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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Agromet BALI MEDICAL JOURNAL (BMJ) Jurnal Kimia (Journal of Chemistry) INDONESIAN JOURNAL OF BIOMEDICAL SCIENCES Jurnal Keteknikan Pertanian Jurnal Ilmu Komputer dan Agri-Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Scientific Journal of Informatics JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal Of Vocational Health Studies Syntax Literate: Jurnal Ilmiah Indonesia Gema Wiralodra Journal of Robotics and Control (JRC) Jurnal Sewaka Bhakti Jurnal Ilmu dan Teknologi Peternakan Terpadu (JITPU) Dharma Jnana Journal of Global Pharma Technology Jurnal Sistem Informasi
Sri Wahjuni
Chemistry Department, Faculty Of Math And Science, Udayana University, Bali-Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Artikel Review: Implementasi Sistem Internet of Things (IoT) Pada Industri Perunggasan Hidayati Soesanto, Iman Rahayu; Wahjuni, Sri; Tanti, Ariyani
Jurnal Ilmu dan Teknologi Peternakan Terpadu Vol. 4 No. 2 (2024): Jurnal Ilmu dan Teknologi Peternakan Terpadu, Desember 2024
Publisher : Program Studi Peternakan Fakultas Pertanian Universitas Bosowa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56326/jitpu.v4i2.5039

Abstract

The implementation of Internet of Things (IoT) systems in the poultry industry has shown great potential in enhancing poultry efficiency and productivity. IoT technology enables real-time monitoring of various aspects of the coop environment, such as temperature, humidity, air quality, and lighting, as well as the health conditions of the chickens. Through connected sensors and communicating devices, data can be collected and analyzed to optimize the maintenance conditions of the chickens, thereby improving livestock health and reducing mortality rates. Additionally, IoT systems can automate feeding and watering processes, contributing to operational cost and time savings. This article reviews various case studies and research related to the application of IoT in the poultry industry. The review results indicate that the use of IoT not only increases operational efficiency but also aids in faster and more accurate decision-making based on precise data. However, challenges such as high initial costs, the need for adequate technological infrastructure, and specialized expertise in managing IoT systems must be addressed. Therefore, a strategic approach and collaboration among farmers, the government, and technology providers are required to maximize the benefits of IoT in the poultry industry.
Multi-Platform Detection of Melon Leaf Abnormalities Using AVGHEQ and YOLOv7 Ishak, Sahrial Ihsani; Priandana, Karlisa; Wahjuni, Sri
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1441

Abstract

This research develops a multiplatform system for detecting abnormalities in melon leaves, integrating an Internet of Things (IoT) approach using Jetson Nano, a Streamlit-based website, and a mobile application for real-time monitoring. The system employs preprocessing with Average Histogram Equalization (AVGHEQ) to enhance image quality, followed by modeling with the YOLOv7 algorithm on a dataset of 469 training images and 52 test images, validated through 5-fold cross-validation. The model achieved a mean Average Precision (mAP) of 84% with an inference detection time of 4.5 milliseconds. Implementation on Jetson Nano resulted in a 25% increase in CPU usage (from 25% to 50%) and a 20% increase in RAM usage (from 70% to 90%). By combining these platforms and leveraging robust data preprocessing and modeling techniques, the system provides an accessible, efficient, and scalable solution for agricultural monitoring, enabling farmers to address plant health issues promptly and effectively.
Prediksi Waktu Tanam Cabai Rawit Berdasarkan Kondisi Lingkungan Berbasis Internet of Things (IoT) Menggunakan Metode Neural Network Djaksana, Yan Mitha; Agus Buono; Sri Wahjuni; Heru Sukoco
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5199

