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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) 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 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 Journal of Health and Nutrition Research 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) Artificial Intelligence in Lifelong and Life-Course Education Journal of Emerging Research in Computer Science and Artificial Intelligence
Andi Baso Kaswar Andi Baso Kaswar
Universitas Negeri Makassar
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CLASSIFICATION OF PAPAYA NUTRITION BASED ON MATURITY WITH DIGITAL IMAGE AND ARTIFICIAL NEURAL NETWORK Andi Ahmad Taufiq; Hanum Zalsabilah Idham; Muh Fuad Zahran Firman; Andi Baso Kaswar; Dyah Darma Andayani; Muhammad Fajar B; Abdul Muis Mappalotteng; Andi Tenriola
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7070

Abstract

Papaya is a tropical fruit with high nutritional content and significant health benefits. Nutritional components such as sugars, vitamin C, and fibre are strongly influenced by ripeness level. Identifying these nutrients usually requires laboratory tests that are time-consuming and rely on sophisticated equipment. Previous studies have focused on classifying ripeness levels, yet none have specifically addressed the classification of nutritional content. This study proposes a classification system for papaya nutrition based on ripeness using digital image processing and artificial neural networks (ANN). The method consists of six stages: image acquisition, preprocessing, segmentation, morphology, feature extraction, and classification with a trained ANN model. Experiments were conducted to evaluate feature combinations, including colour and texture features. The combination of LAB colour features and texture features-contrast, correlation, energy, and homogeneity-produced the best results. Testing on 75 images achieved an average precision of 97.22%, recall of 96.67%, F1-Score of 96.80%, and accuracy of 97.33%, with an average computation time of 0.02 seconds per image. These findings indicate that the proposed method provides fast and highly accurate classification of papaya’s nutritional content, offering a practical alternative to laboratory testing. Nevertheless, the study is limited by the relatively small dataset and controlled acquisition environment. Future research should extend the dataset, incorporate deep learning approaches, and validate performance under real-world conditions to enhance robustness and generalization
Lightweight Image-Based Mold Detection System for Real-Time Bread Quality Monitoring Using Artificial Neural Networks (ANN) Saputra, Nikola; Ilyas, Muh.; Riswansyah , Muh Fikra Junian; Kaswar, Andi Baso; Lamada, Mustari S.
International Journal of Electronics and Communications Systems Vol. 5 No. 2 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v5i2.28706

Abstract

Mold contamination of white bread is an ongoing challenge for quality monitoring, while conventional visual inspection remains unreliable for early and consistent detection. This study aims to propose a lightweight image-based mold detection system for white bread oriented towards real-time quality monitoring using Artificial Neural Networks (ANNs). An experimental workflow combining digital image acquisition, pre-processing, Otsu-based segmentation, morphological refinement, multicolor color space feature extraction, and an Artificial Neural Network (ANN) classifier is implemented. Results indicate that color information is the dominant discriminatory cue for mold identification, while texture descriptors provide complementary structural information that improves class separation. The RGB+HSV+LAB combination achieved the highest performance, with a training accuracy of 97.91 percent and a testing accuracy of 96.66 percent. These findings demonstrate that effective mold classification can be achieved without relying on deep or computationally intensive architectures when the feature representation is well-designed. In conclusion, a lightweight, feature-centric ANN (Artificial Neural Network) is sufficient for reliable classification of mold growth levels on white bread. This study confirms that a compact, feature-based learning strategy is sufficient for reliable classification of mold on white bread, providing a technically efficient basis for a vision-based food quality assessment system.
Sistem Absensi Menggunakan Near Field Communication Pada Jurusan Teknik Informatika dan Komputer Universitas Negeri Makassar Imran, Al; Andi Baso Kaswar; Ahmad Adzan Lain
Jurnal MediaTIK Volume 7 Issue 1, Januari (2024)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v7i1.1262

