p-Index From 2021 - 2026
18.446
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Bulletin of Electrical Engineering and Informatics JEJAK Jurnal Natapraja : Kajian Ilmu Administrasi Negara Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Jurnal Borneo Administrator: Media Pengembangan Paradigma dan Inovasi Sistem Administrasi Negara Sinergi Jurnal Informatika dan Teknik Elektro Terapan ELINVO (Electronics, Informatics, and Vocational Education) CESS (Journal of Computer Engineering, System and Science) Jurnal Keperawatan Sriwijaya Media Penelitian Pendidikan : Jurnal Penelitian dalam Bidang Pendidikan dan Pengajaran Jurnal Riset Fisika Edukasi dan Sains Jurnal Maneksi (Management Ekonomi Dan Akuntansi) JISPO (Jurnal Ilmu Sosial dan Ilmu Politik) Jurnal Informatika Jurnal Inovasi Bisnis (Inovbiz) Jurnal Rekayasa Material, Manufaktur & Energi Jusikom : Jurnal Sistem Komputer Musirawas Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Informasi MURA MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal EDUTECH Undiksha J-SAKTI (Jurnal Sains Komputer dan Informatika) Jesya (Jurnal Ekonomi dan Ekonomi Syariah) YUME : Journal of Management MEDIA INFORMASI Transparansi Jurnal Ilmiah Ilmu Administrasi Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Applied Technology and Computing Science Journal Jurnal Doktor Manajemen (JDM) EAJ (ECONOMICS AND ACCOUNTING JOURNAL) Jurnal Ilmiah Edunomika (JIE) JATI (Jurnal Mahasiswa Teknik Informatika) JURNAL PENELITIAN PERAWAT PROFESIONAL Journal of Telenursing (JOTING) E-Link: Jurnal Teknik Elektro dan Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Jurnal Trias Politika JEKPEND Jurnal Ekonomi dan Pendidikan Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Industri Terintegrasi (JUTIN) Indonesian Journal of Global Health research JOINT (Journal of Information Technology GUYUB: Journal of Community Engagement Jurnal Teknik Informatika (JUTIF) International Journal Of Science, Technology & Management (IJSTM) Asia-Pacific Journal of Public Policy Educative Sportive Jurnal Optimasi Teknik Industri (JOTI) Buletin Poltanesa Bulletin of Computer Science Research Journal of Informatics Management and Information Technology Narra J KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Bisnis dan Manajemen (JBM) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Conten : Computer and Network Technology INDOGENIUS Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Akuntansi AKUNESA Journal of Management and Digital Business Dinamika Jurnal Administrasi Bisnis Jurnal VNUS (Vocational Nursing Science) Journal of Indonesian Economy and Business TSAQIFA NUSANTARA: Jurnal Pembelajaran dan Isu-Isu Sosial Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Innovative: Journal Of Social Science Research TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Indo-Fintech Intellectuals: Journal of Economics and Business AMMA : Jurnal Pengabdian Masyarakat Jurnal REP (Riset Ekonomi Pembangunan) Influence: International Journal of Science Review Coreid Journal Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sistem Informasi dan Manajemen Prosiding Seminar Nasional Unimus Jurnal Polimesin E-Amal: Jurnal Pengabdian Kepada Masyarakat EKOBIMA Ekonomi Bisnis dan Manajemen SISFOTENIKA Informasi interaktif : jurnal informatika dan teknologi informasi Journal of Economic and Bussiness Retail CEJou Ekliptika: Jurnal Inovasi Teknologi Berkelanjutan Assyfa Journal of Farming and Agriculture Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal UNIV.BI MENGABDI
Claim Missing Document
Check
Articles

Classification of palm oil fruit ripeness based on AlexNet deep Convolutional Neural Network Kurniawan, Rudi; Samsuryadi, Samsuryadi; Mohamad, Fatma Susilawati; Wijaya, Harma Oktafia Lingga; Santoso, Budi
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.019

