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All Journal Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Syntax Jurnal Informatika Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Informatika dan Teknik Elektro Terapan Jurnal Inspiration Jurnal Ilmiah Ekonomi Islam INTEGER: Journal of Information Technology SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JUTIM (Jurnal Teknik Informatika Musirawas) NUSANTARA : Jurnal Ilmu Pengetahuan Sosial Jurnal RESISTOR (Rekayasa Sistem Komputer) Jurnal Keperawatan Komprehensif (Comprehensive Nursing Journal) Jurnal Penelitian Informatika : Jurnal Informatika, Manajemen dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Informatika dan Rekayasa Elektronik bit-Tech Jurnal MEBIS (Manajemen dan Bisnis) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurnal Abdi Insani Jifosi Nusantara Science and Technology Proceedings IKONIK : Jurnal Seni dan Desain Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Ilmiah Teknologi Informasi dan Robotika Jurnal Ilmiah Wahana Pendidikan Jurnal Manajemen Informatika Jayakarta Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia KARYA: Jurnal Pengabdian Kepada Masyarakat Unram Journal of Community Service (UJCS) International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Pengabdian Multidisiplin Jurnal Pengabdian Pada Masyarakat Indonesia (JPPMI) Jurnal Informatika Teknologi dan Sains (Jinteks) NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Indonesia (JPMI) Safari : Jurnal Pengabdian Masyarakat Indonesia JUSIFOR : Jurnal Sistem Informasi dan Informatika INCOME: Indonesian Journal of Community Service and Engagement DEVOTE: Jurnal Pengabdian Masyarakat Global Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia Jurnal Nusantara Berbakti JEECS (Journal of Electrical Engineering and Computer Sciences) Majalah Ilmiah METHODA JURNAL PENGABDIAN MASYARAKAT AKADEMISI Jurnal Penelitian Sistem Informasi Jurnal Kabar Masyarakat Jurnal Informasi Pengabdian Masyarakat Sammajiva: Jurnal Penelitian Bisnis dan Manajemen Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Pelayanan Hubungan Masyarakat Nusantara Journal of Computers and its Applications Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Kegiatan Positif : Jurnal Hasil Karya Pengabdian Masyarakat Abdimas Terapan: Jurnal Pengabdian Kepada Masyarakat Terapan JOTTER Jurnal Riset Sistem dan Teknologi Informasi Aspirasi : Publikasi Hasil Pengabdian dan Kegiatan Masyarakat Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia JEBD GEMBIRA (Pengabdian Kepada Masyarakat) Sains Data Jurnal Studi Matematika dan Teknologi Harmoni Sosial : Jurnal Pengabdian Dan Solidaritas Masyarakat Jurnal Pengabdian Masyarakat Indonesia (JPMI) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Manfish: Jurnal Ilmiah Perikanan dan Peternakan Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Jurnal Teknokes Jurnal Pengabdian Masyarakat Indonesia MPKM
Maulana, Hendra
Department Of Computer Science, Faculty Of Informatics, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
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Klasifikasi kendaraan bermotor berdasarkan jumlah gandar menggunakan adaptive minimal ensemble Al Hakim, Abdurrahman; Muttaqin, Faisal; Hendra Maulana
Computer Science and Information Technology Vol 7 No 1 (2026): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v7i1.11239