Abstract

In Indonesian cuisine, the red Tabasco pepper holds a significant place as a commonly used ingredient. However, the cultivation of this chili variety is not without its challenges, primarily due to the volatile nature of the chili prices. Farmers often struggle with the critical decision of when to plant Tabasco peppers to optimize their yields and income. Understanding the complexities of this decision-making process in the context of varying environmental conditions is crucial. Thanks to recent advances in Internet of Things (IoT) technology, innovative systems have emerged to address these challenges.This study focuses on the development of an IoT-based solution aimed at helping farmers in precisely determining the optimal planting time for Tabasco pepper. It uses five key criteria—average temperature (°C), average humidity (%), rainfall (mm), length of sunlight (hours) and groundwater usage data (m3) to make data-driven planting decisions. The urgent need for such a system becomes evident when considering the unpredictability of climate patterns and their direct impact on crop outcomes. Using historical data from 2019, obtained from the Jakarta Provincial Government Open Data DKI, and climate data from the Meteorological Agency, Climatology, and Geophysics (BMKG), the authors have successfully developed an IoT-based prototype. This prototype employs a neural network algorithm to analyze the aforementioned criteria. The result is a reliable prediction system that boasts an impressive accuracy rate of 91.26%. By offering this level of precision in determining the ideal planting time for Tabasco pepper, the system extends invaluable support to farmers, helping them optimize their cultivation practices and navigate the uncertainties of the chili market.
The Use of Artificial Neural Networks to Estimate Reference Evapotranspiration Haris, Abdul; Marimin; Wahjuni, Sri; Setiawan, Budi Indra
Agromet Vol. 39 No. 1 (2025): JUNE 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.1.1-7

Abstract

Evapotranspiration is defined as the loss of water from soil and vegetation to the atmosphere, driven by weather conditions. It reduces the availability of water for agricultural purposes, which affects the amount of irrigation water, particularly during the dry season. The objective of this paper is to present a comparative analysis of the estimated reference evapotranspiration value based on artificial neural networks (ANN) with backpropagation bias 1 (BP-1) and backpropagation bias 0 (BP-0) architectures. The model was fed with data of air temperature, relative humidity, and solar radiation. The model is utilized to calculate the evapotranspiration using the Hargreaves method as the training data. The performance of ANN model was evaluated using the mean square error (MSE), root mean square error (RMSE), and coefficient determination (R2). Our results showed that both ANN models performed well as indicated by low error (MSE < 0.01) and high R2 (>0.99). Also, we found that air temperature and relative humidity determine the optimal prediction. Further, this proposed model can serve as a reference for other models seeking to determine the most appropriate computational model for evapotranspiration value estimation.
UAV-Based Segmentation and Correlation Analysis of Vegetation Indices for Cassava Crop Health Assessment Maryana, Sufiatul; Herdiyeni, Yeni; Wahjuni, Sri; Santosa, Edi
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3078

Abstract

Cassava, an essential staple food with diverse applications, has been relatively underexplored in terms of health analysis using vegetation indices. Conventional field surveys face challenges in covering large areas due to resource constraints. Recent advancements in remote monitoring techniques, such as satellite imagery and Unmanned Aerial Vehicles (UAVs), offer a promising alternative. While satellite imagery enables broad-scale surveys, its limited spatial resolution restricts detailed analyses of individual plants or smaller ecosystems. UAV-based vegetation surveys commonly utilize Vegetation Indices (VI) to assess unique spectral information. This study investigated UAV-based methods for mapping cassava distribution in the Telaga Kahuripan smallholder plantation in Bogor, Indonesia, focusing on UAV imagery, segmentation, and vegetation indices to evaluate cassava plant health at 2, 5, and 8 months of age. The results revealed significant variations in vegetation indices across different cassava plant ages. Particularly, the highest values observed at 5 months of age indicated substantial growth, with NDVI and GNDVI values exhibiting R2 ranging from 0.95 to 0.98, indicating a strong correlation. The robust correlation between NDVI and GNDVI implies that both indices can effectively predict plant health using UAV-based monitoring. Comparisons with existing studies suggest potential variations attributable to factors such as geographical location, environmental conditions, and cultivation practices. Understanding these variations is crucial for refining monitoring techniques and informing agricultural practices. Consequently, the findings have implications for enhancing cassava health monitoring and optimizing agricultural practices to ensure sustainable crop production.
PEMANFAATAN EKSTRAK BUAH NAGA MERAH (HYLOCEREUS POLYRHIZUS) SEBAGAI PEWARNA ALAMI UNTUK MENINGKATKAN PRODUKSI PADA KELOMPOK JAJANAN TRADISIONAL DI DESA SANGGING KUSAMBA, KLUNGKUNG Wahjuni, Sri; Ida Bagus Putra Manuaba; Ni Made Puspawati; Ni Ketut Puspa Sari; Haqqika Pasha; Ashri Rizki Hidayati
JURNAL SEWAKA BHAKTI Vol 11 No 2 (2025): Sewaka Bhakti
Publisher : UNHI Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32795/3eh7zz71