Abstract

The palm oil industry faces significant challenges in accurately classifying fruit ripeness, which is crucial for optimizing yield, quality, and profitability. Manual methods are slow and prone to errors, leading to inefficiencies and increased costs. Deep Learning, particularly the AlexNet architecture, has succeeded in image classification tasks and offers a promising solution. This study explores the implementation of AlexNet to improve the efficiency and accuracy of palm oil fruit maturity classification, thereby reducing costs and production time. We employed a dataset of 1500 images of palm oil fruits, meticulously categorized into three classes: raw, ripe, and rotten. The experimental setup involved training AlexNet and comparing its performance with a conventional Convolutional Neural Network (CNN). The results demonstrated that AlexNet significantly outperforms the traditional CNN, achieving a validation loss of 0.0261 and an accuracy of 0.9962, compared to the CNN's validation loss of 0.0377 and accuracy of 0.9925. Furthermore, AlexNet achieved superior precision, recall, and F-1 scores, each reaching 0.99, while the CNN scores were 0.98. These findings suggest that adopting AlexNet can enhance the palm oil industry's operational efficiency and product quality. The improved classification accuracy ensures that fruits are harvested at optimal ripeness, leading to better oil yield and quality. Reducing classification errors and manual labor can also lead to substantial cost savings and increased profitability. This study underscores the potential of advanced deep learning models like AlexNet in revolutionizing agricultural practices and improving industrial outcomes.
PENINGKATAN MODEL SEGMENTASI PENGGUNA TERMINAL TIPE B SUMBER KABUPATEN CIREBON DALAM PERBAIKAN SARANA DAN PRASARANA DENGAN ALGORITMA K-MEANS Kusmiyaty, Agesty; Kurniawan, Rudi; Arie Wijaya, Yudhistira; Hayati, Umi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12466

Abstract

Terminal Sumber, sebuah terminal tipe B di Kabupaten Cirebon, menghadapi tantangan dalam memenuhi kebutuhan pengguna akibat pengelolaan sarana dan prasarana yang belum optimal. Tingkat kepuasan pengguna terhadap fasilitas, kebersihan, kualitas layanan, dan infrastruktur sering kali beragam, mencerminkan kebutuhan perbaikan yang terarah. Penelitian ini bertujuan untuk menganalisis kepuasan pengguna dengan memanfaatkan algoritma K-Means Clustering. Data kepuasan pengguna dikumpulkan melalui survei langsung, menghasilkan dua klaster berdasarkan nilai Davies Bouldin Index (DBI) optimal sebesar 0,547. Klaster 0 merepresentasikan pengguna dengan tingkat kepuasan lebih rendah, sedangkan klaster 1 memiliki tingkat kepuasan lebih tinggi. Hasil ini menunjukkan bahwa segmentasi pengguna dapat membantu pengelola terminal merancang strategi perbaikan layanan yang lebih spesifik dan efektif. Dengan demikian, penelitian ini berkontribusi dalam penerapan metode clustering untuk meningkatkan kualitas layanan transportasi umum, baik secara praktis maupun akademis
ALGORITMA RANDOM FORETS UNTUK PENINGKATAN MODEL KLASIFIKASI PADA DATA DIAGNOSA PASIEN PUSKESMAS PEKALANGAN KOTA CIREBON Arisa, Arisa; Kurniawan, Rudi; Hayati, Umi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12676

Abstract

Puskesmas Pekalangan Kota Cirebon menghadapi tantangan dalam memanfaatkan data diagnosis pasien secara efektif untuk mendukung keputusan medis. Pengelolaan data yang tidak seimbang dan kompleks sering kali menghambat akurasi klasifikasi diagnosis. Penelitian ini bertujuan untuk meningkatkan akurasi model klasifikasi diagnosis pasien menggunakan algoritma Random Forest dengan optimasi parameter "number of trees" dan "max depth". Metode penelitian ini mengadopsi pendekatan Knowledge Discovery in Databases (KDD) yang mencakup prapemrosesan data, seleksi fitur, dan evaluasi model. Dataset terdiri dari 3.769 data rekam medis pasien Puskesmas Pekalangan periode Januari hingga Juni 2024. Hasil penelitian menunjukkan bahwa parameter optimal "number of trees" adalah 28 dan "max depth" adalah 10, keduanya menghasilkan akurasi model sebesar 76,39%. Selain itu, atribut "keluhan utama" terbukti menjadi faktor yang paling berpengaruh terhadap prediksi, dengan akurasi mencapai 53,58%. Temuan ini menegaskan pentingnya pemilihan parameter yang tepat dan seleksi fitur dalam meningkatkan efisiensi serta keandalan model klasifikasi. Implementasi model ini diharapkan mampu mendukung pengambilan keputusan medis yang lebih akurat dan cepat di tingkat puskesmas.
ALGORITMA FP-GROWTH UNTUK MENINGKATKAN MODEL ASOSIASI PADA DATA PERMINTAAN BARANG LOGISTIK RUMAH SAKIT XXX JAKARTA Anggraeni, Anggi; Kurniawan, Rudi; Wijaya, Yudhistira; Hayati, Umi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12688