Abstract

The increasing volume of motor vehicles requires automated monitoring for the classification of heavy vehicle categories (Category I–V) based on the number of axles using side-view cameras. This process represents a complex fine-grained visual classification challenge due to the similar body shapes of trucks. To address the dilemma between the need for high accuracy and computational efficiency, this study implements an Adaptive Minimal Ensemble (AME) architecture that adaptively combines small-scale models.  The model is evaluated using a confusion matrix along with accuracy, precision, recall, and F1-score metrics. The testing results demonstrate that a single EfficientNetV2-S model is only able to achieve a maximum accuracy of 83% and exhibits significant limitations in extracting crucial distinguishing features, leading to misclassification of Category 4 and 5 vehicles. In contrast, the AME architecture, which utilizes the two best-performing EfficientNetV2-S base models, successfully achieves a substantial performance improvement with 95% accuracy, 95.21% precision, 95% recall, and a 94.99% F1-score.  In conclusion, the adaptive layer mechanism in AME is proven to be highly effective in compensating for the individual prediction weaknesses of its base models, resulting in a significantly more precise vehicle classification monitoring system.
Pendidikan Desa Berkualitas : Revitalisasi Pemberdayaan Literasi dan Kreativitas Anak di Desa Balongwono Widia, Elfitra; Bimantoro, Adi; Firmansyah, Riki Zogik; Ghazian, Himdani; Anggraini, Elvina Rosita; Endjani, Siti Kayyisa Nakhwa; Wijaya, Hanjas Mahatma; Gunawan, Bintang Anggraini Fania; Wati, Septya Asmoro; Maulana, Hendra
Media Pengabdian Kepada Masyarakat ( MPKM ) Vol. 2 No. 02 (2025): Media Pengabdian Kepada Masyarakat (MPKM)
Publisher : Rey Media Grafika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66084/mpkm.v2i02.324

Abstract

Program Kuliah Kerja Nyata (KKN) merupakan salah satu bentuk pengabdian mahasiswa kepada masyarakat yang bertujuan untuk memberikan kontribusi nyata melalui berbagai kegiatan. Dalam KKN ini, fokus tujuan program kerja adalah untuk mengembangkan literasi, kreativitas anak dan membangun fasilitas bermain edukatif di Desa Balongwono. Program ini terdiri dari 3 kegiatan utama, yaitu Taman Baca, Taman Bermain, dan Kreativitas Menghias dengan biji-bijian. Pojok Baca dibuat dengan tujuan untuk meningkatkan minat membaca dan peluang literasi bagi anak-anak setempat. Selain itu, program menghias gambar dengan biji-bijian dirancang untuk mengajarkan kreativitas dan keterampilan motorik halus anak-anak sekaligus memperkenalkan mereka pada proyek seni yang sederhana. Sedangkan pembangunan taman bermain berfokus pada penciptaan taman bermain yang aman dan mendidik, dimana anak-anak dapat belajar dan bermain pada saat yang bersamaan. Hasil dari kegiatan ini menunjukkan adanya peningkatan minat membaca, kreativitas dan partisipasi aktif anak dalam berbagai kegiatan yang diselenggarakan. Keterlibatan masyarakat dalam mendukung keberlanjutan proyek ini juga sangat penting bagi keberhasilan proyek. Kajian ini memberikan gambaran tentang pentingnya kolaborasi antara pelajar, masyarakat dan pemerintah desa untuk menciptakan lingkungan pendidikan yang mendukung perkembangan anak di pedesaan. Hasil kerja ini diharapkan dapat memberikan dampak jangka panjang bagi masyarakat.
Peningkatan Pemahaman Personal Branding melalui Media Sosial bagi Siswa SMPN 04 Tilamuta Rizqiyah Ahmad; Hendra Maulana; Indri Afriyani Yasin; Zainal Abidin Achmad
Jurnal Abdimas Indonesia Vol. 5 No. 3 (2025)
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v5i3.1943

Abstract

Kegiatan pengabdian ini dilatarbelakangi oleh rendahnya pemahaman remaja terhadap pentingnya membangun personal branding secara positif di ruang digital. Tujuan utama dari kegiatan ini adalah untuk meningkatkan literasi digital siswa, khususnya dalam membentuk citra diri yang bertanggung jawab melalui media sosial. Kegiatan dilaksanakan melalui metode sosialisasi dan edukasi interaktif yang mencakup observasi awal, penyampaian materi, diskusi, serta evaluasi menggunakan instrumen pre-test dan post-test. Kegiatan diikuti oleh 55 siswa kelas IX SMP Negeri 4 Tilamuta, yang terbagi dalam satu kelompok besar dan mengikuti seluruh rangkaian sosialisasi secara langsung. Hasil kegiatan menunjukkan adanya peningkatan pemahaman siswa, dengan nilai rata-rata post-test meningkat dari 49 menjadi 77. Peserta menunjukkan antusiasme tinggi dalam diskusi, dan mitra kegiatan menyatakan kepuasan terhadap pelaksanaan program. Kegiatan ini menunjukkan bahwa pendekatan edukatif berbasis personal branding dapat menjadi strategi efektif dalam membangun karakter digital siswa di wilayah 3T. Kolaborasi lintas perguruan tinggi juga menjadi nilai tambah dalam memperluas jangkauan pengabdian berbasis literasi digital.
Prediksi Kadar Air Greenbeans Kopi Pra-Roasting Menggunakan Metode ANFIS Muchammad Fadika Naddiyanto; Mohammad Idhom; Hendra Maulana
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 2 (2026): April 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i2.3568

