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All Journal Inersia : Jurnal Teknik Sipil dan Arsitektur Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Semantik Journal of Education and Learning (EduLearn) Jurnal Pendidikan Fisika Indonesia Journal of Educational Science and Technology Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Jurnal Intelektualita: Keislaman, Sosial, dan Sains CESS (Journal of Computer Engineering, System and Science) Jurnal Pendidikan Fisika Jurnal Pendidikan Agama Islam Squalen Bulletin of Marine and Fisheries Postharvest and Biotechnology Journal of Natural Science and Integration Cetta: Jurnal Ilmu Pendidikan Technomedia Journal JURNAL PENDIDIKAN TAMBUSAI Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Aptisi Transactions on Management IQTISHADUNA: Jurnal Ekonomi dan Keuangan Islam Aptisi Transactions on Technopreneurship (ATT) CCIT (Creative Communication and Innovative Technology) Journal MANAZHIM SENSITEK ADI Journal on Recent Innovation (AJRI) Journal of Innovation and Future Technology (IFTECH) ICIT (Innovative Creative and Information Technology) Journal MARLIN : Marine and Fisheries Science Technology Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics JISA (Jurnal Informatika dan Sains) Jurnal Inovasi Pendidikan MH Thamrin Jurnal Abdimas Ilmiah Citra Bakti (JAICB) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Integrated Science Education Journal ENVIRONMENTAL OCCUPATIONAL HEALTH AND SAFETY JOURNAL Nusantara Hasana Journal ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Bima Journal : Business, Management and Accounting Journal Startupreneur Business Digital (SABDA Journal) Jurnal Teknik Industri Universal Raharja Community (URNITY Journal) Jurnal Ilmiah Pendidikan dan Keislaman Nanggroe: Journal Of Scholarly Service Jurnal Bintang Pendidikan Indonesia Indonesian Journal of Education Research (IJoER) Proceeding Mercu Buana Conference on Industrial Engineering El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Blockchain Frontier Technology (BFRONT) Jurnal Elementaria Edukasia International Transactions on Artificial Intelligence (ITALIC) Journal of Ekonomics, Finance, and Management Studies Jurnal Pendidikan MIPA Mathematics Education Journal Atom Indonesia IJIS Edu : Indonesian Journal of Integrated Science Education

Muhamad Yusup

Universitas Raharja

Author-ID : 2412078

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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PERUBAHAN BERAT BADAN SELAMA LOCKDOWN DI RUMAH COVID- 19 PENGARUH PADA VARIABEL PSIKOSOSIAL Yusuf, Maulana; Maulana, Sabda; Yusup, Muhamad
Universal Raharja Community (URNITY Journal) Vol. 2 No. 1 (2022): URNITY (Universal Raharja Community)
Publisher : UNIVERSITAS RAHARJA

Pengabdian pada masyarakat ini bertujuan untuk menilai hubungan antara perubahan berat badan individu dan gejala depresi, optimisme dan aktivitas fisik. Sebagian besar orang menyatakan bahwa berat badan mereka tidak berubah. Mulai dari anak muda, orang gemuk, hingga orang tua yang memiliki fluktuasi berat badan yang lebih besar. Dengan adanya strategi koping menemukan bahwa gejala depresi dikaitkan dengan perubahan berat badan yang lebih besar lagi. MVPA dan optimisme mengikuti tren penurunan berat badan sebesar 3 hingga 5 kg. Kepatuhan terhadap MVPA per menit/minggu dan rekomendasi aktivitas fisik berbanding terbalik dengan perubahan berat badan. Kesimpulan: Termasuk COVID19 mempengaruhi berat badan individu dan menyebabkan penurunan berat badan pada depresi obesitas. Optimisme dan aktivitas fisik tampaknya menjadi "elemen pelindung".

DESAIN DAN IMPLEMENTASI PEMBELAJARAN MEDIA INTERAKTIF MENGGUNAKAN CAMTASIA STUDIO: DESAIN DAN IMPLEMENTASI PEMBELAJARAN MEDIA INTERAKTIF MENGGUNAKAN CAMTASIA STUDIO Warsito, Ary Budi; Yusup, Muhamad; Purnomo, Yunianto
Universal Raharja Community (URNITY Journal) Vol. 2 No. 2 (2022): URNITY (Universal Raharja Community)
Publisher : UNIVERSITAS RAHARJA

