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Pembuatan Bahan Bakar Diesel dari Limbah Plastik HDPE dengan Proses Pirolisis Iskandar, Taufik; Abrina Anggraini, Sinar Perbawani; Melinda, Melinda
Reka Buana : Jurnal Ilmiah Teknik Sipil dan Teknik Kimia Vol 6, No 1 (2021): EDISI MARET 2021
Publisher : Universitas Tribhuwana Tunggadewi Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/rekabuana.v6i1.2251

Abstract

Indonesia menduduki posisi ke dua setelah cina penghasil sampah plastik terbesar di dunia. Dimana salah satu limbah plastik tersebut adalah HDPE (High Density Polyethylene). Sedangkan plastik merupakan produk hasil pengolahan minyak bumi yang dapat direcycle ke bentuk semulanya karena bahan baku pembuatan limbah plastik adalah nafta yang merupakan salah satu unsur dari minyak bumi. Salah satu solusi yang diperlukan adalah recycle dengan mengubah limbah plastik menjadi bahan bakar dengan proses pirolisis. Pirolisis merupakan salah satu proses terbaik dari recycle limbah plastik, dengan pertimbangan memahami sifat limbah plastik HDPE. Penelitian ini menggunakan alat pirolisis dengan variable suhu proses yaitu 300⸰C, 325⸰C, dan 350⸰C, waktu proses pirolisis yaitu 2 dan 4 jam. Dari proses pirolisis diperoleh hasil volume bahan bakar diesel yaitu pada suhu 300⸰C sebanyak 95 ml, suhu 325⸰C sebanyak 100 ml, dan suhu 350⸰C sebanyak 145 ml. Dari hasil analisa data optimal  untuk suhu dan waktu optimum proses pirolisis limbah plastik HDPE yaitu pada suhu 325⸰C selama 2 jam, bahan bakar diesel yang didapat memiliki kadar abu 0,044 (b/b), dan kadar air 0,031(%vol). ABSTRACTIndonesia is in second place after China, the largest plastic waste producer in the world. Where one of the plastic wastes is HDPE (High-Density Polyethylene). Meanwhile, plastic is a product of petroleum processing that can be recycled to its original form because the raw material for making plastic waste is naphtha, which is an element of petroleum. One solution that is needed to recycle by converting plastic waste into fuel by the pyrolysis process. Pyrolysis is one of the best processes for recycling plastic waste, with consideration of understanding the nature of HDPE plastic waste. This study used a pyrolysis tool with process temperature variables, namely 300⸰C, 325⸰C, and 350⸰C, the pyrolysis process time was 2 and 4 hours. From the pyrolysis process, the results of the volume of diesel fuel are at a temperature of 300 ⸰C as much as 95 ml, a temperature of 325 C as much as 100 ml, and a temperature of 350 ⸰C as much as 145 ml. From the results of the optimal data analysis for the optimum temperature and time of the HDPE plastic waste pyrolysis process, which is at a temperature of 325⸰C for 2 hours, the obtained diesel fuel has an ash content of 0.044 (w / w), and a moisture content of 0.031 (vol%).
Performance Comparison of Variational Mode Decomposition and Butterworth in Processing EEG Signals of Autism Patients Wardana, Surya; Melinda, Melinda; Ramdhana, Rizka; Yunidar, Yunidar; Away, Yuwaldi; Basir, Nurlida
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 3 (2025): August
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i3.105

