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The Role of Islamic Religious Education in Building the Character of the Muslim Generation in the Modern Era Nasrudin, Ahmad; Elsa Junita, Ika; Suhestiwi, Rini; Septiria, Dalima; Irawan, Bambang
Al-Bahtsu: Jurnal Penelitian Pendidikan Islam Vol 11, No 1 (2026): Penelitian Pendidikan Islam
Publisher : UIN Fatmawati Sukarno Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/btu.v11i1.9578

Abstract

Background: Technological developments in the modern era significantly impact education by providing easier access to information while posing new challenges for character development in the younger generation. This study analyzes the role of Islamic Religious Education in shaping Muslim generation character amidst modernization and identifies challenges arising from digital technology. Current moral crises manifest through problematic behaviors indicating weak internalization of religious values and insufficient synergy between educational institutions, families, and communities.Method: This study employs a library research methodology by reviewing relevant academic literature including journals, books, and scientific reports. This approach facilitates deep understanding of the research topic, theoretical analysis, and logical conclusion drawing regarding PAI function in character formation.Results: The findings demonstrate that PAI plays a central role in shaping Islamic character through internalizing values of honesty, discipline, responsibility, and tolerance. PAI serves as a moral bulwark protecting youth from negative technology impacts including decreased empathy and spiritual degradation. Obstacles include weak application of moral values in learning and lack of synergy between schools, families, and communities. While digital technology offers opportunities through virtual platforms, uncontrolled usage risks moral crises, necessitating wise integration that maintains alignment with Islamic values.Conclusion: PAI possesses an essential role in forming Muslim personalities with deep spiritual understanding while protecting students from modern era negative impacts through comprehensive Islamic teachings. Despite challenges regarding minimal ethical approaches and environmental influences, PAI must adapt to contemporary developments while maintaining Islamic identity and producing faithful generations with noble character.
The Capacity of Human Resources at the Bontang City DPRD Secretariat in Supporting the Legislative Function: An Analysis of Competencies and Bureaucratic Barriers Mappaelo; Irawan, Bambang; Saipul
International Journal of Science and Society Vol 8 No 1 (2026): International Journal of Science and Society (IJSOC)
Publisher : GoAcademica Research & Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/ijsoc.v8i1.1603

Abstract

This study aims to examine how bureaucratic competence and institutional constraints influence the effectiveness of legislative support provided by the Secretariat of the Regional House of Representatives of Bontang City in carrying out its legislative function. The study employs a qualitative approach with a case study design to capture empirical conditions related to the technical, managerial, and behavioral capacities of public officials, as well as structural and procedural obstacles within the organizational environment. The findings indicate that disparities in staff competencies, low educational qualifications, ineffective internal coordination, and rigid administrative procedures have hindered the timely provision of legislative support. In addition, limited technological facilities and a reactive work culture have reduced organizational responsiveness. The study concludes that enhancing the effectiveness of legislative support requires integrated efforts through strengthening staff capacity, simplifying bureaucratic procedures, improving coordination mechanisms, and reforming organizational work culture within the Secretariat of the Regional House of Representatives of Bontang City.
SECTORAL EGO VERSUS COLLABORATION: COMPARING THE REGULATORY AND INSTITUTIONAL FOUNDATIONS OF DIGITAL TRANSFORMATION IN BALIKPAPAN CITY AND SAMARINDA CITY Akbar, Paisal; Nurmandi, Achmad; Mutiarin, Dyah; Jubba, Hasse; Qodir, Zuly; Made Kutanegara, Pande; Irawan, Bambang
Kybernology : Journal of Government Studies Vol. 5 No. 2 (2025): Oktober 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/dkjeeg56

