Article Per Year (5 Year)
p-Index From 2021 - 2026
2.233
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer IJCIT (Indonesian Journal on Computer and Information Technology) IKRA-ITH Informatika : Jurnal Komputer dan Informatika JURNAL REKAYASA TEKNOLOGI INFORMASI Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Sains, Aplikasi, Komputasi dan Teknologi Informasi Journal of Computer Science and Engineering (JCSE) PLAKAT : Jurnal Pelayanan Kepada Masyarakat Buletin Poltanesa Buletin Ekonomika Pembangunan
Fahrul Agus
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences

Published : 30 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 30 Documents
Search

 1   2   3 
Rancang Bangun Radio Streaming Berbasis Android Rahmania Hatta, Heliza; Gusfiannur; Agus, Fahrul
Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan Vol. 6 No. 2 (2015): Oktober, 2015
Publisher : FT- UNDAR

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

Abstract

Secara konvensional radio merupakan sebuah teknologi yang digunakan untuk pengiriman sinyal informasi dengan cara modulasi dan radiasi gelombang elektromagnetik. Gelombang ini melintas dan merambat melalui udara. Dengan demikian radio konvensional memiliki keterbatasan dalam hal jangkauan penyiaran. Hal inilah yang mengawali perubahan teknologi radio agar dapat didengar di berbagai tempat secara langsung. Audio streaming merupakan solusi yang tepat untuk mengatasi keterbatasan ini. Melalui media streaming, sebuah radio dapat memperluas jangkauan siarannya dengan memanfaatkan kemudahan teknologi internet. Teknologi streaming mampu mengkompresi atau menyusutkan ukuran file sehingga dapat dengan mudah ditransfer melalui jaringan internet. Sehingga radio dapat memanfaatkan teknologi ini untuk mentransmisikan siarannya agar dapat didengar di seluruh jaringan internet di dunia. Tujuan penelitian ini adalah membangun server radio streaming dan klien radio streaming berbasis Android yang diharapkan dapat membantu member Tangan di Atas Samarinda untuk mengetahui berbagai ilmu tentang wirausaha. Selain itu juga untuk media promosi produk member Tangan di Atas Samarinda. Metode perancangan yang digunakan adalah menggunakan permodelan UML. Penelitian ini telah menghasilkan server radio streaming dan klien radio streaming berbasis Android. Aplikasi radio streaming “TDA Samaradio” berbasis Android ini diharapkan dapat menjadi media berbagi informasi yang dapat membantu member untuk lebih mengenal Tangan di Atas Samarinda
Comparison of Moora and Waspas Methods for Recommendations of Cayenne Pepper Seeds Wardani, Agus Tri; Hamdani, Hamdani; Agus, Fahrul
Journal of Computer Science and Engineering (JCSE) Vol 5, No 2: August (2024)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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

Abstract

Multiple Criteria Decision Making (MCDM) encompasses several methodologies, including MOORA and WASPAS. These strategies demonstrate unique approaches and produce varying results. The main aim of this work is to provide a comparative analysis of the MOORA and WASPAS procedures. To achieve this objective, we conduct a detailed analysis that specifically examines five parameters related to cayenne pepper seeds: prospective crop yields, optimal harvesting time, recommended conditions for highland cultivation, weight of 1000 seeds, and plant height. The study utilizes the sensitivity test approach in a comparative analysis framework to ascertain the superior method. The computations using both the MOORA and WASPAS methods determine that the Bisi Hp 35 (A3) alternative is the best choice. This alternative has a MOORA preference value of 0.1463, while the WASPAS approach gives it a preference value of 0.8374. Next, we perform a sensitivity test by increasing the weight criteria for each criterion by 0.5 and 1. The sensitivity analysis indicates that the MOORA approach has a level of 380, whereas the WASPAS method has a level of 376. The data suggest that the MOORA method is more effective than the WASPAS method when it comes to making recommendations for cayenne pepper seeds.
Expert System for Early Detection of High-Risk Pregnancy Conditions Using Certainty Factor and Forward Chaining Methods Agus, Fahrul; Vadlisky, Febria Dwi; Hamdani, Hamdani
Journal of Computer Science and Engineering (JCSE) Vol 6, No 1: February (2025)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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

