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Slamet Widodo
Politeknik Negeri Semarang
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Rapid Analysis of ICUMSA Value of Cane Sugar Using Multi-Channel Spectra Sensor Based-Portable Device Khairani, Fadhilah; Khairani, Fadilah; Solahudin, Mohamad; Widodo, Slamet
Jurnal Keteknikan Pertanian Vol. 12 No. 3 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.3.409-423

Abstract

One of important quality parameters of white crystal cane sugar is its color, which is measured as the ICUMSA value referring to the standard method established by the International Commission for Uniform Methods of Sugar Analysis (ICUMSA). It is usually measured in a laboratory using a complex and lengthy chemical analysis method. To overcome this challenge, this research attempts to explore the potential use of multi-channel spectral sensors in the UV-Vis-NIR region as an alternative method to predict the ICUMSA value. The proposed portable device uses an AS7265X sensor as the main component. The spectra data of 60 cane sugar samples were collected using the proposed device followed by measurements of ICUMSA value in the laboratory using standard methods as reference. The prediction using partial least squares regression (PLSR) model achieved R2 = 0.896, RMSEC = 0.072%, RMSEP = 0.103%, CV = 26.087%, and RPD = 3.104. The multiple linear regression (MLR) model achieved R2 = 0.910, RMSEC = 0.067%, RMSEP = 0.111%, CV = 24.328%, and RPD = 3.328. The artificial neural network (ANN) model achieved R2 = 0.999, RMSEC = 0.004%, RMSEP = 0.037%, CV = 1.433% and RPD = 9.543. This result indicates that the developed PLSR, MLR, and ANN models can predict the ICUMSA value well with ANN as the best model. It also can be concluded that the proposed portable device can be an alternative for rapid analysis of ICUMSA value.
Non-destructive Prediction of Brix Value in Sugarcane Based of Portable NIR Spectroscopy Ahmar, Afdhalul; Solahudin, Mohamad; Widodo, Slamet
Jurnal Keteknikan Pertanian Vol. 12 No. 3 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.3.424-437

Abstract

The quality of sugarcane in the plantation is the most important information for farmers and sugar factories for assessing the maturity of sugarcane and determining the optimal harvest schedule. The brix value is used as a quality index in the sugar industry and is an important parameter for the evaluation of cane quality and maturity. Traditional methods of determining brix involve time-consuming and labor-intensive processes, often involving destructive sampling. To overcome these challenges, this study proposes a non-destructive approach using portable near-infrared (NIR) spectroscopy to predict the sugar content in sugarcane stalks. The main objective of this study was to develop a nondestructive prediction model for the brix value in sugarcane using portable NIR spectroscopy. Data processing involved two models: Partial Least Squares (PLS) and an Artificial Neural Network (ANN), along with various data pre-treatment techniques. The PLS model showed an improvement in prediction accuracy with data pre-treatment, especially with the Savitzky-Golay method (R2 = 0.755, RMSEP = 1.22%, RMSEP = 1.43%, CV = 6.13%, and RPD = 2.02). In addition, the ANN model combined with Principal Component Analysis (PCA) showed high predictive performance when sugarcane was 11 months old (R2 = 0.797, RMSEC = 0.56%, RMSEP = 0.87%, CV = 3.04%, and RPD = 2.96).
Adaptive-Historical Energy-Efficient Temperature Control for Tropical Greenhouses Laumal, Folkes; Suhardiyanto, Herry; Solahudin, Mohamad; Widodo, Slamet
Jurnal Keteknikan Pertanian Vol. 13 No. 1 (2025): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.013.1.55-73

