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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Hortikultura Indonesia (JHI) Jurnal Ilmu Tanah dan Lingkungan (Journal of Soil Science and Environment) Journal of Tropical Soils Siscode Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Ampere Edu Komputika Journal Kultivasi Turbo : Jurnal Program Studi Teknik Mesin Jurnal Penelitian Kelapa Sawit Antivirus : Jurnal Ilmiah Teknik Informatika JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Budimas : Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Abdi Masya International Journal Of Computer, Network Security and Information System (IJCONSIST) Teknika Jurnal Insan Pembangunan Sistem Informasi dan Komputer (IPSIKOM) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Sanskara Hukum dan HAM Jurnal Bisnis dan Manajemen West Science West Science Interdisciplinary Studies West Science Interdisciplinary Studies ITIJ West Science Social and Humanities Studies West Science Agro Jurnal Komplikasi Anestesi IPSIKOM INERSIA Modem : Jurnal Informatika dan Sains Teknologi Journal of Social Sciences and Technology for Community Service Journal of Computer Science Advancements
Budi Nugroho
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Estimation of the Potential Carbon Emission from Acrotelmic and Catotelmic Peats Nurzakiah, Siti; Sabiham, Supiandi; Nugroho, Budi; Nursyamsi, Dedi
JOURNAL OF TROPICAL SOILS Vol. 19 No. 2: May 2014
Publisher : UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5400/jts.2014.v19i2.81-89

Abstract

Agricultural development on peatland in Indonesia has been constrained by the presence of environment issues in relation to the release of greenhouse gases (GHGs) particularly carbon dioxide (CO2) and methane (CH4) to the atmosphere. This study was aimed to predict the potential carbon emission based on carbon stocks in acrotelmic and catotelmic peats with the reference of groundwater level of peatland.  The results showed that groundwater levels have played an important  role  in  carbon  release, which  has  close  relationship  with  water  regime  of  the upper  layer  of  peats  that influenced by oxidative and reductive conditions of the land.  From the layer that having groundwater level fluctuations during the period from rainy to dry season (acrotelmic peat), the emissions were mostly dominated by CO2 release, while from permanent reductive-layer (catotelmic peat) was not detected.  The decrease of groundwater level from -49.6 to -109 cm has clearly influenced carbon emission.  From each decreasing 1.0 cm groundwater level, CO2 emission measured during the period of February - October 2013 was calculated to yield about 0.37 Mg ha-1 yr-1.Keywords: Acrotelmic and catotelmic peat, carbon emission, groundwater level [How to Cite: Siti N, S Sabiham, B Nugroho and Di Nursyamsi. 2014. Estimation of the Potential Carbon Emission from Acrotelmic and Catotelmic Peats. J Trop Soils 19(2): 91-99. Doi: 10.5400/jts.2014.19.2.91]    
Characteristics of Soil Chemical Properties Associated with Inceptisols in Various Land Use in Jasinga, Bogor Rahmayuni, Erlina; Anwar, Syaiful; Nugroho, Budi; Indriyati, Lilik Tri
JOURNAL OF TROPICAL SOILS Vol. 28 No. 3: September 2023
Publisher : UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5400/jts.2023.v28i3.89-97

Abstract

Inceptisols are soils with low to moderate fertility and have not experienced further development. This study aims to characterize the chemical properties of inclusions and base exchange fractionation of P of soil on Inceptisol soil map units of forest land, dry land, and paddy fields in Jasinga. Soil samples were taken at three horizons (Ao or Ap, AB/B1, and B/Bt) on forest soil profiles and dry land, while on paddy fields, they were taken at a depth of 0-20 cm, 20-40 cm, and 40-60 cm from the surface land. The chemical properties of the soil analyzed were soil pH, C-organic, soil bases, P-total, CEC, base saturation, and P fractionation. The results showed that the chemical properties of inclusions in the Inceptisol Jasinga soil map unit included high CEC and BS and low Mn-dd. The dominant soil inclusions are in paddy fields, followed by forests, and the lowest is in dry land. The chemical properties findings did not significantly differentiate the available inorganic P, Al-P, (Fe, Mn)-P, and (Ca, Mg)-P fractions. The inclusion of chemical characteristics did not result in a reversal of the correlation with the inorganic P fraction.
Monitoring Konsumsi Daya Dan Pencegahan Kerusakan Pada Pendingin Udara Berbasis Iot Nugroho, Budi; Rahmat, Rahmat; Suprianto, Agung
Jurnal Ampere Vol. 9 No. 2 (2024): JURNAL AMPERE
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/ampere.v9i2.16552