Abstract

The maternal mortality rate is the proportion of deaths that occur during pregnancy due to disorders that specifically impact the uterus. Experts attribute the high number to a lack of knowledge and delays in its management. Samarinda, located in East Kalimantan, has the second highest mortality rate, following Kutai Kartanegara. Hence, the implementation of an early detection system is important to effectively address this issue. The objective of this study is to develop an expert system that utilizes the certainty factor technique to identify high-risk factors in pregnant women before delivery. This study identified three high-risk conditions in pregnant women: preeclampsia, gestational diabetes mellitus (GDM), and constipation. There are a total of 22 symptoms associated with each condition, and for each disease, there are three distinct treatment options available. An expert in the field of obstetrics and gynecology provided the research data. The research yields an expert system that demonstrates accuracy by comparing 10 test data sets from both human experts and computing systems. The system achieved a 90% accuracy rate. Through the use of an expert system methodology, we expect this system to be a valuable resource for pregnant women and healthcare professionals seeking early detection of high-risk diseases in pregnant women.
Peningkatan Kemampuan Analisis Statistik Kuantitatif Pada Riset Eksperimen Dengan Metode Workshop Agus, Fahrul; Putra, Gubtha Mahendra; Kamil, Zanu Alfandi; Arifin, Iswanto; Gifari, Okta Ihza
Plakat : Jurnal Pelayanan Kepada Masyarakat Vol 4, No 2 (2022): Volume 4, Nomor 2 Desember Tahun 2022
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/plakat.v4i2.8954

Abstract

Riset merupakan kegiatan akademik yang wajib dilakukan oleh mahasiswa tugas akhir di Program Studi Informatika, Fakultas Teknik Universitas Mulawarman, Samarinda Kalimantan Timur. Riset eksperimen memerlukan pengetahuan dan pemahaman yang kuat di bidang Statistik. Pelajaran Matematika dan Statistika termasuk materi yang sulit dipahami di kalangan mahasiswa di beberapa perguruan tinggi. Pelatihan atau workshop ini betujuan untuk melakukan penguatan kembali (recharging) serta peningkatan pengetahuan peserta tentang ilmu pengetahuan, konsep dan aplikasi Statistik Kuantitatif untuk riset eksperimen. Pelatihan dilakukan dengan cara pembelajaran secara langsung di dalam kelas. Monitoring pelatihan dilakukan dengan observasi selama kegiatan berlangsung, sedangkan evaluasi dilakukan melalui survey kepada peserta. Bobot penilaian oleh peserta terhadap materi, narasumber, fasilitas pelatihan dan peningkatan kemampuan diukur dengan Skala Likert. Pelatihan dilaksanakan dengan 38 peserta dan observasi monitoring menunjukkan dinamika peserta dan fasilitator yang aktif dan lancar. Hasil evaluasi kegiatan pelatihan menunjukkan materi, narasumber, fasilitas pelatihan dan peningkatan kemampuan telah memenuhi kebutuhan peserta dengan persentase rata-rata sebesar 99.7%. Evaluasi juga menunjukkan bahwa sebesar 64% peserta menyatakan peningkatan pengetahuan yang sangat tinggi, 31% menilai tinggi dan 5% menyatakan sedang. Students in the Department of Informatics at the Faculty of Engineering, Mulawarman University, Samarinda, East Kalimantan, are required to conduct research for their final project. Strong statistical expertise and understanding are necessary for conducting experimental research. Many universities' students report having trouble understanding math and statistics classes. The purpose of this training is to deepen and broaden participants' understanding of scientific principles and the uses of quantitative statistics in experimental research. Direct learning takes place during the training in the classroom. Evaluation of training is done through surveys given to participants, while monitoring is done by observing during the activity. A Likert Scale was used to gauge how seriously the participants took the content, resource people, training facilities, and capacity building. 38 people attended the training, and monitoring observations revealed the dynamics of fluent and active participants and facilitators. According to the findings of the evaluation of training activities, an average percentage of 99.7% of the participants' needs were met by the training materials, resource people, training facilities, and capacity building. Additionally, the evaluation revealed that 64% of participants rated the level of knowledge gain as very high, 31% as high, and 5% as moderate.
Analisis Kualitas Sarang Burung Walet Menggunakan Metode Fuzzy Tsukamoto Agus, Fahrul; Sulfika, Ega; Mahendra Putra, Gubtha
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 2: April 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025129441