Abstract

Maintaining an optimal microclimate is essential for efficient operation of tropical greenhouses, particularly under fluctuating weather conditions. This study proposes an adaptive energy-efficient model for regulating air temperature in tropical greenhouses using historical climate data. The model optimizes the fan rotation speeds via an inverter to meet the temperature targets while minimizing energy consumption. Key methodologies include climate data analysis, development of a predictive model for indoor air temperature using Artificial Neural Networks, and optimization of fan speed control. The model achieved high predictive accuracy, with an RMSE of 0,02 and an R² of 0,96. The practical implementation demonstrated effective temperature control, with fan speeds ranging between 30 and 40 Hz during cloudy periods and 50 Hz in sunny conditions. Notably, the system reduced electricity consumption by 33,93% during cloudy weather and 18,54% in sunny weather, showing its potential for significant energy savings. This data-driven adaptive model approach is highly suited for tropical greenhouses experiencing dynamic climatic variations and offers a sustainable and efficient solution for greenhouse microclimate management.
Prediction of Phenotypic Parameters of Sugarcane Plants Based on Multispectral Drone Imagery and Machine learning Hasskavendo, Febri; Solahudin, Mohamad; Supriyanto, Supriyanto; Widodo, Slamet
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1182-1195

Abstract

Measuring phenotypic parameters is important in evaluating the productivity of sugarcane. Existing manual measurements are considered less efficient, so a better alternative method is needed. This research aims to explore the potential of using multispectral drone imagery and machine learning to estimate phenotypic parameters of sugarcane plants that are efficient, accurate, inexpensive, and support sustainable agricultural practices. Spectrum data captured by drones, namely Green, Red, RedEdge and NIR are used as inputs to estimate phenotypic parameters including brix value, number of stands, stem diameter, and plant height. Based on the results of machine learning model development, the ANN algorithm model is most effective in predicting Brix Value with R2 0.74 and RMSE 0.06 and number of stands with R2 0.68 and RMSE 2.13. All models could not predict stem diameter and plant height well. The best model to predict plant height was obtained by RF algorithm with R2 0.53 and RMSE 14.09. SVR algorithm was the best model to predict plant diameter with R2 0.39. and RMSE 0.49. This indicates that the effectiveness of an algorithm depends on the specific parameter being predicted and there is no dominant algorithm for all phenotypic parameters. Keywords: Machine learning, Multispectral drone imagery, Phenotypic parameter, Plant productivity, Sugarcane.
Performance Comparison of Two Portable Near-infrared Devices for Rapid Authentication of Aceh Aromatic Rice ‘Sigupai’ Widodo, Slamet; Masyitah, Masyitah; Purwanto, Yohanes Aris; Njume, Akeme Cyril
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.851-862

Abstract

Sigupai rice, Indonesia local aromatic rice varieties grown in South-West region of Aceh, is highly valued for its fragrance and quality, making it susceptible to adulteration. This study compares the performance of two portable Near-infrared (NIR) devices, SCiO and NeoSpectra, for rapid authentication of Sigupai rice. We evaluated 86 samples for qualitative analysis (i.e. authentic vs adulterated rice) and 44 samples for quantitative analysis (i.e. the level of adulteration). For the qualitative analysis using partial least squares-discriminant analysis (PLS-DA), the best estimation model could differentiate authentic and adulterated samples with an accuracy, sensitivity, specificity, and false positive rates of 89.29%, 92.86%, 85.71% and 14.29% for the NeoSpectra and 97.44%, 100%, 94.87%, and 5.13% for the SCiO, respectively at the validation stage. For quantitative analysis using partial least squares-regression (PLS-R), the best estimation model could estimate the level of adulteration with a coefficient of determination (R²), RMSEP, RPD, and consistency values of 0.92, 1.50%, 5.93 and 100.69% for the NeoSpectra and 0.96, 1.31%, 6.83 and 104.78% for the SCiO. Both portable NIR devices could be used as a rapid analysis tool for the authenticity of Sigupai rice with high accuracy. However, in this study the SCiO device showed a better performance. Keywords: Portable NIR device, Authentication, Aromatic rice, Rapid analysis, Sigupai variety.
Portable Near-Infrared Spectroscopy and Support Vector Regression for Fast Quality Evaluation of Vanilla (Vanilla planifolia) Widyaningrum, Widyaningrum; Purwanto, Yohanes Aris; Widodo, Slamet; Supijatno, Supijatno; Iriani, Evi Savitri
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.515-526

