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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Buana Informatika Teknosains: Media Informasi Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer SIGMA: Jurnal Pendidikan Matematika AlphaMath: Journal of Mathematics Education JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JPM (Jurnal Pemberdayaan Masyarakat) Faktor Exacta Jurnal Penjaminan Mutu JITK (Jurnal Ilmu Pengetahuan dan Komputer) JTAM (Jurnal Teori dan Aplikasi Matematika) CARADDE: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURNAL MathEdu (Mathematic Education Journal) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) GERVASI: Jurnal Pengabdian kepada Masyarakat TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Sistem informasi dan informatika (SIMIKA) Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Unri Conference Series: Community Engagement Jurnal Dedikasi Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Online Learning in Educational Research Seminar Nasional Pengabdian Kepada Masyarakat Catimore: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Edutic : Pendidikan dan Informatika Internet of Things and Artificial Intelligence Journal Jurnal Penjaminan Mutu Indonesian Journal of Fundamental Sciences IPTEK: Jurnal Hasil Pengabdian kepada Masyarakat Teknovokasi : Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat Information Technology Education Journal Pengabdian Jurnal Abdimas Journal of Embedded Systems, Security and Intelligent Systems Ininnawa: Jurnal Pengabdian Masyarakat Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Jurnal Sipakatau Jurnal Ilmu Pengetahuan dan Teknologi Bagi Masyarakat Jurnal MediaTIK Mekongga: Jurnal Pengabdian Masyarakat Media Elektrik Malaqbiq : Jurnal Pengabdian kepada Masyarakat. Sasambo: Jurnal Abdimas (Journal of Community Service) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Andi Baso Kaswar Andi Baso Kaswar
Universitas Negeri Makassar
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Smart System for Stabilizing Water Flow Output on Android-Based Taps Parenreng, Jumadi M; Zain, Satria Gunawan; Yusuf, Zulfatni; Suhardi, Iwan; Kaswar, Andi Baso
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 4 (2023): Vol. 3 No. 4 (2023): Volume 3 Issue 4, 2023 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i4.668

Abstract

This study aims to produce and find out the results of the Smart System Stabilization Water Discharge Output Test on Android-Based Faucets based on the results of water flow sensor readings whose data is used as a reference for the rotation of the Adj or Adjustable Water Pressure Reducing Regulator Valve. The tests were carried out in the form of measuring water flow without and with Adj and measuring water discharge without and with Adj. Based on the research results, the water flow without Adj is 7 L/min for tap 1.9 L/min for tap 2. The water flow with Adj for both taps is 8 L/min. The flow of water from both taps is more stable with Adj than without Adj because the flow of both taps is 8 L/min. The measurement results of the water discharge without Adj are 0.1216 L/s for tap 1 and 0.1470 L/s for tap 2; the difference in water discharge is 0.0254 L/s. Water debit with Adj 0.135 L/s tap 1 and 0.14125 L/s tap 2, the difference in water discharge is 0.00625 L/s. The water debit is more stable with Adj than without Adj because the difference in water discharge is smaller.
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.
Identifying Rice Plant Damage Due to Pest Attacks Using Convolutional Neural Networks Tenriola, Andi; Azis, Putri Alysia; Kaswar, Andi Baso; Adiba, Fhatiah; Andayani, Dyah Darma
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6125

Abstract

Rice (Oryza Sativa) is an important crop for meeting global food needs; however, one of the main challenges in its cultivation is the attack of stem borer pests, which can cause significant damage. This study aims to identify the damage caused by these pest attacks using Convolutional Neural Networks (CNN) methods. We developed and trained several CNN architectures, including the proposed architecture, MobileNet, and EfficientNetB0, to detect pest attacks on rice. The dataset used consists of 700 images per class taken directly from the field, where the images depict rice plants that have been peeled or opened to inspect for the presence of pests, specifically stem borer pests. To enhance the quality and diversity of the dataset, we applied a rigorous selection process, ensuring that only high-quality images were used. Additionally, augmentation techniques such as rotation were employed to expand the dataset to 2000 images per class. Labeling was carried out carefully to ensure that each image accurately reflected the condition of the pest attack. The results of the study indicate that the proposed CNN model can identify damage with high accuracy, thereby contributing to efforts to increase rice production through early detection of pest attacks using computer vision technology.
Pelatihan Pembuatan Video Animasi dengan Aplikasi Animiz untuk Mendukung Pembelajaran Kreatif di Sekolah Dasar Nurjannah, Nurjannah; Kaswar, Andi Baso; Andayani, Dyah Darma; Dirawan, Gufran Darma; Risal, Andi Akram Nur
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 3: Issue 2 (May 2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v3i2.8327

