Article Per Year (5 Year)
p-Index From 2019 - 2024
1.116
P-Index
This Author published in this journals
All Journal JUTI: Jurnal Ilmiah Teknologi Informasi Journal of Information Systems Engineering and Business Intelligence ELLITE: Journal of English Language, Literature, and Teaching JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Journal of English Teaching, Literature, and Applied Linguistics Jurnal Layanan Masyarakat (Journal of Public Service) Jurnal Nasional Pengabdian Masyarakat
Indah Werdiningsih
Prodi Sistem Informasi, Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
MODEL PENGEMBANGAN DASHBOARD UNTUK MONITORING DAN EVALUASI KINERJA PERGURUAN TINGGI Hariyanti, Eva; Werdiningsih, Indah; Surendro, Kridanto
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 9, No 1, Januari 2011
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.545 KB) | DOI: 10.12962/j24068535.v9i1.a63

Abstract

Tujuan utama dari penelitian ini adalah merancang model pengembangan dashboard untuk kebutuhan perguruan tinggi. Dashboard adalah aplikasi sistem informasi yang menyajikan informasi mengenai indikator utama dari aktifitas organisasi secara sekilas dalam layar tunggal. Pembuatan model memperhatikan 3(tiga) aspek utama dashboard yaitu penyajian data/informasi, personalisasi, dan kolaborasi antar pengguna. Model yang dihasilkan digunakan untuk pengembangan dashboard bagi kebutuhan monitoring dan evaluasi kinerja perguruan tinggi. Monitoring dan evaluasi kinerja mutlak dilakukan secara terus menerus oleh perguruan tinggi untuk memastikan bahwa proses bisnis yang dijalankannya dapat mencapai tujuan yang telah ditetapkan, melalui strategi pengelolaan yang tepat. Metode penelitian yang digunakan adalah studi literatur dan survei kuesioner. Studi literatur dilakukan untuk membuat rancangan awal model. Sedangkan survei kuesioner dilakukan untuk mengidentifikasi kebutuhan calon pengguna dashboard dan mengetahui faktor-faktor yang yang mempengaruhi kesuksesan pengembangan sistem informasi di perguruan tinggi. Jumlah responden sebanyak 95 orang di lingkungan Universitas Airlangga (UA) dan Institut Teknologi Bandung (ITB). Hasil penelitian menunjukkan bahwa terdapat perbedaan prioritas kebutuhan dashboard untuk pengguna di UA dan ITB. Namun secara umum dapat dinyatakan bahwa kebutuhan yang terkait aspek penyajian data/informasi, personalisai, dan performansi merupakan hal yang dianggap penting untuk sebuah dashboard. Sedangkan aspek kolaborasi hanya dianggap sebagai daya tarik dashboard. Model pengembangan dashboard yang dihasilkan menggambarkan bahwa kepuasan pengguna dipengaruhi oleh kualitas sistem, kualitas layanan, dan manfaat positif yang diberikan oleh sistem.
Sistem Pendukung Keputusan Peramalan Jumlah Kunjungan Pasien Menggunakan Metode Extreme Learning Machine (Studi Kasus : Poli Gigi Rsu Dr. Wahidin Sudiro Husodo Mojokerto) Fardani, Delia Putri; Wuryanto, Eto; Werdiningsih, Indah
Journal of Information Systems Engineering and Business Intelligence Vol 1, No 1 (2015): April
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.829 KB)

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto dengan menggunakan metode Extreme Learning Machine (ELM). Dengan adanya  sistem pendukung keputusan ini direktur Rumah Sakit dapat meramalkan jumlah kunjungan pasien dan membantu dalam pembuatan kebijakan rumah sakit, mengatur sumber daya manusia dan keuangan, serta mendistribusikan sumber daya material dengan benar khususnya pada poli gigi. Dalam rancang bangun sistem pendukung keputusan ini dilakukan dalam beberapa tahap. Tahap yang pertama, pengumpulan data untuk mengidentifikasi inputan yang dibutuhkan dalam penghitungan metode ELM. Tahap kedua, pengolahan data, data dibagi menjadi data training dan data testing dengan komposisi data training sebanyak 80% (463 data) dari total 579 data dan 20% (116 data) sisanya sebagai data testing yang kemudian di normalisasi. Tahap ketiga, peramalan jumlah kunjungan pasien menggunakan metode ELM. Tahap terakhir, perancangan sistem menggunakan sysflow dan pembangunan sistem berbasis desktop serta evaluasi sistem. Hasil penelitian berupa aplikasi sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien. Dan melalui uji coba menggunakan 116 data testing berdasarkan fungsi aktivasi sigmoid biner dengan jumlah hidden layer sebanyak 7 unit dan Epoch 500 diperoleh hasil optimal MSE sebesar 0.027 Kata Kunci— Sistem Pendukung Keputusan, Peramalan, Jaringan Syaraf Tiruan, Extreme Learning MachineAbstract— In this research, a decision support system to predict the number of patients visit RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto was designed and developed using Extreme Learning Machine (ELM) method which aims to assist director in making decision for the hospital, managing human and financial resource, as well as distributing material resource properly especially in the Department of Dentistry. The design of this decision support system to predict the number of patients visit with ELM method is divided into several stages. The first stage is to identify the input data collection needed in the calculation method of ELM. The next stage is processing the data; the data is divided into training data and testing data and then normalized, in which training data is 80% (452 data) and testing 579 data 20% (116 data). The third stage is problem solving using ELM. The last stage is the design and development of systems using sysflow and desktop-based system that includes the implementation and evaluation of the system. The result of this research is an application of decision supporting system to predict number of patients. By using 116 testing data based on the binary sigmoid activation function using 7 units of hidden layer and 500 Epoch then Optimal MSE value that was obtained is 0.027. Keywords— Decision Supporting System, Prediction, Artificial Neural Network, Extreme Learning Machine
The Use of Debate Method to Improve Students’ Speaking Skill Werdiningsih, Indah
Jetlal Vol 2 No 2 (2018)
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (481.355 KB) | DOI: 10.30587/jetlal.v2i2.623