Abstract

Universitas Negeri Makassar saat ini, khususnya Jurusan Teknik Informatika dan Komputer menggunakan sistem absensi konvensional saat melakukan luring atau kuliah tatap muka secara langsung dan juga menggunakan sistem absensi menggunakan Learning Management System (LMS) Syam Ok pada saat melakukan kuliah secara daring atau kuliah online. Kecurangan mahasiswa dapat terjadi karena sistem absensi perkuliahan konvensional. Kecurangan itu dilakukan dengan menitipkan absen pada temannya meskipun sebenarnya mereka tidak hadir di perkuliahan. Selain itu, sistem absensi perkulihan konvensional membutuhkan lebih banyak pegawai untuk menyalin semua data para mahasiswa setelah perkuliahan setiap hari. Penelitian ini merupakan jenis penelitian dan pengembangan (R&D) yang bertujuan untuk menghasilkan sistem absensi dengan menggunakan fitur Near Field Communication (NFC) yang terdapat pada handphone. Penelitian ini menggunakan model pengembangan prototyping dan menggunakan pengujian standar kualitas ISO/IEC 25010 pada 8 aspek yaitu functional suitability, usability, reliability, security, performance efficiency, portability, security dan maintainability. Penelitian dilaksanakan di Jurusan Teknik Informatika dan Komputer. Penelitiaan ini menghasilkan sebuah aplikasi sistem absensi berbasis android untuk meminimalisir kecurangan sistem absensi pada perkuliahan secara luring. Hasil pengujian aplikasi menggunakan ISO/IEC 25010 pada 8 aspek menunjukkan bahwa aplikasi layak untuk digunakan.
Sistem Pendeteksi Objek Tanaman Selada Hidroponik Dalam Netpot Menggunakan Metode Segmentasi Otsu Thresholding disertai Operasi Morfologi Kaswar, Andi Baso
Jurnal MediaTIK Volume 6 Issue 1, Januari (2023)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v6i1.1351

Abstract

Petani selada hidroponik sering menghadapi masalah dalam memantau pertumbuhan dan perkembangan selada yang mereka tanam. Hal tersebut disebabkan oleh beberapa faktor, antara lain kurangnya keterampilan dalam pengoperasian alat dan teknologi, serta kesibukan dalam mengurus kegiatan pertanian lainnya. Beberapa penelitian telah dilakukan untuk memonitoring tanaman hidroponik namun sistem yang dikembangkan hanya berfokus pada pengontrolan dan monitoring kondisi lingkungan dan media tanam hidroponik. Padahal berhasil atau tidaknya pengkondisian tanaman tersebut, terlihat secara visual pada perkembangan fisik tanaman. Dalam rangka mengatasi hal tersebut, telah dikembangkan sistem monitoring berbasis citra digital untuk memonitoring tanaman selada hidroponik secara langsung. Namun, dari metode tersebut membutuhkan data yang sangat banyak dan komputasi yang sangat kompleks agar model yang diusulkan dapat mendeteksi objek secara akurat. Oleh karena itu, pada penelitian ini diusulkan sistem pendeteksi objek tanaman selada hidroponik dalam netpot menggunakan metode segmentasi Otsu Thresholding disertai operasi morfologi. Metode yang diusulkan terdiri atas 5 tahapan utama yaitu, tahap input citra, ekstraksi channel RGB, segmentasi Otsu, operasi morfologi dengan image substraction, dan pelabelan objek menggunakan bounding box. Metode yang diusulkan dapat mendeteksi objek citra selada hidroponik dalam netpot dengan rata-rata akurasi 99,41%, Missclassification Error sebesar 0,59% dan waktu komputasi sebesar 0,64 detik. Hasil yang diperoleh menunjukkan bahwa metode yang diusulkan dapat mendeteksi objek selada hidroponik dalam netpot dengan akurasi yang tinggi dan waktu komputasi yang cepat.
Sistem Pendeteksi Kematangan Buah Tomat Berbasis Pengolahan Citra Digital Menggunakan Metode Jaringan Syaraf Tiruan Ishak; Ihlasul Amal; Maulana Muhammad; Andi Baso Kaswar
Jurnal MediaTIK Volume 5 Issue 1, Januari (2022)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/mediatik.v5i1.1384

