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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Jurnal Media Wahana Ekonomika PREDIKSI Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL MANAJEMEN BISNIS Jurnal Literasiologi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Tekno Kompak Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Jurnal Abdidas Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA Journal of Electrical Engineering and Computer (JEECOM) Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Silva Samalas: Journal of Forestry and Plant Science Jurnal Elkasista ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An Jurnal Ilmiah Pendidikan Dasar (JIPDAS) Journal of Engineering, Technology and Computing (JETCom) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Journal of Management, Economic and Accounting (JMEA) Insand Comtech : Information Science and Computer Technology Journal International Journal of Engineering Continuity Valid Jurnal Pengabdian Journal of Economics and Management Scienties Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN) Prosiding Seminar Nasional Unimus Prosiding Seminar Nasional CORISINDO Media Pendidikan Matematika

Hairani Hairani

Universitas Bumigora, Mataram, Indonesia

Author-ID : 2377224

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Prediction of Electricity Usage with Back-propagation Neural Network Anthony Anggrawan; Hairani Hairani; M. Ade Candra
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 1 No 1 (2022): March 2022
Publisher : Universitas Bumigora Mataram-Lombok

The use of electricity has become a need that is increasing day by day. So it is not surprising that the problem of using electricity has attracted the attention of many researchers to research it. Electricity users make various efforts and ways to save on the use of electrical energy. One of them is saving electricity usage by electricity users using electrical energy-efficient equipment. That is why the previous research confirms the need for interventions to reduce the use of electrical energy. Therefore, this study aims to predict electricity use and measure the performance of the anticipated results of electricity use. This study uses the back-propagation method in predicting the use of electricity. This study concluded that the backpropagation architectural model with better performance is the six hidden layer architecture, 0.4 learning rate, and the Root Means Square Error (RMSE) value of 0.203424. Meanwhile, the training data test results get the best architectural model on hidden layer 8 with a learning rate of 0.3 with an RMSE performance value of 0.035811. The prediction results show that the prediction of electricity consumption is close to the actual data of actual electricity consumption.

Web-Based Application for Toddler Nutrition Classification Using C4.5 Algorithm Hairani Hairani; Lilik Nurhayati; Muhammad Innuddin
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 1 No 2 (2022): September 2022
Publisher : Universitas Bumigora Mataram-Lombok

Health is something that is important for everyone, from year to year various efforts have been developed to get better and quality health. Good nutritional status for toddlers will contribute to their health and also the growth and development of toddlers. Fulfillment of nutrition in children under five years old (toddlers) is a factor that needs to be considered in maintaining health, because toddlerhood is a period of development that is vulnerable to nutritional problems. There are more than 100 toddler data registered at the Integrated Healthcare Center in Peresak Village, Narmada District, West Lombok Regency. The book contains data on toddlers along with the results of weighing which is carried out every month. However, to classify the nutritional status of toddlers, they are still going through the process of recording in a notebook by recording the measurement results and then looking at the reference table to determine their nutritional status. This method is still conventional or manual so it takes a long time to determine the nutritional status. Therefore, the solution in this study is to develop a web-based application for the classification of the nutritional status of children under five using the C4.5 method. The stages of this research consisted of problem analysis, collection of 197 instances of nutritional status datasets obtained from Integrated Healthcare Center Presak, analysis of system requirements, use case design, implementation using the C4.5 method, and performance testing based on accuracy, sensitivity, and specificity. The results of this study are a website-based application for the classification of the nutritional status of children under five using the C4.5 method. The performance of the C4.5 method in the classification of the nutritional status of toddlers using testing data as much as 20% gets an accuracy of 95%, sensitivity of 100%, and specificity of 66.6%. Thus, the C4.5 method can be used to classify the nutritional status of children under five, because it has a very good performance.

