Article Per Year (5 Year)
p-Index From 2020 - 2025
4.068
P-Index
This Author published in this journals
All Journal MEDISAINS International Journal of Advances in Intelligent Informatics Jurnal Rekayasa Mesin ZOO INDONESIA JOIV : International Journal on Informatics Visualization Journal of Applied Information, Communication and Technology (JAICT) Home Economics Journal Journal of Maternal and Child Health Journal of Telenursing (JOTING) Indonesian Journal of Global Health research MAHESA : Malahayati Health Student Journal Abditeknika - Jurnal Pengabdian Kepada Masyarakat Society: Jurnal Pengabdian Masyarakat Journal Of Human And Education (JAHE) Innovative: Journal Of Social Science Research Berita Biologi
Kurnianingsih Kurnianingsih, Kurnianingsih
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Geographical Variations in Moringa Oleifera and Its Potential for Stunting Intervention: A Systematic Review Muryasari, Ika; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih; Aquarista, Nita
Indonesian Journal of Global Health Research Vol 7 No 3 (2025): Indonesian Journal of Global Health Research
Publisher : GLOBAL HEALTH SCIENCE GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37287/ijghr.v7i3.5787

Abstract

Stunting is a major global health issue, particularly in Indonesia, where malnutrition rates remain high. Poor childhood nutrition affects growth, cognition, and long-term health. Moringa oleifera is a nutrient-rich herbal supplement, but its nutritional composition varies by geography, potentially influencing its effectiveness in stunting interventions. Objective: To identify the best Moringa leaf source for extract production to support weight and height improvement in stunted children. Method: A systematic literature review (SLR) was conducted using Google Scholar, ScienceDirect, and PubMed (2014–2024). From 70 initially identified articles, 6 were selected using the PICOS method, focusing on Moringa supplementation, malnourished children, and growth outcomes. Results: Highland Moringa contains higher vitamin C and flavonoid levels, while lowland Moringa offers greater biomass for large-scale production. Studies confirm that dried Moringa extract significantly improves weight gain (p = 0.002), though its effects on height and inflammation reduction were less pronounced. Conclusion: Dried Moringa extract shows promise for weight gain and nutrition enhancement in stunted children. However, geographical factors influence its nutrient content, requiring further research to standardize formulations, optimize dosages, and assess long-term effects in human trials.
Implementation of Web-Based Marketing System Technology for Bakat Jaya MSMEs, Magelang Aji, Nurseno Bayu; Yudantoro, Tri Raharjo; Mardiyono, Mardiyono; Kurnianingsih, Kurnianingsih; Yanwari, Muhammad Irwan; Kuntarjo, Samuel Beta; Anif, Muhammad; Wiktasari, Wiktasari; Prayitno, Prayitno; Triyono, Liliek
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2025): Mei
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i3.571

Abstract

This study explores a digital transformation initiative implemented for UMKM Bakat Jaya, a micro-enterprise based in Magelang specializing in animal feed production. Initially hindered by limited market reach, low digital literacy, and a lack of integrated technological tools, the enterprise relied primarily on traditional social media platforms for promotion. To address these challenges, a comprehensive and user-friendly website was developed using WordPress, featuring a professional company profile, product gallery, contact information, and seamless integration with existing social media accounts. The project was executed in four key phases: needs identification, website design and development, training and mentoring, and implementation followed by evaluation. Remote interviews and surveys were conducted to assess the partner’s needs, while capacity-building activities empowered stakeholders to manage the digital platform independently. Preliminary outcomes indicate a substantial improvement in market visibility, customer engagement, and operational efficiency. The results highlight the potential of structured digital interventions to transform the promotional strategies of rural micro and small enterprises, offering a scalable and sustainable model for enhancing competitiveness in similar contexts.
Efektivitas Penggunaan Media Gambar Dalam Pembelajaran Menulis Deskripsi Di Kelas IV SD Pebriana, Putri Hana; Nurhaswinda, Nurhaswinda; Kusuma, Yanti Yandri; Henra, Mustika; Miyar, Miyar; Kurnianingsih, Kurnianingsih
Innovative: Journal Of Social Science Research Vol. 4 No. 1 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i1.15953