Abstract

Penyediaan energi listrik semakin terbatas, penghematan penggunaan daya pada pengguna listrik perlu dilakukan efisiensi dan menghindari pemborosan untuk mengurangi kerugian dari sisi pembiayaan. Pendingin udara sebagai salah satu beban listrik jika pendingin udara tersebut bekerja sudah tidak sesuai nameplate dari pabrik konsumsi dayanya sudah tidak sesuai, jika tidak segera diperbaiki akan mengalami kerusakan. Untuk mencegah terjadinya pemborosan daya diperlukan perangkat untuk memonitor arus listrik yang digunakan. Penelitian ini merancang dan membuat sistem monitoring penggunaan daya pada pendingin udara yang dapat dipantau pada Handphone sebagai bentuk penerapan teknologi IoT. Sistem yang dibuat dirancang untuk memonitor daya listrik dan pencegahan kerusakan pada pendingin udara. Tahapan penelitian dimulai dengan merancang wiring sensor pada pendingin udara;Wiring dan setting jaringan komputer dan Router; Pembuatan dan setting Web Server; Pembuatan program mikrokontroler ESP8266; Pembuatan program di Handphone, selanjutnya dilakukan uji coba dan  dilakukan pengambilan data performa alat. Hasil sistem yang dibuat telah bekerja dan memproteksi pendingin udara jika terjadi kenaikan daya yang digunakan pada pendingin udara
Analisis Perbandingan Metode Algoritma C4.5 dan KNN dalam Prediksi Nilai Kebutuhan Gizi Ibu Hamil di Kecamatan Pandaan Miftahul Nuril Silviyah; Budi Nugroho; Yisti Vita Via
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1171

Abstract

This study aims to compare the performance of the C4.5 algorithm and the K-Nearest Neighbor (KNN) method in predicting the nutritional needs of pregnant women. The research method involves six main stages: field data collection, dataset reading, basic data exploration, data preprocessing, predictive model development, and model evaluation using test data. The dataset was collected through a Google Form distributed to pregnant women in the Pandaan sub-district and then underwent a preprocessing phase to clean and prepare the data for further analysis. The C4.5 and KNN algorithms were built using the preprocessed data, and the complexity of each model was evaluated to determine their prediction accuracy. These methods were used to predict the nutritional requirements of pregnant women. The findings of the study indicate that the C4.5 algorithm achieved a higher accuracy rate of 95%, compared to 87.50% achieved by the KNN algorithm. Based on these results, it can be concluded that the C4.5 algorithm is more accurate and reliable for predicting the nutritional needs of pregnant women.
DESIGN AND IMPLEMENTATION OF A PIEZOELECTRIC PEDESTRIAN-POWERED ENERGY HARVESTING SYSTEM FOR SUSTAINABLE URBAN INSTALLATIONS Islam, Muhammad Qamarul; Ghoni, Ruzlaini; Ibrahim, Mohd Tarmizi; Nugroho, Budi
Teknika Vol 10 No 2 (2025): October 2025
Publisher : Pusat Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52561/teknika.v10i2.611

