changes present major challenges in understanding seasonal patterns. Data uncertainty, outliers, and inter-season variability further complicate weather analysis using conventional methods. To address this issue, this study integrates Density-Based Spatial Clustering of Application with Noise (DBSCAN) and Gaussian Mixture Model (GMM) to analyze daily weather patterns in Makassar City. A total of 2,192 daily records from 2019 to 2024, including rainfall, specific humidity, atmospheric pressure, and wind speed, were examined. DBSCAN detected one dominant cluster (2019 data) and 173 outliers. The main cluster was further partitioned by GMM into three sub-clusters representing the wet (511 records, 13.39 mm rainfall), dry (633 records, 0.15 mm), and transition (875 records, 2.53 mm) seasons. GMM identified 1,764 fixed clusters and 255 ambiguous data points, with a log-likelihood of 5091.22 and the highest Silhouette Score of 0.188. Comparative evaluation demonstrated that the hybrid DBSCAN-GMM achieved superior performance (Silhouette Score = 0.1434) compared to DBSCAN or GMM individually. The novelty of this research lies in applying the DBSCAN-GMM integration, which is rarely used in tropical weather analysis, to capture seasonal structure and anomalies adaptively. This study contributes methodologically to clustering-based weather modeling and practically supports applications such as agricultural planning, disaster mitigation, and adaptive climate strategies in tropical regions.
Pengembangan E-Modul Mata Kuliah Sistem Terdistribusi di Jurusan Teknik Informatika dan Komputer FT-UNM Sul Fikran; Jumadi M. Parenreng; Muhammad Riska
Journal of Computers, Informatics, and Vocational Education Volume 1 Issue 3, November (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

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

Abstract

Penelitian ini bertujuan untuk mengetahui kelayakan dan kepraktisan, e-modul mata kuliah Sistem Terdistribusi pada Jurusan Teknik Informatika dan Komputer di Fakultas Teknik Universitas Negeri Makassar. Penelitian ini dilakukan dalam bentuk penelitian pengembangan (Research and Development) dengan model Analysis, Design, Development, Implementation, Evaluation (ADDIE). Subjek penelitian adalah mahasiswa Jurusan Teknik Informatika dan Komputer di FT UNM yang telah memprogram mata kuliah Sistem Terdistribusi. Instrumen yang digunakan untuk mengumpulkan data meliputi lembar uji validasi dan angket respon mahasiswa, Teknik analisis data yang digunakan adalah analisis data deskriptif. Hasil penelitian menunjukkan bahwa e-modul Sistem Terdistribusi untuk Jurusan Teknik Informatika dan Komputer di FT UNM memiliki nilai persentase validitas sebesar 96,16% dengan kategori sangat layak. Selain itu, e-modul tersebut juga dinyatakan praktis berdasarkan analisis frekuensi mahasiswa dengan nilai persentase kepraktisan sebesar 73,17%. Oleh karena itu, dapat disimpulkan bahwa e-modul Sistem Terdistribusi dapat diterima sebagai bahan ajar bagi mahasiswa Jurusan Teknik Informatika dan Komputer di Fakultas Teknik Universitas Negeri Makassar.
Pengembangan Sistem Informasi Inventaris Unit Kegiatan Mahasiswa Search and Rescue Berbasis Website Karmila; Haripuddin; Jumadi M. Parenreng
Journal of Computers, Informatics, and Vocational Education Volume 1 Issue 3, November (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