Underwear Rules for Preventing Sexual Violence Vina Vitniawati; Iis Sopiah Suryani suryani; Mia Nisrina Anbar Fatin; Novitasari Tsamrotul Fuadah; Hairani Hairani
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2023): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35568/abdimas.v6i1.3013

Child sexual violence is a phenomenon that requires joint attention because it affects all aspects such as the growth and development of children both physically, emotionally and psychologically so that it requires prevention efforts.program to teach how to provide sexual education for early childhood as an effort to prevent sexual violence in children.Madrasah Ibtidaiyah Permata Bangsa does not yet have a program andhave not received information about efforts to prevent child sexual violence including the Underwear Rules program. So it is necessary to increase knowledge about how to prevent sexual violence in children. The method in Community Service is health education about reproductive health and sexual violence. For the impact of sexual violence and its handling, it will be carried out through seminars involving psychologists which are carried out in a hybrid manner and methods of playing with children regarding underwear rules. Before and after implementation, pretest and posttest measurements were carried out to measure the understanding of teachers, parents and children regarding efforts to prevent sexual violence in children. Keywords: Community Service, Underwear Rules, Sexual Violence

Improvement Performance of the Random Forest Method on Unbalanced Diabetes Data Classification Using Smote-Tomek Link Hairani Hairani; Anthony Anggrawan; Dadang Priyanto
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1069

Most of the health data contained unbalanced data that affected the performance of the classification method. Unbalanced data causes the classification method to classify the majority data more and ignore the minority class. One of the health data that has unbalanced data is Pima Indian Diabetes. Diabetes is a deadly disease caused by the body's inability to produce enough insulin. Complications of diabetes can cause heart attacks and strokes. Early diagnosis of diabetes is needed to minimize the occurrence of more severe complications. In the diabetes dataset used, there is an imbalanced data between positive and negative diabetes classes. Diabetes negative class data (500 data) is more than diabetes positive class (268), so it can affect the performance of the classification method. Therefore, this study aims to apply the Smote-Tomeklink and Random Forest methods in the classification of diabetes. The research methodology used is the collection of diabetes data obtained from Kaggle, as many as 768 data with eight input attributes and 1 output attribute as a class, pre-processing data is used to balance the dataset with Smote-Tomeklink, classification using the random forest method, and performance evaluation based on accuracy, sensitivity, precision, and F1-score. Based on the tests conducted by dividing data using 10-fold cross-validation, the Random Forest algorithm with Smote-TomekLink gets the highest accuracy, sensitivity, precision, and F1-score compared to Random Forest with Smote. The Random Forest algorithm with Smote-Tomeklink has 86.4% accuracy, 88.2% sensitivity, 82.3% precision, and 85.1% F1-score. Thus, using Smote-Tomeklink can improve the performance of the random forest method based on accuracy, sensitivity, precision, and F1-score.

Pelatihan Implementasi Machine Learning pada Bidang Pendidikan Hairani Hairani
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 2 No 2 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v2i2.3046

Machine learning is a machine that can learn like humans. Machine learning (ML) technology was developed so that machines can learn by themselves without direction from the user. Machine learning consists of various disciplines such as statistics, mathematics and data mining so that machines can learn by analyzing data patterns without the need to be explicitly reprogrammed. Making machine learning applications is not easy because you have to have good understanding of methods and programming skills. Therefore, this service uses a solution to improve the abilities of the participants, namely a training approach by presenting material and demonstrating the use of machine learning in midwifery education. The activity was carried out on April 21 2021 online via the Zoom Meeting application with student participants. Based on the results of the material presentation session and hands-on practice using the Python programming language at Google Colab, it showed that the participants looked enthusiastic in following the material. Not only that, the participants know various machine learning methods and can apply them in completing a case study and building web applications with Flask tools.

SOSIALISASI INTERNET SEHAT, CERDAS, KREATIF DAN PRODUKTIF PADA MASYARAKAT KALIJAGA BARU Hairani Hairani; Muhammad Innuddin; Dedy Febry Rachman; Ahmad Fathoni; Samsul Hadi
Valid Jurnal Pengabdian Vol. 1 No. 3 (2023)
Publisher : Lembaga Pengembangan, Penelitian dan Pengabdian Kepada Masyarakat Sekolah Tinggi Ilmu Ekonomi AMM