Abstract

Moisture content of green coffee beans is a critical parameter that determines quality stability during storage and the pre-roasting stage; however, conventional measurement methods are destructive and unsuitable for continuous monitoring. This study aims to develop an Internet of Things (IoT)-based moisture content prediction system using the Adaptive Neuro-Fuzzy Inference System (ANFIS). Input variables include temperature, relative humidity (RH), and capacitive sensor ADC signals, while moisture content is used as the target variable. A dataset consisting of 1032 observations was divided into training and testing sets with an 80:20 ratio. The ANFIS model employed Gaussian membership functions and an early stopping mechanism, and its performance was evaluated using MAE, RMSE, MAPE, and the coefficient of determination (R²). Experimental results achieved MAE of 0.2648, RMSE of 0.4187, MAPE of 2.077%, and R² of 0.8109 with an accuracy of 97.923%. The proposed system enables accurate, non-destructive, and real-time moisture content prediction.Keywords: Moisture content; Green beans; Coffee; ANFIS; Prediction.AbstrakKadar air biji kopi hijau merupakan parameter penting yang menentukan stabilitas mutu selama penyimpanan hingga tahap pra-roasting, namun metode pengukuran konvensional bersifat destruktif dan tidak mendukung monitoring berkelanjutan. Penelitian ini bertujuan mengembangkan sistem prediksi kadar air berbasis Internet of Things (IoT) menggunakan metode Adaptive Neuro-Fuzzy Inference System (ANFIS). Variabel input meliputi suhu, kelembaban relatif (RH), dan sinyal ADC sensor, dengan kadar air sebagai variabel target. Dataset sebanyak 1032 data dibagi menjadi data latih dan data uji dengan rasio 80:20. Model ANFIS menggunakan fungsi keanggotaan Gaussian dan mekanisme early stopping, serta dievaluasi menggunakan MAE, RMSE, MAPE, dan koefisien determinasi (R²). Hasil pengujian menunjukkan MAE 0,2648, RMSE 0,4187, MAPE 2,077%, dan R² sebesar 0,8109 dengan akurasi 97,923%. Sistem yang diusulkan mampu melakukan prediksi kadar air secara akurat, non-destruktif, dan real-time. 
Deteksi Serangan DDoS pada Trafik IoT Menggunakan Random Forest dengan Dataset CICIoT2023 Muchammad Basroil Billah; Mohammad Idhom; Hendra Maulana
Progresif: Jurnal Ilmiah Komputer Vol 22, No 2 (2026): April
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v22i2.3614