Abstract

Vanilla (Vanilla planifolia) is a high-value agricultural product, with its quality influenced by essential factors such as moisture and vanillin content. Conventional techniques for evaluating these characteristics are inefficient, require sample destruction, and are impractical for swift assessments. This research explores the feasibility of using portable Near-Infrared (NIR) spectroscopy combined with Support Vector Regression (SVR) to enable quick and noninvasive property prediction. Spectral information was obtained from vanilla samples using two portable NIR instruments, SCiO (740–1070 nm) and Neospectra (1350 2550 nm). Preprocessing techniques such as normalization, SNV, MSC, first derivative, first derivative-SNV, and first derivative-MSC were applied. For moisture content prediction, SCiO achieved an R² of 0.768, an RMSE of 4.720%, an RPD of 2.075 and an RER 10.197 using Min-Max normalization, while Neospectra yielded an R² of 0.758, an RMSE of 5.161%, an RPD of 2.033 and an RER 9.325 with MSC preprocessing. In contrast, predicting vanillin concentration proved more challenging, with SCiO achieving moderate accuracy with an R² 0.406, an RMSE 0.379%, an RPD 1.297, an RER 5.039, and Neospectra demonstrating limited performance with an R² 0.172, an RMSE 0.576%, an RPD 1.098 and an RER 3.315. These findings highlight the potential of portable NIR spectroscopy as a practical tool for assessing vanilla quality, particularly for moisture content, in industrial and field applications. Keywords: Moisture content, Portable NIR spectroscopy, Support vector regression, Vanilla planifolia, Vanillin content.
Fluorescence Imaging as a Non-Destructive Method for Aflatoxin Detection in Corn Kernels: Recent Advances and Challenges Nofiyanti, Sri Handayani; Ahmad, Usman; Tondok, Efi Toding; Widodo, Slamet
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.714-731

Abstract

Fluorescence imaging has developed as a promising non-invasive method for identifying aflatoxin contamination in agricultural commodities, especially corn kernels. This paper examines current improvements in fluorescence imaging technologies, highlighting its potential to improve food safety through swift and precise detection of mycotoxins. The paper examines the basics of fluorescence, the necessary setup for optimal imaging, and the issues related to background fluorescence interference, sensitivity, and the construction of calibration models. Although there are some limitations, fluorescence imaging presents considerable advantages, such as cost-efficiency and the capacity to obtain concurrent spectral and spatial data. Proposed future research objectives include the validation of imaging systems using naturally contaminated samples, the optimization of imaging parameters, and the integration of machine learning techniques to enhance data processing. By overcoming existing constraints and utilizing technical progress, fluorescence imaging can serve as an essential instrument in the detection of aflatoxin contamination, hence enhancing food safety. Keywords: Aflatoxin, Detection, Fluorescence imaging, Food safety, Machine learning.
Livelihood Strategies and Adaptation of Sonok Cattle Farmers During the COVID-19 Pandemic Safariyah, Laelatus; Zuhriyah, Amanatuz; Widodo, Slamet
JURNAL ILMIAH PETERNAKAN TERPADU Vol. 12 No. 3 (2024)
Publisher : DEPARTMENT OF ANIMAL HUSBANDRY, FACULTY OF AGRICULTURE, UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jipt.v12i3.p220-235

Abstract

Madura is an area in Indonesia that is well-known for its high cattle population. However, like many other industries, the Sonok cattle business in Madura has been greatly impacted by the COVID-19 pandemic. In order to determine the extent of this impact, as well as the adaptation and livelihood strategies of Sonok cattle farmers, a study was conducted in West Dempo Village, Pasean District, Pamekasan Regency. This village is the center of superior Sonok cattle and the origin of their existence. The study used descriptive statistics as its method and found that the pandemic has caused a decline in the prices of Sonok cattle and lowered the motivation of farmers to buy them. As a result, farmers have had to adapt and reduce costs wherever possible. The access to capital owned by Sonok cattle breeders, however, is relatively good and is used to form a livelihood strategy. These strategies include on-farm strategies, multiple livelihood patterns, and migration. In response to the pandemic, some farmers have also added other farm animals, such as fighting chickens, to their livelihood strategies.
MOTIVASI MASYARAKAT DALAM MEMBUDIDAYAKAN AYAM GAOK DI PULAU POTERAN, KABUPATEN SUMENEP, JAWA TIMUR Wulandari, Anggi Dwi; Zuhriyah, Amanatuz; Widodo, Slamet
Jurnal Ilmu Ilmu Agribisnis: Journal of Agribusiness Science Vol. 13 No. 1 (2025)
Publisher : Lampung University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jiia.v13i1.8652

