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All Journal Biospecies Edu-Sains: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Jurnal Natur Indonesia AL KAUNIYAH SPEKTRUM INDUSTRI TEKMAPRO Journal of Industrial Engineering and Management Inspiratif Pendidikan Edukasi: Jurnal Pendidikan dan Pengajaran OPERATION EXCELLENCE: Journal of Applied Industrial Engineering PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Jurnal Penelitian Pendidikan IPA (JPPIPA) JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri Metode : Jurnal Teknik Industri Jurnal Biologi Tropis Tibuana : Journal of Applied Industrial Engineering Martabe : Jurnal Pengabdian Kepada Masyarakat BIOEDUSAINS: Jurnal Pendidikan Biologi dan Sains Jurnal Iktiologi Indonesia (Indonesian Journal of Ichthyology) Industri Inovatif : Jurnal Teknik Industri Matrik : Jurnal Manajemen dan Teknik Industri Produksi Dedikasi: Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Indonesian Journal of Law and Economics Review Jurnal Filsafat Indonesia Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering Indonesian Journal of Innovation Studies BIOMA : Jurnal Biologi dan Pembelajarannya Jurnal Literasi Pendidikan Fisika (JLPF) Jurnal Pengabdian Masyarakat Akademisi PELS (Procedia of Engineering and Life Science) Jurnal Teknologi dan Manajemen Industri Terapan Takuana: Jurnal Pendidikan, Sains, dan Humaniora Jurnal Karya Abdi Masyarakat Journal of Fish Health MIMBAR INTEGRITAS Jurnal Pengabdian Masyarakat Pinang Masak Innovative Technologica: Methodical Research Journal Physical Sciences, Life Science and Engineering Journal for Technology and Science Biodik: Jurnal Ilmiah Pendidikan Biologi Jurnal Natur Indonesia IJOT Widya Teknik Academia Open Biodiversitas Journal of Biological Diversity International Journal of Economic Integration and Regional Competitiveness
Tedjo Sukmono
Program Studi Teknik Industri Universitas Muhammadiyah Sidoarjo
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Genetic Diversity of Mahseer (Tor spp.) in Jambi: A DNA Barcoding Approach for Conservation Nazifa, Boti Iffa; Sulistiono; Mashar, Ali; Sukmono, Tedjo
Al-Kauniyah: Jurnal Biologi Vol. 19 No. 1 (2026): AL-KAUNIYAH JURNAL BIOLOGI
Publisher : Department of Biology, Faculty of Science and Technology, Syarif Hidayatullah State Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/kauniyah.v19i1.46562

Abstract

Genetic-based management is a critical approach to maintain the sustainability of mahseer fish (Tor tambra and T. tambroides), which are facing threats from habitat degradation and overfishing in Jambi Province. This study aims to analyze the genetic diversity and population structure of mahseer using the COI gene markers. A total of 18 specimens were collected from six locations in the Jambi rivers (June-August 2024). DNA sequencing results showed 98.51–99.85% similarity to the references T. tambra and T. tambroides in GenBank. Phylogenetic analysis confirmed the grouping of this species, with a bootstrap value of 100% and closeness to the species Barbonymus gonionotus and Hampala macrolepidota. There were 11 haplotypes with the highest diversity at stations 3 and 6 (Hd= 0.90000), while moderate genetic differentiation (Fst= 0.109–0.141) was found between station 2 and other locations, indicating isolation due to habitat fragmentation. Water quality parameters (dissolved oxygen 6.3–7.1 mg/L, pH 7.0–7.3, current velocity 0.2–0.4 m/s) support habitat suitability, but anthropogenic activities potentially threaten genetic connectivity. These findings underscore the need for genetic data-driven conservation strategies, such as restocking of highly diverse populations and protection of critical habitats. Further research is needed to monitor long-term genetic dynamics.
Optimalisasi Preventive Maintenance Ground Power Unit pada Perawatan Pesawat Udara di PT. IAA AMO Menggunakan Metode FMEA Kurniawan, Sandi; Apriliana Sari Wulandari, Indah; Sukmono, Tedjo
JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Vol. 8 No. 1 (2024): October
Publisher : Industrial Engineering, Engineering of Faculty, Universitas Kadiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/jatiunik.v8i1.5535