Abstract

Penelitian ini bertujuan untuk merancang sistem yang mampu mendeteksi tingkat kematangan buah tomat dengan memanfaatkan pesatnya perkembangan ilmu pengetahuan khususnya di bidang artificial intelligence yang dikolaborasikan dengan pengolahan citra digital. Terdapat lima tahapan metode yang digunakan dalam penelitian ini yakni, tahap akuisisi citra, tahap preprocessing, tahap segmentasi, tahap morfologi dan tahap klasifikasi. Hasil penelitian menunjukkan bahwa metode yang digunakan peneliti sangat cocok untuk merancang sistem pendeteksi tingkat kematangan buah tomat yakni mentah, mengkal, dan matang. Hal tersebut dibuktikan dengan tingkat akurasi pengujian sistem yang mencapai 100%. Jumlah dataset yang digunakan sebanyak 90 citra tomat yaitu 30 citra tomat mentah, 30 citra tomat mengkal, dan 30 citra tomat matang.
KLASIFIKASI TINGKAT KESEGARAN DAUN BAWANG MENGGUNAKAN JARINGAN SYARAF TIRUAN BERBASIS PENGOLAHAN CITRA DIGITAL Andi Fitri Novianti; Muhammad Atthariq; Juliano Nufiansyach Dini; Andi Baso Kaswar; Jessica Crisfin Lapendy
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i2.3378

Abstract

Green onions, commonly used in Indonesian cuisine, have significant agricultural potential. Despite high production, their quality, particularly freshness, is traditionally evaluated visually, leading to inconsistent and subjective results. This study aims to develop an objective and accurate method for classifying the freshness of green onions using an Artificial Neural Network (ANN). Previous studies have employed ANN but have not specifically targeted the freshness classification of leeks. The proposed method utilizes the color and texture features of green onions.The research methodology includes image acquisition, preprocessing, segmentation, morphology, feature extraction, and classification using ANN. A total of 300 images were acquired and categorized into three freshness levels: not fresh, less fresh, and fresh. During the training phase, 240 images were used, and 80 images were reserved for testing. The optimal feature combination identified includes HSV and LAB color features along with texture features (Contrast + Energy). The results demonstrated that the freshness classification of green onions achieved 100% accuracy in both training and testing phases. The training process, with 240 images, had a computation time of 142.684 seconds, while the testing process, with 80 images, took 35.648 seconds. These findings indicate that using ANN based on color and texture features is highly effective in determining the freshness level of green onions.
Digital Balance in the AI Era: A Life-Course Perspective on AI Interaction, Digital Well-Being, and Academic Performance among Engineering Students Fauziyah Alfathyah; Nur Aisyah Fadliyah Faizal; Andi Dio Nurul Awalia; Andi Baso Kaswar; M. Miftach Fakhri
Artificial Intelligence in Lifelong and Life-Course Education Vol 1 No 1 (2026): Artificial Intelligence in Lifelong and Life-Course Education
Publisher : PT. Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/aillce.v1i1.1

Abstract

Purpose – The increasing integration of artificial intelligence (AI) in higher education offers substantial benefits for learning efficiency and personalization, yet it also raises concerns regarding digital ethics, learner autonomy, and digital well-being. From a life-course education perspective, early adulthood represents a critical transitional stage in which patterns of AI interaction may shape long-term learning habits and readiness for lifelong learning. However, empirical evidence examining how multidimensional AI interactions influence academic outcomes through psychological mechanisms remains limited, particularly in developing country contexts. This study investigates the effects of cognitive, affective, and social-ethical interactions with AI on academic performance among Indonesian engineering students, with digital well-being positioned as a mediating mechanism.Design/methods/approach – A quantitative cross-sectional survey was conducted with 103 engineering students from multiple universities, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).Findings – The findings indicate that cognitive interaction with AI significantly enhances academic performance, while affective interaction primarily contributes to digital well-being. Notably, higher levels of digital well-being are associated with reduced academic performance, suggesting a paradox in which increased comfort and convenience from AI may weaken sustained cognitive engagement. Digital well-being significantly mediates the relationship between affective interaction and academic performance, revealing potential risks of emotional overreliance on AI.Research implications/limitations – These results highlight the importance of balanced and self-regulated AI use in higher education and underscore the need to design AI-supported learning environments that foster cognitive engagement while sustaining digital well-being. From a life-course perspective, the findings suggest that AI interaction patterns formed during early adulthood may have implications for lifelong learning autonomy and educational sustainability.Originality/value – This study provides empirical evidence on multidimensional AI interaction in higher education from a life-course perspective and emphasizes the importance of ethical and responsible AI integration to safeguard academic performance and student well-being.
Pengembangan Sistem Informasi Pariwisata Kabupaten Soppeng sebagai Media Informasi Berbasis Web Aisyah Ramadani; Dyah Darma Andayani; Andi Baso Kaswar
Journal of Emerging Research in Computer Science and Artificial Intelligence Vol 1, No 2 (2026): Maret 2026
Publisher : PT. Global Research Collaboration