Abstract

Electroencephalography (EEG) is a non-invasive technique for monitoring and recording the brain's electrical activity with electrodes applied to the scalp. The method is important in neurological studies, like that of Autism Spectrum Disorder (ASD), because it measures patterns of brain waves that can identify developmental abnormalities. However, EEG signals are often contaminated by multiple noise sources, including eye movements, muscle activity, and extraneous interference. This interference can significantly reduce the quality and intelligibility of signals. Therefore, preprocessing is required to enhance the reliability and precision of the data obtained. In this study, a Butterworth Band-Pass Filter (BPF) was used during preprocessing to filter out undesirable frequency components and to mitigate noise. After filtering, EEG signals were handled using the Variational Mode Decomposition (VMD) technique. VMD is an adaptive method for decomposing multidimensional signals into intrinsic mode functions while preserving critical details of the original data. For performance comparison, four quantitative metrics were used: Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Signal-to-Noise Ratio (SNR). Results showed that VMD performed better than BPF alone. As an example, for Subject 1, VMD achieved an MAE of 0.26 and MSE of 0.42, which was far superior to the MAE of 13.72 and MSE of 674.96 of BPF. Subject 3 had the least RMSE (0.40) when using VMD, whereas BPF scored 25.90. VMD also reported a highest SNR of 28.56, compared to BPF's 2.43. Overall, integrating VMD with BPF significantly improves EEG signal quality and enables more accurate analysis, particularly in ASD-related studies.
Autism EEG Signal Pre-Processing: Performance Evaluation of MS-ICA and Butterworth Filter Mirza Rahmat, Muhammad; Nurdin, Yudha; Melinda, Melinda; Away, Yuwaldi; Irhamsyah, Muhammad; Wong, W. K
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 3 (2025): August
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i3.107

Abstract

Autism Spectrum Disorder (ASD) is a neurological condition characterized by challenges in communication and social interaction, accompanied by the development of repetitive behavioral patterns. Electroencephalography (EEG) is primarily used to assess brain function in children with Autism Spectrum Disorder (ASD), mainly due to its non-invasive nature and superior temporal resolution compared to other neuroimaging methods. However, EEG signals are often contaminated by biological artifacts, such as eye movements and muscle contractions, which can significantly distort analysis outcomes. Pre-processing is therefore required to increase the accuracy of the EEG signal before additional analysis. The goal of this study was to compare and evaluate the performance of two pre-processing techniques, the Butterworth Band-Pass Filter and Multiscale Independent Component Analysis (MS-ICA), using four different performance metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Signal-to-Noise Ratio (SNR). The Butterworth method has an MAE of 227.57, which is acceptable. However, it produced an MSE of 160,653.22, an RMSE of 394.49, and a maximum SNR of only 1.33 dB. MS-ICA performs far better with a best MAE of only 0.44, an MSE of 3.33, an RMSE of 1.76, and an SNR of 30.88 dB. Paired t-test (p < 0.05) was employed to determine statistical significance,  while Cohen's d was used to assess the practical significance of the results. The effect sizes of MAE (d = 1.60), MSE (d = 1.02), RMSE (d = 1.54), and SNR (d = -9.50) were all calculated as large. These findings demonstrate that MS-ICA offers both statistical advantages and strong practical usefulness for noise removal while preserving the structural integrity of the original EEG signals. Therefore, MS-ICA proves to be the best approach for pre-processing EEG signals to be used for analysis in children with ASD
Ecofeminist Empowerment: In Preserving the Musi River Waters of Palembang City in 2023 Sanny Nofrima, Sanny Nofrima; Melinda, Melinda; Alam Mahadika, Alam Mahadika
JOURNAL OF GOVERNMENT SCIENCE Vol 6 No 2 (2025)
Publisher : Program Studi Ilmu Pemerintahan Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54144/govsci.v6i2.125

Abstract

This article discusses ecofeminist empowerment in efforts to conserve the waters of the Musi River in Palembang City in 2023. This research takes an ecofeminist approach by combining environmental and gender perspectives, focusing on the understanding that human relationships with nature have complex social and cultural dimensions. This research used a qualitative approach involving interviews and observations. The data collected were thematically analyzed to explore the understanding of ecofeminist contributions to the preservation of the waters of the Musi River. The results showed that the ecofeminist approach has made an important contribution to the efforts to conserve the waters of the Musi River. However, several factors that influence ecofeminist empowerment still need to be addressed. Social and cultural factors, such as gender stereotypes and limited roles for women in environmental affairs, are obstacles in increasing women’s active participation in water conservation. In addition, inadequate policies and regulations also need to be considered to create a supportive environment for ecofeminist empowerment. In this context, collaborative efforts need to be made between the government and civil society to overcome these problems. It is hoped that the results of this research can make a significant contribution to efforts to conserve the waters of the Musi River in Palembang City, while strengthening awareness of the link between the environment and gender.
Smart Door Locking System for Children Using HC-SR04 and IoT Technology Melinda, Melinda; Yunidar, Yunidar; Khairia, Syaidatul; Miftahujjannah, Rizka; Sakarkar, Gopal; Basir, Nurlida
JURNAL NASIONAL TEKNIK ELEKTRO Vol 14, No 2: July 2025
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v14n2.1293.2025