Abstract

As the number of Internet of Things (IoT) devices continues to grow, these devices become increasingly vulnerable to Distributed Denial of Service (DDoS) attacks. However, their limited computational capacity makes it difficult to implement conventional security mechanisms. This study proposes a model for detecting DDoS attacks using Random Forest, trained using the CICIoT2023 dataset, which consists of 46 flow-based features collected from 105 real-world IoT devices. The preprocessing stage includes binary classification, normalization using StandardScaler, and handling class imbalance through a combination of 1:10 undersampling and class weighting. Evaluation on 1,154,684 test samples shows excellent performance, achieving 99.99% accuracy, 100% precision, 99.99% recall, and 99.99% F1-score. To ensure reliability, six validation checks are conducted, including overfitting analysis, cross-validation. The results confirm that the model can generalize well beyond the training data. Most attack types are detected perfectly, although application-layer attacks such as DDoS-SlowLoris remain more challenging. Overall, Random Forest proves to be an effective and relatively lightweight approach for DDoS detection in IoT environments.Keywords: DDoS; Random Forest; IoT; CICIoT2023; Machine LearningAbstrakPertumbuhan jumlah perangkat IoT menyebabkan peningkatan risiko terhadap berbagai ancaman keamanan terhadap serangan Distributed Denial of Service (DDoS). Namun, keterbatasan kapasitas komputasi pada perangkat IoT menyulitkan penerapan mekanisme keamanan konvensional. Penelitian ini mengusulkan model deteksi DDoS berbasis Random Forest yang dilatih menggunakan dataset CICIoT2023, yang terdiri dari 46 fitur berbasis flow yang dikumpulkan dari 105 perangkat IoT nyata. Tahap preprocessing meliputi klasifikasi biner, normalisasi menggunakan StandardScaler, serta penanganan ketidakseimbangan kelas melalui kombinasi undersampling (1:10) dan class weighting. Hasil evaluasi pada 1.154.684 data uji menunjukkan performa yang sangat tinggi, dengan accuracy sebesar 99,99%, precision 100%, recall 99,99%, dan F1-score 99,99%. Untuk memastikan keandalan model, dilakukan enam pengujian validasi, termasuk analisis overfitting, cross-validation. Hasil penelitian mengonfirmasi bahwa model mampu melakukan generalisasi dengan baik terhadap data di luar data pelatihan. Sebagian besar jenis serangan berhasil dideteksi secara sempurna, meskipun serangan pada lapisan aplikasi seperti DDoS-SlowLoris masih menjadi tantangan. Secara keseluruhan, Random Forest terbukti sebagai pendekatan yang efektif dan relatif ringan untuk deteksi DDoS pada lingkungan IoT Kata kunci: DDoS; Random Forest; IoT; CICIoT2023; Machine Learning
PEMBERDAYAAN PENINGKATAN KOMPETENSI MASYARAKAT DESA KAMPUNGANYAR BANYUWANGI MELALUI INOVASI DAN IMPLEMENTASI EDUTECHNOPRENEUR Nadiyah Myrilla; Hendra Maulana; Sheidy Yudiasta; Priza Pandunata; Muhammad Rafli Alviro; Jauhari Achmad Pradana; Alvin Rama Saputra; Tsalis Rahmad Dharmawan
Devote: Jurnal Pengabdian Masyarakat Global Vol. 4 No. 4 (2025): Devote: Jurnal Pengabdian Masyarakat Global, 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/devote.v4i4.5078

Abstract

This community service program aims to provide insight and knowledge about financial literacy, competitive pricing, sound financial management, how to hygienically and attractively package fish and vegetables, how to choose the right service and marketing strategies, and how to create technological innovations by following current trends such as delivery apps or social media. This Community Service activity, under the Community Empowerment Assistance Lecturer Service scheme, was conducted at the Berkah Bersama Mobile Vegetable Vendor Community in Palangka Raya City. The activities were implemented using various methods: Financial Literacy Socialization and Training, Training and Mentoring on the Use of Digital Marketing, Training on Appropriate Service and Marketing Strategy Management, and Training and Mentoring on skills in analyzing competitive pricing and how to manage and package products properly so that they appear fresh and attract buyers to increase profitability. The training delivery methods used were lectures, interactive dialogues, and hands-on demonstrations on the use of digital marketing applications.
Traffic Sign Detection Using Region And Corner Feature Extraction Method Hendra Maulana; Dhian Satria Yudha Kartika; Agung Mustika Riski; Afina Lina Nurlaili
IJCONSIST JOURNALS Vol 3 No 1 (2021): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3139.835 KB) | DOI: 10.33005/ijconsist.v3i1.54