Abstract

High operational costs and downtime risks can affect industry efficiency making equipment maintenance optimization an urgent need. PT. IAA AMO, as a manufacturing industry in the field of aircraft maintenance, faces significant challenges with the low reliability of Ground Power Unit (GPU) engines which only reaches 86%. This has led to an increase in the company's operating costs. The purpose of this study is to optimize Preventive maintenance on the Ground Power Unit (GPU) in aircraft maintenance at PT. IAA AMO using the Failure Mode and Effect Analysis (FMEA) method. The results show that the MTTF of the GPU is 311 hours, while the MTBF is 373 hours. To prevent  sudden breakdowns, preventive maintenance is recommended every 311 hours for non-repairable components  and 373 hours for repairable components. This research offers a more effective maintenance strategy to improve GPU reliability and lower operational costs. This research results in more effective maintenance planning, which not only minimizes downtime and operational costs, but also improves the overall reliability of the GPU machine. With the implementation of FMEA methods and  the right preventive maintenance  strategy, companies can anticipate breakdowns early, extend engine life, and ensure smooth operations in support of aircraft maintenance.
Prediksi Waktu Kerusakan Mesin Batching plant Menggunakan Metode Support Vector Machine untuk Meningkatkan Efisiensi Operasional Rany Riyantati, Dena; Sukmono, Tedjo
JATI UNIK : Jurnal Ilmiah Teknik dan Manajemen Industri Vol. 8 No. 1 (2024): October
Publisher : Industrial Engineering, Engineering of Faculty, Universitas Kadiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/jatiunik.v8i1.5543

Abstract

The increasing need for productivity and the use of high technology in the form of machines increases the need for maintenance functions. At PT. XYZ, which produces ready mix concrete  , has problems with the production machine with excess machine load. This results in downtime and delays in the production process, resulting in a decrease in machine operational productivity. The purpose of this study is to predict the time of damage to the engine, so that it can determine the right engine maintenance schedule periodically. In this research, the method used is Support Vector Machine which is implemented to python. This prediction is carried out to improve the efficiency and performance of the machine by predicting damage or failure that may occur in the future. Where this SVM can accurately predict breakdowns and proactively optimize maintenance schedules at the right time. This allows companies to improve efficiency in their operational systems, extend the life of machines, and reduce maintenance costs.
WORKSHOP DAN TRAINING PENGGUNAAN MODEL PEMBELAJARAN KOLABORATIF-KREATIF SERTA MODEL PROJECT BASED LEARNING BERBANTUAN MULTIMEDIA INTERAKTIF DENGAN SISTEM BLENDED LEARNING BAGI GURU-GURU IPA SMP KABUPATEN BATANG HARI JAMBI Zurweni, Zurweni; Haryadi, Bambang; Hamidah, Afreni; Sukmono, Tedjo; Mardhotillah, Bunga; Suzanti, Sriliah
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2024): Volume 5 No. 4 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i4.31190