Abstract

This project proposes integrating a pedestrian-powered system into a public installation to create a renewable energy source in urban environments. The system utilizes piezoelectric sensors embedded in the sidewalk to convert mechanical energy from footsteps into electrical energy, which is then used to power lights and display kinetic movement in the art installation. The main goal of this project is to provide a participatory, environmentally friendly, and sustainable solution in the form of an interactive artwork, while reducing dependence on conventional energy sources. Test results show that the greater the applied load, the higher the generated voltage. The lowest voltage recorded was 11.76 mV at a weight of 50 kg, while the highest voltage reached 315.16 mV at a weight of 90 kg, with an average voltage of 168.46 mV for the load range of 50–90 kg. These findings demonstrate that piezoelectric technology has great potential as an energy harvesting system in public areas, as it can provide power for energy-efficient devices while enhancing the aesthetic quality and awareness of sustainable energy in urban spaces.
Palm Oil in the Millennial Era: The Effects of Digital Campaigns and Public Education on Brand Engagement through Awareness Generation Mediation in West Sumatra Judijanto, Loso; Nugroho, Budi
West Science Interdisciplinary Studies Vol. 3 No. 10 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i10.2336

Abstract

This study investigates the impact of digital campaigns and public education on brand engagement through the mediating role of brand awareness in the palm oil industry of West Sumatra, Indonesia. The research was conducted in response to the growing need for sustainable branding and public perception management within an industry often associated with environmental controversy. A quantitative approach was employed using Structural Equation Modeling (SEM) with Partial Least Squares (SmartPLS 3.0). Data were collected from 115 respondents, primarily millennials, using a five-point Likert scale questionnaire. The results indicate that both digital campaigns and public education have significant positive effects on brand awareness and brand engagement. Moreover, brand awareness plays a partial mediating role, amplifying the indirect influence of digital campaigns and educational initiatives on engagement. The findings confirm the applicability of the Stimulus–Organism–Response (S-O-R) model, illustrating that digital and educational stimuli (S) enhance awareness (O), which subsequently drives engagement (R). The study contributes theoretically by integrating digital marketing communication and sustainability education into the brand engagement framework, and practically by offering strategies for improving consumer trust and advocacy through transparent, educational digital content.
Palm Oil in the Millennial Era: The Effects of Digital Campaigns and Public Education on Brand Engagement through Awareness Generation Mediation in West Sumatra Judijanto, Loso; Nugroho, Budi
West Science Interdisciplinary Studies Vol. 3 No. 10 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i10.2336

Abstract

This study investigates the impact of digital campaigns and public education on brand engagement through the mediating role of brand awareness in the palm oil industry of West Sumatra, Indonesia. The research was conducted in response to the growing need for sustainable branding and public perception management within an industry often associated with environmental controversy. A quantitative approach was employed using Structural Equation Modeling (SEM) with Partial Least Squares (SmartPLS 3.0). Data were collected from 115 respondents, primarily millennials, using a five-point Likert scale questionnaire. The results indicate that both digital campaigns and public education have significant positive effects on brand awareness and brand engagement. Moreover, brand awareness plays a partial mediating role, amplifying the indirect influence of digital campaigns and educational initiatives on engagement. The findings confirm the applicability of the Stimulus–Organism–Response (S-O-R) model, illustrating that digital and educational stimuli (S) enhance awareness (O), which subsequently drives engagement (R). The study contributes theoretically by integrating digital marketing communication and sustainability education into the brand engagement framework, and practically by offering strategies for improving consumer trust and advocacy through transparent, educational digital content.
Perbandingan Aplikasi Algoritma Kernel K-Means pada Graf Bipartit dan K-Means pada Matriks Dokumen- Istilah dalam Dataset Penelitian Covid-19 RISTEKBRIN Nugroho, Budi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 2: April 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021824365