Abstract

One of the native chicken breeds in Indonesia with the potential for broiler development is the gaok chicken, originating from Poteran Island, Sumenep Regency, East Java. This research aims to understand the motivations of the community in breeding native chickens. The study was conducted in three villages on Poteran Island, Sumenep Regency, namely Palasa Village, Gapurana Village, and Essang Village. The selection of these locations was based on the origin of the native chicken, Poteran Island, which is administratively situated in Talango District, Sumenep Regency, East Java. A sample of 30 respondents was determined using the snowball sampling technique. The research was conducted from September 2023 to February 2024. Data collection was carried out through structured interviews employing a questionnaire. Motivation in this research was assessed through three aspects: existence needs, relatedness needs, and growth needs. Measurement utilized Likert scales and was analyzed descriptively. The study's findings indicate that the level of motivation among the community to breed native chickens mostly falls into the low category. Keywords: existence needs, growth needs, motivation, native chicken, relatedness needs
ANALYSIS OF VITAMIN D LEVELS & COMPLETENESS OF COVID-19 VACCINE WITH RECURRENT COVID-19 INFECTIONS: Hubungan Kadar Vitamin D dan Kelengkapan Vaksin COVID-19 dengan Kejadian Infeksi COVID-19 Berulang pada Dosen Universitas Malahayati Nurjanah, Siti; Hermawan, Dessy; Aryastuti, Nurul; Muhani, Nova; Furqoni, Prima Dian; Sary, Lolita; Widodo, Slamet
Amerta Nutrition Vol. 8 No. 1 (2024): AMERTA NUTRITION (Bilingual Edition)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/amnt.v8i1.2024.33-39