Abstract

Pengelolaan logistik rumah sakit membutuhkan analisis pola permintaan barang untuk meningkatkan efisiensi operasional. Penelitian ini menggunakan algoritma FP-Growth untuk mengidentifikasi pola asosiasi antar barang logistik berdasarkan data permintaan Rumah Sakit XXX Jakarta tahun 2023. Algoritma ini dipilih karena kemampuannya dalam menganalisis frequent itemsets secara efisien dan akurat. Data penelitian mencakup 1.433 entri transaksi permintaan barang, meliputi nama barang, jumlah, dan frekuensi permintaan. Proses penelitian mengikuti tahapan Knowledge Discovery in Database (KDD), meliputi praproses data, transformasi, analisis menggunakan FP-Growth, dan evaluasi hasil. Analisis menemukan bahwa Tissue Hand Towel memiliki nilai support tertinggi (0,645), diikuti oleh Tissue Toilet Roll (0,174). Pola asosiasi antara keduanya menunjukkan confidence 79,4%, mengindikasikan hubungan kuat dalam pemesanan bersama. Hasil penelitian menunjukkan bahwa penerapan algoritma FP-Growth mampu memberikan wawasan strategis untuk manajemen logistik, seperti pengelolaan stok yang lebih efisien, pengurangan pemborosan, dan ketersediaan barang yang tepat waktu. Disarankan pengembangan sistem otomatis berbasis algoritma ini untuk meningkatkan efisiensi dan akurasi pengelolaan logistik di sektor kesehatan.
ALGORITMA K-MEANS UNTUK MENINGKATKAN MODEL KLASTERISASI DATA SISWA SMK SAMUDRA NUSANTARA KABUPATEN CIREBON BERDASARKAN NILAI AKADEMIK Alif Prayudha, Bimo; Kurniawan, Rudi; Wijaya, Yudhistira; Hayati, Umi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12689

Abstract

Pengelolaan data nilai akademik siswa yang besar dan kompleks menjadi tantangan signifikan dalam dunia pendidikan, khususnya di SMK yang fokus mempersiapkan siswa untuk dunia kerja. Data yang tidak terorganisir dengan baik sering kali menghambat proses pengambilan keputusan berbasis data. Algoritma K-Means dipilih dalam penelitian ini karena kemampuannya yang efektif dalam menganalisis data dan mengelompokkan pola tersembunyi. Penelitian ini menerapkan metodologi Knowledge Discovery in Databases (KDD), meliputi seleksi data, praproses, transformasi, klasterisasi, evaluasi menggunakan Davies-Bouldin Index (DBI), dan interpretasi hasil. Dataset terdiri dari nilai akademik siswa pada mata pelajaran utama, seperti Matematika, Bahasa Inggris, dan Kimia. Hasil penelitian menunjukkan klaster ideal terdiri dari dua kelompok dengan nilai DBI 0.519, di mana atribut Kimia memiliki pengaruh paling signifikan. Klasterisasi ini memberikan wawasan yang mendalam tentang pola akademik siswa, mendukung strategi pembelajaran berbasis data, serta membantu sekolah menyusun kebijakan pendidikan yang lebih efektif.
Analysis of Village Fund Supervision in Gampong Geulumpang Tujoh, Matangkuli District (Study at the Inspectorate of North Aceh Regency) Kurniawan, Rudi; Junaidi, Junaidi; Muhammad, Muhammad
Transparansi : Jurnal Ilmiah Ilmu Administrasi Vol. 3 No. 2: Desember 2020
Publisher : Institut Ilmu Sosial dan Manajemen STIAMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/transparansi.v3i2.1139

