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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) JMM (Jurnal Masyarakat Mandiri) JTAM (Jurnal Teori dan Aplikasi Matematika) International Journal of Pedagogy and Teacher Education CARADDE: Jurnal Pengabdian Kepada Masyarakat JURNAL PENDIDIKAN TAMBUSAI 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 International Journal of Electronics and Communications Systems 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 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) Journal of Emerging Research in Computer Science and Artificial Intelligence
Andi Baso Kaswar Andi Baso Kaswar
Universitas Negeri Makassar
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KEEFEKTIFAN COMPUTATIONAL THINKING DALAM MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIKA SISWA Kaswar, Andi Baso; Nurjannah, Nurjannah
SIGMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 16 No. 1: Juni 2024
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/sigma.v16i1.14574

Abstract

Computational Thinking merupakan kemampuan dasar berpikir untuk siswa serta guru dimana kemampuan tersebut dapat memberikan pola pikir yang baru untuk memperoleh pemecahan masalah serta untuk mengembangkan peluang. Tujuan dari penelitian ini adalah untuk mengetahui efektifitas computational thinking terhadap kemampuan pemecahan masalah siswa. Penelitian ini merupakan penelitian kuantitatif dengan pretest postest control grup desain. Instrumen dalam penelitian ini adalah tes kemampuan pemecahan masalah yang diperoleh berdasarkan soal-soal computational thinking yang dikembangkan oleh Bebras. Teknik analisis data dilakukan dengan uji paired sample t test. Berdasarkan hasil analisis data dengan paired sample t-test diperoleh nilai probabilitas 0,000. Karena nilai probabilitas lebih kecil dibanding  maka dapat dikatakan bahwa computational thinking efektif digunakan untuk meningkatkan kemampuan pemecahan masalah matematika siswa. Dengan demikian, kemampuan computational thinking tidak hanya meningkatkan kemampuan pemecahan masalah siswa, tetapi juga mempersiapkan mereka untuk menghadapi tantangan dalam berbagai bidang studi dan situasi kehidupan nyata yang memerlukan pemikiran kritis, kreatif, dan terstruktur.
CLASSIFICATION OF TOMATO QUALITY BASED ON COLOR FEATURES AND SKIN CHARACTERISTICS USING IMAGE PROCESSING BASED ARTIFICIAL NEURAL NETWORK Agung, Andi Sadri; SR, Amin Farid Dirgantara; Hersyam, Muh Syachrul; Kaswar, Andi Baso; Andayani, Dyah Darma
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.730

Abstract

Tomato (Solanum Lycopersicum) is a plantation commodity in Indonesia with a production rate that tends to increase every year. With a high economic value, maintenance is important so that the quality is getting better. The problems that arise at this time are related to the determination of the quality of tomatoes which is still done manually and depends on humans so classification using technology is considered important to be developed. Previously there has been researching related to the classification of tomatoes. However, accuracy and computation time still need to be improved. Therefore, in this research, a method of classification of tomatoes was carried out using Artificial Neural Network (ANN) Backpropagation algorithm by utilizing color features and skin characteristics based on image processing. This research followed several stages, from acquiring 300 tomato images with 3 class levels to the classification process using ANN Backpropagation. Several training scenarios and tests were conducted to select the feature combined with the highest accuracy and fastest computation time. The combination of 3 best features used is RGB color feature with shape and texture features as skin characteristic parameters. Based on training results with 210 training images, an accuracy of 100% was obtained with a computation time of 2.58 seconds per image. While test results with 90 test images, accuracy reaches 95.5% with a computing time of 1.39 seconds per image. So it can be concluded that the method used has gone well in classifying tomato image quality based on color features and skin characteristics.
MATURITY CLASSIFICATION SYSTEM OF TOMATO BASED ON RGB COLOR FEATURES USING BACKPROPAGATION ARTIFICIAL NEURAL NETWORK METHOD Massie, Gary Jeremi; Pratama, Azir Zuldani; Sakira, Tiara Putri; Kaswar, Andi Baso; Andayani, Dyah Darma
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.732