Abstract

The increasing incidence of minors accessing hazardous indoor areas—such as staircases, balconies, and rooms with sharp objects—raises serious safety concerns, often due to insufficient parental supervision. This study proposes an Internet of Things (IoT)-based automatic door lock system to enhance child safety in home environments. The system integrates dual ultrasonic sensors for distance and height detection, a KY-037 sound sensor, and an ESP32-CAM for real-time video monitoring, all accessible via a web interface. A key novelty lies in the integration of multi-sensor spatial awareness with live surveillance, enabling automated control and proactive safety features. Tested on ten children aged 4 to 6 years, the system achieved a 90% success rate in locking the door when a child under 120 cm approached within 1 meter, with an average response time of approximately 2 seconds. A sound-based alarm is also triggered when noise levels exceed 120 decibels, serving as an emergency alert. However, a 10% false negative rate was observed when children were detected at distances of 1.3 to 1.5 meters, suggesting the need for further sensor calibration. Overall, the system demonstrates strong potential as a scalable and cost-effective smart home safety solution, combining automation, real-time monitoring, and child-specific access control. Future work should focus on improving detection accuracy and extending functionality for multi-object scenarios.
EEG Performance Signal Analysis for Diagnosing Autism Spectrum Disorder using Butterworth and Empirical Mode Decomposition Fathur Rahman, Imam; Melinda, Melinda; Irhamsyah, Muhammad; Yunidar, Yunidar; Nurdin, Yudha; Wong, W.K.; Zakaria, Lailatul Qadri
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 3 (2025): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i3.788

Abstract

Electroencephalography (EEG) is a technique used to measure electrical activity in the brain by placing electrodes on the scalp. EEG plays an essential role in analyzing a variety of neurological conditions, including autism spectrum disorder (ASD). However, in the recording process, EEG signals are often contaminated by noise, hindering further analysis. Therefore, an effective signal processing method is needed to improve the data quality before feature extraction is performed. This study applied the Butterworth Band-Pass Filter (BPF) as a preprocessing method to reduce noise in EEG signals and then used the Empirical Mode Decomposition (EMD) method to extract relevant features. The performance of this method was evaluated using three main parameters, namely Mean Square Error (MSE), Mean Absolute Error (MAE), and Signal-to-Noise Ratio (SNR). The results showed that EMD was able to retain important information in EEG signals better than signals that only passed through the BPF filtration stage. EMD produces lower MAE and MSE values than Butterworth, suggesting that this method is more accurate in maintaining the original shape of the signal. In subject 3, EMD recorded the lowest MAE of 0.622 compared to Butterworth, which reached 20.0, and the MSE value of 0.655 compared to 771.5 for Butterworth. In addition, EMD also produced a higher SNR, with the highest value of 23,208 in subject 5, compared to Butterworth, which reached only 1,568. These results prove that the combination of BPF as a preprocessing method and EMD as a feature extraction method is more effective in maintaining EEG signal quality and improving analysis accuracy compared to the use of the Butterworth Band-Pass Filter alone.
Peningkatan Minat Literasi Siswa pada Era Perkembangan Zaman di Sekolah Dasar Danau Sadar Silaban, Pangeran O. J; Jalianery, Joanita; Setiawan, Rendy; Rofiah, Siti; Yudesman, Fatriani Margareta; Nego, Abed; Cloudya, Cindy; Melinda, Melinda; Kristiana, Kristiana; Nabella, Putri Rama; Rajagukguk, Katarina Rani; Alfian, Ridho; Syahputra, Daniel; Simanjorang, Rican; Peronika, Agustina
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 7 (2025): September
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i7.2979