Abstract

The training on creating animated videos using the Animiz application at SDN 2 Sinjai aimed to enhance teachers' competencies in developing creative and interactive digital learning media. This activity was conducted on December 16, 2024, through four stages: planning, implementation, observation, and evaluation, using a hands-on training approach combined with intensive mentoring. The results showed that teachers were able to understand the material well, operate the Animiz application independently, and produce animated videos relevant to primary school learning themes. The evaluation indicated that most participants responded very positively regarding the clarity of the material, the relevance of the training, and the ease of using the application. Despite some technical challenges and time constraints, the training was considered effective in improving teachers' motivation and skills in utilizing digital technology. This initiative serves as a strategic first step in promoting digital transformation in primary schools and should be followed up with advanced training and continuous mentoring.
Penerapan Data Science sebagai Upaya Meningkatkan Kompetensi Mahasiswa di Era Industri Modern Rivai, Andi Tenri Ola; Risal, Andi Akram Nur; Edy, Marwan Ramdhany; Adiba, Fhatiah; Kaswar, Andi Baso
TEKNOVOKASI : Jurnal Pengabdian Masyarakat Volume 3: Issue 2 (May 2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/teknovokasi.v3i2.8450

Abstract

Data Science adalah bidang multidisipliner yang menggabungkan statistik, analitik data, dan machine learning untuk mengolah data besar menjadi informasi yang bermakna berbasis Data. Program Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan pemahaman mahasiswa terhadap konsep dan penerapan Data Science melalui workshop berbasis praktik. Kegiatan dilaksanakan dalam bentuk workshop satu hari yang mencakup materi eksplorasi data, visualisasi, dan penerapan algoritma sederhana menggunakan Python dan Google Colab. Peserta yang terdiri dari mahasiswa program studi Teknologi Informasi Universitas Bosowa menunjukkan peningkatan pemahaman terkait Data Science dan keberhasilan dalam mengerjakan mini-proyek berbasis data. Keberhasilan kegiatan ini didukung oleh antusiasme peserta, fasilitas yang memadai, serta pendekatan pembelajaran yang aplikatif dan interaktif. Namun, terdapat beberapa hambatan seperti keterbatasan waktu, variasi tingkat kemampuan peserta, dan kendala koneksi internet saat pelatihan. Secara keseluruhan, pelatihan ini memberikan kontribusi nyata terhadap peningkatan literasi data dan keterampilan digital mahasiswa serta relevan untuk diterapkan secara berkelanjutan di institusi pendidikan tinggi.
Enhancing Computational Thinking Skills through Digital Literacy and Blended Learning: The Mediating Role of Learning Motivation Nirmala, Putri; Suhardi, Iwan; Kaswar, Andi Baso; Surianto, Dewi Fatmarani; B, Muhammad Fajar; Soeharto, Soeharto; Lavicza, Zsolt
Online Learning In Educational Research (OLER) Vol 5, No 1 (2025): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v5i1.504

Abstract

In the digital era, computational thinking becomes an essential skill to overcome technological challenges in 21st centuryeducation. This study investigates the impact of digital literacy and blended learning on computational thinking skills, focusing on the mediating role of learning motivation. A total of 413 university students from blended learning environments participated, using a structured questionnaire with validated scales for digital literacy, computational thinking, and learning motivation. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test direct and mediation relationships. The results showed that digital literacy and blended learning significantly influenced computational thinking, with learning motivation acting as a mediator that strengthened this relationship. Digital literacy showed a greater influence than blended learning. These findings highlight the importance of integrating digital literacy and motivational strategies into blended learning to optimize the development of computational thinking skills, as well as providing insights for learning design that is relevant to the needs of the 21st century.
EKSPLORASI HUBUNGAN ANTARA LITERASI MATEMATIKA DAN KEMAMPUAN PROBLEM SOLVING PADA SISWA DI ERA DIGITAL Nurjannah, Nurjannah; Kaswar, Andi Baso
SIGMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 17 No. 1: Juni 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/sigma.v17i1.17060