Abstract

Background: There is a continued increase in the fatality rate of COVID-19 pandemic despite the apparent containment of the virus. In September 2022, the death toll from this disease has exceeded 150 thousand individuals. Furthermore, Vitamin D has been observed for its correlation with the immune system. Objectives: This study aimed to analyze correlation between blood vitamin D levels, completeness of COVID-19 vaccine, and compliance with health protocols for recurrent infection. Methods: This analytical observational study with a cross-sectional method examined correlation between blood vitamin D levels, vaccine completeness status, as well as compliance with health protocols, age, and gender. The population consisted of 62 lecturers at Malahayati University, Bandar Lampung, who were willing to volunteer as subjects. The method used was non-probability sampling and the inclusion criteria were individuals infected with COVID-19 in 2022, resulting in 47 samples. The collected data was analyzed using the chi-square test and logistic regression test. Results: The results showed that there was a significant correlation between the completeness status of COVID-19 vaccine (p-value=0.001) with an OR of 8.24 and 8.47, as well as low levels of vitamin D in the blood (p-value=0.007) and recurrent infection. Conclusions: The possibility of recurrent COVID-19 infection was increased when there were lower levels of vitamin D in the bloodstream and a less comprehensive response to vaccine.
Co-Authors , Nashrudin Setiawan - Hermawan - Kamarullah - Nurhayati - Ridwan - Sutarno -, Elkanady -, Sugihartono ., Sawaluddin A. Rahman, Rian Hidayat Abizar, Koswari Abu Hasan Abubakar Alwi Abubakar, Endang Achmad, Netto Adam Alamsyah, Juan Adhy Putri Rilianti Adi Wibowo, Nur Afifah, Luthfiyah Afriani, Nur Afrilia, Tiara Agrista, Pregi Agus Susanto Ahmad Madaul, Rahful Ahmar, Afdhalul Aji, Dwiki Nusantara Akhmadali . Akhmadali, - Akhmadali, Akhmadali Alam, Risma Alamsyah - Albert, Jhoni Alfianda, - Alfina Maysyurah Alfirahman, Rifki Alfitri Alfitri alhadi, alvia Alparizi, Melki Amalia, Reni Amanatuz Zuhriyah Amanda, Adisa Tria Ami, Hidayati Amir Muhiddin, Amir Amir, Sakinah Andriani, Nety Andy Alfatih Anggia Dewi, Sapteriawuri Anggraini, Ade Fitra Anom, Antonius Haryo Pungkas Anton Royanto Ahmad Anugerah, M Dias Apriansyah Aprianti, Dwi Wahyuni Aprianti, Endang Apriantoro, Roni APRILIANA, APRILIANA Ardhyantama, Vit Ardyansyah, Surya Arianto, Yogik Arif Bramantyo, Hutama Arif Bramantyo, Hutama Arif Bramantyo Aris Budiyanto Aris Munandar Ariyani, Aminah Happy Moninthofa Armiwaty, Armiwaty Arum Ratnaningsih Aryastuti, Nurul Aski Safarizki, Hendramawat Asnawi, Uray Farizi Aulia, Rizqiandrie Zakie Auliatama, Randy Julianda Ayu Agustin, Wilujeng Baidlowi, Muhammad BAKHRANI RAUF Bani, - Basry, Wahyuddin Berlilana Besse Qurani Betarina , Nurmalia Budi, Setio Budiarti, Ade Tia Bungaalsa, Sirfia Kaulani Busyro, Muhammad Alvin Cahyani, Shofi Yulia Chofiyana, Robbi’ul Dalfian, Dalfian Darmawang, Darmawang Daryoto ., Daryoto Daud, Pamungkas Dealisa, Laora Desembardi, Faried Desembardi, Faried Desembarti, Faried Destiarni, Resti Prastika Dewi ANGGRAENI Dian Farida Asfan Dian, Ansela Brigita Didik Setyo Purwantoro efendi, Usti rustam Efi Toding Tondok Eka Priadi Eka