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

Metode penelitian ini adalah metode deskriptif kualitatif. Teknik yang digunakan dalam pengumpulan data adalah teknik observasi, teknik wawancara, dan dokumentasi. Hasil penelitian ini menemukan dua masalah, antara lain belum memahami cara menggunakan dan memanfaatkan teknologi internet dengan baik dan benar. Kesimpulan dari penelitian ini adalah penggunaan dan pemanfaatan teknologi secara tepat, menimbulkan dampak positif dan mengurangi dampak negatif. Dengan mengetahui cara memanfaatkan teknologi internet secara baik dan benar akan mampu menjadikan masyarakat cerdas, kreatif, dan produktif. Tujuan cerdas, kreatif, dan produktif adalah agar masyarakat dapat mengembangkan dan menerapkan apa yang telah diperoleh dalam teknologi internet, yang diterapkan dalam kehidupan sehari-hari.

Combination of Smote and Random Forest Methods for Lung Cancer Classification Christopher Michael Lauw; Hairani Hairani; Ilham Saifuddin; Juvinal Ximenes Guterres; Muhammad Maariful Huda; Mayadi Mayadi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3333

Lung cancer is a network of cells that grow abnormally in the lungs. Lung cancer has four severity levels, namely stages 1 to 4. If lung cancer is not treated quickly, it is at risk of causing death. This research aimed to combine Synthetic Minority Over-sampling (Smote) and Random Forest methods for lung cancer classification. The method used was a combination of Smote and Random Forest. Smote was used to balance the data, while Random Forest was used to classify lung cancer data. The results showed that the combination of Smote and Random Forest methods obtained an accuracy of 94.1%, sensitivity of 94.5, and specificity of 93.7%. Meanwhile, without Smote, the accuracy is 89.1%, sensitivity is 55%, and specificity is 94.5%. The use of Smote can improve the performance of the Random Forest classification method based on accuracy and sensitivity. There was an increase of 5% in accuracy and a 39% increase in sensitivity.

Sentiment Analysis and Topic Modeling of Kitabisa Applications using Support Vector Machine (SVM) and Smote-Tomek Links Methods I Nyoman Switrayana; Diki Ashadi; Hairani Hairani; Afrig Aminuddin
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3406

Kitabisa is an Indonesian application that functions to raise funds online. Users can easily support various types of campaigns and donate funds to various social causes through the app. User reviews of the application are very diverse, and it is not sure whether user reviews of the application tend to be positive, neutral, or negative. This research aimed to analyze the sentiment of the Kitabisa application by modeling topics using Latent Dirichlet Allocation (LDA) and classifying user reviews using a Support Vector Machine (SVM). The scrapped dataset showed imbalanced dataset problems, so the SMOTE-Tomek Links oversampling technique was proposed. The results of this study show that using LDA produces five topics often discussed in 750 reviews. Then, the performance of SVM without using SMOTE-Tomek Links was 72% accuracy, 76% precision, 72% recall, and 64% f1 score. Meanwhile, using SMOTE-Tomek Links could significantly improve the performance, namely 98% accuracy, 98% precision, 98% recall, and 98% f1 score. Based on this research, the application of SVM achieved high performance for user sentiment classification, especially when the dataset was in a balanced state. Therefore, the SMOTE-Tomek Links oversampling technique is recommended for dealing with unbalanced sentiment datasets.

Optimalisasi Sumber Daya untuk Hidup Sehat dan Berdaya Wening Asih Sutrisno; Mamay Maulana; Muhamad Reza Pahlevi; Tri Nur Jayanti; Hairani Hairani
Warta Pengabdian Andalas Vol 30 No 4 (2023)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jwa.30.4.722-731.2023

Health problems are not only indicated by disease. Attention also needs to be given to people who are between healthy and sick with promotive and preventive efforts. The activity was carried out by optimizing existing resources through promotive and preventive efforts to increase community independence in health status. This community service activity was conducted in Sukabakti Village from 8 August to 21 September 2023. It included health screening, hypertension exercises, optimizing the Harum Madu program by planting medicinal and vegetable seeds, and health education about hypertension. Counselling was also given to students at SDN 2 Sukabakti about Clean and Healthy Living Behavior and students at SMP Plus Al-Kohar and Vocational School Insan Prima Mandiri about reproductive health. The results of the health examination screening showed that several participants had blood pressure >140/90 mmHg and blood sugar >140 mg/dL, they did hypertension exercises well, optimized the Harum Madu program by planting chilli and shallot seeds, and students had a better understanding of the counselling topics provided. It is hoped that the information presented during this activity can be applied to achieve optimal health.