Abstract

This study critically examines the foundational readiness for digital government transformation by comparing the regulatory and institutional capacities of two major cities in East Kalimantan, Indonesia: Kota Balikpapan and Kota Samarinda. Using a qualitative comparative case study, data were gathered from in-depth document analysis, surveys of eight local government officials, and semi-structured interviews with eight key informants from the Communication and Information Offices. The findings reveal a stark divergence in institutional execution despite similar regulatory frameworks. Kota Balikpapan’s strong technical regulations are hindered by pervasive sectoral ego (reported by all respondents), creating implementation friction. In contrast, Kota Samarinda exhibits a collaborative institutional culture with no inter-agency resistance, driven by its integrative “Smart City Plus” vision and a centralized service platform. The study concludes that mature digital government depends less on regulatory completeness and more on deliberate governance engineering, intentional design of collaborative structures, leadership as integrators, and trust-based operational cultures. This research contributes by asserting that in decentralized contexts, the sociopolitical dynamics of local bureaucracy are the ultimate determinants of success, outweighing technology alone.
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN METODE TOPSIS UNTUK PENERIMA BANTUAN PUPUK SUBSIDI Mubarok, Muhammad Zaqi; Irawan, Bambang; Bachri, Otong Saeful
JUTECH : Journal Education and Technology Vol 6, No 2 (2025): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i2.5288

Abstract

Program bantuan pupuk subsidi NPK 15-15-15 di Kecamatan Adiwerna, Kabupaten Tegal, masih menghadapi kendala pada proses seleksi penerima yang dilakukan secara manual dan subjektif, sehingga berpotensi menimbulkan ketidaktepatan sasaran. Penelitian ini bertujuan merancang Sistem Pendukung Keputusan (SPK) berbasis metode TOPSIS untuk meningkatkan objektivitas, akurasi, dan transparansi dalam penentuan penerima bantuan pada kelompok tani. Metode TOPSIS diterapkan melalui tahapan penyusunan matriks keputusan, normalisasi, pembobotan berdasarkan lima kriteria (komoditas, tahun pembentukan, jumlah anggota, kelas, dan luas lahan), penentuan solusi ideal positif dan negatif, perhitungan jarak, serta penentuan nilai preferensi. Hasil penelitian menunjukkan bahwa kelompok tani dengan nilai preferensi tertinggi mencapai 0,82 sehingga dinilai paling layak, sedangkan nilai terendah 0,31 berada pada prioritas akhir penerimaan bantuan. Sistem ini dibangun berbasis web menggunakan PHP dan MySQL, serta dilengkapi diagram UML dan rancangan antarmuka untuk administrator, petugas, dan pengguna. Implementasi SPK ini meningkatkan efisiensi penyaluran bantuan pupuk subsidi dan mendukung pengambilan keputusan yang lebih terukur bagi kelembagaan pertanian di wilayah Adiwerna.
PENERAPAN METODE ANALYTICAL HIERARCHY PROCESS UNTUK PENILAIAN TENAGA KESEHATAN KOTA TEGAL Ghaffar, Dzaky Abdul; Bachri, Otong Saeful; Irawan, Bambang
JUTECH : Journal Education and Technology Vol 6, No 2 (2025): JUTECH DESEMBER
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i2.5292

Abstract

Penilaian kinerja tenaga kesehatan berperan penting dalam menjaga kualitas pelayanan kesehatan. Namun, penilaian manual sering kali subjektif dan kurang terstruktur, sehingga dapat memengaruhi objektivitas keputusan. Penelitian ini bertujuan merancang Sistem Pendukung Keputusan (SPK) berbasis metode Analytical Hierarchy Process (AHP) untuk menghasilkan evaluasi kinerja yang objektif dan terukur. Sistem ini diterapkan di Dinas Kesehatan Kota Tegal dengan sembilan kriteria penilaian berdasarkan nilai-nilai ASN BerAKHLAK dan indikator profesionalisme. Data dikumpulkan melalui observasi, wawancara, dan dokumentasi yang melibatkan 83 tenaga kesehatan. Metode AHP digunakan untuk menentukan bobot kriteria melalui perbandingan berpasangan, menghitung rasio konsistensi, dan menghasilkan peringkat akhir pegawai. Hasil penelitian menunjukkan bahwa SPK ini efektif dalam memproses data penilaian dan menghasilkan peringkat yang akurat. Sistem ini mendukung pengambilan keputusan terkait promosi, penghargaan, dan pengembangan kompetensi secara transparan dan objektif. Pengembangan di masa depan dapat mencakup integrasi dengan sistem manajemen kepegawaian dan fitur pelaporan otomatis.
PERANCANGAN CHATBOT MUSIK WEB UNTUK REKOMENDASI LAGU BERDASARKAN MOOD Leonardo, Nicholas; Ramadhan , Rafly Surya; Rumi, Nur Ananda; Nisa, Hoirun; Wijaya, Valentino; Ariz , Naufal; Irawan, Bambang
Journal of Information System Management (JOISM) Vol. 7 No. 2 (2026): Januari (On Progress)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2026v7i2.2319