Abstract

Penelitian ini bertujuan untuk menguji efektivitas penggunaan media gambar dalam pembelajaran menulis deskripsi di kelas IV SD. Media gambar digunakan sebagai alat bantu visual untuk membantu siswa mengembangkan kemampuan menulis deskripsi yang lebih baik dengan cara memberikan stimulus visual yang konkret. Metode penelitian yang digunakan adalah kuasi eksperimen dengan desain pretest-posttest. Subjek penelitian adalah siswa kelas IV di sebuah sekolah dasar yang dibagi menjadi dua kelompok: kelompok eksperimen yang menggunakan media gambar dan kelompok kontrol yang tidak menggunakan media gambar. Data dikumpulkan melalui tes menulis deskripsi sebelum dan sesudah pembelajaran. Hasil penelitian menunjukkan bahwa penggunaan media gambar secara signifikan meningkatkan kemampuan siswa dalam menulis deskripsi, terutama dalam hal penggunaan kata-kata yang lebih kaya dan deskripsi yang lebih rinci. Media gambar terbukti efektif dalam membantu siswa memvisualisasikan dan mendeskripsikan objek dengan lebih baik dalam tulisan mereka.
Classification System of Crystal Guava (Psidium Guajava) Using Convolutional Neural Network And Rectrified Linear Unit Method Based on Android Wiktasari, Wiktasari; Yudantoro, Tri Raharjo; Alifiansyah, Muhammad Fikry; Kurnianingsih, Kurnianingsih; Triyono, Liliek; Hasan, Abu
JAICT Vol. 10 No. 1 (2025)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v10i1.6170

Abstract

These instructions Abstract - However, determining the ripeness of fruit is frequently done by hand, which presents problems with consistency and efficiency. In order to improve the sorting of crystal guava fruit maturity, this study suggests combining machine learning technology with the creation of digital image-based apps. Fruit ripeness is classified using a convolutional neural network (CNN), a deep learning model, based on the color of its skin. It is anticipated that the method will increase productivity and offer superior precision while sorting crystal guava fruit. The System Development Life Cycle (SDLC) with a Waterfall approach is the methodology employed. The system design formed from the deep learning model resulted in excellent performance in classifying images of crystal guava fruit by utilizing model training from the base models ResNet50V2, DenseNet121, NASNetMobile, and MobileNetV2 with a combination of training using K-fold cross-validation with a 5-fold configuration. The best-trained model achieved an average highest accuracy of 99.92% in model training using MobileNetV2 with the lowest average loss value of 0.0088. The system application was developed using mobile Android, leveraging the Flutter framework and Dart programming language. The research results demonstrate a comparison of testing on crystal guava and local guava fruits against ripeness classification parameters
Penerapan Teknologi Sistem Penilaian Guru di Yayasan Islam Nurus Sunnah Wiktasari, Wiktasari; Yudantoro, Tri Raharjo; Mardiyono, Mardiyono; Kurnianingsih, Kurnianingsih; Sulistiyo, Wahyu; Prayitno, Prayitno; Triyono, Liliek; Yanwari, M. Irwan; Aji, Nurseno Bayu; Fahriah, Sirli; Fitriyani, Rizki Putri; Santosa, Naufal Adli
Abditeknika Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2024): April 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v4i1.3022