Abstract

Supervision of village funds is an action in the management of village funds carried out by government officials. This is because village funds are funds sourced from the State Revenue and Expenditure Budget intended for villages through the Regency / City Regional Revenue and Expenditure Budget and are used to finance government administration, development and community and community empowerment. The purpose of this study was to determine the supervision of village funds carried out by the Inspectorate at Gampong Geulumpang Tujoh, North Aceh Regency. The type of research is using a qualitative approach. Data analysis used data reduction, data presentation and drawing conclusions or verification. The results of this study were the supervision of village funds carried out by the Inspectorate at Gampong Geulumpang Tujoh, Matangkuli District, North Aceh Regency, carried out in several stages, namely inherent supervision, functional supervision, legislative supervision and community supervision and the obstacles faced by the inspectorate in monitoring village funds in Gampong. Geulumpang Tujoh, Matangkuli District, North Aceh Regency, is that there is no element of accuracy of village funds, is not timely in providing village fund information and is not objective in managing village funds. It is hoped that the obstacles in the supervision of village funds carried out by the Inspectorate of North Aceh Regency should require a special budget provided by the central government to further support the implementation of supervision of village funds carried out by the North Aceh District inspectorate, besides that the North Aceh Inspectorate needs to add members to each supervisory team so that the inspection can run thoroughly.
Comparative study of anti-SARS-CoV-2 receptor-binding domain total antibody titer before and after heterologous booster with mRNA-based COVID-19 vaccine Kamil, Qatrunnada; Putri, Widia; Ayulinda, Arianisah P.; Maelani, Imelda; Anwar, Samsul; Ichsan, Ichsan; Pranata, Agung; Mudatsir, Mudatsir; Syukri, Maimun; Rizal, Samsul; Kurniawan, Rudi; Sofyan, Sarwo E.; Harapan, Harapan
Narra J Vol. 4 No. 3 (2024): December 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i3.788

Abstract

The waning immunity following the COVID-19 vaccination become a significant concern and the immunological dynamics of vaccine-induced antibodies after vaccination need to be explored. The aim of this study was to compare anti-SARS-CoV-2 receptor-binding domain (RBD) antibody levels before and after a booster dose with heterologous COVID-19 vaccine and to identify factors influencing the levels after receiving the booster dose. A cross-sectional study was conducted in which individuals who received primary doses of CoronaVac and a booster dose with an mRNA-based vaccine were recruited using a purposive sampling technique. The titers of anti-SARS-CoV-2 RBD antibodies were measured using an enzyme-linked immunosorbent assay (ELISA), and plausible associated factors were collected using a questionnaire-assisted face-to-face interview. The Wilcoxon test was used to compare the titers before and after the booster dose, while the Kruskal-Wallis and Mann-Whitney tests, followed by multivariate linear regression, were used to assess the factors associated with RBD total antibody titers. The results showed that there was a significant increase of anti-SARS-CoV-2 RBD total antibody titers before and after receiving the booster dose (1,558.7 BAU/mL vs 140.6 BAU/mL, p<0.001). The analysis revealed that age (p=0.555), sex (p=0.254), type of vaccine (p=0.914), presence of hypertension (p=0.541), diabetes (p=0.975), chronic obstructive pulmonary disease (COPD, p=0.620), and gout (p=0.364) were not associated with anti-SARS-CoV-2 RBD total antibody titers. However, the titers of anti-SARS-CoV-2 RBD total antibody were significantly different between those with and without hyperlipidemia (p=0.021). This study suggests that a booster dose with a heterologous COVID-19 vaccine could significantly enhance immune responses against COVID-19, and therefore, this strategy may be recommended as part of preventive measures to strengthen immunity against COVID-19.
Efektivitas Konseling Terhadap Peran Keluarga dalam Pengelolaan Diabetes Melitusdi Wilayah Kerja Puskesmas Cipaku Setiani, Tia; Kusumawaty, Jajuk; Asmarani, Sri Utami; Novianti, Elis; Kurniawan, Rudi; Nurapandi, Adi
Prosiding Seminar Nasional Unimus Vol 7 (2024): Transformasi Teknologi Menuju Indonesia Sehat dan Pencapaian Sustainable Development G
Publisher : Universitas Muhammadiyah Semarang