Abstract

Determining the ripeness level of tomatoes, for now, is still done manually (conventional), and in general, determining the ripeness of tomatoes using the manual method often gets inconsistent results due to differences in everyone's perception so in determining ripe or not ripe tomatoes to be not very accurate. There have been various previous studies that have been conducted, especially in terms of classifying maturity levels, but from these studies, the level of accuracy achieved is relatively low. Therefore, the researcher proposes research on Tomato Fruit Maturity Classification System Based on RGB Color Features Using the Backpropagation Neural Network Method. This research consists of the image acquisition stage, the preprocessing stage, the image segmentation stage including performing morphological operations, the RGB feature extraction stage, and the last stage is conducting Image Classification using Backpropagation Neural Networks. From the results of the training phase, the resulting computational time is 87,735 seconds with an overall accuracy rate of 99.04%. And based on the results of the testing phase, the architecture of the backpropagation neural network that has been built can accurately classify the ripeness level of tomatoes, from a total of 90 test images, with an accuracy of 98.88% obtained and a more efficient computational time of 30.390 seconds. This can help farmers in harvesting tomatoes.
CLASSIFICATION OF THE LEVEL OF SUGAR CONTENT IN PAPAYA FRUIT BASED ON COLOR FEATURES USING ARTIFICIAL NEURAL NETWORK Nurfitri, Andi Aisyah; Kaparang, Adam Indra; Hidayat, Muh. Taufik; Kaswar, Andi Baso; Andayani, Dyah Darma
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.733

Abstract

Papaya (Carica papaya L) is consumed by many people because it is beneficial for health. Along with increasing consumption or enthusiasts of papaya, the quality of papaya needs to be considered. One of the determining factors of the quality of papaya is its physical characteristics, which can be seen from its color, shape, and texture. Papaya of good quality has a delicious and sweet taste. The sweet taste of papaya is certainly influenced by the sugar content contained in it. However, to determine the sugar content in papaya is only done by human assessment based on its physical characteristics, this assessment is often less accurate. With a system that can determine the sugar content in papaya, it will make it easier for farmers to sort papaya fruit. Therefore, in this study, it is proposed to classify the level of sugar content in papaya based on color features using an Artificial Neural Network. The proposed method consists of 5 stages, namely, image acquisition, preprocessing, segmentation with the Otsu method, morphological operations, and classification with artificial neural networks. The number of papaya datasets used is 300 images which are divided into 3 classes, low class, medium class, and tal class. Based on the results of the tests that have been carried out, an accuracy of 92.85% is obtained for the training data, and for the test data, an accuracy of 100% is obtained. These results indicate that the proposed method can classify the level of sugar content in papaya fruit accurately.
CLASSIFICATION OF RICE QUALITY LEVELS BASED ON COLOR AND SHAPE FEATURES USING ARTIFICIAL NEURAL NETWORK BASED ON DIGITAL IMAGE PROCESSING Asnidar, Asnidar; Perdana, Am Akbar Mabrur; Ilham, Muhammad Ryan; Kaswar, Andi Baso; Andayani, Dyah Darma
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 6 (2023): JUTIF Volume 4, Number 6, Desember 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.6.734

Abstract

Rice is the staple food of most Indonesians. In identifying the quality of rice, it can be seen from physical characteristics such as the color and shape of rice, because these characteristics can make an object can be identified properly and clearly. In general, what is done in determining the quality of rice by looking at its color and shape. But usually the human eye in identifying objects is sometimes less accurate which is influenced by several factors, such as age. So, several studies were conducted that tried to solve the problem by using digital image processing. However, the accuracy results obtained are still not accurate, because the datasets used in the previous study were relatively small, namely around 80 images, although the average level of accuracy obtained was quite high, but the number of datasets used was very small so that the level of accuracy was still inaccurate. Therefore, in this study, it is proposed that the title of classification of rice quality levels using JST based on digital image processing which divides rice into 3 classifications, namely, good, good enough, and not good where in this study using 330 digital images to produce a more accurate level of accuracy. In this study, there are several stages, namely, image retrieval, preprocessing, segmentation, morphological, feature extraction, and classification using artificial neural networks. Based on the research conducted, training accuracy was produced with an average accuracy of 98,75% while the test accuracy was produced with an average accuracy of 98,89%.
Carrot Quality Classification Based on Color and Texture Features Using Artificial Neural Network Method Idris, Muh Gimnastiar; Fauzi, A. Arfan; Syasikirani. N, Adelia; Kaswar, Andi Baso
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.1401