Abstract

Pada era saat ini hampir semua kegiatan tidak terkecuali bidang pendidikan sudah menerapkan penggunaan teknologi dalam menjalankan kegiatan pembelajaran. Yayasan Islam Nurus Sunnah yang terletak di Kelurahan Bulusan Kecamatan Tembalang Kota Semarang belum menerapkan teknologi informasi untuk sistem penilaian guru. Permasalah utama yang ada Yayasan Nurus Sunnah ini adalah melakukan penilaian guru mitra masih dilakukan secara manual sehingga mengalami beberapa kendala. Kendala yang dihadapi yaitu data yang tidak terintegrasi, kurangnya aksesibilitas terhadap data, proses penilaian yang tidak fleksibel dan keamanan data yang kurang terjamin. Alternatif solusi yang akan diterapkan pada mitra tersebut adalah menyediakan sistem online berbasis web untuk proses penilaian kinerja guru. Proses digitalisai penilaian guru diharapkan dapat mengintegrasikan data dan mempermudah proses penilaian guru. Kegiatan ini terdiri dari empat tahapan, tahapan pertama adalah identifikasi kebutuhan untuk kegiatan observasi lapangan, diskusi dengan mitra, dan analisis situasi untuk menetapkan permasalahan yang dihadapi mitra. Tahapan  kedua adalah perencanan dilakukan dengan proses desain aplikasi dan database aplikasi online berbasis web serta pembuatan aplikasi web dan database. Tahapan ketiga digunakan untuk pelatihan SDM agar terampil dalam mengoperasikan sistem aplikasi berbasis web dan sekaligus dilakukan uji coba (trial and error) penerapan dan koreksi sistem aplikasi web. Tahapan keempat adalah evaluasi terkait kerja sistem. Impelementasi hasil kegiatan menunjukkan meningkatkan performansi kegiatan penilaian guru yang dilakukan setiap periode menjadi lebih cepat dan akurat. Mitra mendapatkan dampak positif dengan diterapkannya sistem digitalisasi sistem penilaian guru. Solusi ini yang diberikan terbukti bisa efektif untuk membantu dalam manajemen penilaian guru pada mitra.   Nowadays, almost all educational activities are conducted online unless the field of education has already adopted the use of technology in teaching. The Nurus Sunnah of Islam that is practiced in the Kelurahan Bulusan Kecamatan Tembalang Kota Semarang does not use information technology for its guru certification system. The primary problem with this Yayasan Nurus Sunnah is that the mitra penilaian is mostly done manually, resulting in a few kendals. The data that is being handled include incomplete data, inconsistent data accessibility, non-flexible data processing procedures, and inconsistent data quality. Offering these partners a web-based online system for the teacher performance assessment procedure is an alternate approach that will be used. It is anticipated that the digitization process for teacher assessments will facilitate data integration and streamline the process. There are four stages to this activity. The first is determining the need for field observation exercises, partner discussions, and situation analysis to ascertain the issues that partners are facing. The creation of web applications and databases, along with the application design process and web-based online application database, comprise the second stage of planning. In the third stage, HR personnel receive training on how to effectively operate web-based application systems and conduct trial-and-error procedures for the purpose of implementing and optimizing web application systems. The assessment of the system's functionality is the fourth step. The application of the activity results demonstrates that there has been an increase in the speed and accuracy of the teacher assessment tasks completed each period. Partners' implementation of the teacher assessment system's digitalization has produced positive results. It has been demonstrated that this solution works well to help partners manage teacher assessments.
Pemanfaatan Electroencephakography (EEG) dalam Evaluasi Asfiksia Neonatal: Literatur Revieuw Veryal, Veryal; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih
MAHESA : Malahayati Health Student Journal Vol 5, No 11 (2025): Volume 5 Nomor 11 (2025)
Publisher : Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/mahesa.v5i11.19608