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Abstract

Penelitian ini adalah rancang bangun yang bertujuan untuk menghasilkan rancangan sistem informasi inventaris berbasis website di Unit Kegiatan Mahasiswa Search and Rescue. Penelitian ini menggunakan metode rancang bangun dengan model pengembangan prototype. Berdasarkan hasil penelitian dihasilkan sebuah sistem yang dapat digunakan untuk mempermudah pencatatan, pengelolaan barang inventaris dan peminjaman barang inventaris di Unit Kegiatan Mahasiswa Search and Rescue. Berdasarkan hasil pengujian menggunakan standar ISO 25010, sistem ini telah memenuhi standar dimana: a) Pengujian aspek functional suitability bernilai 1 yang berarti semua fungsi dari sistem berjalan dengan baik; b) pengujian aspek performance efficiency berada pada kategori sangat baik; c) pengujian aspek usability dengan jumlah responden 30 orang dari anggota yang aktif diperoleh rata-rata presentase kelayakan 89% dengan kategori sangat baik; d) hasil pengujian aspek portability tidak ditemukan kesalahan atau error pada sistem; e) pengujian aspek reliability dilakukan menggunakan aplikasi WAPT dengan keberhasilannya sebesar 100%; f) pengujian aspek maintainability dilakukan menggunakan PhpMetrics yang diperoleh nilai 85,81 dengan level Moderate yang dapat diinterpretasikan normal untuk dirawat; g) pengujian aspek compatibility yang dilakukan menggunakan tools sortsite keberhasilannya tanpa ada masalah fungsi pada browser; h) pengujian aspek security yang diperoleh berada pada level 2 atau medium.
Pengembangan Sistem Informasi Apotek Melati Borong Berbasis Web Muh. Rifqi Fadhil; Jumadi M. Parenreng; Fhatiah Adiba
Journal of Computers, Informatics, and Vocational Education Volume 2 Issue 3, November (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