Abstract

Traffic signs are an important feature in providing safety information for drivers about road conditions. Recognition of traffic signs can reduce the burden on drivers remembering signs and improve safety. One solution that can reduce these violations is by building a system that can recognize traffic signs as reminders to motorists. The process applied to traffic sign detection is image processing. Image processing is an image processing and analysis process that involves a lot of visual perception. Traffic signs can be detected and recognized visually by using a camera as a medium for retrieving information from a traffic sign. The layout of different traffic signs can affect the identification process. Several studies related to the detection and recognition of traffic signs have been carried out before, one of the problems that arises is the difficulty in knowing the kinds of traffic signs. This study proposes a combination of region and corner point feature extraction methods. Based on the test results obtained an accuracy value of 76.2%, a precision of 67.3 and a recall value of 78.6.
Digital Image Segmentation Resulting from X-Rays of Covid Patients using K-Means and Extraction Features Method Dhian Satria Yudha Kartika; Anita Wulansari; Hendra Maulana; Eristya Maya Safitri; Faisal Muttaqin
IJCONSIST JOURNALS Vol 3 No 1 (2021): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (970.953 KB) | DOI: 10.33005/ijconsist.v3i1.55

Abstract

The COVID-19 pandemic has significant impact on people's lives such as economic, social, psychological and health conditions. The health sector, which is spearheading the handling of the outbreak, has conducted a lot of research and trials related to COVID-19. Coughing is a common symptoms among humans affected by COVID-19 in earlier stage. The first step when a patient shows symptoms of COVID-19 was to conduct a chest x-ray imaging. The chest x-rayss can be used as a digital image dataset for analysing the spread of the virus that enters the lungs or respiratory tract. In this study, 864 x-rays were used as datasets. The images were still raw, taken directly from Covid-19 patients, so there were still a lot of noise. The process to remove unnecessary images would be carried out in the pre-processing stage. The images used as datasets were not mixed with the background which can reduce the value at the next stage. All datasets were made to have a uniform size and pixels to obtain a standard quality and size in order to support the next stage, namely segmentation. The segmentation stage of the x-ray datasets of Covid-19 patients was carried out using the k-means method and feature extraction. The Confusion Matrix method used as testing process. The accuracy value was 78.5%. The results of this testing process were 78.5% of precision value, 78% of recall and 79% for f-measure
Performance of Contrast Adjustment Techniques on The Face Recognition Method with Test Data Under Varying Lighting Conditions Budi Nugroho; Hendra Maulana; Anny Yuniarti
IJCONSIST JOURNALS Vol 6 No 2 (2025): March
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v6i2.130

Abstract

In the face recognition process influenced by lighting, the application of the image enhancement process at the preprocessing stage plays an important role in normalizing image contrast so that the quality of the input image becomes better. This step is expected to improve face recognition performance. In this study, we implement a lighting-influenced face recognition method, namely Robust Regression, and test several image enhancement techniques in the preprocessing phase to determine their effects on face recognition performance under different image lighting conditions, including Contrast-limited Adaptive Histogram Equalization (CLAHE), Histogram Equalization (Histeq), and Image Intensity Adjustment (Imadjust). HE uses a global technique that adjusts the overall intensity of the image. CLAHE uses a local technique that adjusts the intensity of pixels based on their surrounding areas. Meanwhile, the Imadjust function adjusts the intensity of image pixels based on the specified minimum and maximum values. The experiment is conducted using the AR Face Database which contains images affected by lighting factors. Lighting conditions include several categories, namely low, medium, high, and very high (extreme) lighting conditions. The experimental scenario is carried out by comparing the results of face recognition using several preprocessing techniques on each test data. The experimental results show that image enhancement techniques improve the performance of face recognition. The face recognition approach that adds the CLAHE technique to the preprocessing shows the highest performance of 95.87%. Meanwhile, the face recognition approach that adds the Imadjust technique to the preprocessing shows the lowest performance of 84.38%.
ANALISIS PENGARUH CLAHE PADA KINERJA MOBILENETV3-SVM KLASIFIKASI AKSARA JAWA Dela Ayu Putri Mayona; Chrystia Aji Putra; Hendra Maulana
Jurnal Informatika dan Rekayasa Elektronik Vol. 9 No. 1 (2026): JIRE April 2026
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v9i1.1997