Abstract

ABSTRACT Neonatal asphyxia is one of the leading causes of death and neurological disorders in newborns. About 1 million babies die each year due to complications related to asphyxia. Decreased oxygen supply to tissues and brain can cause damage to the brain or even death if not treated appropriately. A rapid and accurate assessment of the severity of neonatal asphyxia is essential to determine effective interventions. Electroencephalography (EEG) is one of the diagnostic tools that can be used to assess the brain activity of newborns, especially in detecting injuries due to hypoxia-ischemia. The purpose of this study was to evaluate the recent literature on the use of electrocardiograms to identify and measure the intensity of neonatal asphyxia This study uses a systematic method of literature review by searching for articles in PubMed, Scopus, and ScienceDirect databases in the period 2020-2025. The results of the analysis showed that electrocardiogram (EEG) could detect significant changes in brain wave patterns in asphyxia patients, such as decreased brain activity, cessation of bursts, and the onset of pathological waves. In addition, EEG has been shown to predict long-term neurological complications, especially in newborns with perinatal asphyxia. Continuous EEG monitoring can also be helpful in determining therapy responses and developing treatment plans. EEG is an effective and non-invasive tool in the evaluation of asphyxia, both for early diagnosis and monitoring of the progression of the patient's condition. The utilization of EEG can improve the accuracy of prognosis and aid in clinical decision-making. However, more research is needed to create an optimal EEG use protocol for asphyxia cases. Keywords: Elecreoencephalography (EEG), Asphyxia, Brain Activity  ABSTRAK Asfiksia neonatal merupakan salah satu penyebab utama kematian dan gangguan neurologis pada bayi baru lahir. Sekitar 1 juta bayi setiap tahun meninggal akibat komplikasi terkait asfiksia. Penurunan pasokan oksigen ke jaringan dan otak dapat menyebabkan kerusakan pada otak atau bisa saja mengalami kematian jika tidak diatasi dengan tepat. Penilaian cepat dan akurat terhadap tingkat keparahan asfiksia neonatal sangat penting untuk menentukan intervensi yang efektif. Electroencephalography (EEG) adalah salah satu alat diagnostik yang dapat digunakan untuk menilai aktivitas otak bayi baru lahir, terutama dalam mendeteksi cedera akibat hipoksia-iskemia. Tujuan dari penelitian ini adalah untuk mengevaluasi literatur terbaru tentang penggunaan elektrokardiogram untuk mengidentifikasi dan mengukur intensitas asfiksia neonatal. Penelitian ini menggunakan metode sistematis literatur reviuew dengan pencarian artikel di database PubMed, Scopus, dan ScienceDirect pada periode 2020-2025. Hasil analisis menunjukkan bahwa elektrokardiogram (EEG) dapat mendeteksi perubahan pola gelombang otak yang signifikan pada pasien asfiksia, seperti penurunan aktivitas otak, penghentian burst, dan timbulnya gelombang patologis. Selain itu, EEG telah terbukti dapat memprediksi komplikasi neurologis jangka panjang, terutama pada bayi baru lahir yang mengalami asfiksia perinatal. Pemantauan EEG terus menerus juga dapat membantu dalam menentukan respons terapi dan menyusun rencana perawatan. EEG merupakan alat yang efektif dan non-invasif dalam evaluasi asfiksia, baik untuk diagnosis awal maupun pemantauan perkembangan kondisi pasien. Pemanfaatan EEG dapat meningkatkan akurasi prognosis dan membantu dalam pengambilan keputusan klinis. Namun, penelitian lebih lanjut diperlukan untuk membuat protokol penggunaan EEG yang optimal untuk kasus asfiksia. Kata Kunci: Elecreoencephalography (EEG), Asfiksia, Aktivitas Otak
LoRaWAN for Smart Street Lighting Solution in Pangandaran Regency Enriko, I Ketut Agung; Gustiyana, Fikri Nizar; Kurnianingsih, Kurnianingsih; Puspita Sari, Erika Lety Istikhomah
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1198