Abstract

Pelaksanaan Kuliah Kerja Nyata (KKN) merupakan bentuk pengabdian mahasiswa kepada masyarakat dalam upaya menanggulangi berbagai permasalahan, termasuk dalam bidang pendidikan. Di Desa Danau Sadar, Provinsi Kalimantan Tengah, program KKN difokuskan pada isu rendahnya minat literasi di kalangan anak-anak dan masyarakat. Meskipun desa ini telah memiliki fasilitas pendidikan seperti perpustakaan desa dan sekolah dasar, tantangan dalam meningkatkan literasi masih signifikan. Salah satu penyebab utama adalah pengaruh media elektronik, seperti handphone, yang mendorong anak-anak lebih aktif di media sosial dibandingkan kegiatan membaca, menulis, dan menyimak. Untuk mengatasi hal tersebut, mahasiswa Universitas Palangka Raya mengembangkan 13 program kerja berbasis literasi yang dilaksanakan melalui kerja sama dengan Perpustakaan Nasional, Perpustakaan Desa, dan lembaga sekolah. Program ini bertujuan meningkatkan kemampuan literasi dasar serta membentuk kebiasaan membaca yang lebih baik di masyarakat Desa Danau Sadar.
H20 and H20 with NaOH-Based Multispectral Classification Using Image Segmentation and Ensemble Learning EfficientNetV2, Resnet50, MobileNetV3 Melinda, Melinda; Yunidar, Yunidar; Zulhelmi, Zulhelmi; Suyanda, Arya; Qadri Zakaria, Lailatul; Wong, W.K
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 4 (2025): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i4.1016

Abstract

High Multispectral imaging has become a promising approach in liquid classification, particularly in distinguishing visually similar but subtly spectrally distinct solutions, such as pure water (H₂O) and water mixed with sodium hydroxide (H₂O with NaOH). This study proposed a classification system based on image segmentation and deep learning, utilizing three leading Convolutional Neural Network (CNN) architectures: ResNet 50, EfficientNetV2, and MobileNetV3. Before classification, each multispectral image was processed through color segmentation in HSV space to highlight the dominant spectral, especially in the hue range of 110 170. The model was trained using a data augmentation scheme and optimized with the Adam algorithm, a batch size of 32, and a sigmoid activation function. The dataset consists of 807 images, including 295 H₂O images and 512 H₂O with NaOH images, which were divided into training (64%), validation (16%), and testing (20%) data. Experimental results show that ResNet50 achieves the highest performance, with an accuracy of 93.83% and an F1 score of 93.67%, particularly in identifying alkaline pollution. EfficientNetV2 achieved the lowest loss (0.2001) and exhibited balanced performance across classes, while MobileNetV3, despite being a lightweight model, remained competitive with a recall of 0.97 in the H₂O with NaOH class. Further evaluation with Grad CAM reveals that all models focus on the most critical spectral areas of the segmentation results. These findings support the effectiveness of combining color-based segmentation and CNN in the spectral classification of liquids. This research is expected to serve as a stepping stone in the development of an efficient and accurate automatic liquid classification system for both laboratory and industrial applications.
BEHAVIORAL COUNSELING MODEL FOR IMPROVING HEMOGLOBIN LEVELS IN ADOLESCENT GIRLS WITH ANEMIA Mayanti, Andi; Winarningsih, Rahayu Arum; Melinda, Melinda; Nurhasanah, Lulu; Umrah, Andi Sitti; Suriati, Israini
INTERNATIONAL JOURNAL OF NURSING AND MIDWIFERY SCIENCE (IJNMS) Vol. 8 No. 3 (2024): VOLUME 8 ISSUE 3 DECEMBER 2024
Publisher : Departement Research and Community Engagement Bina Sehat PPNI Institute of Health Science, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29082/IJNMS/2024/Vol8/Iss3/632