Abstract

Guru sebagai pendidik yang menyelenggarakan proses pembelajaran di kelas, ditantang untuk mampu membelajarkan siswanya menjadi peserta didik yang kreatif dan inovatif sesuai tuntutan Era Global dimasa Industri 4.0 dan Society 5.0. Hal ini bisa terwujud, apabila guru-guru yang mendidik siswa tersebut mampu berkinerja kreatif dan inovatif terlebih dahulu dalam tugasnya sebagai pendidik. Kinerja ini juga harus didukung oleh lingkungan sekolah dan komunitas sesame bidang studinya masing-masing berbasis learning school.Program Merdeka Belajar Guru Penggerak. adalah program kebijakan Menteri Pendidikan, Kebudayaan, Riset dan Teknologi yang merancang bahwa Guru Penggerak ini diharapkan bisa menggerakkan kemerdekaan belajar siswa, dengan adanya kemerdekaan siswa belajar akan terjadi transformasi yang cukup potensial dalam pendidikan sekolah sehingga lebih berkualitas dalam tatanan etika pendidikan yang berkarakter baik. Pada kesempatan ini sekolah yang menjadi perhatian Tim Pengabdian ini adalah komunitas profesional MGMP Sains IPA SMP di Kabupaten Batang Hari Provinsi Jambi. MGMP Sains IPA SMP ini merupakan organisasi prosesi Guru yang anggotanya adalah seluruh Guru-guru IPA SMP di Kabupaten Batang Hari sebanyak 29 SMP. Sekretariatnya berjarak sekitar 56 km dari Kampus Universitas Jambi Mendalo. Pembaharuan atau inovasi kinerja yang secara kontinu harus dilaksanakan guru adalah dalam hal persiapan serta penggunaan perangkat pembelajaran yang selalu terbarukan, termasuk memvariasikan penggunaan Model-Model Pembelajaran di Kelas masing-masing. Guru-guru IPA di SMP se Kabupaten Batang Hari sebagian besar masih membutuhkan penyegaran dan pengayaan keterampilan berupa kompetensi pengayaan dalam memvariasikan dan merancang kinerja inovatif guru yang relevan dengan Merdeka Belajar Guru Penggerak. dan sejalan dengan tuntutan pembelajaran abad 21 dan sudah berada di Era Revolusi 4.0 dan Society 5.0 sekarang ini. Selanjutnya dalam rangka pengembangan kompetensi dan skills guru IPA SMP ini dalam hal merancang pembelajaran berbasis blended learning menggunakan model pembelajaran komtemprer, maka guru masih membutuhkan pendampingan maupun pelatihan singkat sehubungan dengan penyusunan Rencana Pembelajaranya. Sebagian besar guru IPA belum menguasainya. Tim PPM membekali Guru-guru melalui Learning Community MGMP Sains IPA SMP dalam memahami serta mengimplementasikan Model Pembelajaran Kolaboratif-Kreatif yang sudah memiliki Sertifikat Hak Cipta, dikembangkan oleh Zurweni dkk. Dan Model Project Based Learning atau Model PjBL oleh Boss & Larmer. Kedua Model Pembelajaran ini dapat membelajarkan learners dengan tantangan kemampuan berpikir tinggi atau High Order Thinking Skills. Metode pengabdian adalah workshop pembelakalan materi dan training. Luaran yang menjadi hasil pengabdian ini adalah Guru-guru IPA SMP Batang Hari memperoleh pengayaan pengetahuan dan keterampilan tentang penyusunan MODUL AJAR dengan Model Pembelajaran Kolaboratif-Kreatif berbantuan Multimedia Interaktif dan Model PjBL sebagai variasi pemanfatan model pembelajaran yang mendukung terpenuhinya tuntutan pembelajaran abad 21 di era global.
Sand Supplier Selection Analysis Based on the Integration of Analytical Hierarchy Process (AHP) and Taguchi Quality Loss Function Methods: Analisa Pemilihan Supplier Pasir Berdasarkan Integrasi Metode Analytical Hierarchy Process (AHP) dan Taguchi Quality Loss Function Sofillauny, Zahara; Wahyuni, Hana Catur; Sukmono, Tedjo; Putra, Boy Isma
Indonesian Journal of Innovation Studies Vol. 21 (2023): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v21i.1043