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

Abstract

Kematian adalah diabetes melitus. Untuk itu, perlu dilakukan pengelolaan untuk mencegah resikokomplikasi dan kematian yang ada.  Keterlibatan keluarga memiliki peran penting dalam penegakkanpengobatan diabetes melitus agar terlaksana dengan baik . Konseling merupakan salah satu metodepengobatan diabetes melitus untuk meningkatkan kualitas hidup pasien. Tujuan penelitian ini untukmengetahui efektivitas konseling keluarga berkaitan dengan fungsi keluarga dalam penatalaksanaandiabetes melitus di wilayah pelayanan Puskesmas Cipaku. Metode penelitian ini menggunakan metodekuantitatif dengan quasi eksperimental non equevalent control group. Sampel penelitian 15 orang darikelompok intervensi dan 15 orang dari kelompok kontrol, semuanya berdomisili di sekitar PuskesmasCipaku, berpartisipasi dalam penelitian ini. Purposive sampling merupakan metode yang digunakan untukpengambilan sampel dalam penelitian ini. Penelitian ini menggunakan analisis bivariat. Hasil penelitianmenunjukkan hasil yang signifikan, yaitu untuk kelompok intervensi (p = 0,000 atau p <0,05). Konselingkeperawatan tidak berpengaruh terhadap peran anggota keluarga dalam penatalaksanaan diabetes melitusmenurut hasil kelompok kontrol (p = 0,063 atau p > 0,05). Simpulan penelitian ini menunjukkan bahwaketerlibatan anggota keluarga dalam penatalaksanaan diabetes melitus menunjukan adanya pengaruh. Kata Kunci : Diabetes Melitus, Konseling, Peran Keluarga
Sistem Pemantauan Tegangan Listrik Menggunakan Mikrokontroler AT Mega 328 Berbasis Web Kurniawan, Rudi; Wijaya, Harma Oktafia Lingga; Nugroho, Aditya
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 1 (2019): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (721.689 KB) | DOI: 10.30645/j-sakti.v3i1.106

Abstract

Electricity is the source of the needs of people all over the world with electricity all human work will be easy, the main thing is electricity is a source of lighting without electricity, so there will not be an era and technology, but the use of electricity by many people who do not care about the electricity impact is a lot short circuit and fire because many electricity users do not know the current of electric current in their homes. Thus the author makes a tool that can measure the voltage used. Tools made using ACS712 and Arduino Uno sensors and Ethernet shield. The sensor will read the power supply voltage and then process it to Arduino Uno and Ethernet shield. After processing via Arduino, the ACS712 sensor readings will be displayed on the web page.
Tuberculosis Detection based on Lung X-Ray Images Using Convolutional Neural Networks (CNN) Kurniawan, Rudi; Badriyah, Tessy; Syarif, Iwan
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 7 No 1 (2024): June
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v7i1.6448