Abstract

Carrots are popular vegetable plants that are usually consumed by the public. Determination of quality using the visual of human eye is considered to have many shortcomings. In previous studies, the carrot classification process had been carried out using a certain method. However, the level of accuracy resulting from several previous studies is still lacking because the processes and methods used are considered to be inaccurate, so innovation is needed by using processes and methods that are more precise to obtain classification results with a better level of accuracy. Therefore, this research proposes a classification of carrot quality based on color and texture features using an artificial neural network method. The proposed method consists of 6 stages, namely image acquisition, preprocessing, segmentation, morphological operations, feature extraction, and classification using artificial neural networks. In this study, quality is divided into three classes, namely feasible, less feasible, and not feasible using 300 carrot image datasets. The results obtained in the testing process obtained an accuracy of 100%, a misclassification error of 0%, and a computation time of up to 55 seconds. Based on the test results it can be seen that the proposed method can classify the quality of carrots accurately.
CLASSIFICATION OF SUGAR LEVELS IN BANANA FRUIT BASED ON COLOR FEATURES USING DIGITAL IMAGE PROCESSING-BASED ARTIFICIAL NEURAL NETWORKS S, Mushawwir; Burhan, Rafli Ananta; Yuliarni, Tarisa; Kaswar, Andi Baso; Andayani, Dyah Darma
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1420

Abstract

Bananas are a fruit that has many benefits for human health, because bananas contain a source of vitamins, minerals and carbohydrates. Bananas are a fruit that is often consumed by Indonesian people because of their sweet taste. With this sweet taste, of course bananas have quite high sugar levels, so diabetes sufferers must pay attention to this when choosing bananas. The level of sugar content in bananas can be distinguished by looking at the ripeness of the fruit. To differentiate between them, of course, we use human vision, but human observation also has weaknesses and errors can occur in the process, whether due to lack of lighting, visual impairment, or age. Therefore, this study proposes a classification of the level of sugar content in bananas in the RGB color space using artificial neural networks (ANN). The proposed method consists of 6 stages, namely image acquisition, preprocessing, segmentation, morphological operations, RGB feature extraction, and classification stage. In this study, 300 samples of banana fruit images were used. 210 datasets will be used for training and 90 datasets for testing. The dataset is divided into 3 classes, namely low sugar content, medium sugar content, and high sugar content. Based on the test results that have been carried out, the accuracy of the classification results is 97.78%, the misclassification is 2.22%, and the computing time is 375 seconds. These results show that the proposed method can accurately classify the level of sugar content in bananas.
Pendampingan Manajemen Preventif, Kuratif, dan Pengaduan Kasus Bullying Melalui Aplikasi Konseling U-Shield Bagi Kelompok Guru MGBK SMA/SMK Umar, Nur Fadhilah; Kaswar, Andi Baso; Aswar, Aswar; Majid, Ahmad Fudhail; Arliandy, Arliandy
CARADDE: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2024): Desember
Publisher : Ilin Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31960/caradde.v7i2.2573