Media pembelajaran mrupakan sesuatu yang dapat digunakan untuk mentransformasikan pesan dan/atau informasi dalam proses pembelajaran sehingga dapat memicu tanggapan atau perhatian dari minat siswa untuk belajar. Apabila media itu membawa pesan atau informasi dengan tujuan sebagai instruksional atau mengandung maksud pengajaran maka media itu dinamakan media pengajaran. Media memiliki fungsi untuk menjembatani informasi dari satu pihak dengan pihak yang lainnya. Dengan dikembangkannya media pembelajaran ini diharapkan dapat meningkatkan data tangkap dan rangsangan otak siswa untuk belajar lebih fokus pada pembelajaran yang diberikan oleh guru. Jurnal ini memberikan gambarakan bagaimana proses merancang sebuah pembelajaran interaktif menggunakan software Camtasia Studio yang banyak memiliki kelebihan dan kemudahan dalam membuat media pembelajaran interaktif.

Comparative Analysis of Machine Learning Methods in Predicting Diabetes Risk Based on Genetic Data Kusumaningrum, Sekar Ayu Wijaya; Soleh, Oleh; Yusup, Muhamad
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2486

Type 2 Diabetes Mellitus (T2DM) is a global chronic disease caused by the interaction of genetic and environmental factors. The use of genetic data offers great potential for early detection and personalized intervention. However, the complex analysis of genetic data requires sophisticated approaches like machine learning. This study aims to compare the performance of three machine learning algorithms Logistic Regression, Random Forest, and K-Nearest Neighbors (KNN) in predicting T2DM risk based on genetic data. By using a Systematic Literature Review of studies published between 2019 and 2024, the accuracy data from each algorithm was compared. The analysis results show that Random Forest has the best performance with an accuracy of 99.3%. This algorithm excels due to its ability to handle high-dimensional datasets and reduce overfitting. In comparison, KNN achieved an accuracy of 87% and Logistic Regression 82%. These findings support the integration of machine learning into early detection systems and more precise and efficient clinical decision-making for T2DM management.

Utilizing AI and Blockchain for Business Innovation in Digital Strategy Sunarya, Po Abas; Yusup, Muhamad; Fae, Nahlie
Technomedia Journal Vol 10 No 3 (2026): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/kwck2v12

In the rapidly evolving digital era, businesses are confronted with the challenge of adapting to fast paced technological changes. Innovative technologies such as Artificial Intelligence (AI) and Blockchain have emerged as solutions that can accelerate business transformation. AI offers data analytics and automation capabilities that enhance operational efficiency, while Blockchain provides the transparency and security required in digital business transactions. This study aims to explore how AI and Blockchain can be leveraged to drive innovation in business strategies and strengthen competitive advantage in an increasingly digital market. The research employs a literature review approach to examine the implementation of AI and Blockchain across various industrial sectors. For example, in the e-commerce sector, major companies such as Amazon and Alibaba have implemented AI to improve customer experience through more accurate product recommendations. Additionally, Blockchain has been utilized by Walmart to enhance supply chain transparency, enabling product traceability from suppliers to consumers. The collected data were analyzed to understand the impact of these technologies on business models and the innovations adopted by companies. The findings indicate that AI accelerates decision making processes and enables personalized customer services, while Blockchain helps establish a more transparent and efficient business ecosystem. Both technologies contribute to the development of stronger and more adaptive digital business models. The implementation of AI and Blockchain in business strategies has proven to enhance innovation, improve operational efficiency, and reinforce competitive advantage. Therefore, adopting these technologies becomes a key factor in achieving success in digitally driven businesses.

Isolation and Selection of Radiation Resistant Fungi from Mamuju High Natural Radiation Soil for Uranium and Thorium Bioremediation Robifahmi, N.; Laksmana, R. I.; Pratama, A. A.; Kusuma, A. T.; Tjiptosumirat, T.; Tuasikal, B. J.; Nugraha, E. D.; Rijal, M. S.; Febrian, V. A.; Yusup, M.; Futy, W.; Mujiyanto, A.; Sugoro, I.
Atom Indonesia Vol 52, No 1 (2026): APRIL 2026
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/aij.2026.1590

Microorganisms from high natural radiation environments hold potential as bioremediation agents for radioactive waste. In this study, isolation and selection of fungi from Mamuju high natural radiation soil was done for radioactive bioremediation. The methods included fungal isolation from soil samples, radiosensitivity tests, sensitivity tests to uranium and thorium, and absorption tests under gamma radiation (100 Gy hour-1). Results revealed three fungal isolates with high growth ratios and resistance to gamma radiation: Talaromyces flavus (A3), Gongronella butleri (A4), and Aspergillus sp. (F1). Isolates A3 and A4 survived up to 2 kGy, while F1 endured up to 8 kGy. At 24 hours, A3 absorbed uranium at 96% with a biomass of 0.73 g and thorium at 84% with 0.98 g biomass. A4 achieved the highest uranium absorption of 97% (biomass 4.11 g) and thorium absorption of 100% (biomass 0.74 g). F1 demonstrated 96% uranium absorption (biomass 1.29 g) and 87% thorium absorption (biomass 2.17 g). These isolates exhibited significant potential for bioremediation of uranium and thorium-contaminated environments, showing unique adaptations to high radiation conditions and effective radioactive metal uptake.