Abstract

Smart street lighting is a key application in smart cities, enabling the monitoring and control of street lamps through internet connectivity. LoRa/LoRaWAN, an IoT technology, offers advantages such as low power consumption, cost-effectiveness, and a wide area network. With its extensive coverage of up to 15 kilometers and easy deployment, LoRa has become a favored connectivity option for IoT use cases. This study explores the utilization of LoRaWAN in Pangandaran, a regency in the West Java province of Indonesia. Implementing LoRaWAN in this context has resulted in several benefits, including the ability to monitor and control street lighting in specific areas of Pangandaran and real-time recording of energy consumption. The primary objective of this research is to estimate the number of LoRaWAN gateways required to support smart street lighting in Pangandaran. Two methods are employed: coverage calculation using the free space loss approach and capacity calculation. The coverage calculation suggests a requirement of 34 gateways, whereas the capacity calculation indicates that only two gateways are needed. Based on these findings, it can be inferred that, theoretically, a maximum of 34 gateways would be necessary for smart street lighting in the Pangandaran area. However, further research, including driving tests, is recommended to validate these results for future implementation. This study provides insights into the practical application of LoRaWAN technology in smart street lighting, specifically in Pangandaran. The findings contribute to optimizing infrastructure and resource allocation, ultimately enhancing the efficiency and effectiveness of urban lighting systems. 
Predicting Battery Storage of Residential PV Using Long Short-Term Memory Rakasiwi, Rizky Khaerul Maulana; Kurnianingsih, Kurnianingsih; Suharjono, Amin; Enriko, I Ketut Agung; Kubota, Naoyuki
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1603

Abstract

Solar power panels, or photovoltaic (PV), have recently grown rapidly as a renewable alternative energy source, especially since the increase in the basic electricity tariff. PV technology can be employed instead of the state electricity company to reduce the electricity used. Indonesia is one of the countries that have great potential in producing electricity from PV technology, considering that most of Indonesia's territory gets sunlight for most of the year and has a large land area. Considering the benefits of PV technology, it is necessary to carry out predictive monitoring and analysis of the energy generated by PV technology to maximize energy utilization in the future. The Internet of Things (IoT) and cloud computing system was developed in this research to monitor and collect data in real-time within 27 days and obtained 7831 data for each parameter that affects PV production. These data include data on the light intensity, temperature, and humidity at the location where the PV system is installed. The feature selection results using Pearson correlation revealed that the light intensity parameter significantly impacted the PV production system. This research used the Long Short-Term Memory (LSTM) method to predict future PV production. By tuning hyperparameters using 3000 epochs, the resulting RMSE value was 171.5720. The results indicated a significant change in the RMSE value compared to 100 epochs of 422.5780. This model can be applied as a forecasting system model at electric vehicle charging stations, given the increasing use of electric vehicles in the future.     Keywords— Forecasting; energy; Photovoltaic; LSTM; Internet of Thing. 
CNN-LSTM for Heartbeat Sound Classification Aji, Nurseno Bayu; Kurnianingsih, Kurnianingsih; Masuyama, Naoki; Nojima, Yusuke
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2115

Abstract

Cardiovascular disorders are among the primary causes of death. Regularly monitoring the heart is of paramount importance in preventing fatalities arising from heart diseases. Heart disease monitoring encompasses various approaches, including the analysis of heartbeat sounds. The auditory patterns of a heartbeat can serve as indicators of heart health. This study aims to build a new model for categorizing heartbeat sounds based on associated ailments. The Phonocardiogram (PCG) method digitizes and records heartbeat sounds. By converting heartbeat sounds into digital data, researchers are empowered to develop a deep learning model capable of discerning heart defects based on distinct cardiac rhythms. This study proposes the utilization of Mel-frequency cepstral coefficients for feature extraction, leveraging their application in voice data analysis. These extracted features are subsequently employed in a multi-step classification process. The classification process merges a convolutional neural network (CNN) with a long short-term memory network (LSTM), forming a comprehensive deep learning architecture. This architecture is further enhanced through optimization utilizing the Adagrad optimizer. To examine the effectiveness of the proposed method, its classification performance is evaluated using the "Heartbeat Sounds" dataset sourced from Kaggle. Experimental results underscore the effectiveness of the proposed method by comparing it with simple CNN, CNN with vanilla LSTM, and traditional machine learning methods (MLP, SVM, Random Forest, and k-NN).
PENGELOLAAN KOLEKSI MUSEUM ZOOLOGICUM BOGORIENSE (MZB) TAHUN 2022 Mujiono, Nova; Alfiah, Alfiah; Apandi, Apandi; Darmawan, Darmawan; Fatimah, Fatimah; Wikanta, Hadi; Haerul, Haerul; Kurnianingsih, Kurnianingsih; Wahyudin, Mohamad; Mulyadi, Mulyadi; Supriatna, Nanang; Santoso, Pramono Hery; Prihandini, Riena; Rachmatiyah, Rina; Sarino, Sarino; Sauri, Sopian; Suparno, Suparno; Nurhaman, Ujang; Sofyani, Umar; Trilaksono, Wahyu; Priyatna, Yayat
Berita Biologi Vol 23 No 1 (2024): Berita Biologi
Publisher : BRIN Publishing (Penerbit BRIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/beritabiologi.2024.892