Abstract

Di era digital, literasi matematika dan kemampuan pemecahan masalah menjadi keterampilan penting bagi siswa untuk beradaptasi dalam masyarakat berbasis teknologi. Literasi matematika melibatkan pemahaman konsep dan penerapannya dalam situasi nyata, termasuk pemecahan masalah. Penelitian ini menggunakan metode kuantitatif dengan pendekatan korelasional untuk mengeksplorasi hubungan antara literasi matematika dan kemampuan pemecahan masalah pada siswa di era digital. Sampel terdiri dari 35 siswa kelas XI di SMA Negeri 5 Sinjai yang dipilih dengan teknik cluster sampling, dengan pengumpulan data melalui tes literasi matematika yang diadaptasi dari PISA dan tes pemecahan masalah yang dirancang khusus untuk konteks digital. Uji normalitas dan linearitas memastikan data memenuhi syarat untuk dilanjutkan ke analisis korelasi. Hasil analisis menunjukkan adanya korelasi yang sangat tinggi antara literasi matematika dan kemampuan pemecahan masalah dengan koefisien korelasi Pearson sebesar 0,997 yang mengindikasikan bahwa hampir seluruh variansi kemampuan pemecahan masalah dapat dijelaskan oleh literasi matematika. Temuan ini menegaskan bahwa literasi matematika tidak hanya penting untuk prestasi akademik, tetapi juga mendukung keterampilan kognitif tingkat tinggi yang diperlukan dalam konteks digital. Implikasi dari penelitian ini adalah bahwa pendidikan literasi matematika harus diperkuat dalam kurikulum sekolah dengan pendekatan berbasis proyek dan aplikasi digital, guna mempersiapkan siswa menghadapi tantangan kompleks di masa depan yang semakin berbasis teknologi.
Identifikasi Kualitas Fisik Shuttlecocks Menggunakan Teknologi Pengolahan Citra Digital dengan Jaringan Syaraf Tiruan Farid, Muhammad Miftah; Sam, Muh Hadal Ali; Kaswar, Andi Baso; Andayani, Dyah Darma
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 11, No 2 (2025): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v11n2.167-180

Abstract

Shuttlecock merupakan bola yang dipakai dalam permainan bulutangkis, terbuat dari bulu angsa dan bulu ayam berwarna putih. Bola ini memiliki panjang sekitar 64-66 mm, diameter 25 mm, dan berat berkisar antara 4,74 hingga 5,67 gram. Sebelum digunakan pada pertandingan, shuttlecock dipilih berdasarkan kualitas pada bulu dan kepala shuttlecock. Namun, proses pemilihan tersebut masih dilakukan secara manual oleh penyelenggara pertandingan bulutangkis. Jumlah shuttlecock yang banyak memerlukan tenaga kerja yang besar, sehingga seringkali muncul kesalahan manusia akibat kelelahan dan tekanan waktu yang tinggi. Untuk itu, pemanfaatan teknologi menggunakan citra digital dirasa sangat perlu digunakan untuk mengidentifikasi kualitas fisik pada shuttlecock. Oleh karena itu, dalam penelitian ini diusulkan sistem identifikasi kualitas fisik pada shuttlecock menggunakan teknologi pengolahan citra digital dengan metode jaringan syaraf tiruan. Penelitian ini melalui beberapa tahap diantaranya tahap akuisisi citra, preprocessing, segmentasi, morfologi, ekstraksi fitur serta klasifikasi. Penelitian ini juga, mencoba beberapa skenario pelatihan dan pengujian untuk menemukan kombinasi fitur terbaik. Kombinasi warna RGB (channel blue), tekstur (fitur energy), dan bentuk (fitur area dan perimeter) memberikan hasil optimal dalam klasifikasi citra shuttlecock. Hasil penelitian menunjukkan bahwa dengan melatih sistem menggunakan 140 citra latih, diperoleh akurasi tertinggi sebesar 100% dengan waktu komputasi 0,136 detik per citra. Selanjutnya, hasil pengujian pada 60 citra uji mencapai tingkat akurasi sebesar 100% dengan waktu komputasi 0,123 detik per citra. Hasil tersebut menunjukkan bahwa metode yang diusulkan dapat mengidentifikasi kualitas shuttlecock dengan akurat dan waktu komputasi yang cepat. Shuttlecock is a ball used in badminton made of goose feathers and white chicken feathers, has a length of 64-66 mm and has a diameter of 25 mm with a weight of 4,74 – 5,67 grams. Before being used in a match, the shuttlecock is selected based on the quality of the feathers and shuttlecock head. However, the selection process is still done manually by the badminton match organizer. The large number of shuttlecocks requires a large amount of labor, so it is not uncommon for human error to occur due to fatigue and high time pressure. For this reason, the utilization of technology using digital images is deemed very necessary to be used to identify the physical quality of the shuttlecock. Therefore, this research aims to develop a physical quality identification system on shuttlecocks using digital image processing technology with artificial neural network method. This research goes through several stages including image acquisition, preprocessing, segmentation, morphology, feature extraction and classification. This research also tries several training and testing scenarios to find the best combination of features. The combination of RGB color (channel blue), texture (energy feature), and shape (area and perimeter features) provides optimal results in shuttlecock image classification. The results showed that by training the system using 140 training images, the highest accuracy of 100% was obtained with a time of 100%.
Deteksi Tingkat Kematangan Buah Mangga Berdasarkan Fitur Warna Menggunakan Pengolahan Citra Digital Aksa, Muhammad; Ranggareksa, Andi; Aras, Muh Riski Farukhi; Kaswar, Andi Baso; Andayani, Dyah Darma; Intam, Reski Nurul Jariah S
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 2 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i2.10578