Implementation of Waste Management Policy in South Tangerang City from the Perspective of Environmental Law and the Effectiveness of Law Enforcement Yusup, Muhamad; Panjaitan, Paris; Sadikin, Mohamad; M, Mentari; Sitorus, Novandrik Yeriko; Suryani, N. Lilis
Nanggroe: Jurnal Pengabdian Cendikia Vol 5, No 1 (2026): April 2026
Publisher : Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19924220

Waste management in South Tangerang City has become an increasingly complex environmental issue along with population growth and urbanization. Although various regulations are already in place, such as Law Number 18 of 2008 and related regional regulations, the implementation of waste management policies still faces numerous challenges, including issues related to legal substance, law enforcement structure, and the legal culture of the community. This Community Service Program (PKM) aims to analyze the implementation of waste management policies from an environmental law perspective and to evaluate the effectiveness of law enforcement in South Tangerang City. The method used is a normative-empirical approach, with activities including seminars, interactive discussions, and workshops involving the community and stakeholders. The findings indicate a gap between preventive regulations and the reality in the field, which remains largely reactive. The main factors contributing to the low effectiveness of law enforcement include limited facilities and infrastructure, weak supervision, and low public awareness regarding waste management. Through this activity, it is expected that public understanding of the importance of environmentally based waste management will increase, along with greater active participation in preserving environmental sustainability. In addition, strengthening derivative regulations, optimizing law enforcement, and implementing technology-based and community-based waste management systems are necessary to achieve effective and sustainable waste management.

Predicting Supply Chain Risks Using Machine Learning for Resilient Operations Widayanti, Riya; Setiyowati, Harlis; Yusup, Muhamad; Rodriguez, Marta
ADI Journal on Recent Innovation (AJRI) Vol. 7 No. 2 (2026): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i2.1376

Rising supply chain disruptions highlight increasing vulnerabilities in global logistics networks caused by geopolitical conflicts, fluctuating demand, transportation failures, and environmental instability. These challenges reveal the limitations of conventional risk assessment approaches that rely heavily on manual analysis and historical data. Machine Learning (ML) offers a promising approach to enhance predictive intelligence and support more accurate decision making in complex supply chain environments. This study aims to develop and evaluate a Machine Learning based risk prediction model capable of identifying potential supply chain disruptions and enabling early detection of critical risk factors in global logistics operations. A quantitative experimental approach was employed using supply chain datasets integrated with disruption indicators from international logistics activities. The dataset consisted of more than 5,000 operational records collected between 2018 and 2024. Several machine learning algorithms were implemented and compared, including Random Forest, Gradient Boosting, and Support Vector Machines. Experimental results indicate that the Gradient Boosting algorithm achieved the highest predictive performance with an accuracy of 94.2%. The model successfully identified key determinants of supply chain risk, including demand variability, supplier reliability, and transportation delays. These findings confirm that machine learning based predictive models can enhance supply chain resilience by enabling early risk detection and supporting proactive decision making in global logistics operations.

Optimizing Graduate Competitiveness through Service with Mathematical Economics and OBE: Optimalisasi Daya Saing Lulusan melalui Pengabdian dengan Matematika Ekonomi dan OBE Muhamad Yusup; Sondang Visiana Sihotang; Meriyana Sunengsih; Lakshmi Devi; Po Abas Sunarya
ADI Pengabdian Kepada Masyarakat Vol 5 No 2 (2025): ADI Pengabdian Kepada Masyarakat
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/adimas.v5i2.1221

The Influence Branding of Social Media to Improve Digital Business in Training and Consulting on Instagram Ridwan Kurniaji; Nur Azizah; Muhamad Yusup
Startupreneur Business Digital (SABDA Journal) Vol. 3 No. 2 (2024): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v3i2.618