Abstract

Penelitian ini membahas pengenalan aksara Jawa sebagai upaya pelestarian budaya di era teknologi digital. Permasalahan utama terletak pada rendahnya kualitas citra dan kemiripan visual antar karakter yang dapat menurunkan akurasi klasifikasi. Penelitian ini bertujuan untuk menganalisis kinerja model MobileNetV3-SVM serta pengaruh penerapan preprocessing Contrast Limited Adaptive Histogram Equalization (CLAHE) dalam meningkatkan akurasi pengenalan. Metode yang digunakan meliputi tahap preprocessing (CLAHE, resize, dan normalisasi), ekstraksi fitur menggunakan MobileNetV3Small, serta klasifikasi menggunakan Support Vector Machine (SVM) dengan kernel linear. Dataset yang digunakan terdiri dari 2.500 citra aksara Jawa yang dibagi dengan rasio 80:20 untuk pelatihan dan pengujian. Hasil penelitian menunjukkan bahwa model dengan CLAHE mencapai akurasi tertinggi sebesar 98,4%, lebih baik dibandingkan tanpa CLAHE yang memperoleh 97,2%. Kebaruan penelitian ini terletak pada integrasi metode CLAHE dengan arsitektur MobileNetV3-SVM untuk meningkatkan diskriminasi fitur pada citra aksara Jawa yang memiliki kemiripan visual tinggi. Implikasi dari penelitian ini menunjukkan bahwa pendekatan yang diusulkan dapat menjadi solusi efektif dalam pengembangan sistem pengenalan aksara daerah berbasis kecerdasan buatan yang lebih akurat dan adaptif.
Co-Authors A. Malik Haramain Abd. Ghofar Abd. Ghofar Abdurrahman Al Hakim Abyansyah Hayyu Sarwono Abyansyah Hayyu Sarwono Achmad Dhany Adam Mu'arif Achmad F, Kemas Achmad Junaidi Achmad Syaifulloh Adelia Agatha Futti Adham Roy Bhafiel Adisty Nadyra Kristianti Adithya Daffa Rabbani Ady F, Rahmad Afandy Yosediputra Afif A, Dana Afina Lina Nurlaili Afitra Azzahra Agung Mustika Riski Agus Zainal Arifin Agussalim, Agussalim Agustin, Risda Rosdiana Ahmad Haikal Nuqqy Zahhar Ahmad Muhajir, Ahmad Ajeng Arum Isfania Ajeng Arum Isfania Aji Bimantoro Aji Prayoga Akbar, Fawwaz Ali Al Hakim, Abdurrahman Alfi Kurinita Widianti Alfiani, Fina Ali Fikri, Yudistia Teguh Alif Syahda Adji Masyuri Alifiah Wulansari Mustofa Alit, Ronggo Althafiansyah, Rafif Althafiansyah, Rafif Zaidan Alvin Rama Saputra Alvina Widya Oktaviani Amanda Amelia S Ananda Asa Firstha Affandi Anandah Amirah Andhika Yudha Fachriza Andhika Yudha Fachriza Andi M. A. K. Parewe Andini Rahmawati Andreas Nugroho Sihananto Angga, Angga Rahmad Purnama Anggit Suryan Rohyan Anggraini Puspita Sari Anggraini, Elvina Rosita Ani Dijah Rahajoe Aniisah Eka Rahmawati Anita Wulansari Annis Oktaviani Annisa Nur Firdaus Anny Yuniarti Anugrah Prasetya, Rajawali Shatika Aprilia Verlianti Aprilia, Erica Aprilia, Salma Ardela Putri Amalia Ardhelia Damayanti Wirawan Ariansyah, Fery Almas Aris Sutejo Arnandhia Fatimah Azzahra Arya Dharma Syahputra Aziz, Muhammad Hilmy Azizah, Ratih Nuur Azizullah, Dana Afif Baehaqi Bagus Sutikno Putra Basuki Rahmat Masdi Siduppa Bimantoro, Adi Bisyrul Kafi I. A. Budi Nugroho Cahya Rafiyoga Harnan