Abstract

The classification of mango Golek ripeness is crucial for ensuring product quality and its economic value, especially in industrial applications. Manual and subjective ripeness determination often leads to inconsistency, resulting in decreased harvest quality and market value. This study aims to classify the ripeness of Golek mangoes into three categories: unripe, semi-ripe, and ripe, using digital image processing based on HSV and LAB color features combined with the K-Nearest Neighbor (KNN) algorithm. The dataset consists of 300 images, split into 80% training data and 20% testing data. The proposed method includes image acquisition, preprocessing, segmentation, morphological operations, feature extraction, and classification. The results show that the combination of HSV and LAB color features is effective in distinguishing ripeness levels, with an accuracy of 81.67% on the testing data and an average precision, recall, and F1-Score of 82%. Consistent color patterns in the unripe and semi-ripe categories enhance accuracy, while fluctuations in color intensity in the ripe category pose challenges. This approach shows potential for implementation in automatic sorting systems in industry.
Co-Authors A. Farha Adella A. Muhammad Idkhan A. Mutahharah A. Mutahharah Mutahharah A.Farha Adella Abd. Rahman Patta Abdul Muis Mappalotteng Abdul Wahid Adiba, Fhatiah Afdhaliyah, Mukhlishah Afyan, Nurbaitul Aglaia, Alifya Nuraisyar Agung, Andi Sadri Agus Zainal Arifin Agus Zainal Arifin Agustinus Suria Darme Ahmad Adzan Lain Ahmad Fudhail  Majid Ahmad Khan, Sardar Faroq Ahmad Mustofa Hadi Ahmad Mustofa Hadi Ainun Zahra Adistia Akbar, Trisakti Aksa, Muhammad Al Imran Alfian Firlansyah Ananta Dwi Prayoga Alwy Andi Ahmad Taufiq Andi Akram Nur Risal Andi Alamsyah Rivai Andi Nurul Izzah Andi Rosman N Andi Tenriola Anggy Heriyanti Anggy Heriyanti Anny Yuniarti Aqsha, Ismail Aras, Muh Riski Farukhi Arifky, Reza Arinanda Alviansyah Arliandy, Arliandy Arsyad, Meisaraswaty Arya Yudhi Wijaya Arya Yudhi Wijaya Aryadi Nurfalaq Ashadi, Ninik Rahayu Asnidar Asnidar Asrofi, Muhammad Ghufran Astuti, Ninik Aswar Aswar Atthariq, Muhammad Aulia, Magfirah Awalia, Nur Ayu Futri Azis, Putri Alysia Azis, Salsabila Bantun, Suharsono Bugdady, Andi Jaedil Bukhari Naufal Nur A.G Burhan, Rafli Ananta Chairati, Chairati Cyahrani Wulan Purnama Cyahrani Wulan Purnama Rasyid Darma Andayani, Dyah Darme, Agustinus Suria Della Fadhilatunisa Dewi Fatmarani Surianto Dhanendra, Fadhil Dina Salam, Fitria Nur Dini, Juliano Nufiansyach Dirawan, Gufran Darma Edy, Marwan Ramdhany Elva Amalia Elva Amalia Eman Wahyudi Kasim Eriyani, Nindy Sri Fachriansyah, Zaky Farid, Muhammad Miftah Farros Taufiqurrahman Fathahillah Fathahillah Fauzi, A. Arfan Fazli Arif Fhatiah Adiba Fhatiah Adiba Fhatiah Adiba Hafidz Muhtar Hanum Zalsabilah Idham Hartanto