In the post-pandemic era, Indonesian entrepreneurs are competing fiercely to promote and sell their products, aiming to boost economic growth and busi- ness resilience. HSP Academy, a company specializing in occupational safety and health training and consulting, is leveraging this momentum by adopting social media-based marketing to reach wider audiences. Recognizing Insta- gram’s power as an accessible and popular platform, HSP Academy utilizes it to share information about its certified training programs, accredited by the Ministry of Manpower of Indonesia and the National Professional Certifica- tion Agency (BNSP). Instagram’s mobile-friendly interface allows prospective clients to easily access information on certified courses, which supports HSP Academy’s visibility and accessibility in the digital space. This article examines effective strategies for advancing business on social media, specifically focus- ing on Instagram as a key promotional tool. By analyzing the digital marketing techniques that resonate on this platform, the author explores methods for op- timizing engagement with potential clients. Topics include content strategies, engagement tactics, and promotional techniques tailored to the digital market- place. Through a focus on best practices for social media marketing, especially within a business like HSP Academy, this discussion aims to offer insights into enhancing business visibility and reach in today’s digital-driven market

Influence of Digital Technology & Data Analytics on Strategic Decision Making Asep Sutarman; Ronal Aprianto; Rendhika Adyatama; Krishna Chaitanya Pokkali; Muhamad Yusup
Startupreneur Business Digital (SABDA Journal) Vol. 4 No. 1 (2025): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v4i1.685

In an increasingly advanced information age, digital technology and data analytics have become important pillars in effective decision making across a wide range of sectors. This journal aims to explore how digital technologies, including big data, artificial intelligence (AI), and machine learning, can be utilized to improve decision quality. Through a case study approach, we analyze several organizations that have successfully implemented these technologies in their decision making processes. The results show that the use of advanced data analytics enables organizations to unearth previously unreachable insights, improving the accuracy and speed of decision making. However, the research also identified several challenges, including the need for high analytical skills, data privacy concerns, and resistance to change in organizational culture. We found that to maximize the benefits of digital technologies, organizations need to adopt the right training strategies and create an environment that supports innovation. This research makes an important contribution to the understanding of how digital technologies can change the way organizations make decisions, as well as practical recommendations for more effective implementation. The findings are expected to help organizational leaders and decision-makers formulate better strategies to face the challenges and opportunities of the digital age. This study uniquely contributes by examining the synergistic interaction between digital technology and data analytics in strategic decision-making across multiple sectors. This study contributes by identifying key factors that influence the effectiveness of digital technology and data analytics adoption in strategic decision making and offering practical recommendations for companies to enhance the adoption of these technologies.