Abstract

This study aims to analyze the impact of Behavioral Counseling on haemoglobin improvement in adolescents with anaemia in Palopo City. The research employed a pre-experimental method with a one-group design (pretest-posttest) approach, where haemoglobin levels were measured before the intervention (P1), followed by four intervention sessions over four weeks. After the intervention, haemoglobin levels were measured again (P2). The study was conducted at SMAN 05 Palopo City. The population and sample consisted of 60 female adolescents with anaemia. Research instruments included observation sheets and questionnaires. Data collection involved two measurements, before and after the intervention. Data analysis was performed using the Wilcoxon test with a 95% significance level. The results showed that the mean haemoglobin level before the intervention was 10.3 g/dL, which increased to 11.6 g/dL after the intervention, indicating an improvement of 1.3 g/dL. Based on statistical testing using the Wilcoxon test, a value of ρ = 0.000 < α = 0.05 was obtained. It means that the behavioural counselling model significantly improved haemoglobin levels in adolescent girls with anaemia. In conclusion, behavioural counselling can serve as a practical and effective strategy to help adolescents change unproductive behaviours into more positive ones and improve health, particularly in treating and preventing anaemia.
Revitalisasi Penulisan Artikel Ilmiah Berbasis Mendeley bagi Guru SMK Negeri 1 Darul Kamal Aceh Besar Melinda, Melinda; Waladah, Bulen; Ananda, Mulya; Khatami, Muhammad; Irvan kurniawan, Muhammad; Herlina, Herlina
Jurnal Pengabdian Rekayasa dan Wirausaha Vol 1, No 2 (2024)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jprw.v1i2.42589