Abstract

Supplier selection process is a step to evaluate and select the most suitable supplier to see the needs of the company or organization. This evaluation is important to ensure that the selected supplier is able to provide quality products or services, competitive prices, timely delivery, and meet ethical and sustainability standards. This research uses two methods, namely Analytical Hierarchy Process (AHP) and Taguchi Loss Function. AHP is used to calculate the weight of criteria, while the Taguchi Loss Function is used to estimate losses caused by suppliers. The criteria applied in supplier evaluation are quality criteria, product accuracy, delivery, price, warranty policy, and response to claims. The results obtained from this study PT. Bumi Makmur with a percentage loss of 21%, while the supplier that has the largest loss value is PT. Mergo Bopo with a percentage of 47%. Highlights : Integration of AHP and Taguchi Loss Function enhances supplier selection accuracy. Identified supplier exhibits substantial loss percentage, emphasizing the importance of thorough evaluation. Findings enable informed decision-making, facilitating risk mitigation and operational optimization Keywords :Supplier Evaluation; Sand; Analytical Hierarchy Process, Taguchi Loss Function
Fusing SVR with PSO Improves E-commerce Sales Prediction with 8.98% MAPE: Penggabungan SVR dengan PSO Meningkatkan Prediksi Penjualan E-commerce dengan MAPE 8,98% Angela, Fitrah Cornellya; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 2 (2024): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i2.1127

Abstract

This study explores the integration of Support Vector Regression (SVR) with Particle Swarm Optimization (PSO) to forecast clothing product sales at Nara Gallery Collection Boutique, addressing the challenge of achieving high forecast accuracy in e-commerce. Through literature review, direct observation, and interviews with a textile SME owner, SVR parameters are optimized using PSO. Results indicate a Mean Absolute Percentage Error (MAPE) value of 8.98% with optimized parameters (C = 34.3642, ε = 0.0110, σ = 0.3677, cLR = 0.1062, λ = 0.0117), enhancing decision-making in inventory management and strategic planning for e-commerce businesses. This research highlights the potential of integrating SVR with PSO for accurate sales forecasting and suggests avenues for further exploration in alternative forecasting methods and optimization techniques. Highlight: Enhanced Forecasting Accuracy: SVR and PSO integration improves e-commerce sales predictions. Parameter Optimization: PSO optimizes SVR parameters, reducing Mean Absolute Percentage Error. Strategic Inventory Management: Accurate forecasts aid in effective e-commerce inventory control. Keywoard: Support Vector Regression, Particle Swarm Optimization, Sales Forecasting, E-commerce, Inventory Management
Fuzzy Logic Optimizes Global Inventory Management: Logika Fuzzy Mengoptimalkan Manajemen Persediaan Global Atika, Dewi Nur; Sukmono , Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 2 (2024): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i2.1131

Abstract

Inventory control is crucial for balancing customer demand and inventory levels, especially in make-to-order production systems like those in refrigeration manufacturing. This study addresses the challenges faced by a company producing sandwich panels, where inefficiencies in inventory processing led to overstock and outstock issues. By applying the fuzzy inventory control method using Python, the study aimed to optimize inventory levels. The results showed a 6% reduction in inventory, from 191,307 m² to 182,619.4627 m², demonstrating the method's effectiveness. This approach can improve inventory management in similar industrial settings, aligning production with demand and reducing excess inventory. Highlight: Efficiency Boost: Fuzzy logic optimizes inventory, minimizing overstock and outstock. Precise Management: Python aids accurate inventory analysis for informed decisions. Cost Savings: Aligning inventory with demand reduces excess, enhancing profitability. Keywoard: Inventory control, Fuzzy logic, Optimization, Production management, Industrial engineering
Indonesia's Breakthrough in Efficient Shellfish Cleaning Transforms Seafood Industry: Terobosan Indonesia dalam Pembersihan Kerang yang Efisien Mengubah Industri Makanan Laut Setiawan, Ari Rio De; Jakaria, Ribangun Bamban; Sari , Indah Apriliana; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 2 (2024): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i2.1133

Abstract

This research aims to design an efficient cleaning tool for bloody cockles to help business actors meet high demand with limited production systems. Conducted in Sidoarjo, data was collected from literature, government reports, and interviews with local business actors, revealing that manual processing of 50 kg of cockles takes 6-8 hours. Using the morphological method, several design concepts were evaluated for maintenance ease, performance, safety, and durability. The selected design (concept 3) showed the highest efficiency with a 37.5% score. This tool is expected to reduce cleaning time and improve outcomes, enhancing productivity and quality in the seafood processing industry. Highlight: Efficient Design: Reduces cleaning time from 6-8 hours significantly. High Demand: Meets increased consumer demand with limited resources. Optimal Concept: Concept 3 excels in maintenance, safety, and efficiency. Keywoard: Bloody Cockles, Cleaning Tool, Morphological Method, Efficiency, Seafood Processing
Machine Learning Predicts Truck Breakdowns in Indonesia with 83% Accuracy: Machine Learning Memprediksi Kerusakan Truk di Indonesia dengan Akurasi 83% Rachman, Meisya Azzahra; Sukmono, Tedjo
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1156