Cantika Dwi Maharani Ningtias Chiristian K Chulaisy Meidianto Citra, Delia Daniel Evanda Darlis Herumurti Davina Azalia Erson Dela Ayu Putri Mayona Dewanti, Felicitas Deru Dewi Puji Arofah Dhian Satria Yudha Dhian Satria Yudha K. Dhian Satria Yudha Kartika Dian Anisa Raya Diana Aqidatun Nisa Dianto, Alfian Rachmad Dimas Arif Setyawan Dimas Arif Setyawan Dini Adni Navastara, Dini Adni Dita Atasa Diva Faridathul Ilmi Diva Rihhadatul ‘Aisy Divana Hikmala Salsabila Puteri Dr. Basuki Rahmat DWI LESTARI, WAHYU Dwi Rahma Putri, Septiani Dwi Rahmadewi, Cynthia Dwi Yanti Margareta Dwiki Aditama Supangkat Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha, Eka Elistiya Elistiya Endjani, Siti Kayyisa Nakhwa Eristya Maya Safitri Ernik Ernawati Eva Yulia Puspaningrum Eva Yulia Puspaningrum Evan Saka Akhfan Fadhilah Labibah Nurjanah Fahmi Anugrah Danendra Fairuz Sany Faisal Muttaqin Faisal Muttaqin Fakhiroh, Luqy Aizzatul Farrel Tiuraka Vierino Fatchur Rozci Fatimah Azzahra Fatinena Candra Tribuana Fatma Endah Cahyaningrum Febriansyah, Rahmad Ady Fetty Tri Anggraeny Figo Afriansyah Fikri, Kemas Achmad Firmansyah, Riki Zogik Firya Nadhira Firza Prima Aditiawan Fitri, Anivea Fachmi Nur Fitrianata, Muhammad Ikhsan Galan Ahmad Defanka Ghazian, Himdani Ghea Lintang Samputri Girycki Sana Aleffin Gunawan, Bintang Anggraini Fania Gusti Eka Yuliastuti Hafid Akmal Alamsah Hakim Bima Ardimas Alam Hakim Bima Ardimas Alam Hamida Seftilutfiana Hana Safira Hidayat Handayani, Alfia Indah Handika, I Putu Susila Hannah Emmanuella Delia Hannah Emmanuella Delia Hapsari Wiji Utami Hayu Desthia Hena Elizabet Herawati, Yoshi Inne Herlin Dwi Dita Tamtamalia I Gusti Agung Socrates Adi Guna I Kadek Susila Satwika I Kadek Susila Satwika I Putu Susila Handika idhom, Mohammad Ignatius Bramantya Prasetyo Dewa Ignatius Bramantya Prasetyo Dewa Ika Faiqotul Ilham Rahmatullah Ilham Rahmatullah Indra Rasendriya Pratama Indra Rasendriya Pratama Indri Afriyani Yasin Intan Mitayani Irawati Irawati Ismiatul Ilmiah Iswanda Fauzan Satibi Ivan Ardiansyah J.A. Jelita Srikandi Pertiwi Jauhari Achmad Pradana Jemima Angella Setyana Jihan Syauqiyah Rosyadah Jonathan Christianto Wibowo Karina, Febrian Agung Dwi Kartika, Dhian Satri Yudha Kartini Kartini Kenneth Ephram Singarimbun KEZIA, KEZIA Khofiatul Rosdiana Windiarti Kowi Akbar Prasetya Kumala, Yudhistira Nanda Kurnia Rafif Shanika Kurniawan, Satria Fajar Dwi KY Margiati, KY Lailatul Badriah Laksamana Zulfikar Satria Decca Harits Latif Ahmad Fauzan Laycha Nazila Supoyo Putri Leli Lestari Lestari, Mufida Diah Liliana Swastina Lina Nurlaili , Afina Listiasari, Rani Lizard Sambawo Dimara, Denis M. Maigy Pratama Ma'ruf, Hafidz Mabruri, Kemal Al Kautsar Made Hanindia Prami Swari Mandyartha, Eka Prakarsa Mannan, Abd Margarita, Devina Mastar Asran Maulana Hassan Sechuti Maulana, M. Abizzar Maulidia Zalsa Wicahyo Putri Meimy Ratnakanyaka Merlina Aris Miftah Nur Miftahul Ichwan Miftakhul Jannah Moch. Rafie