Tantriawan Heriyanti, Anggy Herman Hermansyah Hermansyah Hersyam, Muh Syachrul Hidayat, Muh. Taufik Ibnu Fikrie Syahputra Idkhan, A. Muhammad Idkhan, Andi Muhammad Idris, Muh Gimnastiar Ihlasul Amal Ikra Ain Fahwa Ikra Ain Fahwa Ilham, Muh Ilham, Muhammad Ryan Indri Pratiwi Ramadhani Intam, Reski Nurul Jariah S Irwansyah Suwahyu Ishak Israwati Hamsar Iwan Suhardi Jamaluddin, Bunga Mawar Jamila Jamila Jamila Jariah S.Intam, Rezki Nurul Jasruddin Daud Malago Jayanti Yusmah Sari Jumadi Mabe Parenreng Jusrawati Jusrawati Jusrawati Kaparang, Adam Indra Kaswar, A Baso Kurnia Prima Putra Kurnia Wahyu Prima Labusab Labusab Labusab Labusab, Labusab Lapendy, Jessica Crisfin Lavicza, Zsolt M. Miftach Fakhri Makmur, Haerunnisya Marwan Eka Ramdhany Marwan Ramdhany Edy Massie, Gary Jeremi Maulana Muhammad Mawaddah, Arini Ulfa Muammar Muammar Muh Aldhy Fatahillah Muh Devan Fahresi Muh Fuad Zahran Firman Muh Omar Hassan ST Muh. Dirgafa Anugra Rais Muh. Dirgafa Anugrah Rais Muh. Fardika Pratama Putra Muh. Fauzan Arifuddin Muh. Rais Muh. Rasul D Muhammad Agung Muhammad Agung Muhammad Akbar Muhammad Akil, Muhammad Muhammad Fajar B Muhammad Naim Muhammad Nur Yusri Maulidin Yusuf Muhammad Nur Yusri Maulidin Yusuf Muhammad Yahya Muhiddin Palennari Muhira Muhira Muhtar, Hafidz Mukhtar Mukhtar Mulia, Musda Rida Muliaty Yantahin Musdar, Devi Miftahul Jannah Mustari Lamada Mutahharah, A Naim, Muhammad Nasrullah, Asmaul Husnah NFH, Alifya NIRMALA, PUTRI Nirsal Novianti, Andi Fitri Nur Anny S. Taufieq Nur Fadillah Bustamin Nur Inayah Yusuf Nurfalaq, Aryadi Nurfitri, Andi Aisyah Nurhidayat Nurhidayat Nurhikma Nurhikma Nurhikma Nurjannah Nurjannah Nurjannah Nurjannah Nurjannah Nurjannah Nurjannah Nurjannah Nurul Amanda Pratiwi Hasbullah Nurul Isra Humaira B Nurul Istiqamah Qalbi Nurul Izzah Dwi Nurul Izzah Dwi Nurdinah Patongai, Dian Dwi Putri Ulan Sari Perdana, Am Akbar Mabrur Pratama, Azir Zuldani R, Muh Raflyawan R, Ranir Aftar Ranggareksa, Andi Ranir Atfar R Rapa, Wiwi Resky, Andi Aulia Cahyana Riana T. Mangesa Riana T. Mangesa Ridwan Daud Mahande Ridwansyah Rivai, Andi Tenri Ola Rosidah RR. Ella Evrita Hestiandari Rusli, Risvan S, Mushawwir Sahribulan Sahribulan Saiful Bahri Musa Sakira, Tiara Putri Sam, Muh Hadal Ali Sanatang Saparuddin Saparuddin Saparuddin Saparuddin Saprina Mamase Sartika Sari Sartika Sari Sasmita Sasmita Sasmita SATRIYAS ILYAS Silvia Andriani Soeharto Soeharto SR, Amin Farid Dirgantara Sri Rahayu St. Fatmah Hiola Suharsono Bantun Suhartono, Suhartono Supria Supria Surianto, Dewi Fatmawati Susiana Sari Syamsuddin Syasikirani. N, Adelia Tenriajeng, Andi Afrah Tenriola, Andi Tri Afirianto, Tri Tsabita Syalza Billa Tsabita Syalza Billa Irawan Umar, Nur Fadhilah Wahda Arfiana AR WAHYUDI Wanda Hamidah Wardani, Ayu Tri Wiwi Rapa WULANDARI Yasser Abd Djawad Yuliarni, Tarisa Yusuf, Zulfatni Zulfikar, Muh. Ihsan