Abstract

Mayoritas sistem rekomendasi musik, termasuk fitur “Made For You” pada Spotify, masih mengandalkan riwayat pemutaran tanpa mempertimbangkan kondisi emosional pengguna secara real-time, sehingga menghasilkan saran yang kurang relevan. Penelitian ini merancang Chatwise, chatbot musik berbasis web yang memberikan rekomendasi lagu personal melalui percakapan interaktif berdasarkan mood pengguna. Sistem memproses input teks berisi pilihan suasana hati dan alasan singkat menggunakan teknik pencocokan kata kunci, kemudian mengintegrasikannya dengan Spotify API untuk memperoleh data lagu secara real-time. Pengembangan dilakukan dengan metode Agile Scrum dan diuji menggunakan black-box testing serta kuesioner kepada 10 responden. Hasil menunjukkan 70% responden memberikan penilaian positif pada aspek tampilan, kecepatan, akurasi deteksi mood, kemudahan penggunaan, dan variasi genre. Temuan menunjukkan Chatwise berhasil mengintegrasikan deteksi mood dengan rekomendasi musik real-time, memberikan solusi adaptif dan kontekstual, meskipun masih diperlukan pengembangan lebih lanjut untuk meningkatkan akurasi dan keragaman musik.
Klasifikasi Huruf Hijaiyah Berbasis Citra Digital Menggunakan Metode Convolutional Neural Network (CNN) Firyal Nabila Ulya H.M; Bambang Irawan; Abdul Khamid
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3308

Abstract

Hijaiyah letters have varying shapes, and some of them are very similar, often causing errors in the manual character recognition process. This study aims to classify Hijaiyah letters based on digital images using the Convolutional Neural Network (CNN) method. This method was used in this study with a dataset consisting of 28 letter classes and a total of 4,480 images obtained from various public sources and private data. All images underwent a preprocessing stage that included labeling, resizing, normalization, and augmentation, then were divided into three parts, namely training data, validation data, and test data with a ratio of 70:20:10. The training process was carried out using the Python programming language with the help of the TensorFlow and Keras libraries on the Google Colab platform. The test results showed that the CNN model achieved an accuracy of 97.10%, with an average precision, recall, and F1-score of 0.97, respectively. Classification errors only occurred in letters that had similar shapes, such as Syin and Sin. Based on these results, the CNN method proved to be effective, efficient, and accurate in recognizing Hijaiyah letter image patterns, so it can be used as a basis for developing classification models with higher accuracy in the future.  
Klasifikasi Jenis Sampah Organik Dan Anorganik Menggunakan Convutional Neural Network Berbasis Citra Digital Nova Eliza; Bambang Irawan; Abdul Khamid
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3309

Abstract

Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.
Prediksi Konsentrasi PM2.5 Resolusi 15 Menit di Kabupaten Brebes Menggunakan Transformer dan GEOS-CF NASA Muhammad Fikri Setiawan; Bambang Irawan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3330