Abstract

PT. Varia Usaha Beton, a cement product company, faces frequent breakdowns of mixer trucks, reducing reliability from the target 90% to 60%. This study aims to predict truck breakdowns using a machine learning model based on the K-NN algorithm within the CRISP-DM framework. Data from the company's maintenance records were cleaned and split into training and testing sets. With k=20, the model achieved 90% accuracy on training data and 83% on testing data. These results can help improve maintenance scheduling and resource planning, enhancing truck reliability. Future research should compare other algorithms and consider different programming environments. Highlights: High Accuracy: K-NN model achieved 90% training and 83% testing accuracy. Maintenance Aid: Improves scheduling and resource planning for truck maintenance. Future Research: Compare algorithms and explore different programming environments. Keywords: Predictive Maintenance, Mixer Trucks, K-NN Algorithm, CRISP-DM, Machine Learning
Unlocking Global Efficiency with Enhanced Milling Machines Worldwide: Membuka Efisiensi Global dengan Mesin Penggilingan Ditingkatkan di Seluruh Dunia Lestari, Wiwik Puji; Wulandari, Indah Apriliana Sari; Sukmono, Tedjo; Jakaria, Ribangun Bamban
Indonesian Journal of Innovation Studies Vol. 25 No. 3 (2024): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v25i3.1157