Abstract

Merebaknya kasus Covid-19 di Indonesia telah memunculkan berbagai macam topik penelitian yang dilakukan oleh para peneliti di berbagai bidang dan dari bermacam institusi. Berdasarkan data yang dihimpun oleh portal Sinta Ristekbrin, terdapat 351 topik penelitian yang telah diunggah oleh para peneliti. Kajian ini dimaksudkan untuk menganalisis dan memetakan topik penelitian yang  sedang dan/atau  telah dilakukan selama kurun waktu terjadinya pandemi  Covid-19 di tanah air. Analisis dan pemetaan dilakukan dengan menerapkan algoritma kernel k-means untuk klastering dokumen berbasis graf bipartit dan k-means pada matriks dokumen-istilah. Dataset penelitian Covid-19 Ristekbrin dimodelkan sebagai graf bipartit antara daftar istilah dengan dokumennya. Selanjutnya skor kemiripan dihitung dengan metode kernel. Nilai matriks kernel yang mencerminkan skor kemiripan antar dokumen digunakan sebagai masukan bagi algoritma klastering kernel k-means yang memberikan hasil berupa pemetaan topik penelitian. Sebagai pembanding, algoritma k-means diterapkan pada matriks dokumen-istilah untuk klastering topik penelitian Covid-19. Dari kedua metode tersebut, hasil klastering diuji dengan validasi internal menggunakan indeks Dunn. Indeks Dunn digunakan karena dalam dataset tidak tersedia informasi awal mengenai label atau nama dari masing-masing klaster. Hasil penelitian ini menunjukkan bahwa algoritma  kernel k-means memberikan validasi yang sedikit lebih baik dibandingkan dengan k-means. Hasil kajian ini diharapkan dapat memberikan tambahan informasi yang mendukung program pemerintah dalam mempercepat penanganan Covid-19 di Indonesia. AbstractThe outbreak concerning  the Covid-19 case in Indonesia has raised various topics of research carried out by researchers in diverse fields and from many institutions. Based on data compiled by the Sinta Ristekbrin portal, 351 research topics have been uploaded by researchers. This study is aimed to analyze and map research topics that are being and/or have been conducted during the period of the Covid-19 pandemic in Indonesia. Analysis and mapping are accomplished by applying the kernel k-means algorithm for document clustering based on bipartite graphs and k-means on document term matrix. Ristekbrin's Covid-19 research dataset is modeled as a bipartite graph between terms and documents. Furthermore, the similarity score is calculated using the kernel method. The kernel matrix value that represents the similarity score between documents is used as input for the kernel k-means clustering algorithm, which provides the results of mapping research topics. As comparison, we applied original k-means algorithm on the document-term matrix of the dataset. From these two methods, the clustering results were validated using Dunn index as an internal validation. The Dunn index was used because the dataset did not provide initial information regarding the label or name of each clusters..The comparison Dunn index shows that the kernel k-means algorithm outperforms than the k-means algorithm. This study is expected to provide additional information that supports government programs in accelerating the handling of Covid-19 in Indonesia..
Kinerja Metode CNN untuk Klasifikasi Pneumonia dengan Variasi Ukuran Citra Input Nugroho, Budi; Puspaningrum, Eva Yulia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021834515