Co-Authors A. Setiawan A. Suhandi Abdullah Arif Kamal Abidin Pasaribu, Abidin Achmad Samsudin Adam Faturahman Adhe Muhammad Rosyid Adi Rusdi Widya Adimayuda, Rizal Adnan, Haidar Bustomi Afifah, Rufnia Ayu Agung Lorenzo Agung Rizky Ahmad Alwi Nurudin Ahmad Asroni Ahmad Munawar Ahmad Yadi Fauzi Alessandro Daeli Garcia Alwiyah Alwiyah Amallia, Naila Amarto, Usman Amarulloh Amarulloh Amin Solihin, Amin Aminudin, Adam Hadiana Ana Nurmaliana Andrew Tirta Andri Saepudin Anggy Giri Prawiyogi Anita Bawaiqki Wandanaya Ankur Singh Bist Anwar, Aang Solahudin Anwar, Muhammad Rehan Apertha, Fanny Khairul Putri Apit Fathurohman Ari Asmawati Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito, Ary Budi Asep Sutarman Aspuri, Muhamad Astuti, Eka Dian Augury El Rayeb Aulia Edliyanti Aulianda Zahrina Fahreza Ayi Rakhmat Ramdani Azahrah, Tiara Azuddin, Muna Bachtiar Bachtiar Baiq Ratna Mulhimmah Bambang Triwibowo Basuki, Sucipto Bhupesh Rawat Bimastari, Inda Hasanah Binar Kurnia Prahani budiarty, frizca Ceria Marcelina Chandra, Ratna Dwi Costu, Bayram Damayanti, Fitria Siska Danny Manongga Dewi Listiani Sukamto Dewi, Yessica Chrisna Diah Aryani Diah Aryani Diah Aryani Diah Aryani, Diah Diego Abbas Dimas Prastama Julianto Eko Prasetiyani Eko Prasetiyani Eliando Erham Budi Wiranto Erlita Rasdiana Erni Astuti Erni Juliana Al Hasanah Nasution Euis Siti Nur Aisyah, Euis Siti Nur FACHROZI. F Fadilah, Jasmine Fae, Nahlie Faizin, Mohammad Noor Faradila, Alya Febrian, V. A. Fidrian Millen Prayogi Firmanul Catur Wibowo Fitria Siska damayanti Fratiwi, Nuzulira Janeusse Fredy Susanto Futy, W. Giandari Maulani, Giandari Hamdi Akhsan Hani Dewi Ariessanti Hani Dewi Arriesanti Haratua, Chandra Sagul Harianja, M Rokhati Haris - Harlis Setiyowati Hatami, Alifa Syauqi Henderi . Hera Novia Hidayatullah, Baeti Sarif I. Sugoro Ida Kaniawati Ifran Sanni Ika Lestari, Ika Ilamsyah - Ilamsyah Ilamsyah Ilamsyah Ilamsyah, Ilamsyah Irawan, Muhammad Zhudy Irenta Irwan Sembiring Irwandani Jaka Suwita John Edwards Kamal, ⁠Abdullah Arif Kelvin Siahaan Khairunnas, Siti Khoirul Rodzikin Kistiono Kistiono Kistiono Krisandi Aprilyanto Krishna Chaitanya Pokkali Kurniasari, Reni Oktavia Kurniasih Kurniasih Kurniawan, Rano Kusuma, A. T. Kusuma, Luqman Hafidz Kusumaningrum, Sekar Ayu Wijaya Lakshmi Devi Laksmana, R. I. Laurentius Andriyanto Lilik Agustin Listiyorini, Listiyorini M, Mentari Mahdayeni, Mahdayeni Mahmudulhasan Maimunah, Ira Mardiana Mardiana Mardiana Marviola Hardini Marzani, Marzani Masrifah, Masrifah Maulana Yusuf Maulana Yusuf Maulana, Sabda Meri Mayang Sari Meriyana Sunengsih Miftakhul Khasanah Millah, Shofiyul Moh. Iqbal Awi Makaram Mohamad Sadikin Mohamad Syarif Sumantri Muh. Salahuddin, Muh. Muhammad Faisal Muhammad Faris Ariq Muhammad Nurtanto Mujiyanto, A. N.Y. Rustaman Nadiya Nidhi Mehra Ninda Lutfiani Ninu Apriyani Nofia Supriyani Novmewi, Yusuf Nugraha, E. D. Nugroho Prihantoni Wibowo Nuke Puji Lestari Santoso Nur Azizah Nurbani, Siti Zachro Nurlaila Suci Rahayu Rais NURUL AZIZAH Oleh Soleh, Oleh Otniel Feliks Putra Wahyudi Padeli Padeli Panjaitan, Paris Pertiwi, Komala Dwi Po Abas Sunarya Pongky Arie Wijaya Pratama, A. A. Priyadi, Agung Purnomo, Yunianto Qurotul Aini Rafika, Ageng Setiani Rahman, Nor Farahwahidah Abdul Ramadhan, Rezki Ramadita, Salsabil Fardha Ramli, Ahmad Rani Lestari Rendhika Adyatama Reza Dani Pramudya Ridwan Kurniaji Rijal, M. S. Riswan Jaenudin Rivai Sungkowo Riya Widayanti Rizky Kurniawan Robifahmi, N. Rodriguez, Marta Romadi Romadi Ronal Aprianto Rosdiana Rosdiana Rosyifa Rosyifa Saepudin, Andri Sairi, Muhammad Salampessy, Randi B.S Sanurdi Sanurdi Sardianto Markos Siahaan Sari, Meri Mayang Sayuti, Mohammad Sekar Ayu Aryani Shalahuddin, Shalahuddin Shofiyul Millah Sinta Puspita Dewi Siti Fauziah Siti Rochmani Sitorus, Novandrik Yeriko Sondang Visiana Sihotang SRI RAHAYU Sri Wahyani, Sri Sri Yulianto Joko Prasetyo Sugiarto, Gerry Suhaepi, Muhamad Iip Suhendi Suhendi Sukmawati, Eva Supriyati . Supriyatman, Supriyatman Suratmi Suryani, N. Lilis Suryari Purnama Susan Oktaviani Susanto Rahardja Sutarto Wijono Syamsiar, Syamsiar Syamsul Arifin Syauqi Naufal, Romzi Takrim, Muhammad Taqwa Hariguna Taqwa Hariguna Tarisya Ramadhan Theopillus J. H. Wellem Tjiptosumirat, T. Tuasikal, B. J. Turki Salim Untung Rahardja Uzma, Wishnu Waston Wibowo, Shesilia Wijil Nugroho Yeni, Alfitri Yulia Putri Ayu Sanjaya Yulia Roma Ito Yuliani, Opie Oktavia Yulianto Yulianto Yulika Ayu Rantama Yunita Kartika Sari Yusuf Abdurachman Zebua, Selamat Zulkardi

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