Abstract

Penulisan artikel ilmiah merupakan salah satu aspek penting dalam pengembangan kompetensi guru, terutama dalam rangka meningkatkan kualitas pendidikan. Namun, banyak guru mengalami kesulitan dalam menyusun artikel ilmiah secara sistematis dan terdokumentasi dengan baik, terutama dalam hal pengelolaan referensi. Untuk menjawab tantangan ini, program revitalisasi penulisan artikel ilmiah berbasis aplikasi manajemen referensi Mendeley dilakukan di SMK Negeri 1 Darul Kamal, Aceh Besar. Program ini bertujuan untuk meningkatkan pemahaman dan keterampilan guru dalam menggunakan Mendeley sebagai alat bantu penulisan ilmiah, sehingga proses penyusunan artikel menjadi lebih efisien dan akurat. Metode yang digunakan dalam program ini meliputi pelatihan dan pendampingan intensif, yang diikuti oleh 30 guru dari berbagai bidang studi. Hasil evaluasi menunjukkan bahwa peserta pelatihan mengalami peningkatan signifikan dalam kemampuan mengelola referensi, menyusun daftar pustaka, serta merapikan struktur artikel ilmiah. Program ini diharapkan dapat berkontribusi terhadap peningkatan produktivitas guru dalam menulis artikel ilmiah yang berkualitas serta memajukan budaya literasi ilmiah di lingkungan sekolah
Co-Authors . Roslidar Aafiyah, Siti Afra Abdurohim Abdurohim, Abdurohim Abed Nego, Abed Abrina Anggraini, Sinar Perbawani Achmad Maqsudi, Achmad Achmad, Ilham Afnan, Afnan Agnesia Candra Sulyani Agung Hilm Ghimri Ahmad, R. Andriadi Ahmadiar, Ahmadiar Ainil Syafitri Akbar, Alif Yafi Al Bahri Alam Mahadika, Alam Mahadika Albar, Nizam Alfatirta Mufti Alfatirta Mufti Alfian, Ridho Alfita Khairah Alfita Khairah Alifia, Rania Sofie Amalia Amalia Amaliatulwalidain, Amaliatulwalidain Ameilia Zuliyanti Siregar Ameilia Zuliyanti Siregar Anabel, Cendana Ananda, Mulya Anik Puryatni Anto Ariyanto Anzelina, Dhea Eprillia Aqif, Hurriyatul Ari Rahmat Putra Ibina Ariyani, Amra Arsy Febrina Dewi Arumi, Naila Azaria Arya Suyanda Asriati Asriati, Asriati Astuti, Meti Aufa Rafiki Aufa Rafiki Aufa Rafiki Aufa Rafiki Aufa Rafiki Aulia Arafat Aulia Rahman Aurelia, Gabrella Azhari, Rizki AZMI, MUHAMMAD RAUDHI Azra, Ery Bashir, Nurlida Basir, Nurlida Basuki Toto Rahmanto Bil Haki, Arif Binti Basir, Nurlida Budi Arianto Buleun Waladah Catur Andryani, Nur Afny Cloudya, Cindy Cut Salsabilla Azra Cut Siti Azola Syiva D Acula, Donata Diana Novita Diana, Fitri Dini, Siti Doke, Herlina Theodensia D. Donata D Acula Donata D Acula Donata D. Acula Duana, Maiza Dwi Rosalina Dwita Sakuntala Dzaki Dhiya Ul-Haq E Elizar Elizar Elizar Elizar Elizar Elizar Elizar Elizar Elizar, Elizar Ellsa Fitria Sari Elsy Rahajeng, Elsy Elya, Chayara Alima Rameyza Erika Lety Istikhomah Puspita Sari* Ernita Dewi Meutia Fadilah Amanda Putri Fahmi Fahmi Fajrul Islamy Fakhrus Syakir Farhan Fathur Rahman, Imam Fathurrahman Fathurrahman Fitri Arnia Fitri Indira Nauli Fitriyanti, Emiliy Fuaidah, Mahayaya Gazali, Syahrul Gopal Sakarkar Hamdani Hamdani Hanryono, Hanryono Hanum Aulia Harahap, Subur Harjoedi Adji Tjahjono, Harjoedi Adji Hasan, Hafidh Hasan, Vania Pratama Heltha, Fahri Hendrik Leo Herlina Dimiati Herlina Dimiati, Herlina Herlina Herlina Herwanto, Agus Holyness Nurdin Singadimedja Hubbul Walidainy I Gusti Bagus Astawa I Ketut Agung Enriko Ichwana Ramli Ichwana Ramli Ichwana Ramli Iis Juniati Lathiifah Ikram Muttaqin Imam Fathur Rahman Imam Fathur Rahman Inda Mariana Harahap Indarti, Ghinna Yulia Indera Sakti Nasution Indera Sakti Nasution Indriani, Berlian Irawan Irawan Irli Masitah Marpaung Irsyan Ramadhan Irvan kurniawan, Muhammad Iskandar Hasanuddin Iskandar Hasanuddin Iskandar Hasanuddin Islamy, Fajrul J Prayoga Joanita Jalianery Junidar Junidar Junidar Karlisa Priandana Kencana, Novia Khairani Khairani Khairia, Syaidatul Kristiana kristiana Lailatul Qadri Zakaria Lailatul Qadri Zakaria Lailatul Qadri Zakaria Lailatul Qadri Zakaria Lerrick, Yudith F. Lisbeth Lesawengen, Lisbeth Lucky, Muhammad Luju, Elisabet Lukman Hidayat M Ary Heryanto M Fahrur Rozi M Ghailan Dhiaulhaq Magfirah, Inayah Zaini Mahdi Syukri