Abstract

Indonesia menjadi salah satu negara yang menghasilkan dan mengekspor sarang burung walet terbesar di dunia. Sarang burung walet memiliki banyak sekali manfaat, itu sebabnya tren ekspor sarang burung walet meningkat. Kualitas yang baik dapat mempengaruhi daya saing produk, harga jual, manfaat kesehatan yang dihasilkan, serta kepuasan konsumen. Selama ini pembeli masih melakukan klasifikasi kualitas sarang burung walet secara manual berdasarkan perkiraan pembeli sehingga dapat menimbulkan kesalahan pada saat melakukan penyortiran dan menyebabkan kerugian sehingga menurunkan nilai jual. Logika fuzzy digunakan untuk mengantisipasi hal tersebut karena dapat memberikan toleransi terhadap suatu nilai sehingga perubahan kecil pada nilai tidak akan memberikan dampak yang signifikan. Tujuan penelitian ini menerapkan metode fuzzy tsukamoto untuk menganalisis kualitas sarang burung walet. Data yang digunakan sebanyak 100 data sarang burung walet yang diperoleh pada 16 Oktober 2023. Proses penentuan kualitas sarang burung walet berdasarkan 5 variabel kriteria input yaitu warna, bulu, jenis, kondisi, dan kadar air. Output fuzzy terdiri dari 3 kategori kualitas Sangat Bagus, Bagus, dan Tidak Bagus. Hasil perhitungan fuzzy tsukamoto dengan data aktual terdapat 3 data sarang burung walet berbeda dari 100 data sarang burung walet dengan memiliki nilai akurasi sebesar 97%.   Abstract   Indonesia is a leading global producer and exporter of the largest quantity of swallow's nests. Swallow's nest consumption offers numerous advantages, which explains the growing trend of exporting this valuable commodity. The quality of a product can have a significant impact on its competitiveness, selling price, health benefits, and consumer happiness. Currently, buyers continue to manually assess the quality of swallow nests, relying on their estimations. However, this method is prone to errors throughout the sorting process and can result in financial losses that diminish the overall sales value. We employ fuzzy logic for prediction purposes because it allows for tolerance towards a value, thereby minimising the influence of minor fluctuations in the value. The goal of this study is to use the Tsukamoto fuzzy method to evaluate the quality of swallow nests. The dataset consisted of 100 samples of swallow nests collected on October 16, 2023. The evaluation of swallow nests' quality relies on five input criteria variables, specifically colour, feathers, type, condition, and water content. The fuzzy output comprises three quality categories: very good, sound, and not good. The fuzzy Tsukamoto calculation yielded three distinct samples out of a total of 100, with an accuracy rate of 97%.
Implementasi Metode Naïve Bayes dan Forward Chaining Untuk Diagnosis Penyakit Gangguan Bipolar Puspitasari, Novianti; Agus, Fahrul; Zali, Wahyu Noor
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 8, No 2 (2023): IJCIT November 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcit.v8i2.17015