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

Abstract

Tujuan penelitian ini yakni untuk menghasilkan sistem informasi pariwisata kabupaten Soppeng sebagai media informasi berbasis web agar objek wisata di kabupaten Soppeng dikenal banyak orang dan mengetahui hasil pengujian sistem menggunakan ISO 25010 dengan delapan aspek pengujian. Penelitian ini menggunakan model pengembangan prototyping dengan tahapan: pengumpulan kebutuhan sistem, membangun prototyping, evaluasi prototyping, mengkodekan sistem, menguji sistem, evaluasi sistem, menggunakan sistem. Adapun hasil yang didapatkan dari penelitian ini yaitu: (1) Aspek suitability diperoleh hasil presentase 100% dengan kategori “Layak”. (2) Aspek reliability diperoleh hasil presentase 100%. (3) Aspek usability diperoleh hasil presentase 90% dengan kategori “Sangat Layak”. (4) Aspek efficiency diperoleh hasil presentase 86% dengan kategori grade B. (5) Aspek maintainability diperoleh hasil memenuhi standar dari indiktor instrumentation, consistensy, dan simplicity. (6) Aspek portability diperoleh hasil sistem dapat berjalan dengan baik diberbagai browser baik dekstop maupun mobile. (7) Aspek security diperoleh hasil dengan kategori A. (8) Aspek compatibility diperoleh hasil sistem yang dibangun kompatibel dengan berbagai browser. Berdasarkan hasil pengujian tersebut sistem informasi pariwisata kabupaten Soppeng sebagai media informasi berbasis web telah memenuhi standar kualitas sistem dan sangat layak digunakan.
Public Sentiment on Indonesia’s Free Nutritious Meal Program: A Mixed-Methods NLP Evaluation Ibrahim, Firmansyah; Prasetya, Didik Dwi; Kaswar, Andi Baso; Pratiwi, Hardyanti
Journal of Health and Nutrition Research Vol. 5 No. 1 (2026)
Publisher : Media Publikasi Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56303/jhnresearch.v5i1.1053

Abstract

Large-scale nutrition intervention programs such as the Free Nutritious Meal Program (MBG) are likely to attract considerable attention on social media. While conventional evaluation techniques are often too slow to capture rapidly shifting sentiment, this study seeks to determine how sentiment can be evaluated. More specifically, we aimed to identify the key emerging issues. Methodology: In this study, one approach to examining emerging issues is to use a two-stage workflow in Natural Language Processing (NLP). The first step in sentiment analysis is using a transformer model (Indo-RoBERTa) to assign 'Positive', 'Negative', or 'Neutral' to 3,459 public texts from X (Twitter) social media. Secondly, we focused on 1,130 'Negative' texts. We used topic modeling (BERTopic) on this and identified the most critical clusters of issues to map and their relative importance. Results & Conclusions: Negative sentiment involves multiple factors, to which our model successfully highlighted four of the most impactful areas: (1) Financial concerns and budgetary priorities; (2) Responses to particular media coverage (e.g., Kompas); (3) Political general discourse; and (4) Expectations of particular local issues (education issues in Papua). Conclusion: Compared with the gaps in the program's nutrition components, the economic consequences, budget gaps, inequities, and regional policy deficiencies drew more public interest. Implications: The findings point to a clear need for a differentiated and open approach to communicating public policy. This approach should communicate the nutritional value and the need to align messaging with the public for the geographic and budgetary realities.
AI Literacy, Technical Skills, and Ethical Awareness in Predicting Students’ Learning Performance Jannah, Devi Miftahul; Huda, Syamsul; Yasin, Muhamad; Fakhri, M Miftach; Wahid, Syahid Nur; Kaswar, Andi Baso; Soeharto, Soeharto; Amukune, Stephen
Online Learning In Educational Research (OLER) Vol. 6 No. 1 (2026): Online Learning in Educational Research
Publisher : CV FOUNDAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/oler.v6i1.565