Abstract

This community service activity aims to improve the quality and competitiveness of traditional snacks in Sangging Kusamba Village, Klungkung, by utilizing red dragon fruit (Hylocereus polyrhizus) pulp extract as a natural dye. Extraction was carried out using a maceration method using 90% ethanol. The characterization results using LC-MS Shimadzu LCMS-8040 showed the presence of betanidin pigments (2.28%), dopaxanthin-quinone (2.27%), valinebetaxanthin (2.12%), 3-O-methylquercetin (2.38%), kaempferol 3-O-galactoside (3.18%), kaempferol 7-O-D-glucopyranoside (2.40%), quercetin 3-rutinoside (2.18%), isorhamnetin 3-O-neohesperidoside (2.92%), betanin (0.94%), isobetanin (0.94%), and neobetanin (1.61%) were detected and contributed to the antioxidant activity of the extract. The presence of betacyanin and betaxanthin pigments plays a role in providing bright red-purple to orange colors, while flavonoid compounds (quercetin, kaempferol, isorhamnetin) and phenolics (ferulic acid, vanillic acid) support the antioxidant activity of the extract. Implementation in traditional snack business groups shows that natural dyes from red dragon fruit produce bright, stable colors, and are more in demand by consumers than synthetic dyes. Thus, the use of red dragon fruit extract can be a functional food solution that is safe, environmentally friendly, and has high economic value. These results indicate that dragon fruit flesh can be used effectively in this community service aims to develop natural dyes based on red dragon fruit peel as a safer alternative to synthetic dyes.
Analisis pengaruh destination image, perceived value, dan kepuasan terhadap loyalitas wisatawan dalam mengunjungi destinasi wisata di Banyuwangi Wibisono, Indra Perdana; Prananta, Rebecha; Lokaprasidha, Pramesi; Nugroho, Margaretta Andini; Wahjuni, Sri
Gema Wiralodra Vol. 14 No. 1 (2023): Gema Wiralodra
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/gw.v14i1.421

Abstract

Kabupaten Banyuwangi berhasil dalam pengembangan Pariwisata. Adanya perubahan dari citra buruk menjadi citra kota wisata dalam waktu 6 tahun perlu diteliti lebih lanjut sehingga citra yang sudah baik tidak menjadi buruk lagi. Citra Destinasi berpengaruh terhadap perilaku wisatawan untuk mengunjungi destinasi wisata. Penelitian ini bertujuan agar citra destinasi di Banyuwangi tetap terjaga dengan baik sehingga memunculkan loyalitas wisawatan yang baik juga. Penelitian ini menggunakan kuesioner dengan skala likert. Metode yang digunakan adalah metode kuantitatif dengan analisis menggunakan Structural Equation Modeling menggunakan program statistik LISREL 8.80. Sampel yang digunakan adalah responden atau wisatawan yang berkunjung ke Banyuwangi. Hasil dari penelitian ini adalah citra tujuan memiliki pengaruh yang kuat terhadap variabel persepsi nilai, kepuasan dan loyalitas wisatawan. Demikian juga, nilai yang dirasakan memiliki pengaruh positif pada kepuasan dan loyalitas wisatawan.
Knowledge Management System Berbasis Web tentang Budidaya Hidroponik untuk Mendukung Smart Society Wardhana, Ariq Cahya; Nurhadryani, Yani; Wahjuni, Sri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 3: Juni 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020732200