Pembinaan Kelompok Istri & Kader Posyandu Sebagai Kader Toga Di Lingkungan Bendega Dalam Upaya Primary Health Care Saat Pandemi Covid-19 I Gusti Agung Ayu Hari Triandini; Hairani Hairani; Diana Hidayati; Widhya Aligita; Nur Intan Hayati; Soni Muhsinin; ED. Yunisa Mega Pasha
Prosiding Seminar Nasional Unimus Vol 4 (2021): Inovasi Riset dan Pengabdian Masyarakat Post Pandemi Covid-19 Menuju Indonesia Tangguh
Publisher : Universitas Muhammadiyah Semarang

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

Kementerian Kesehatan telah mencanangkan beberapa program terkait pengembangan kesehatantradisional melalui teknologi tanaman obat keluarga (TOGA) yaitu saintifikasi jamu, asuhan mandiri(selfcare), serta perawatan herbal dan terapi tradisional akupresur yang bertujuan untukmeningkatkan akses dan keterjangkauan masyarakat terhadap obat-obatan. Peran keluarga sebagaigarda terdepan dalam upaya PHC membuat ibu/istri sebagai sosok yang berperan penting dalamkesehatan keluarga yang diharapkan akan membawa perubahan ke komunitas kecil di sekitarnyadan perlahan diterapkan ke dalam komunitas yang lebih besar dan beragam. Kader Posyandu yangsehari-harinya berinteraksi dalam mendampingi ibu dalam membangun kesehatan keluarga jugamenjadi sosok yang berperan dalam program asuhan mandiri keluarga yang telah dicanangkanpemerintah. Lingkungan Bendega merupakan salah satu lingkungan yang ada di Kelurahan TanjungKarang Kecamatan Sekarbela, Kota Mataram Provinsi Nusa Tenggara Barat. Lingkungan tersebutmerupakan lingkungan binaan kesehatan ibu dan anak dari Universitas Bhakti Kencana PSDKUMataram, IBI Tanjung Karang dan Puskesmas Tanjung Karang. Sebelumnya, telah dilakukanpengabdian masyarakat dengan mengangkat sosialisasi pembuatan vertical garden TOGA dilingkungan tersebut. Selama ini belum ada program khusus tentang TOGA ataupun pembentukankader TOGA di lingkungan Bendega. Tujuan kegiatan pengabdian kepada masyarakat kali ini adalahuntuk melakukan perekrutan kader TOGA pada mitra, sosialisasi tupoksi kader serta meningkatkanpengetahuan dan keterampilan mitra dalam mengolah jenis TOGA yang secara ilmiah berfungsimencegah COVID-19. Metode pelaksanaan: persiapan, sosialisasi, evaluasi dan dokumentasi.Kegiatan dilaksanakan secara daring dan luring. Berdasarkan hasil yang diperoleh, didapatkanbahwa mitra telah mendapatkan peningkatan pengetahuan dan keterampilan tentang TOGA danpemanfaatannya. Selain itu, telah dibentuk organisasi Kader TOGA di lingkungan Bendega yangberfungsi mengembangkan TOGA di lingkungan Bendega. Kata kunci : Bendega, COVID-19, herbal, istri, kader, TOGA.