Abstract

Bipolar disorder merupakan salah satu gangguan suasana perasaan (mood afektif) yang menunjukan suasana perasaan pasien, dimana tingkat aktivitasnya jelas terganggu. Gangguan ini pada waktu tertentu terdiri dari peninggian maupun penurunan suasana perasaan serta peningkatan maupun pengurangan energi dan aktivitas. Kurangnya pengetahuan masyarakat mengenai pemahaman tentang gangguan kesehatan mental bipolar disorder yang gejalanya hampir sama dengan perubahan mood pada manusia normal, menyebabkan telatnya penanganan terhadap pasien. Penelitian ini bertujuan untuk membuat suatu sistem pakar untuk mendiagnosa penyakit bipolar disorder. Sistem pakar yang dibuat menerapkan metode forward chaining dan naïve bayes dalam mendiagnosa jenis penyakit bipolar disorder. Penelitian ini menggunakan 26 gejala dan tiga jenis penyakit yaitu bipolar disorder episode mania, bipolar disorder episode depresi dan bipolar disorder episode campuran. Penelitian ini menghasilkan sistem pakar yang dapat membantu masyarakat umum dalam mendiagnosa jenis penyakit bipolar disorder yang diderita serta solusi dan penanganannya. Sehingga masyarakat dapat mengetahui apakah terkena penyakit bipolar disorder tersebut atau tidak. Berdasarkan hasil pengujian Black Box diperoleh tingkat akurasi 100% dan sistem pakar yang dibuat dapat berjalan dengan baik. Bipolar disorder is a mood disorder (affective mood) that shows the patient's mood, in which the level of activity is clearly disturbed. These disturbances at any given time consist of either elevated or decreased mood and increased or decreased energy and activity. The lack of public knowledge regarding the understanding of mental health disorder bipolar disorder, whose symptoms are almost the same as changes in mood in normal humans, causes delays in treating patients. This research aims to create an expert system to diagnose bipolar disorder. The expert system created applies forward chaining and naïve Bayes methods in diagnosing bipolar disorder. This study used 26 symptoms and three types of illness, namely bipolar disorder manic episode, bipolar disorder depressive episode, and mixed episode bipolar disorder. This research produces an expert system that can help the general public in diagnosing the type of bipolar disorder they are suffering from as well as solutions and treatment. So that people can find out whether they have bipolar disorder or not. Based on the results of Black Box testing, an accuracy rate of 100% was obtained and the expert system created could run well.
Sistem Pendukung Keputusan Pemilihan Objek Wisata Kabupaten Berau Menggunakan Metode Additive Ration Assessment (ARAS) Lengkong, Mira S.; Dengen, Nataniel; Agus, Fahrul
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 9 No. 1 (2025): IKRAITH-INFORMATIKA Vol 9 No 1 Maret 2025
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v9i1.4382

Abstract

Indonesia is a country that is famous for its natural wealth and tourist destinations worldwide, and it is spread out in various regions. One of the regions in East Kalimantan that is popular and often visited by tourists every year because it is famous for its stunning underwater tourist destinations is the Berau Regency. According to the East Kalimantan Tourism Office, this district has the highest number of tourist attractions in East Kalimantan, which is 224. Many tourist attractions trigger confusion among tourists when deciding which alternative option to visit. Therefore, this research aims to build a decision support system to assist tourists in getting alternative tourism recommendations that are appropriate and to their needs. The method used in this research is the Additive Ratio Assessment (ARAS) method. There are 30 alternative attractions and 5 criteria: facilities, safety, cleanliness, cost, and distance. The results show that the ARAS method can recommend the best alternative to tourist attractions. The accuracy testing results using the confusion matrix method get a percentage value of 80%.
Air Pollution Assessment of Samarinda Using the C4.5 Algorithm Prafanto, Anton; Astuti, Indah Fitri; Salamah, Ummi; Agus, Fahrul; Kridalaksana, Awang Harsa; Kamila, Vina Zahrotun
Poltanesa Vol 24 No 2 (2023): December 2023
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v24i2.2946