Abstract

Saat ini banyak dikembangkan proses pendeteksian pneumonia berdasarkan citra paru-paru dari hasil foto rontgen (x-ray), sebagaimana juga dilakukan pada penelitian ini. Metode yang digunakan adalah Convolutional Neural Network (CNN) dengan arsitektur yang berbeda dengan sejumlah penelitian sebelumnya. Selain itu, penelitian ini juga memodifikasi model CNN dimana metode Extreme Learning Machine (ELM) digunakan pada bagian klasifikasi, yang kemudian disebut CNN-ELM. Dataset untuk uji coba menggunakan kumpulan citra paru-paru hasil foto rontgen pada Kaggle yang terdiri atas 1.583 citra normal dan 4.237 citra pneumonia. Citra asal pada dataset kaggle ini bervariasi, tetapi hampir semua diatas ukuran 1000x1000 piksel. Ukuran citra yang besar ini dapat membuat pemrosesan klasifikasi kurang efektif, sehingga mesin CNN biasanya memodifikasi ukuran citra menjadi lebih kecil. Pada penelitian ini, pengujian dilakukan dengan variasi ukuran citra input, untuk mengetahui pengaruhnya terhadap kinerja mesin pengklasifikasi. Hasil uji coba menunjukkan bahwa ukuran citra input berpengaruh besar terhadap kinerja klasifikasi pneumonia, baik klasifikasi yang menggunakan metode CNN maupun CNN-ELM. Pada ukuran citra input 200x200, metode CNN dan CNN-ELM menunjukkan kinerja paling tinggi. Jika kinerja kedua metode itu dibandingkan, maka Metode CNN-ELM menunjukkan kinerja yang lebih baik daripada CNN pada semua skenario uji coba. Pada kondisi kinerja paling tinggi, selisih akurasi antara metode CNN-ELM dan CNN mencapai 8,81% dan selisih F1 Score mencapai 0,0729. Hasil penelitian ini memberikan informasi penting bahwa ukuran citra input memiliki pengaruh besar terhadap kinerja klasifikasi pneumonia, baik klasifikasi menggunakan metode CNN maupun CNN-ELM. Selain itu, pada semua ukuran citra input yang digunakan untuk proses klasifikasi, metode CNN-ELM menunjukkan kinerja yang lebih baik daripada metode CNN. AbstractThis research developed a pneumonia detection machine based on the lungs' images from X-rays (x-rays). The method used is the Convolutional Neural Network (CNN) with a different architecture from some previous research. Also, the CNN model is modified, where the classification process uses the Extreme Learning Machine (ELM), which is then called the CNN-ELM method. The empirical experiments dataset used a collection of lung x-ray images on Kaggle consisting of 1,583 normal images and 4,237 pneumonia images. The original image's size on the Kaggle dataset varies, but almost all of the images are more than 1000x1000 pixels. For classification processing to be more effective, CNN machines usually use reduced-size images. In this research, experiments were carried out with various input image sizes to determine the effect on the classifier's performance. The experimental results show that the input images' size has a significant effect on the classification performance of pneumonia, both the CNN and CNN-ELM classification methods. At the 200x200 input image size, the CNN and CNN-ELM methods showed the highest performance. If the two methods' performance is compared, then the CNN-ELM Method shows better performance than CNN in all test scenarios. The difference in accuracy between the CNN-ELM and CNN methods reaches 8.81% at the highest performance conditions, and the difference in F1-Score reaches 0.0729. This research provides important information that the size of the input image has a major influence on the classification performance of pneumonia, both classification using the CNN and CNN-ELM methods. Also, on all input image sizes used for the classification process, the CNN-ELM method shows better performance than the CNN method.
Pembuatan Pupuk Kalium Silikat Berbahan Dasar Pasir Kuarsa dari Bangka Nugroho, Budi; Edwar, Feabri Kurniawan; Hartono, Arief
Jurnal Ilmu Tanah dan Lingkungan Vol 25 No 1 (2023): Jurnal Ilmu Tanah dan Lingkungan
Publisher : Departemen Ilmu Tanah dan Sumberdaya Lahan, Fakultas Pertanian, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jitl.25.1.19-24