Co-Authors Abdillah, Mokhammad Nurkholis Abdurraghib Segaf Suweleh Abdurraghib Segaf Suweleh Abu Tholib Adam, M. Awaludin Afrig Aminuddin Ahmad Ahmad Ahmad Fathoni Ahmad Zuli Amrullah Aleeka Jasmine Amelia, Bengi Amin, Farda Milanda Andi Sofyan Anas Andi, Moh syaiful Andini, Nisha Anggarawan, Anthony Anthony Anggrawan Arfa, Muhammad Arifah Ulayya Ashadi, Diki Astuti, Ni Luh Budi Ayu Dasriani, Ni Gusti Candra, M. Ade Christine Eirene Christopher Michael Lauw Christopher Michael Lauw Dadang Priyanto Dedi Aprianto Dedy Febry Rachman Dedy Febry Rahman Deny Jollyta Dian Syafitri Diana Hidayati Diana Hidayati Didik Dwi Prasetya Diki Ashadi Dirgantara, Bhintang Donny Kurniawan Dyah Susilowati Dyah Susilowaty ED. Yunisa Mega Pasha ED. Yunisa Mega Pasha Eka Setiawan, Rian Putra Ezra Azzahra Fahry, Fahry Fatimatuzzahra Fatimatuzzahra Fitra Rizki Ramdhani Gede Yogi Pratama Gibran Satya Nugraha Gibran Satya Nugraha Gumangsari, Ni Made Gita Guntara, Muhammad Gusti Ayu Diah Gita Kartika Santi, I Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasbullah Hasbullah Herawati, Baiq Candra Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila Husnul Madihah I Gusti Agung Ayu Hari Triandini I Nyoman Switrayana Ida Putu Andika Ifnaldi Ifnaldi Iis Sopiah Suryani Ilham Saifuddin Indah Puji Lestari Indradewa, Rhian Isviyanti, Isviyanti Janhasmadja, Mengas Jauhari, M. Thonthowi Jupriadi, Jupriadi Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Kandisa, Amelia Kasiyanto Kasiyanto, Kasiyanto Khairan marzuki Khairil Ihsan Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lalu Zazuli Azhar Mardedi Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho M.Khaerul Ihsan Maariful Huda, Muhammad Malika, Riwayati Mamay Maulana Mamay Maulana Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Melati Rosanensi Mia Nisrina Anbar Fatin Michael Lauw, Christopher Miftahul Madani Muhamad Azwar Muhamad Azwar, Muhamad Muhamad Reza Pahlevi Muhamad Reza Pahlevi Muhammad Arfa Muhammad Fahmi Muhammad Innuddin Muhammad Maariful Huda Muhammad Ridho Akbar Muhammad Ridho Hansyah muhammad Syahbudi, muhammad Muhammad Zulfikri Muhammad Zulfikri Muhammad Zulkarnaen Haris Mujahid Mujahid Neny Sulistianingsih Noor Akhmad Setiawan Novitasari Tsamrotul Fuadah Nur Intan Hayati Nur Intan Hayati Nurhayati, Lilik Nurul Azmi Nurvianti, Nurvianti Nuzululnisa, Bq Nadila Pahrul Irfan Putu Tisna Putra Qososyi, Sayidina Ahmadal Rahman, Mochamad Farhan Caesar Rahmawati, Lela Rahmi, Agustina Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rangga Wijaya Rifqi Hammad Rio Riswanto Simanjuntak Riosatria, Riosatria Riwayati Malika Rizki Wahyudi RR. Ella Evrita Hestiandari Saifuddin Zuhri Saifuddin, Ilham Samsul Hadi Santoso, Heroe Shudiq, Wali Ja'far Soepriyanto, Harry Sofiansyah Fadli Soni Muhsinin Sri Farida Utami Sri Winarni Sofya Sri Winarni Sofya Sudi Prayitno Sukron, Moh Sutarman Sutarman Syahrir, Moch. tadianta m., Winardi aries Teguh Bharata Adji Tri Nur Jayanti Tri Nur Jayanti Triwijoyo, Bambang Krismono Triyanna Widiyaningtyas Umi Hanifah Utomo, Rokhim Vidiasari, Herlita Vidiasari, Viviana Herlita Vina Vitniawati Wahyuningsih, Rr. Sri Handari Wangiyana, I Gde Adi Suryawan Wening Asih Sutrisno Wening Asih Sutrisno Widhya Aligita Widhya Aligita Widiatmoko, Dekki Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Zilullah Nazir Hadi

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