Abstract

The degradation of air quality in numerous Indonesian cities is attributed to the swift proliferation of motorised vehicles, rapid population growth, and inadequate green spaces. Samarinda, the capital of East Kalimantan province, is plagued by high levels of pollution resulting from heavy vehicle exhaust emissions. The provision of accurate air quality information can mitigate respiratory issues. However, the public does not have access to air quality information due to the high cost of air quality measuring devices. Therefore, an Internet of Things (IoT)-based air pollution monitoring system using ESP32 is needed to provide interactive and real-time information. This study tested the C4.5 algorithm to classify air quality data based on six measurement parameters: PM10, PM2.5, CO, O3, and NO2. PM10 and PM2.5 particles are the primary pollutants that significantly impact human health. The World Health Organization (WHO) has set an annual quality standard value of 20μg/m3 for PM10 and 10μg/m3 for PM2.5. Carbon Monoxide (CO) can reduce the blood's ability to carry oxygen, which can affect the function of vital organs such as the heart and brain. Ozone (O3) on the Earth's surface is a harmful pollutant that can damage the lungs and other respiratory systems. Nitrogen dioxide (NO2) can cause lung inflammation and lower immunity to infections, such as influenza and pneumonia. This study uses the C4.5 algorithm to classify air quality data based on these parameters, which are important for determining air quality. The results show that air quality is divided into two types: good and moderate, with different proportions each day. The C4.5 algorithm achieved a success rate of 99.5074% and a failure rate of 0.4926% when processing air quality data. It was effective in classifying air quality and processing data. An Internet of Things (IoT)-based air pollution monitoring system using ESP32 is needed to provide interactive and real-time information to the public.
Analisis Tren Indikator Pendidikan dan Pengeluaran per-Kapita Kalimantan Timur 2020-2025 Rahmatullah, Muhammad Nabil; Pangestu, Jovan Bagas; Mayasha, Alya; Natasya, Aulia; Sofwani, Sifwah Fatin; Fachrodhiya, Muhammad Riva; Rajiansyah, Rajiansyah; Agus, Fahrul
Buletin Ekonomika Pembangunan Vol 7, No 1 (2026): FEBRUARY
Publisher : Jurusan Ilmu Ekonomi Fakultas Ekonomi Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/bep.v7i1.32922

Abstract

Human development and economic welfare are the two main pillars in the progress of a region. This study aims to analyze trends in education indicators, including Expected Length of School (HLS) and Average School Length (RLS), as well as their relationship with Per Capita Expenditure in East Kalimantan Province for the period 2020-2025. This topic was raised because there is a consistent gap between expectations and realization of education that can affect economic productivity. The novelty of this study lies in the use of recent time-series data covering the post-2020 recovery period, providing strong  evidence for policymakers. This research method uses a quantitative descriptive approach and simple linear regression analysis with data sources from the Central Statistics Agency (BPS) of East Kalimantan. The results of the study showed a significant positive trend, where RLS grew by 3.38% and Per Capita Expenditure grew by 21.54% during the observation period. The main findings show a very strong correlation (r=0.989) between education and the economy, where the regression model estimates that every 1-year increase in average school length is associated with an increase in per capita expenditure of Rp7.94 million. In conclusion, the acceleration of education realization has direct implications for increasing people's purchasing power. Therefore, the strategy of accelerating compulsory learning is crucial to boost the regional economy. Keywords: Education Indicators; Development Economics; Human Capital;      Expenditure per Capita; East Kalimantan 
The Effect of Expected Years of Schooling and Adjusted Expenditure per Capita on Life Expectancy in East Kalimantan Province (2022- 2024) Rifa'i, Muhammad Dzaki; Togatorop, Santoso Parlindungan; Fahmi, Muhammad Ilma Yusrian; Ramadhani, Inayah; Hasan, Andi Nurfadillah; Rajiansyah, Rajiansyah; Agus, Fahrul
Buletin Ekonomika Pembangunan Vol 7, No 1 (2026): FEBRUARY
Publisher : Jurusan Ilmu Ekonomi Fakultas Ekonomi Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/bep.v7i1.32952