Abstract

This study investigates the effectiveness of six milling machines at PT. INKA, a railroad car manufacturing company, focusing on CNC Plano 133 and Horizontal Milling 142. Utilizing Overall Equipment Effectiveness (OEE) and Age Replacement methods, the research aims to optimize machine performance and propose preventive maintenance strategies. Data spanning from January 2021 to December 2022 were collected and analyzed. Results indicate that both CNC Plano 133 and Horizontal Milling 142 exhibit suboptimal OEE values, primarily due to breakdown losses. Applying Age Replacement within 10 days significantly enhances reliability, with post-replacement reliability reaching 100%. The findings underscore the importance of preventive maintenance in improving milling machine reliability and overall productivity, thereby enhancing competitiveness and sustainability in the manufacturing sector. Highlight: Improved productivity: Preventive maintenance boosts milling machines' reliability and effectiveness. Resource efficiency: Analyzing OEE minimizes downtime, optimizes production output. Competitive edge: Enhanced performance sustains competitiveness, strengthens manufacturing sector's sustainability. Keyword: Milling machines, Overall Equipment Effectiveness (OEE), Preventive maintenance, Age Replacement, Manufacturing industry
Co-Authors Abdul Rohman Abdul Rohman Adistyas Nastiti, Octavia Afreni Hamidah Agung Laksono Agus Subagyo Ahmad Fikri Ardianto Alfian Fajar Gunawan Ali Mashar Ali Sadikin Ali Sadikin Amatullah, Dhiny Angela, Fitrah Cornellya Apriliana Sari Wulandari, Indah Arba, Risqi Mutia Ardiansyah Eko Saputra Arifin , Zainul Arinda Jayanti Putri Askhaarina Aulia Tsalits Asni Johari Asrial Asrial Atika, Dewi Nur Atikha Sidhi Cahyana Azhari, Asri Bambang Hariyadi Bambang Hariyadi Bambang Haryadi Benedika Ferdian Hutabarat Bestia Dewi Boy Isma Putra Damayanti , Maharani Lutfiah Damris Muhammad Dani Sartika Darlim Darmawi Dawam Suprayogi Desfaur Natalia Dewi Nurus Silmi Dian Ratna Sari Didin Muhjidin Diwanti Faradiba, Nabila Dristiana, Fila Dwi Kakung Saputro Dyah Ayu Shinta Permatasary Dzati Fauziyah Ervan Johan Wicaksana Erwin Widiantono Fahrell Andhika Pratama Fajar Ardian Cahyo Putra FEBRINA ROLIN Fila Dristiana Gusti Nurina Azhariani Hafizah, Mutia Hana Catur Wahyuni Harlis Harlis Harlis Harlis Hartanti, Lusia Permata Sari Heni Asmora Ritonga Hery Murnawan, Hery Hutwan Syarifuddin Ihsan, Mahya Indra Lesmana Inggit Marodiyah Jamaaluddin Jamaluddin Jamaluddin Kania Fatikasari Khairatinisa Khairatinisa Krisna Risky Putra Irawan Lega Anattri Leksono, Rudy Bowo Lestari, Wiwik Puji Lindyawati, Lely M. F. Rahardjo M. Rusdi M.Haris Efendi Hsb Mardhotillah, Bunga Mauli, Fajar Dwi Mishani, Adinda Chamilia Mochammad Amru Nail Suherman Mochammad Imam Mashuri Mohammad Andi Rasyid Mohammad Buchori Mohammad Ekki Hadian Much Syafiudin Muhaimin Muhaimin Muhammad Arizki Zainul Ramadhan Muhammad Dio Dwi Septian Muhammad Erick Sanjaya Muhammad Hafid Fikrianto Mukhammad Rifky Ramadhan Mukhammad Surya Lesmana Muswita Muswita Muswita Muswita Nafis Khumaidah Natalia, Desfaur Naufalut Tharif Qurniawan Naufalut Tharif Qurniawan Nazifa, Boti Iffa Nisrina Salsabila Novi Prastyanda Putra Pratama Nugraha, A. Prima Nugroho, Dizsa Arliansyah NURJIRANA NURJIRANA Nurma M. Hidayatulloh Octavia Adistyas Nastiti Octavia Adistyas Nastiti Pangestu, Retno PRADITA EKO PRASETYO UTOMO Putra, Tri Syukria Putri Ramadhani Putri, Andini Faizatul Putri, Melinda Aprilia R. Dwi Hadidjaja Rasjid Saputra Rachman, Meisya Azzahra Radiana Atika Sari Rahmansyah, Muhammad Miftah Arzaq Rany Riyantati, Dena Rasyid, Mohammad Andi Rayandra Asyhar Revis Asra Revis Asra Ribangun Bamban Jakaria Rifli Rindes Riska Afrilia Rista Dwi Cahyaningurm Rizky Janatul Magwa Rudy Bowo Leksono Safitri , Salsa Zulfa SANDI KURNIAWAN Sanjaya, Muhammad Erick Saputra, Nur Qomaruddin Sari , Indah Apriliana Sari W, Indah Apriliana Sari Wulandari, Indah Apriliana SARWO EDY WIBOWO Setiawan, Ardhi Wahyu Setiawan, Ari Rio De Sigit Wahono sisiliani, fitria trisna Sofillauny, Zahara Sonia Angellina Saputri Suhadak Sulistiono Suzanti, Sriliah Syaiful Syaiful Syaifullah, Dikril Ilham TARUNI SRI PRAWAST MIEN KAOMINI ANY ARYANI DEDY DURYADI SOLIHIN Tedy Azmi Nasution TEJA KASWARI Tia Wulandari TIA WULANDARI Tri Syukria Putra Ucop Haroen Upik Yelianti Utomo, Pradita Eko Prasetyo Vanisa Reyhan Faradiba Varid Jainuri Vivin Nur Oktavianty Wahono, Sigit Wahyu Nugroho Wahyu Setiawan, Ardhi Wardhani, Devira Kusuma Wawan Kurniawan Wijatmiko, Erie Fadma Noer Fitriana Wilda Syahri Winda Dwi Kartika, Winda Dwi Wiwik Sulistiyowati Wulandari, Indah Apriliana Sari Yoppie Wulanda Yusuf Effri Prastyo Budi Zurweni Zurweni