Abstract

Since the integration of LIPI into BRIN in 2021, the Museum Zoologicum Bogoriense (MZB), which is managed by the coordinator of the zoological collection assisted by 20 collection technician staffs, has been transferred to the Directorate of Scientific Collections Management. The process of integration and management transfer does not change the main duties and functions of MZB as the national depository for zoological specimen collections. In addition to managing collections, researchers frequently ask MZB staff for assistance during field research and teaching collection management courses to students, teaching staff, and regional museum directors. The management of the MZB collection is described in a scientific publication for the first time. We hope that this documentation will continue so that museum management science can advance and assist the scientific community, particularly in Indonesia.
Co-Authors Abu Hasan Adi Wibowo alfiah alfiah Alifiansyah, Muhammad Fikry Amalia, Dhanty Nurul Amin Suharjono Anindya Wirasatriya Anis Roihatin Apandi, Apandi Aquarista, Nita Ari Suwondo Arselatifa, Elviga Asmaul Husna Avisyah, Gisnaya Faridatul Azka Khoirunnisa Chin, Wei Hong Darmawan Darmawan Dhanio, Yeyen Wulandari Diana, Tri Rettagung Donny Kristanto Mulyantoro edy susanto Fahriah, Sirli Fatahul Arifin, Fatahul fatimah Fatimah Fitriyani, Rizki Putri Gustiyana, Fikri Nizar Haerul, Haerul Hajrianti, Siti Hashimoto, Takako Henra, Mustika Hesti Kurniasih I Ketut Agung Enriko Ika Rahmawati Istiqomah, Nursita Kubota, Naoyuki Kuntarjo, Samuel Beta Kusuma, Yanti Yandri Lutfan Lazuardi Maharadatunkamsi Maharadatunkamsi, Maharadatunkamsi Mardiyono Mardiyono Masuyama, Naoki Melyana Nurul Widyawati Miyar, Miyar Muhammad Anif Mulyadi Mulyadi Muryasari, Ika Nana Supriatna Nojima, Yusuke NOVA MUJIONO Nur Ghaniaviyanto Ramadhan Nurhaman, Ujang Nurhaswinda Nurseno Bayu Aji, Nurseno Bayu Oktaviani, Nur Hilda Prayitno Prayitno Prihandini, Riena Priyanti, Esteria Priyatna, Yayat Puspita Sari, Erika Lety Istikhomah Putri Hana Pebriana Putri, Winda Astria Rachmatiyah, Rina Rakasiwi, Rizky Khaerul Maulana Runjati Santosa, Naufal Adli Santoso, Pramono Hery Sarino . Sauri, Sopian Septiani, Camilla Sidiq Syamsul Hidayat, Sidiq Syamsul Sofyani, Umar Sri Sumarni Sudiyono Sudiyono Suparno Suparno Susmiyati, Susmiyati Tatag Bagus Putra Prakarsa Tri Raharjo Yudantoro Triastuti, Unggul Yuyun Trilaksono, Wahyu Triyono, Liliek Veryal, Veryal Wahyu Sulistiyo Wahyudin, Mohamad Walin Walin, Walin Wikanta, Hadi Wiktasari Wiktasari, Wiktasari Yanwari, M. Irwan Yanwari, Muhammad Irwan Yusuf Dewantoro Herlambang