Abstract

Tujuan pelaksanaan Pemberdayaan Kemitraan Masyarakat ini adalah untuk memberdayakan mitra dalam menyelesaikan masalah yang dialami terkait dengan kurangnya pengetahuan dan keterampilan mitra dalam menangani masalah bullying dan tidak adanya teknologi atau alat yang digunakan oleh mitra dalam menangani kasus bullying. Metode yang digunakan dalam Pemberdayaan Kemitraan Masyarakat (PKM) ini adalah metode partisipatori. Kegiatan pendampingan ini dilaksanakan di SMA Negeri 1 Pangkajene Kepulauan (Pangkep), Sulawesi Selatan pada Juli-Agustus 2024. Peserta berjumlah 50 Guru Bimbingan Konseling (berasal dari SMA dan SMK). Tahap pendampingan dimulai dari mengidentifikasi, mempersiapkan, merencanakan, melaksanakan Pelatihan, dan melakukan evaluasi pelatihan. Hasil pendampingan yang telah dilakukan bersama mitra yakni pada 50 guru mengindikasikan adanya peningkatan sebelum guru didampingi hingga evaluasi pendampingan berlangsung. Dibuktikan dari pemahaman guru tentang bullying yang terjadi, keterampilan yang sesuai dalam kasus bullying, serta kemampuan dalam mengakses teknologi berupa aplikasi U-Shield secara tepat dalam membantu mereka mencegah, melaporkan dan mengatasi bullying. Kegiatan PKM ini memperoleh respon yang sangat baik oleh peserta yang mengikuti kegiatan pendampingan. Rekomendasi pendampingan kepada pihak pengabdi adalah dengan melakukan jaringan kerja sama yang kuat antara stakeholder terkait dan terus berkomunikasi dengan mitra jika terdapat pendampingan secara berkala bilamana diperlukan oleh mitra
Public Speaking Clinic for Tour Guides: A Community Service Program in Matano Iniaku Tourism Village in Collaboration with PT. Dialogika Pesona Indonesia Asrofi, Muhammad Ghufran; Nirsal, Nirsal; Nurfalaq, Aryadi; Naim, Muhammad; Kaswar, Andi Baso; Idkhan, Andi Muhammad
MEKONGGA: Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2025): November 2025
Publisher : Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mekongga.v2i2.252

Abstract

The main problem faced by the partner, namely the Matano Iniaku tourism management group in Matano Tourism Village, is the low communication ability and public speaking skills of tour guides in delivering information about tourist destinations in an engaging and persuasive manner. To address this issue, a Public Speaking Clinic was conducted to improve participants’ speaking abilities, build self-confidence, and enhance their storytelling techniques. The program was implemented using an experiential learning approach through interactive training, hands-on practice, presentation simulations, and mentoring by professional trainers from PT. Dialogika Pesona Indonesia. The two-day activity was attended by 19 participants consisting of tour guides and destination managers. The evaluation results showed a 93% increase in communication skills, particularly in articulation, intonation, message structure, and nonverbal expression. This program has provided a tangible solution for partners in improving tourism service quality and can serve as a model for communication competency development in the local tourism sector.
Pemanfaatan Aplikasi berbasis Artificial Intelligence untuk Pengembangan Bahan Ajar Guru di SMP Negeri 2 Kahu Kaswar, Andi Baso; Adiba, Fhatiah; Andayani, Dyah Darma; Nurjannah, Nurjannah; Risal, Andi Akram Nur
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 2 Issue No. 1: July 2024
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v2i1.20243