Abstract

Salah satu upaya pemanfaatan potensi pasir kuarsa yaitu melalui pembuatan pupuk Kalium Silikat (K2SiO3), melalui reaksi SiO2 dalam pasir kuarsa dengan kalium hidroksida (KOH). Penelitian ini bertujuan mendapatkan suhu optimal dalam pembuatan pupuk K2SiO3 melalui pencampuran pasir kuarsa dari Bangka dengan KOH. Lebih jauh penelitian ini bertujuan mengevaluasi kelarutan pupuk K2SiO3 pada tanah serta pengaruhnya terhadap pH tanah, alumunium dapat ditukar (Al-dd), kalium dapat ditukar (K-dd) dan silika (Si) tersedia melalui percobaan inkubasi pada Ultisol Dramaga. Hasil menunjukan bahwa kandungan kalium dalam bentuk kalium oksida (K2O) tertinggi pada perlakuan suhu 1000 oC sebesar 66.9%, sedangkan terendah pada suhu 700 oC sebesar 55.1%. Sebaliknya, kandungan Si dalam bentuk SiO2 pada suhu 1000 oC sangat rendah. Kandungan SiO2 pupuk Kalium Silikat tertinggi pada suhu 800oC sebesar 35.1%. Pupuk K2SiO3 yang paling optimal dari penelitian ini adalah pada suhu 800 oC dengan memiliki kandungan K2O 60.0% dan SiO2 35.1%. Percobaan inkubasi menunjukkan dosis pupuk Kalium Silikat 2.50% adalah dosis yang paling efektif karena selain meningkatkan hara K-dd dan Si tersedia, juga mampu menurunkan nilai Al-dd dan memperbaiki nilai pH tanah menjadi relatif netral.
Co-Authors -, Rahmat AA Sudharmawan, AA Achmad Azhari Sidik Adi Laksono, Surya Afif Faishal Ageng Setiani Rafika Agung Karuniawan Agung Mustika Rizki Agung Supriyanto, Agung Ahmad, Raudah Akbar, Fawwaz Ali Akhmad Ridconi Alliah, Rahmadina Alwi, Salma Anandyawati, . Anas Dinurrohman Susila Anggraeni, Fetty Tri Anny Yuniarti Anugerah, Rico Putra Arafah, Salsabilla Putri Arif Agus Yulianto Arini, Rani Eka Atang Sutandi Awandi, Nadhif Mahardika Baba Barus Basuki Rahmat Masdi Siduppa Cale, Wolnough Cicilia Puji Rahayu Darda Effendi Debi Unsilatur Utami Dedi Nursyamsi Dermawan, Rahmansyah Dermawan Desi Nadalia Dian Koswara Edwar, Feabri Kurniawan Erlina Rahmayuni, Erlina Ernawati Eso Solihin Eva Yulia Puspaningrum Fachlevi, Muhammad Reza Fajar Setyawan, Handi Faridah Faridah Fernando Sitorus, Alberth Ghoni, Ruzlaini Hadi, Surjo Hari Agung Hayatu, Aiun Herning Indriastuti Heru Bagus Pulunggono I Gede Susrama Mas Diyasa Ibayasid Ibrahim, Mohd Tarmizi Indriyati, Lilik Tri Islam, Muhammad Qamarul J. Kuleh Jamaldi, Agus Jepriani, Sujiati Jie, Lie Joko Suryono Judijanto, Loso Juniardi, Salim Kamil, Insan Karminto, Karminto Kristiawan, Y. Yulianto Kukuh Murtilaksono Kurniawan, Abdi Lestari, Tri Rahayu Kuwat Margono Margono Maulana, Haris Maulana, Hendra Miftahul Nuril Silviyah Muhammad Muharrom Al Haromainy Mustika Rizki, Agung Nadia Nuraniya Kamaluddin Noviala Dwijayanti, Ayunda Noviana Prima Nurwijayanti Oki Dwi Endras Setyo Oscar, Schersclight OWB, Sektalonir Prihatin, Kukuh purbaningtyas, daru Purwono Purwono Purwono, Purwono Putrawirawan, Ashadi RAHAYU WIDYASTUTI Rahmat Rahmat Rahmawati, Heni Rahayu Rahmawati, Rahmawati Rahutomo, Suroso Ramadhan, Nur Muhammad Rengga, Fedrian Ahmadthur Reza Hanjaya Rija Sudirja Roedy Kristiyono, Roedy RR. Ella Evrita Hestiandari Santoso, Dwi Andreas Santoso, Sri Fuji Septiani, Nia Siswo Wardoyo Siti Nurzakiah Soelistianto, Farida Arinie Sri Ayu Winarti Sri Djuniwati Sri Indrawanti, Annisaa Sugiarto, Anton Sugimin . Sugiyanta Sujiati Jepriani Sukma, Azizah Marwa Sumarsih, Enok SUNARNO Suria Darma Tarigan Suroso , Priyo Suroso, Priyo Syaiful Anwar Syarifah Hudayah Teguh Firmansyah Tistro, Rafian Tumingan Untung Sudadi Vita Via, Yisti Wahid, Radical Rakhman Wardana, Amir Wibowo, Haryo Bagus Widiawati, Dhiana Dwi Wiyono Wiyono Yasmuna , M. Rajiv Yisti Vita Via Yusuf, Sri Malahayati