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Abstract

Penelitian ini bertujuan untuk menghasilkan sistem informasi apotek Melati Borong berbasis web guna mempermudah pengelolaan data serta mengevaluasi kelayakan sistem menggunakan pengujian ISO 25010 yang mencakup delapan aspek kualitas. Penelitian ini menggunakan metode Research and Development dengan model pengembangan Agile Scrum. Data dikumpulkan melalui wawancara, angket, dan dokumentasi, kemudian dianalisis menggunakan analisis kualitatif deskriptif. Hasil penelitian menunjukkan bahwa sistem yang dibangun layak digunakan. Pada aspek suitability dan reliability, sistem memperoleh persentase kelayakan 100% dan dinyatakan “Layak”. Aspek usability memperoleh persentase 93% dengan kategori “Sangat Layak”. Aspek efficiency mencapai rata-rata 84% dengan kategori grade B yang menunjukkan kinerja baik. Pada aspek maintainability, sistem memenuhi indikator instrumentation, consistency, dan simplicity. Aspek portability menunjukkan bahwa sistem berjalan baik di berbagai browser, baik desktop maupun mobile. Aspek security mendapatkan kategori grade A, yang berarti sangat aman. Aspek compatibility menunjukkan sistem kompatibel dengan berbagai browser dan dinyatakan “Sangat Layak”. Dengan demikian, sistem informasi apotek Melati Borong memenuhi standar kualitas ISO 25010 dan dinyatakan sangat layak untuk digunakan.
Co-Authors Abd. Fattah Abd. Rahman Patta Abd. Rasyid Syamsuri Abdul Hafizh Abdul Muis Mappalotteng Abdul Wahid Abdul Wahid Adiba, Fhatiah Afrisal Arifin Ahmad Ridwan Ahmad Wahyudi Akbar, Trisakti Al Imran Al Imran Alfandy Pratama Alimuddin Sa’ban Miru Alwi, Muh Naufal Ramadhani Aminuddin Bakry Anak Agung Istri Sri Wiadnyani Andani, Andi Ferry Adlian Tri Andi Akram Nur Risal Andi Baso Kaswar Andi Baso Kaswar Andi Farmadi Andi Muh. Sahirul Haq Andi Wawan Indrawan Andi, Asirah Annisa Syah Shadira Ary Masharuddin Shiddiqi Asham Bin Jamaluddin Aswa, M. Andika Atthariq, Atthariq Ayu Lestari Ayu Safitri Azhar Azhar Briliant Noviansel Cyahrani Wulan Purnama Cyahrani Wulan Purnama Rasyid Dendy Mahabror Dewi Fatmarani Surianto Djawat, Yasser Abd Djuanda, Djuanda Dodon Turianto Nugrahadi Dyah Vitaloka Edi Suhardi Rahman Edy, Marwan Ramdhany Fachrul, Achmad Fadhlirrahman Baso FADIAH, NUR Fahmi, Moghfina Moghfina Fathahillah Fathahillah Fatimah Hidayahni Amin Febry Maryani Yatu Fhatiah Adiba Firdaus Firdaus Firdaus Firdaus, Muhammad Eka Fitra Yusuf Ganefri . Harifuddin Haripuddin Hartono Hartono Hasrul Bakri Hendarawaty, Hendarawaty Hendra Jaya Hentje Ponto I Nyoman Sila Ibnu Fikrie Syahputra Iin Mahgafhira Ikram Anas Ilham Juliady Irmawati Irmawati Irmawati Irmawati Irmawati Irvanshah Irvanshah Irwan Budiman Istiqamah, Nurfadilah Iwan Suhardi jamaluddin Jamaluddin Jamaluddin Jariah, Rezki Nurul Jufri, Muhammad Fadhil Juliady, Ilham Jumriah, Titin Jusniar . Karmila Kurnia Prima Putra Lia, Resky Amalia M. Ruhan Bachry M. Syahid Nur Wahid Manguling, Inez Sri Wahyuningsi Maratus Shalihah Marwan Ramdhany Edy Massikki, Massikki Moghina Fahmi Muh Azikin Sofyan Muh Irfan Nur Muh Mujahidin Muh Rais Muh. Alief Rezky Anisar Muh. Alwi Rizkyansyah Kasim Muh. Azfa Azra Muh. Irfan Nur Muh. Rifqi Fadhil Muh. Yusuf Mappeasse Muh.Fahmi Muhammad Agung Muhammad Agung Muhammad Agung Muhammad Agung Muhammad Alkaff Muhammad Fajar B Muhammad Fajri, syamsir Muhammad Fathur Rachman Muhammad Ilyas Syarif Muhammad Mahdinul Bahar Muhammad Mahdinul Bahar Muhammad Reza Faisal, Muhammad Reza Muhammad Syaiful Muhammad Yahya Muhammad. Yusuf Mappeasse Muharram Muharram Muhira Muhira Muliadi Muliadi Muliadi Musdania Musgamy, Muh Faqih S Nanda Aulia Ash Siddiq Niranti Jihan Sari Nununk Febryanti NUR FADILAH Nur Risal, Andi Akram Nurdin Nurhikma Nurul Istiqamah Qalbi Nurul Izzah Dwi Nurul Izzah Dwi Nurdinah Parenreng, Syarif Mabe Prima, Delta Ardy Puput Dani Prasetyo Adi Putra, Muh. Fardika Irwan Pratama Ramli Rasyid Rasyid, M. Udin Harun Al Rhesky Annisa Basri Riana T.Mangesa Ridwan Daud Mahande Risaldi, Muhammad Riska, Muhammad Rizal, Fahru Ros Sariningrum rosyidah, aliyyah Salsa Dillah Sanatang Saragih, Triando Hamonangan Seny Luhriyani Sunusi Setia Ningsih Shabrina Syntha Dewi Shiraj, Muhammad Reza Sugeng A. Karim Suhartono Suhartono Suhartono, Suhartono Suhendar Aji Putra Suhendhar Aji Putra Sul Fikran Supeno Djanali Supriadi, Dewi Sri Mulyana Suyanta Suyanta Syafriandi K, Fahri Syahrul Syahrul Syahrul Syamsinar Syarifuddin Kasim Tenri Nadya Wenny Tri Setyo Budi Udin Sidik Sidin Usman Mulbar Wahda Arfiana AR Wahid, M. Syahid Nur Wahyu Hidayat M Wahyu Hidayat M Wahyuni , Maya Sari Wahyuni, Maya Sari Welly Chandra Kusumah Kusnandar Winda Agustina Yasdin, Yasdin Yunus Tjandi Yusuf, Zulfatni Zulhajji, Zulhajji Zulkiplih Zulkiplih Zulkiplih Zulkiplih Zulkiplih