Rahma Sari, Eka Rahma Ekaputri, Seprianti Eko Sediyono Elsa Tri Mukti Elvira Elvira Endang Abubakar Erizal Ermansyah, Derry Erwin Supriadi Eti Sulandari Etty Harya Ningsi Evi Savitri Iriani, Evi Savitri Ezzel, Nevara Meisya Fadhilah Khairani, Fadhilah Fadly, Galih Fadzilah, Nur Fajriani, Qonaah Falderika, Falderika Fandy Setyo Utomo Fatikhunnada, Alvin Fatikhunnada Fauzi, Hafidz N. Felderika, Felderika Ferianto, Maidar Ferry Juniardi Festy Ladyani Mustofa Ficayuma, Lina Aris Fiky Y. Suratman Fiona, Febzi Firmanda, Abied Fitri Yanti Fitriani, Lia Firdia Fitriyanto, Azis folkes laumal, folkes Frangky Silitonga Furqoni, Prima Dian Gawarti Gawarti, Gawarti Ghiffari Ramadhan, Aqsal Ginta Perdana, Fakhruddin Goib Wiranto, Goib Gumilar, Rian Doto Gusti Zulkifli Mulki Habiburrahman, - Hadi Riyadi Hadwi Widi Sasono, Sindung Haerani Haerani Hakim, Faisal Hananiyah, Hananiyah Handayani, Pretty Ramdhawuri Handayani, Raynanda Hanif, Sayed Muhammad Hardianti, Andi Haris Haris, Haris Hasskavendo, Febri Hayati, Soufiana Heri Azwansyah Heriyadi, - Herlambang Brawijaya Herlambang Saputra Herliza Hermawan, Dessy Herry Suhardiyanto Hery Setijasa, Hery Hesti Wulandari Hidayat Hidayat Hidayat, Nanang Hidayati, Ridha Hifni, Muchammad Hilmi Hilmansyah Hilmi Hilmansyah Hs, Atika Maulidina Hutapea, Sabar Maranatha Ica, Mariani Idhawati Hestiningsih Iffan Maflahah Ikeu Tanziha Indika, Angelia Drata Iqbal Iqbal Irna Triannur Lubis Ishak Hasan Ishaq, Muhammad Maulana Isnaini, Ardi Fajar Israk, Galamda Jeanilora, Jeanilora Jemi, Marlianilius Judhi, Julius Juliarsih, Santi Junaidi, Lalu Muhamad Jusman, Ika Kadarini, S. Nurlaily Kadir, Kasdy Kameistu, Ponsianus Kanang S. Hindarto, Kanang Karim, Sugeng A. Karimah, Nur Karnela, Karnela Karomah, Diah Kasyfi, Fathul Qadir Katmoko, Desi Susilo Keswara, Umi Romayati Khafizan, - Khairani, Fadilah Khairul Rizwan, Al Khasanah, Sholikhatun Kholifah, Aisyah Nur Klau, Stevanus Viki Komala Erwan Kristanto, Benny Kuncoro, Ardityo Dwi Kurniati Kurniati Kurniawan, Ardian Kurniawan, Fikar Kurniawan, Yengkie Kurrahman, Taupik Kusman, Asep Kussoy, Steven Daniel La Ibal Laila, Ema Laksana, Ryan Dharmawan Lambok Manurung Lembang Jaya, Muhamad Lestari, Syndi Aprilia Lesyani, Agustinus Hendy Linda, Rizky Fadjar Choirul Liyantono Lolita Sary Lubis, Anwar Lubis, Etrie Septiani LUBIS, IRNA TRIANNUR M. Sobri, Kgs, Ma'arif, Faqih MADE ASTAWAN Malawat, Titi Marchelli, Edni Mardianto Mardiyah Mardiyah Maris Setyo Nugroho Marlena, Leni Marpaung, Zailani Surya Marsudi, - Marwahyudi Marwahyudi Maskatim Masyitah Masyitah Mega Wulandari, Mega Melyng, Navisa Tan Minardi, - Mi’roj, Az-zahratul Mohamad Solahudin Mohammad Khambali, Mohammad Muhammad Afief Mubayyin Muhammad Farid Muhammad Jufri Muhammad Nur Fajar Muhani, Nova Muharrama, A. Firli Augina Muliani Muliani Muliani, Muliani Mumtaz, Putri Yasmin Munazil, Chilmy murni murni Murni Murni Murshal Manaf, Murshal Muslimah, Nadiyah Mu’alif, Fazar Nabila, Risma Nahriana Nahriana, Nahriana Najwa, Wulida Arina NANIK PURWANTI Nasution Nasution Neving, Diliardi Ngazizah, Nur Njume, Akeme Cyril Nofiyanti, Sri Handayani Noratama, Gilang Nova Kurniawan Novi Diana Badrut Tamami Novianto, Verry Nugraha, Nosa Nujum, Laelatul Nur Aida, Nur Nur Azizah, Firda Nikmah Nur Ilmi Azisa Nurafrina Siregar Nurhayati Nurhayati