Abstract

The increasing integration of AI systems into various sectors of the economy has also raised ethical concerns. Even as education in AI has developed to ensure that learners have the appropriate technical skills, the existing systems have failed to address the issue of ethics. As a way of addressing the problem, the current study aims at investigating learning about AI literacy and ethical reasoning. The author in this research applied the Partial Least Squares Structural Equation Modeling (PLS-SEM), from a questionnaire consisting of 400 university students (conducted of informatics and computer engineering department) to examine the relevance of AI literacy (AI-DAIB theories/basics), technical skills (TS), learning performance (LPER and EAI as moderating effect on AI perception (AIP). The findings found interesting result that AI literacy and technical skills have significant effects on learning performance and the moderating effect of AI ethics also increases the added value. This study indicates the need for a wider framework of all educational activities focusing on the development of technical skills, AI literacy and (semi)AI ethics to respond effectively to gaps in both development and moral responsibility of AI technologies
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 Aisyah Ramadani Akbar, Trisakti Aksa, Muhammad Alfian Firlansyah Amukune, Stephen Ananta Dwi Prayoga Alwy Andi Ahmad Taufiq Andi Akram Nur Risal Andi Alamsyah Rivai Andi Dio Nurul Awalia Andi Fitri Novianti Andi Nurul Izzah Andi Rosman N 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 Arsyad, Meisaraswaty Arya Yudhi Wijaya Arya Yudhi Wijaya Aryadi Nurfalaq Ashadi, Ninik Rahayu Asmi Ulfiah Asnidar Asnidar Asrofi, Muhammad Ghufran Astuti, Ninik 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 Didik Dwi Prasetya 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 Fauziyah Alfathyah 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 Ibrahim, Firmansyah 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 Jannah, Devi Miftahul 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 Lavicza, Zsolt M. Miftach Fakhri Makmur, Haerunnisya Mappaita, Al Haytsam Marwan Eka Ramdhany Marwan Ramdhany Edy Massie, Gary Jeremi Maulana Muhammad Maulana Muhammad Mawaddah, Arini Ulfa 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 Akil, Muhammad Muhammad Atthariq 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 Nur Aisyah Fadliyah Faizal 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 Pramudya Asoka Syukur Pratama, Azir Zuldani Pratiwi, Hardyanti Putri Ramdani R, Muh Raflyawan R, Ranir Aftar Ranggareksa, Andi Ranir Atfar R Rapa, Wiwi Resky, Andi Aulia Cahyana Riana T. Mangesa Ridwan Daud Mahande Ridwansyah Riswansyah , Muh Fikra Junian Rivai, Andi Tenri Ola Riyama Ambarwati 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 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 Syamsul Huda Syasikirani. N, Adelia Tenriajeng, Andi Afrah Tenriola, Andi Tri Afirianto Tsabita Syalza Billa Tsabita Syalza Billa Irawan Umar, Nur Fadhilah Wahda Arfiana AR Wahid, Syahid Nur WAHYUDI Wanda Hamidah Wardani, Ayu Tri Wiwi Rapa WULANDARI Yasin, Muhamad Yasser Abd Djawad Yuliarni, Tarisa Yusuf, Zulfatni