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis, primarily affecting the lungs. Despite being preventable and curable, TB remains a significant global health issue, especially in developing countries. The success of TB treatment heavily depends on the accuracy of the diagnosis, which typically requires expertise from pulmonology or radiology specialists to interpret chest X-ray images.  This study aims to design an assistive tool for TB detection that can automatically diagnose the disease using chest X-ray data.  The study implemented a Convolutional Neural Network (CNN) architecture to analyze the X-ray images. Additionally, image preprocessing and early stopping methods were employed to enhance accuracy performance, optimize computation, and prevent overfitting.  Experiment was conducting using 75% of the data as training data to generate the model and then applied to 25% of the data as testing data. This study comparing image sizes in RGB and grayscale modes. Experimental results show that the use of early stopping has a significant impact on training time, reducing training time substantially in almost all scenarios without drastically sacrificing accuracy. Without early stopping, accuracy does tend to be higher, as seen in grayscale color mode with an image size of 128x128, where the accuracy reaches 0.992, and in RGB mode with an image size of 64x64 which reaches 0.995. However, training time also increases significantly, for example for a 299x299 image with RGB mode, the training time reaches 927 seconds. Therefore, while RGB yields slightly higher accuracy, grayscale is recommended due to significantly faster training times. Additionally, the early stopping mechanism proves effective in reducing computational time, making the training process more efficient.
Co-Authors A.A. Gede Agung Abdul Ghani, Raihan Abdul Latif Abdul Razak Munir Abdussamad . Adawiyah , Rabiatul Adinda Maharani, Azahra Aditia Aditia Putra Pranjaya Aditya Nugroho Adriani, Weni Yunisa Afifah, Izza Nur Agni, Vega Putra Dwi Agung Pranata AGUNG SEDAYU Agustin, Maulina Aisy, Rahadatul Aktavera, Beni Alfirda Sofyan, Zahra Ali Ridho Barakbah Ali, Luthfi Gosan Alif Prayudha, Bimo Amaliah, Novi An-naziz Safaat, Wafik Ananda, Seprian Haris Andini, Selvi Andriani, Meri Andriyani, Wini Anggraeni, Anggi Annisa Desty Puspatriani Ansori, Ilman Anwari, Saeful APRIANDY, KEVIN ILHAM Aprianto, Wili Aprisusanti, Rani Purnama Aribah, Firyal Arief Rachman Arip Budiman, Arip Armanda, Dicky Armanto, Armanto Arna Fariza Aruni , Fidhia Aruni, Fidhia Arya Rudi Nasution Aryanto, Vincent Didiek Wiet Asep Gunawan asep gunawan Asmarani, Sri Utami Atun Farihatun Awaludin, Ade Ayu Endang Purwati Ayulinda, Arianisah P. Azzahrah, Dynda Shafiyah Bahri, Saiful Belli Nasution Berizky, Kekieta Gustie Bima Sena Bayu Dewantara Bimastari Aviani, Tri Hasanah Chasanah, Amalia Nur Chulyatunni’mah D.A, Dyah Kuntorini Dadan Suhendar, Asep Dadet Pramadihanto Danar Dana, Raditya Darma Irawan, Bobi Darussalam, Luthvi Nurfauzi Daulay, Nelly Khairaini Dayanti, Resda Dermawan, Hibrizi Dzaky Dewiyana, Dewiyana Dheri Febiyani Lestari Diana Puspitasari Diana Sari, Deuis Ducha, Moh Syamsi Dwi Budi Santoso Elmayati, Elmayati Enik Sulistyowati Ernawati Ernawati Esti Andarini Fahmi Wardhani, Masitha Fajar Ramadhan, Fajar Falih, Alfi Rizqi Falih Fanny Rifqi El Fuad, Fanny Rifqi Fauzan . Febrianur Ibnu Fitroh Sukono Putra Ferrina Ermalina Rumbik, Ferrina Ermalina Rumbik Fery Riyanto Fikri, Achmad Firmansyah, Andan Firmansyah, Tegar Fitriani Fitriani Fitriyani, Ida Fonna, Syarizal Frans Sudirjo Gapatra, Reja Gifthera Dwilestari Gilang Ramadhan Ginting, Helmina Br. Haekal Susanto, Ahmad Hamida, Silfiana Nur Hamonangan, Ryan Harapan Harapan Hayati, Umi Heni Marliany Henri Setiawan Herdiana, Ruli Herwantono, Herwantono