Abstract

Polusi udara partikulat halus (PM2,5) merupakan ancaman serius bagi kesehatan masyarakat di Kabupaten Brebes, Jawa Tengah. Faktor penyumbang utamanya adalah emisi kendaraan di jalur Pantura, aktivitas industri perikanan, serta konsentrasi tinggi selama musim kemarau (Juni–November). Tidak adanya model peramalan sub-jam yang akurat menghambat pengembangan sistem peringatan dini yang efektif. Penelitian ini mengembangkan dan mengevaluasi model deep learning berbasis Transformer untuk memprediksi konsentrasi PM2,5 dengan resolusi waktu 15 menit. Data yang digunakan berasal dari NASA GEOS-CF (band PM25_RH35_GCC) yang diakses melalui Google Earth Engine menggunakan API Python. Dataset mencakup periode 1 Januari hingga 22 November 2025, menghasilkan 7.813 observasi per jam, yang kemudian diinterpolasi linear menjadi 31.249 titik data dengan resolusi 15 menit. Arsitektur Transformer terdiri dari 3 lapis enkoder, 4 kepala perhatian multi-head, dimensi embedding 128, dimensi feed-forward 256, panjang sekuen 60 timestep, dan augmentasi fitur menggunakan rerata bergulir (*rolling mean*, jendela = 3) dan beda pertama (*first difference*). Pelatihan dilakukan dengan TensorFlow-Keras, pengoptimal Adam, penjadwal peluruhan kosinus (*cosine decay scheduler*), dan fungsi kerugian Huber. Pembagian data dilakukan secara kronologis: 70% pelatihan, 30% validasi. Evaluasi pada set uji independen (16 Agustus–21 November 2025, 9.357 observasi atau 97 hari 11 jam 15 menit) menghasilkan MAE 0,7691 µg/m³, RMSE 1,2052 µg/m³, R² 0,9945, dan *Explained Variance Score* 0,9948. Model ini mampu menggambarkan variasi diurnal dan anomali musiman secara akurat, jauh melampaui model LSTM dan GTWR konvensional. Penelitian ini memberikan kontribusi signifikan di bidang Teknologi Informasi melalui kerangka kerja pengolahan *big data* satelit untuk aplikasi lingkungan.
Klasifikasi Preferensi Destinasi Wisata Gunung dan Pantai Menggunakan Metode Deep Learning Andin Ayu Oksilia Ramadhani; Bambang Irawan
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3331