Abstract

Meningkatnya jumlah populasi penduduk di Indonesia berdampak pada terbatasnya luas wilayah pertanian di Kota Bogor yang mengakibatkan ancaman produksi pertanian karena konversi lahan persawahan sebesar 88,12% menjadi perumahan dan kebun. Solusi sistem produksi pertanian dengan terbatasnya lahan salah satunya adalah hidroponik. Untuk meningkatkan pengetahuan budidaya hidroponik dan memudahkan akses fasilitas belajar digital sebagai bagian penting dari rencana pemerintah Kota Bogor yaitu smart society diperlukan dukungan teknologi informasi. Penelitian ini bertujuan mengembangkan Knowledge Management System (KMS) budidaya hidroponik dengan mengadopsi metode Knowledge Management Life Cycle melalui identifikasi pengetahuan tacit maupun explicit dari komunitas hidroponik. Proses menangkap pengetahuan berorientasi pada seluruh proses budidaya sayuran hidroponik dengan menggunakan bibit yang siap tanam. Knowledge map digunakan untuk kodifikasi pengetahuan menghasilkan 34 pengetahuan explicit berupa media interaktif video maupun dokumen yang dapat digunakan oleh pengguna. Implementasi sistem menggunakan aplikasi berbasis Web dengan pendekatan object oriented yang sudah diuji oleh pakar dan semua fungsi berjalan dengan baik. Sistem ini memiliki fitur klasifikasi KMS yaitu knowledge capture, knowledge sharing, serta knowledge discovery. AbstractThe increasing number of populations in Indonesia has an impact on the limited area in Bogor, which has resulted in the threat of agricultural production because of the conversion of 88.12% of paddy fields to housing and gardens. A solution to agricultural production systems with limited land, one of which is hydroponics. Facilitate access to digital learning facilities as an essential part of the plan of the Bogor City government, namely smart society, information technology support is needed as a means of sharing hydroponic cultivation knowledge. Based on this, we developed a knowledge management system (KMS) adopting the Knowledge Management Life Cycle method by identifying tacit and explicit knowledge from the hydroponic community. The process of capturing knowledge is oriented to the whole process of hydroponic vegetable cultivation by using seeds that are ready for planting. Knowledge map is used for codification of knowledge that produces 34 explicit knowledge in the form of interactive media in the form of videos and documents that can be used by user. The output generated from this study is KMS was implemented using Web-based applications with an object-oriented approach that has been tested by experts with system functions is working and has KMS classification features, namely knowledge capture, knowledge sharing, and knowledge discovery.
Rancang Bangun Protokol Perutean SDGR+R pada Vehicular AD-HOC Network Berbasis Arah Manapa, Eliyah Acantha; Wahjuni, Sri; Neyman, Shelvie Nidya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722927

Abstract

Vehicular Ad-Hoc Network (VANET) merupakan pengembangan jaringan wiresless yang melakukan komunikasi secara Inter Vehicle Communication (IVC). VANET memiliki mobilitas yang tinggi untuk setiap node nya sehingga jaringan komunikasi jenis ini adalah jaringan yang bersifat sementara dikarenakan node bergerak di lintasan dengan arah dan kecepatan yang dinamis. Dengan demikian, pengiriman paket data dari node sumber ke node tujuan menggunakan VANET memerlukan beberapa teknik komunikasi. Teknik terbaru komunikasi VANET saat ini adalah menggunakan SDN (Software Defined Network) yang berbasis geographic (SDGR) sebagai control plane dalam mengontrol komunikasi ad-hoc antar node. Dalam membentuk topologi jaringan komunikasi, SDGR mencari nilai jalur terpendek antar node dan kepadatan node yang tinggi. Tujuan utama penelitian ini melakukan analisis konsep protokol perutean (routing protocol) SDGR dan dilakukan pengembangannya dengan mempertimbangkan arah rute (SDGR+R). Pada SDGR+R, penambahan basis arah rute menggunakan multicast. Selanjutnya, dilakukan perbandingan kinerja antara SDGR dan SDGR+R. Hasil simulasi menunjukkan SDGR+R memiliki kinerja lebih baik daripada SDGR dalam hal latency sebesar 1.88% dan packet delivery ratio (PDR) sebesar 8.12%. Perancangan protokol perutean SDGR+R menambah ide pengembangan teknologi pada VANET untuk masa mendatang. AbstractVehicular Ad-Hoc Network (VANET) is a wireless network developed for communication on Inter-Vehicle Communication (IVC). Each node in a VANET has high mobility so that this type of communication network is a temporary network because the node moves on the track with dynamic direction and speed. Thus, sending data packets from source node to destination node using VANET requires some communication techniques. The latest technology for VANET communication is to use SDN-based geographic-based SDN (SDGR) as a control plane in controlling Ad-hoc communication between nodes. In forming the communication network topology, SDGR looks for the shortest path value between nodes and high node density. The main objective of this research is to analyze the concept of SDGR routing protocol and to develop it, considering the direction of the route (SDGR+R). In SDGR + R, the addition of route base directions uses multicast. Next, we compare the performance between SDGR and SDGR+R. Simulation results show SDGR+R has better performance than SDGR in terms of latency of 1.88% and packet delivery ratio of 8.12%. The design of the SDGR+R routing protocol gives to the idea of technology development on VANET in the future.
Identifikasi Kemurnian Daging Berbasis Analisis Citra Yulianti, Nila Susila; Seminar, Kudang Boro; Hermanianto, Joko; Wahjuni, Sri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813307