Nurhayati Nurhijrah Nurhijrah, Nurhijrah Nurkhowati, Nurul Nurmaizar, Siti Nursafitri, Reza Nursyahrifa, Nursyahrifa NY, Erlina Satri Okgarianda, Jimmi Oktaviana, Ananda Rizka Oktomi, Abang Vebri Patrysya, Chelina Putri Permadi, Agung Satriyo Permata, Inonsensia Injilia Intan Pradana, Afanda Satya Prakasa, Aras Teguh Pramesti, Woro Prameswari, M. Mikhus Sammawati Pranata, Harry Mulya Prasetyo, Julyar Pratama, Nugraha Yuda Pratama, Nurul Hidayah Prayoga, Muhammad Andi Pristianto, Hendrik Pritasari, Laili Pujianto, Julianus Purify, Aura Purwansih, Deta Mardiana Pusaka, Semerdanta Puspita, Anggri Puspita, Windy Eka Putra, Mukti Trio Putranto, Muhammad Agung Putri, Asri Mutiara Qur'ani, Besse Qur’ani , Besse Rachmi, Dewi Rafinzar, Rahmat Rahadi, - Rahayu, Usiyani Rahesta, Nindira Tartila Rahful A. Madaul Rahmah Hidayah, Alisah Rahmansah Rahmi Ariani Salam Rajiv Ramadan, Irvan Ramadhan, Andra Ramadhani, Jiyan Ockta Ramadhoni, Eggy Putra Raniasa Putra RATNAWATI Ratnawati Ratnawati Ratnawati T Rian Histiariani, Aprisa Rilyani, Rilyani Rissa Megavitry Rizal, - Rizal, Ali Syah Rochmanto, Raditya Artha Rochmatika, Rizkha Romadhon, Akbar Rosita Hermiyati Rosmaniar Gailea Rosmini Maru Roy Waluyo Rudi Sugiono Suyono, Rudi Sugiono Rumakefing, Sadli Ruskamdi S Nurlaily Kadarini S, Pebriyetti S. Suyono, Rudi Safariyah, Laelatus Sahari, Wira SAID . Said Basalim Said Said, Said Saifuddin Sirajuddin Sajali Sakina, Putri Salihin, Sakina Marwa Sam Herodian Samudi Samudi Saputra, Andhika Sahid Saputra, Ryan Perdana Saputri, Nining Saputro, Eko Danan Sarfin, Anggie Anjani Sarpawi, - Sarwoko, Iwan Satriyo, Wahyu Sembiring, Rinawati Semil, Nurmah Septhalia, Aisyah Putri Septi Ambar Indraningtia Sukma Setiawan, Wildan Setiawati, Octa Reni Setya Permana Sutisna Setyanto Setyanto Sholahuddin Sigit Mujiharjo, Sigit Sigit Nugroho Simamora, Herberto Yeremia Sindung HW Sasono, Sindung HW Siti Mayuni Siti Nurjanah Siti Nurlaily Kadarini, Siti Nurlaily Situmorang, Milton Sjahriani, Tessa Slamet Subari Slamet Widodo Sobri, Kgs M. Sobri, Kgs, M. Soenawan, Rapwansoni Soengkono Slamet Widodo, Soengkono Sofitra, M. Sri Ratna Triyasari, Sri Ratna Sriati Sriati Sriati, Sriati Sriyanto Sriyanto Stefanus, Stefanus Sugasta, Hervian Handika Sugiarti, Teti Sugiono, Rudi S Suhardi Suhardi Suhendi Suhendi, Redi Sukariyadi, Teja Insyaf Summiyattinah, - Supardi, Stepanus Supijatno Supratman, Iknatius Eko Supriyanto Supriyanto Supriyono Supriyono Suryadwanti, Novia Suryani, Pegi Suryosukmono, Gerry Susetyo, Sugeng Susianto, - Sutarno Sutarno Sutiono, Wilis Sutrisna, Dedy SUTRISNO Sutrisno, Ady Suyono, Rudi S. Syahputra, Budi Syamsidah, Syamsidah Syamsul Hidayat, Sidiq Syamsuriah T., Ratnawati Tahan Prahara, Tahan Prahara Tajuddin, Tamrin Tamala, Evi Tamaulina Br Sembiring Teguh Pribadi Thamrin, Djuni Thamrin, M.H. Thomas Agung Setyawan, Thomas Agung Turrahmi, Aulia Udin Sidik Sidin Ummi Hanifah Marshush Ummi Marshush Usman Ahmad Utama, M Ramadhi Waruwu, Ahmad Wati, Erni Sisna Wibowo, Romadhonsyah Putra Widhya Budiawan, Widhya Widiarsa , I Nyoman Gede Widuri, Bunga Widyaningrum Widyaningrum Widyantara, Muhamad Ridwan Wulandari, Anggi Dwi Yasdin, Yasdin Yoke Lestyowati Yolanda Saraswati, Ni Putu Yon Saputri, Lintang Tiara Yulendasari, Rika Yulianti, Yuni Zaini Zaini Zainudin, - Zaqlul Iqbal