Abstract

Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.
Co-Authors Abdul Khamid Abdul Kolik Abdullah Karim Abdullah Karim Achmad Djumlani Achmad Fikri Achmad Nurmandi Adam Idris Adam Malik Adhani, Karenina Dwi Adigunawan, Adigunawan Agung Prayitno Agustin, Dania Safira Agustinus Lejiu Agustinus Suryantoro Ahmad Faqih Aisa Tri Agustini Ajeng Pratiwi Akbar, Paisal Albertus Maqnus Soesilo Alfiandri Alfiandri Alfiandri, Alfiandri Algopeng, Zozi Alifiansyah, Roby Fathan Amanda, Jesi Amar, Zafran Arifah Amelia Putri Dewi Nilam Sari Ananda, Alfin Andi Hafidz Khanz Andika Saputra Andin Ayu Oksilia Ramadhani Andri Prasetyo Angger Bagus Prasetiyo Anggit Murdani Ani Purwati Anthonius Margono Ardian Nugraha Putra Ardiano, Muhammad Rayyan Ardyansyah, Luthfi Arieyasmieta, Wildan Lutfi Arisandi, Bobi Ariz , Naufal Arniti, Ni Ketut Aryasatya, Muhammad Fathi Aryo Wibisono Asep Maulana, Asep Aspita Laila Astriani, Linda Axel Prasetyo Sudiro azharia, Jenny Clarisa azis, santowi Azizah, Enur Badarita, Badarita Ballianie, Novia Bambang Suharno Banun Binaningrum Barelang, Syaeful Bachri Bato, Bulan Erika Bhakti, M.Herdian Bhimo Rizky Samudro Budi Rahayu Budi Tjahjono Budiman Budiman Chairi, Minal Charles Raymond Jeffrey CHIANI, SARASWATI HAYLIAN Christina Nugroho Ekowati, Christina Nugroho Christover, Deandlles Cin, Muksin Cornelia, Geby Dan Buntu Paranoan Darmawan , Ade Daryono Daryono, Daryono Dayutama, Theodorus Dedy Miswar Dini Zulfiani Djumadi . Dudik Djaja Sidarta Dyah Mutiarin, Dyah Efriliyanti, Lia Eki Darmawan Eko Fuji Pangestu Eko Priyo Purnomo Elsa Junita, Ika Endang Nurcahyani Enos Paselle Erizal Eva Sri Handayani Pongtuluran Fadilah, Muhammad Rizky Faisal Nasar Bin Madi Fajar Apriani Farhanuddin Jamanie Farisi, Salman Fathurrahman Fathurrahman Fatullah, Iqbal Fauzi, Dzikri Ahmad Fauzia, Gina Febri Juita Anggraini Fernando Mersa Putra Fetia Harsa Fina Marshella Finnah Fourqoniah Firda Safira, Masnoni Firyal Nabila Ulya H.M Fransiska Xeviria Furqanul Hakim Gabriel Putra Gea Cita Meiratri Ghaffar, Dzaky Abdul Gintings, M. Fajar Mediyawan Gintings, Mohammad Fajar Mediyawan Giyarsi, Giyarsi Guspani, Reta Gusti Naufal Rizky Perdana Hamid Abdillah Hamzah, A. Hadian Pratama Hania Ayu Karin Hapidah, Hapidah Haqqi, Abdul Harfiani, Nabela H.N. Hariestya Viareco Haris Puspito Buwono Harmitalia, Mita Hartutiningsih . Hayati, Zahratul Hendra Wibowo Hului Hendra Wibowo Hului Hengki Satrisno Hernawan, Renaldy Herwanto, Agus Heryono Susilo Utomo Hidayat Hidayat Hidayat, Moh. Yusuf Hidayat, Muhammad Nizar Hilmi Mubarok Hutagalung, Winny Laura Christina Ibrahim, Adil Hasan Ibrahim, Adil Hassan Idris, Adam Ika Barokah Suryaningsih Ikhsanudin Ikhsanudin Ilham Yusuf Maulana Ilmi, Fikri Ikmalul Indah Purnamawati Indarto, Kus Iradhad Taqwa Sihidi Irmansah Isnaeni Yuliani Izma, Muhammad Athallah JAHIRUDIN, JAHIRUDIN Jani Master, Jani Jorgi Rivaldo Jubba, Hasse Juniarti, Eni Kadja , Deky Baleanus Kafa, Mushfi Abdulloh Kartika Kartika Kartini Kartini Kezia Arum Sary Khaerunnisa, Rindiyani Khair . Khairina, Etika Kris Witono Kundang Karsono Kurnia, Dian Ade Kus Indarto Kus, Indarto Kusdaryanto, Ardo Kustantina, Kustantina Latifatus Safariyah Leonardo, Nicholas Liky Faizal Lisdawati Lisdawati Liza Marina Loilatu, Mohammad Jafar Lustari, Reli Luthfi Sultan Jauhary Lito Made Kutanegara, Pande Mahfut Maimun Maimun Mappaelo Maradona Abdullah Mardeli Mardeli Martitah Martitah Masjaya . Maskud, Maskud Maulana, Muhammad Evan Maulida, Azkiyatul Mawaddah, Merisa Rahma Mawardi Mayasari, Windatania Meilinda, Nadia Mirawati Yanita Mochammad Iqbal