Abstract

Daging sapi merupakan salah satu sumber protein hewani yang diperlukan oleh tubuh. Pada tahun 2015 dan 2016 konsumsi daging sapi per kapita sebesar 0,417 kg dan terjadi kenaikan pada tahun 2017 yaitu 12,50 % sebesar 0,469 kg. Sementara harga rata-rata daging sapi di tahun 2015 sebesar Rp 104 747 per kg dan mengalami kenaikan pada tahun 2016 yaitu 8,41 % sebesar Rp 113 555 per kg.  Di tahun 2017 kembali terjadi kenaikan yaitu 2,09 % sebesar 115 932 per kg. Berdasarkan sensus penduduk tahun 2010 mendata jumlah penduduk muslim sebesar 207176162 yaitu 87 % dari total penduduk di Indonesia. Kekhawatiran daging halal sangat penting di negara mayoritas muslim. Metode secara konvensional dengan uji laboratorium untuk mendeteksi daging celeng membutuhkan waktu yang relatif lama, tempat khusus, serta biaya yang relatif mahal. Sementara daging yang diwaspadai dicampur dengan daging babi hutan bisa terjadi di berbagai tempat seperti pasar, retailer serta  distributor yang sepatutnya bisa dideteksi seketika di tempat tersebut secara cepat. Oleh karena itu, diperlukan sistem yang mudah, cepat, dan mudah dibawa untuk mendeteksi daging sapi murni (tanpa campuran daging lainnya) dalam penelitian ini adalah daging celeng.Paper ini membahas metode deteksi daging campuran berbasis citra menggunakan Convolutional Neural Network (CNN) yang dapat dioperasikan di android. Keunggulan metode ini dapat melakukan proses pembelajaran secara mandiri yaitu ekstraksi citra dan klasifikasi, adapun kemampuan lain yang dimiliki yaitu dapat menangani deformasi gambar seperti translasi, rotasi dan skala. Akurasi yang didapatkan dari metode ini yaitu 94 % untuk mendeteksi daging sapi murni, daging celeng murni, dan daging campuran sapi dan celeng. Sementara presisi untuk celeng, campuran dan sapi yaitu 100 %, 90 % dan 95 %. Selain itu, recall untuk celeng, campuran dan sapi yaitu 85 %, 95 %, dan 97,5 %. Prototipe sistem deteksi yang dikembangkan telah diimplementasikan pada platform android dan diuji pada situasi pencahayaan yang masih terkondisikan. Upaya penyempurnaan ke depan adalah menambah fitur sistem pencahayaan  khusus/standar dengan kamera khusus yang memiliki cahaya tambahan yang mengatasi keragaman tingkat pencahayaan di tempat terbuka. AbstractBeef is one of animal protein source that important for human body. In 2015 and 2016 beef consumption per capita was 0.417 kg and it was increasing in 2017 by 12.50 % (i.e., 0.469 kg). While The average price of beef  at Rp 104 747 per kg in 2015 and went up  by 8,41 % at Rp 113 555 per kg in 2016. In 2017, there was an increase by 2,09 % at Rp 115 932 per kg. The increase of beef price average occurred in 2015 amounting to Rp 104 747 per kg and an increase in 2016 that was 8.41% amounting to Rp 113 555 per kg. Based on the population census in 2010 recorded a Muslim population of 207176162 which is 87% of the total population in Indonesia. The concern of halal (lawful) meat is very critical in the muslim majority country. The conventional method with laboratory testing to detect wild boar meat requires a relatively long time, a special place, and a relatively expensive cost. While meat that is mixed with wild boar can happen in various places such as markets, retailers and distributors which can be detected immediately in that place quickly.Therefore, a system that can be easily, quickly and portably used for detecting pure beef (without other mixed meat) in this study is wild boar.  