Abstract

Media pembelajaran memainkan peran penting dalam meningkatkan pengalaman belajar peserta didik di sekolah. Salah satu unsur terpenting  yang menentukan kualitas dalam desain media pembelajaran adalah bahan ajar.  diperoleh. Faktanya, proses penyusunan bahan ajar yang efektif dengan cara konvensional membutuhkan perencanaan yang matang, waktu yang lama, pemahaman yang mendalam tentang kurikulum, serta kemampuan untuk menyajikan materi dengan pendekatan yang inovatif.  Namun, upaya-upaya peningkatan kompetensi guru dalam pengembangan bahan ajar berdasarkan kegiatan yang telah banyak dilakukan sebelumnya hanya berfokus pada pengembangan bahan ajar dalam konteks pemanfaatan media digital dan konteks materi bahan ajar. Dengan banyaknya kesibukan administrasi dan pengajaran di kelas, guru semakin kesulitan untuk mengembangkan bahan ajar dengan efektif dan efisien jika menggunakan cara-cara konvensional. Permasalahan ini juga terjadi pada sebagian Guru SMP Negeri 2 Kahu Kabupaten Bone Sulawesi Selatan yang merupakan mitra dalam kegiatan pengabdian kepada masyarakat ini. Oleh karena itu pada kegiatan program kemitraan masyarakat ini dilaksanakan pelatihan pemanfaatan aplikasi berbasis Artificial Intelligence (AI) untuk pengembangan bahan ajar guru. Kegiatan ini terbagi ke dalam 3 tahapan yaitu tahap persiapan, pelaksanaan kegiatan dan tahap evaluasi. Dimana materi inti yang disampaikan adalah berkaitan dengan teknik penggunaan prompt Google Gemini dalam mendukung dan membantu guru untuk penyusunan dan pengembangan bahan ajar.  Hasil pelatihan menunjukkan bahwa terjadi peningkatan yang signifikan pada para peserta terkait pengetahuan dan kompetensi peserta dalam pengembangan bahan ajar dengan memanfaatkan aplikasi berbasis AI.
Co-Authors A Mutahharah 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 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 Aisyah Ramadani Akbar, Trisakti Aksa, Muhammad Alfian Firlansyah Ananta Dwi Prayoga Alwy Andi Ahmad Taufiq Andi Akram Nur Risal Andi Alamsyah Rivai Andi Fitri Novianti Andi Nurul Izzah Andi Rosman N Andi Tenri Ola Rivai Andi Tenriola Anggy Heriyanti Anggy Heriyanti Annajmi Rauf Anny Yuniarti Aprilianti Nirmala S Aqsha, Ismail Aras, Muh Riski Farukhi Arifky, Reza Arinanda Alviansyah Arliandy, Arliandy Arya Yudhi Wijaya Arya Yudhi Wijaya Aryadi Nurfalaq Ashadi, Ninik Rahayu Asmi Ulfiah Asnidar Asnidar Asrofi, Muhammad Ghufran Aswar Aswar 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 Desitha Cahya Dewi Fatmarani Surianto Dhanendra, Fadhil Dina Salam, Fitria Nur 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 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 Ilham, Muh Ilham, Muhammad Ryan Ilyas, Muh. Imran, Al 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 Jessica Crisfin Lapendy Juliano Nufiansyach Dini 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 M. Miftach Fakhri Makmur, Haerunnisya Mappaita, Al Haytsam Marhayati Marwan Eka Ramdhany Marwan Ramdhany Edy Massie, Gary Jeremi Maulana Muhammad Maulana Muhammad Mawaddah, Arini Ulfa Meisaraswaty Arsyad Muammar Muammar Muh Aldhy Fatahillah Muh Devan Fahresi Muh Fuad Zahran Firman Muh Ilham Suherman Muh Omar Hassan ST Muh. Dirgafa Anugra Rais Muh. Dirgafa Anugrah Rais Muh. Fardika Pratama Putra Muh. Fauzan Arifuddin Muh. Ihsan Zulfikar Muh. Rais Muh. Rasul D Muhammad Agung Muhammad Agung Muhammad Akbar Muhammad Akbar Muhammad Akil, Muhammad Muhammad Atthariq Muhammad Fajar B Muhammad Naim Muhammad Nur Yusri Maulidin Yusuf Muhammad Nur Yusri Maulidin Yusuf Muhammad Rais Muhammad Yahya Muhiddin Palennari Muhira Muhira Muhtar, Hafidz Mukhtar Mukhtar Mulia, Musda Rida Muliaty Yantahin Musdar, Devi Miftahul Jannah Mustari Lamada Naim, Muhammad Nasrullah, Asmaul Husnah NFH, Alifya Ninik Astuti Nirsal Nur Anny S. Taufieq Nur Fadillah Bustamin Nur Inayah Yusuf Nurbaitul Afyan Nurfalaq, Aryadi Nurfitri, Andi Aisyah Nurhidayat Nurhidayat Nurhikma Nurhikma Nurhikma 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 Nurwijayanti Patongai, Dian Dwi Putri Ulan Sari Perdana, Am Akbar Mabrur Pramudya Asoka Syukur Pratama, Azir Zuldani Putri Nirmala Putri Ramdani R, Muh Raflyawan R, Ranir Aftar Radha Hasda Halfis Ranggareksa, Andi Ranir Atfar R Rapa, Wiwi Resky, Andi Aulia Cahyana Riana T. Mangesa Ridwan Daud Mahande Ridwansyah Ridwansyah Riswansyah , Muh Fikra Junian Riyama Ambarwati Rosidah Rosidah Rosidah Rusli, Risvan S, Mushawwir Sahribulan Sahribulan Saiful Bahri Musa Sakira, Tiara Putri Sam, Muh Hadal Ali Sanatang Saparuddin Saparuddin Saprina Mamase Saputra, Nikola 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 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 Zsolt Lavicza