Fadhlurrohman Moh. Hidayatullah Mohammad Taufik Mohammad Taufik Mohammad Taufik Mubarok, Muhammad Zaqi Muhamad Tamamul Iman Muhammad Bagus Sistriatmaja Muhammad Dhaffa Nugroho Muhammad Dinar, Yusadiningrat Muhammad Fahad Muhammad Fikri Setiawan Muhammad Guntur Muhammad Hidayat Muhammad Ilham Effendy Muhammad Imaduddin Muhammad Nizar Muhammad Noor Muhammad Raihan MUHAMMAD REZA FAHLEVY Muhammad Taufik Hidayat Muhammad Zaini Muhammad Zaki Muhimatul Ifadah Murni Murni Mutia Dewi Muzaki, Mochamad Najahatul Hananah Napitupulu, Richard RP Nasrudin, Ahmad Nida Handayani Nisa, Hoirun Nizirwan Anwar Nova Eliza Nova Sintia Dewi Sitorus Novalina Nurul Imama Noviandi Noviandi, Noviandi Noviantika, Stefanny Amalia Nugroho Susanto, Gregorius Nur Ariesanto Ramdhan Nur Fitriyah Nur Handayati Nur Hasan Nur Ilmiah Rivai Nurdin, Akhmad NURJANNAH, ANA Nurmawati, Subekti Nurrofiq, Ainan Zaky Nursaidah Nursaidah, Nursaidah Oktaviani, Ratna Ordas Dewanto Otong Saeful Bachri Pandoyo, Pandoyo Pidesia . Poppy Andriany Prabowo, Ary Pramuja, Trisena Pratama, Denni Pratama, Fristian Adi Pratama, Rizky Prawita Sari, Bening Premana, Agyztia Prihartono, Willy Prihartono Purnama Agustin, Kharisma Purwoko Purwoko Putra, Farrel Reyhan Putri, Cici Amelia Putri, Tasya Kamila Putri, Yoana Nabilah Qurani, Suci Ayu Qurrotaini, Lativa r. Patmiarsih Rabiatul Adawiyah Rachmatullah, Mochamad Miftah Raden Mohamad Herdian Bhakti Rahmat, Al Fauzi Rahmawati, Firda Devi Rahmi Dianita Ramadhan , Rafly Surya Ramadhan, Azki Ramadhan, Satrio Surya Ramdanis, Sapril Nurul Ramdhan, Nur Ariesanto Rande, Santi Rande, Santi Ratih Wirapuspita Wisnuwardani Reri Aprizal Reza Laksana Putra Riko Angga Bayu Kusuma Rini merliana, Setia Ririn Irmadariyani Rismayana . Rista Angraeni Rita Kalalinggi Riyan Ningsih Rizka, Yola Rizki Andre Handika Rizki Raja Putra Rizky Nugraha, Gilang Rizky Reynaldi Rochmah Agustrina Rodhiyah, Zuli Rohayu Rohayu Rohmah, Ainun Nimatu Rosid, Abdur Rumi, Nur Ananda Rusdiansyah Rusdiansyah Said Amaddin Saipul Saipul, Saipul Salahudin Salahudin Samsul Hadi Samuel ., Samuel Samuel Samuel Sandy Dwi Prasetyo Saprudin, Mohamad Sari, Mira Yulia Sari, Vita Komala Sarkani Sarkani Sarwoko, Jonathan Puji Sasongko, Mohammad Umar Sasongko Satrisno, Hengki Senobaan, Riska Tipa Septiria, Dalima Setiawan, Rafli Putra Shahib, Muhammad Umar Simamora, Nurcahaya Sintia, Delva Sinulingga, Samuel Mahesa Siti Kurniasih Siti Rodiyah Siti Triaminingsih Sofia Rahmasari Sonny Sudiar, Sonny Sri Wahyuningsih Steven Christian Subhaini Jakfar Sugeng Supriadi, Sugeng Suherlan Suhestiwi, Rini Sulistio, Alip Sulistiyono, Rovy SUMADI SUMADI Sumardi Sumardi . Sundari Meganingrum, Alpa Sundi, Venni Herli suratman Surpendi . Surya Nanda Situmorang Suryono Suryono Susilo Utomo, Heryono Syafitri, Ranny Aulia Syahrani . Syahrul Borman Syaifurrahim Azhari Syamsul Hadi Syaogi, Moh. Syifa Min Zaytun, Salwa tamlica, Agam Tampubolon, M. Ahsan Tan, Firwan Tasman, Alfadhli Thalita Rifda Khaerani Theresia, Maya Thriwaty Arsal Tiani, Lilis Tien Rohmatin, Tien Timothy Christian Tito Winnerson Sitanggang, Tito Winnerson Tjahjojo, Budi Tjokro Prasetyadi, Tjokro Totalia, Sherly Sustantien Tri Syukria Putra Tugiyono Tundjung Tripeni Handayani, Tundjung Tripeni Valentino Aris, Valentino Wibowo, Rahmat Catur Wijaya, Valentino Winda Khoritotul Jannah Windi Astuti Yofita Sandra Yogi Pasca Pratama, Yogi Pasca Yohani . Yosefa Sayekti Yulhendri Yulhendri Yulia Prihartini Yulianty Yulianty Zahidah, Athiya Zahriani, Nurul Zahrotun Ni'mah Zaky Mubarak, Ahmad Zhikry Fitrian Zulfikar, Iqbal Zulkifli, Zarina Zuly Qodir