Mahfuzha, Raudhatul Mahidin Mahidin Mahidin Mahidin Malahayati, M. Margarethy Rohanie Mbado Maulana Imam Muttaqin Maulana, Muhammad Iqbal Maulisa Oktiana Maulisa Oktiana Maulisa, Oktiana Mauliza Putri Mauliza Putri Maya Fitria Mayanti, Andi Mega Fatimah Rosana Meutia Nauly Miftahujjannah, Rizka Mirza Rahmat, Muhammad Mohd. Syaryadhi Morita Sari Muhajir Muhajir Muhamad Risal Tawil Muhammad Dika Rafi Kasha Muhammad Fauzan Alfariz Muhammad Furqan Muhammad Hakkan Syukur Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhamsyah Muhammad Irhmasyah Muhammad Irwanto Muhammad Ridwan Muhammad Saifullah Nur Muhammad Saifullah Nur Muhammad Syafrudin Muharratul Mina Rizky Muharratul Mina Rizky Muhibbuddin Muhibbuddin Muhibuddin Muhibuddin Muhibuddin Muhsin Muhsin Muliyadi Muliyadi Muliyadi Muliyadi Muliyadi Muliyadi Mulyadi Mulyadi Mulyadi, Yose Ega Muslimsyah Mustikawati, Yunitari N Nasaruddin Nabella, Putri Rama Nabila, Nissa Hasna Nasaruddin Nasaruddin Nasaruddin Nasaruddin Nasaruddin Syafie Nasrul Arahman Nasrul Nasrul Nasrul Nasrul Nazilla, Izza Netti Herlina Siregar Netti Herlina Siregar Niza Aulia Nofrima, Sanny Novandri, Andri Nur Afny Catur Andryani Nuraini, Endah Nurbadriani, Cut Nanda Nurfatikah, Aisyah Ariyani Nurhasanah, Lulu Nurlida Basir Nurlida Basir Nurlida Basir Nurlida Basir Nurlida Basir Nurlida Basir Nurlida Basir Nurmalia Zakaria Nusa Muktiadji OKTADINATA, ALEK Oktiana, Maulisa Peronika, Agustina Prabowo, Bangkit Yudo PRATIWI, SASKIA Prayoga, Bima Wicaksana Dwi Pringgandini, Laras Ayu Purwati, Agnes Susana Merry Purwatiningsih, Sri Desti Putra Anwar Ginting, M. Alief Akhbar Qadri Zakaria, Lailatul Rachmawati Rachmawati Rafiki, Aufa Rahmat Maulana Rahmi Susanti Raihan, Siti Rajagukguk, Katarina Rani Rakhmad Syafutra Lubis Ramadan, Muhammad Fahreza Ramadhani, Hanum Aulia Ramdhana, Rizka Ramli, Amaliatulwalidain Raudhatul Mahfuzha Razita Nadhira Rika Sri Utami Rina Ridara Rini Safitri Riska Sufina Rita Khatir Rizal Syahyadi Rizka Miftahujjannah Rizka Miftahujjannah Rizka Miftahujjannah Rizka Miftahujjannah Rizka Ramadhana Romal Ijuddin Rosmawati Rosmawati Rosmawinda Rosmawinda Rosmawinda Rosmawinda Rosminazuin Ab Rahim Rosminazuin Ab Rahim Roy Budiharjo RoziqiFath, Zain Fuadi Muhammad Rusdha Muharar Rusmardiana, Ana Ruzdy, Nabilah Nameera saepudin, udin Safrizal Razali Safrizal Razali Saifullah Nur Muhammad Sakarkar, Gopal Saminan Sanjani, Fenti Sanny Nofrima, Sanny Nofrima Saputra, Nanda Sari*, Erika Lety Istikhomah Puspita Setiawan, Verdy Shaquille Rizki Ramadhan Na Silaban, Keysha Octarina Silaban, Pangeran O. J Simanjorang, Rican Siska, Emi Yulia Siti Rofiah, Siti Siti Rusdiana Siti Rusdiana Siti Rusdiana Siti Rusdiana Siti Rusdiana Siti Rusdiana Siti Rusdiana Siti Rusdiana Sitti Suhada Solissa, Ferdinando Souvik Das Souvik Das Sri Rahayu Ade Sugiatno . Suhara, Ade Sulastri Sulastri Suriadi Suriadi Suriati, Israini Suwandi Suwandi Suyanda, Arya Syahputra, Daniel Syahrial, Syahrial Syahrul Gazali Syahrul Gazali Syahrul Gazali Syahyadi, Rizal Syakir, Fakhrus Syarifah Rauzatul Jannah Syifa Anzella Syifa Anzella Tandi, Asrin Tariliani, Cut Dara Taufik Iskandar Taufiq Abdul Gani Teuku Muhammad Mirza Keumala Teuku Yuliar Arif Tulus Tulus Tulus Tulus Tulus Tulus Ugi Nugraha Ulul Azmi Umrah, Andi Sitti Victoria Ari Palma Akadiati W.K Wong W.K Wong Waani, Fonny J Wahyudianty, Melsa Ulfie Waladah, Bulen Waladah, Buleun Wardana, Surya Wawan Junresti Daya Winarningsih, Rahayu Arum Wong, W. K Wong, W.K Wong, W.K. Yatim, Hertasning Yenti, Riza Reni Yovhandra Ockta Yudesman, Fatriani Margareta Yudha Nurdin Yudha Nurdin Yulia, Prima Dwi Yuliati - Yunidar yunidar Yunidar Wahab Yunidar Yunidar Yunidar Yunidar Yunidar Yunidar Yunidar Yunidar Yunidar yunidar Yunidar Yunidar Yunidar Yunidar Yunidar Yunidar Yusup, Syafina Ainur Yuwaldi Away Yuwaldy Away Zahra, Viqqy Nur Zahran Jemi , Faris Zainal, Zulfan Zetira, Zetira Rizqia Erlin Zharifah Muthiah Zulfan Zainal Zulfan Zulfan Zulfikar Taqiuddin Zulhelmi . Zulhelmi, Zulhelmi Zulkifli Nasution Zulkifli Nasution