This paper discusses image-based mixed meat detection methods using the Convolutional Neural Network (CNN) that can be operated on android. so the proposed computationally method is Convolutional Neural Network (CNN). The advantages of this method can do the learning process independently, object extraction and classification, while the other capabilities that can handle image deformation such as translation, rotation, and scale. This method yields an overall accuracy of 94% for detecting pure beef, pure wild boar meat, and mixed beef and wild boar. The obtained precision values for wild boar, mixed meat and beef  are by 100 %, 90 % and 95 % respectively. Moreover, the values recall for wild boar, mixed meat and beef are by 85 %, 95 % and 97,5 % respectively. The prototype detection system developed has been implemented on the Android platform and tested in a lighting situation that is still conditioned. A  future effort to improve is providing   special / standard lighting with a special camera that has additional light that can overcome the diversity of levels of exposure in the open areas. 
Co-Authors A.A.G. Sudewa Agus Buono Alfiansyah Halomoan Siregar Anisa Nur Halimah Ariq Cahya Wardhana Ariyani Tanti Ashri Rizki Hidayati Auriza Rahmad Akbar Barlianto, Agus Betty Kostradiyanti Budi Indra Setiawan dan Luh Putu Arisanti Edi Santosa Eknanda, Rafael Tektano Grandiawan Eliyah Acantha Manapa Sampetoding Elly Rusdiana, Elly Eny Inayati, Eny Faisyah, Shilvy Arofatul Haqqika Pasha Haris, Abdul Haula Robbi, M. Kautsar Hendra Rahmawan Hendra Rahmawan Hidayat Hidayat Hidayat I M, Sukadana I NYOMAN MANTIK ASTAWA I W. Wita, I W. I Wayan Suirta I Wayan Wita I. A Raka Astiti Asih Ida Bagus Putra Manuaba Iman Rahayu Hidayati Soesanto Irman Hermadi Ishak, Sahrial Ihsani Joko Hermanianto Karlisa Priandana Komara N, Fatthurohman Kudang Boro Seminar Kusdarjanti, Endang Lita Rosa, Mia Laksmi Lokaprasidha, Pramesi Lusiana Tabuni Marimin , Maxiwinata, Maxdha Michel Williams, Michel Ni Ketut Puspa Sari Ni Luh Rustini Ni Made Puspawati Ni Made Puspawati Ni Nyoman Astuti Wulandari Ni Putu Rahayu Artini Nirmala Ratna Harda, Sasadhara Noer Muslimah, Meia Nugroho, Margaretta Andini Oka Ratnayani Putu Yuliantari Rahmadani, Annisa Ratwita, Rr. Dwiyanti Feriana Rebecha Prananta, Rebecha Sanjiwo, Suryo Hamukti Sefy Ayu Mandanie, Sefy Ayu Septianto, Yudhi Setyowati, Okti Shelvie Nidya Neyman Sianiwati Goenharto Sri Rahayu Santi Sri Redjeki Sri Redjeki Indiani Sufiatul Maryana Sujati Sujati Sujati, Sujati Toto Haryanto Wafi, Azmi Sabilakisbatul Wahyu Dwijani Sulihingtyas Wasudewa, K. M. Wibisono, Indra Perdana Willy Bayuardi Suwarno Wulandari Wulandari Yan Mitha Djaksana Yani Nurhadryani Yulianti, Nila Susila Zakiah, Rizqi Alifahasni