Hidayat, Asep Toyib Hidayat, Muhamad Taufiq Hidayat, Peri Hidayat, Zaids Syarif Huda, Achmad Thorikul I Made Tegeh Ichsan Ichsan Ida Farida Idris Winarno Ikhwan Fahruddin, Yusuf Ikramullah, Ikramullah Ima Sukmawati, Ima Inawati, Windi Indriastuti, Marlina Intan, Bunga Islamiatik, Fena Ayu Ismail Ismail iwan Syarif j.ezugwu, umezurike Jannah, Zahratul Jayawarsa, A.A. Ketut Jonathan, Fandy Junaidi Junaidi Kamil, Qatrunnada Kaslani Khairani Daulay, Nelly Khristina Yunita Komala, Wulan Kristianti, Veronica Ernita Kurniadi, Yudi Kurniawan, Efik Kusman Ibrahim Kusmiyaty, Agesty Kusuma, Fujianti Kusumawaty, Jajuk Lily Herlinah Linda Oktavianingsih Lingga Wijaya, Harma Oktafia Lorentiana Wijayanti, Rima M Rusdi M. Azka Kesuma Wardana Ma’sum, Hadiansyah Maelani, Imelda Maimun Syukri, Maimun Makhfud Syawaludin Manzis, Zian Masru’ah, Iim Imas MJW, Endrian Mohamad, Fatma Susilawati Monica, Intan Mubarok, Khoirul Mudatsir Mudatsir Muhaimin, Ahmad Muhamad Chairul Basrun Umanailo MUHAMMAD FAHMI Muhammad Muhammad Muhsin Muhsin Muhyi, Adbdul Mujib, Miftachul Muktar, Muktar Mulyawan, Mulyawan Mustikasari, Julia Arum Mustofa Bisri, Mu'ammar Muzaki, Fazri Narasati, Riri Narasati Naufan, Muhammad Hilmy Ningtias, Restika Puspa Nining Rahaningsih NOVIANTI, ELIS Noviati, Elis Novilia, Fitri Nur Amalia, Yustika Nur Hamidah, Nur Nur Hidayat Nurapandi, Adi Nurazijah, Wulan Nurbaiti, Seni Nurholipah, Titin Nurmalawati, Nurmalawati Nurmasyahyati Nurmasyahyati, Nurmasyahyati Nurul Huda Nurul Kamaly Oktafia Lingga Wijaya, Harma Oktavia, Vicky Pamungkas, Angling Sadewo Aji Perdana, Tito Aditya Pratama, Annisa Salsabilah Pratama, Vishal Indu Prawitasari, Dian Prikurnia, Anas Khair Purusa, Nanda Adhi Purwo Suwignyo Puspitasari, Yeni Putri ayu, Putri Ayu Dara Sekarwangi Putri, Widia Rachmawati, Oktavia Citra Resmi Raden Mohamad Herdian Bhakti Rafila, Amal Julio Rafles Ginting Rahayu, Anisa Dinda Rahmad Nuthihar Rahmadiawan, Dieter Rahman Sahputra, Rizky Rahman, Sakilah Rai Fatkaozi, Ahmad Ramadhan, Teddy Muhammad Rano Raudotul Janah, Fina Regina Regina Ria Kurniawati Rifaai Alldi Ananda, Muhamad Riyana, Iis Rizki Ani, Fitri Rizki Fauzi, Ahmad Rizki Lesmana, Ghali Rizki, Fido Rizqi, A Faisal Maulana Rocky Putra A Rohman, Idan Saepul Rusdiyanto Sabilla, Raissa Sabri Sadiyyah, Putri Aisyatus Saeful Anwar, Saeful Safitri, Maria Safrida Safrida Safrida Safrida, Nila Salma Munada, Mutiara Salsabila, Denaya Bethary Samsul Anwar Samsul Rizal Samsuryadi Samsuryadi Sandi, Yudisa Diaz Lutfi Sandova, Firdaus Sanjaya, Handika Sari Rusmita Sari, Wisdalia Maya Sasabone, Luana Savero, Raihan Vito Septian Nugraha, Titan Sesulihatien, Wahjoe Tjatur Setiani, Tia Setiawardhana, Setiawardhana Shalihah, Ghina Sholeha, Mia Sintaningrum, Picantia Bunga Siti Nurhamidah, Lena Situmeang, Alona sobri, ahmad Sofyan, Sarwo E. Sofyan, Verra Rosyalia Widia Sormin, Rahma Diani Srinayanti, Yanti Sugiyono . Suhanda Suhanda Suhita Whini Setyahuni Sumiarsih, Mia Sunardi, Lukman Supratati, Tati Suprihartini, Yayuk Suryawijaya, Tito Wira Eka Susana, Heliyanti Susanti, Puspasari Susilawati Mohamad, Fatma Syach Putra, Yanuar Syafruddin, Muhammad Andri Syahrial Sidik Syamsul Anwar, Syamsul Syifaul Huzni Taryana Taryana, Taryana Tati Suprapti Taufik Hidayat Tedjo Darmanto Tedjo Darmanto Tessy Badriyah, Tessy Tri Harsono Triswanto, Triswanto Usmiyatun Usmiyatun Vitriyan Espa Wabula, Abdul Latif Wahyudi Wahyudi Wahyunisari, Nina Waluyo, Endrian Mulyadi Justitia Waqar Mazhar, Muhammad Wardana, Affan Hanafi Wibowo, Mochammad Eric Suryakencana Widianto, Fuad Hassan Widiawati, Fitri Wijaya, Yudhistira Wijaya, Yudhitira Arie Winayah, Winayah Yudhistira Arie Wijaya Yudi Setia Rachmanda yulani, Yulani - Yulia, Yuli Yunitri, Ninik Yusnawati, Yusnawati Yusuf Sidiq, Yusuf Sidiq Zahara, Ana Zahrul Fuadi Zainullah Zakaria, Fakhmi Zulius, Antoni