Abstract

This study examines the impact of Expected Years of Schooling (EYS) and Adjusted Expenditure per Capita (AEPC) on Life Expectancy (LE) in 10 regencies and cities in East Kalimantan Province during 2022–2024 (BPS East Kalimantan Province, 2024). This topic is relevant because East Kalimantan exhibits strong economic performance yet continues to face disparities in human development across regions. At the same time, empirical studies that directly link education and household purchasing power to life expectancy at the district and municipal level in this province remain limited (Susanti Hidayat, 2020; Williyan Hasmarini, 2024). The novelty of this study lies in the use of recent panel data for 10 regencies and cities that simultaneously incorporate AEPC and EYS as determinants of LE, thereby providing more context-specific empirical evidence for East Kalimantan (Hasanah et al., 2021; Swastika Arifin, 2023). The study employs secondary data sourced from BPS East Kalimantan Province, comprising EYS, AEPC, and LE for 2022–2024, which are analysed using panel data regression, specifically the Common Effect Model (CEM). The model's validity is assessed using statistical tests, namely the t-test, the F-test, and the coefficient of determination (Statistics Indonesia, 2024; BPS East Kalimantan Province, 2024). The estimation results indicate a positive and statistically significant relationship between EYS and AEPC, and an increase in LE, while these two variables jointly explain approximately 71–73% of the variation in LE across regencies and cities (Hasanah et al., 2021; Meilinna et al., 2024). These findings suggest that expanding access to and improving the quality of education, alongside strengthening household economic capacity, are crucial prerequisites for improving health status and overall quality of life in East Kalimantan (Sari Syechalad, 2022; Swastika Arifin, 2023). Keywords: Life Expectancy (LE), Expected Years of Schooling (EYS), Adjusted                   Expenditure per Capita (AEPC), Panel data, Multiple linear regression. 
Co-Authors A., Amelia Alfirama, Dandhi Noufal Arifin, Iswanto AW., Sawung Awang Harsa Kridalaksana Dedy Cahyadi Dedy Fuadi, Dedy Dyna Marisa Khairina Fachrodhiya, Muhammad Riva Fahmi, Muhammad Ilma Yusrian Gifari, Okta Ihza Gusfiannur Hamdani . Hamdani Hamdani Hasan, Andi Nurfadillah Haviluddin Haviluddin Heliza Rahmania Hatta, Heliza Rahmania Hendra Saputra Indah Fitri Astuti, Indah Fitri Ismail Ismail Jimi, Jimi Kamil, Zanu Alfandi Kamila, Vina Zahrotun kusnandar kusnandar Lengkong, Mira S. Mahendra Putra, Gubtha Mahfud Iman Mayasha, Alya Muhamad Azhari Nasution, Ali Napiah Nasution, Annio Indah Lestari Nataniel Dengen Natasya, Aulia Pangestu, Jovan Bagas Prafanto, Anton Puspitasari, Novianti Putra, Gubtha Mahendra Rahmania Hatta, Heliza Rahmatullah, Muhammad Nabil Rajiansyah, Rajiansyah Ramadhani, Inayah Ramadiani - Rifa'i, Muhammad Dzaki Rosmasari Rosmasari, Rosmasari S., Wardana Salamah, Ummi Septya Maharani, Septya Sofwani, Sifwah Fatin Sulfika, Ega Taruk, Medi Togatorop, Santoso Parlindungan Vadlisky, Febria Dwi Wardani, Agus Tri Wiwik Anisiyah Yona Widya Sabrina Suprihatini Yunizar Fahmi Badron, Yunizar Fahmi Zali, Wahyu Noor