Pratama Mochammad Rayhan Faujan Mohamad Fikri Azam Mohamad Fikri Azam Mohamad Ilham Prasetyo Raharjo Mohammad Faisal Riftiarrasyid Mohammad Idhom Mohammad Idhom Moy Yustiwa Muchammad Basroil Billah Muchammad Fadika Naddiyanto Muhammad Bagas Ikmal Rifki Muhammad Fabbian Rachmansyah Muhammad Imam Haramain Muhammad Muharrom Al Haromainy Muhammad Rafli Alviro Muhammad Rizki Firmansyah Muhammad Rizki Firmansyah Mustofa, Tsabita Safana Muttaqin, Faisal Muttaqin, Faisal Nadiyah Myrilla Nadya Putri Najwa Belvana Nakrowiyah, Finda Rohmatin Narendra Pasha Maulana Natasya Ika Marshanda Naufal Hilmy Fauzan Nazhmi Fadhil Neri Gareta Bintang Armevia Nidya Arum Niken Hefa Zakkiya Nina Zenitha Sekar Sari Nira Fitryani Nirwana Septania Galih Perwira Moekti Nirwana Septania Galih Perwira Moekti Nisa', Choirun Novia Rahmadhani Nugroho Sihananto, Andreas Nur Indah Fatmala Nur Mila Eka Zaliyanty Nur Vita Dewan Tari Nurdianto, Muhammad Akbar Nurhaliza, Risma Nurmanida Azizah Nuha Nurul Wasiela Nuryananda, Praja Firdaus Octaviani, Vincentia Indri Parlika, Rizky Pratama Diko Marindo Pratama, Gede Ardi Pratiwi, Iramandha Putri Priza Pandunata Putra, Chrystia Aji Putri Wardhani, Lintang Sari Putri, Desya Ristya Rafael Octava Brilliante Rafli Aprilian Firmansyah Rahmadewi, Cynthia Dwi Ratna Yulistiani Reygita Arintya Ayu Pramesti Reynaldi Rizky Utomo Richul Munawaroh Rinda Purwati Rindyi Putri Lestari Rizka Fadhillah, Irnanda Rizki, Agung Mustika Rizqiyah Ahmad Rizqy Ahsana Putri Rohyan, Anggit Suryan Rolando Limantara, Kristian Ronggo Alit Rozy, Achmad Safana, Tsabita Safira Kusmindasari, Anggun Safira Salma Azzahra Salsabila Firdaus Sari, Lintang Satria Fajar Dwi Kurniawan Satria Yudha Kartika , Dhian Satwika, I Kadek Susila Sefiko Putra, Benedictus Renee Shabirina Laila Azka Shafa Diva Syaharani Shafira Rahmawati Sharla Putri Aisha Sheidy Yudhiasta Sheidy Yudiasta Sijabat, Riris Oktauli BR Siti Mi’Danur Rahmah Sri Trisnaningsih Sri Utami Bina Wijayanti Sufi Miftakhoneki Sufi Miftakhoneki Sugiarto, Mercy Aulia Sugiarto, Sugiarto Sugiyanto, Edi Sulastri Sulastri Sutrisni, Erica Aprilia Syaifullah Jauharis Saputra, Wahyu Syarifuddin Aryasatya Nugraha Tarissa Satya Laksmi Triyana, Dimas Tsabita Safana Mustofa Tsalis Rahmad Darmawan Tsalis Rahmad Dharmawan Ulfatillah Salmi Utami, Hapsari Wiji Vita Via, Yisti Vivi Aprilliya Ningsih Vynka Zahira Sausan Wafa Muqsithoh Subchan Wahyu Dwi Lestari Wahyu Setiawan Wardhani, Lintang Sari Putri Wati, Septya Asmoro Wicaksa Putra Pribadi, Achareeya Widia, Elfitra Widyana Dini Maylinda Widyana Dini Maylinda Wijaya, Hanjas Mahatma Wiji Utami, Hapsari Wilda Cahyani Sukma Wirya Atmaja, Pratama Wisnu Wardana, Mahendra Yemima Dya Novitasari Yisti Vita Via Yisti Vita Via Yisti Vita Via Yisti Vita Via Yolanda Irfania Yolanda Irfania Yudha K., Dhian Satria Yurisa Wianuari Zacky Yaser Malik Gumiwang Zainal Abidin Achmad Zaky Ikhsanudin Zein, Isynariyah Zumrotul Liana Putri Zumrotul Liana Putri