Abstract

Speaking is a crucial part of the language learning process. However, many students find speaking as one of the most difficult skills in English. Therefore, the researcher wants to improve the students’ speaking ability through the suitable teaching method, in this case the debate. The objective of this research referring to the research problem is to find out how the debate method can improve speaking ability. Based on the research problem and the relevant theory, the hypothesis of this research is described as follows: Debate method improves the speaking ability of the fifth semester students of Universitas Muhammadiyah Jember in the 2017 / 2018 academic year by developing their activeness in expressing oral argument logically in a systematic way. The design of this research is classroom action research. The research subject is the fifth semester class consisting of 34 students. Test and observation are used to obtain the data. The data collection involved a number of instruments namely Test of Speaking English and Speaking Rubric. It was then evaluated by using speaking rubric covering fluency, pronunciation, vocabulary and grammar. Debate method improves the students’ speaking ability in two cycles from M = 61.84 in Cycle 1 to M = 70.34 in Cycle 2 and the percentage of students scored (E = 66.67%) in Cycle 1 to (E = 83.34%) in Cycle 2. The observation result from 56.15% students’ activeness in Cycle 1 to 85.29% students’ activeness in Cycle 2. Based on the data above, there was significant impact of Cycle 2 implementation on the students’ speaking ability. It can be concluded that debate method is able to improve the students’ speaking ability.
Fostering Listening Comprehension through Total Physical Response Werdiningsih, Indah; Mardiyah, Binti Ainul
ELLITE Vol 4, No 2 (2019): ELLITE
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (103.552 KB) | DOI: 10.32528/ellite.v4i2.2986

Abstract

EFL Learners’ distress in listening to English records in the classroom is one of the matters commonly discovered in Indonesian middle scholars. Listening activities bring students to the mastery of other skills; speaking, writing, and reading. Total Physical Response was created to enhance the students’ ability in listening to a spoken foreign language discourse by giving a physical response when they hear aparticular command. This study works toward finding the effect of Total Physical Response utilization on students’ listening comprehension at MTs Negeri 4 Banyuwangi.The samples of this study were two groups of students; 30 students of VII A and 30 students of VII B. Class VII B was assigned as the control group, while Class VII A as the experimental group where both pre-test and post-test were conducted to each group. The experimental group was taught by using TPR, while in the control group learning is carried out in the way teachers normally teach, that is using Three-phase technique.The hypothesis was tested using independent sample t-test and analyzed by using SPSS. Total Physical Response could administer some refinement on students’ listening, which is evidently manifested in the result of the post-test. Students in experiment group achieved better score than those in control group. This study suggests the use of Total Physical Response to the early middle scholars as an alternative to other teaching methods.
The Use of Identity Card to Improve Students’ Speaking Skill Werdiningsih, Indah
ELLITE Vol 2, No 2 (2017): ELLITE
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (106.207 KB) | DOI: 10.32528/ellite.v2i2.1506

Abstract

The study aimes to describe how a communicative activity through the useof identity card influences speaking skills of junior high schools students inBondowoso. Classroom Action Research (CAR) was implemented using a modelby Elliot to the first graders; 10 males and 15 females. It was done in two cycles;each of which consisted of two meetings. The researcher used collaborativeaction research with some of the English teachers. The data collection involvedTest of Speaking English and Speaking Rubric which evaluated fluency,pronunciation, vocabulary, and grammar. The finding showed the mean scoreof pretest reached 67.8 and that of posttest reached up to 70.2, resulting in asignificant improvement of 42 % in posttest 1 and 64% in posttest 2. Therefore,the criteria of success was achieved, indicated by the improvement of students’active participation, confidence and their fluency positively in speaking inpeer-interaction and discussion through the contents of Identity Card beforepracticing in front of the class. Hereby proposed some suggestions addressedto teachers and other researchers who wish to pursue related topics in futureresearch, concerning the importance of communicative activities using IdentityCard that can improve students’ enthusiasm and motivation.
Sistem Pendukung Keputusan Peramalan Jumlah Kunjungan Pasien Menggunakan Metode Extreme Learning Machine (Studi Kasus : Poli Gigi Rsu Dr. Wahidin Sudiro Husodo Mojokerto) Delia Putri Fardani; Eto Wuryanto; Indah Werdiningsih
Journal of Information Systems Engineering and Business Intelligence Vol. 1 No. 1 (2015): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.829 KB) | DOI: 10.20473/jisebi.1.1.33-40

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto dengan menggunakan metode Extreme Learning Machine (ELM). Dengan adanya  sistem pendukung keputusan ini direktur Rumah Sakit dapat meramalkan jumlah kunjungan pasien dan membantu dalam pembuatan kebijakan rumah sakit, mengatur sumber daya manusia dan keuangan, serta mendistribusikan sumber daya material dengan benar khususnya pada poli gigi. Dalam rancang bangun sistem pendukung keputusan ini dilakukan dalam beberapa tahap. Tahap yang pertama, pengumpulan data untuk mengidentifikasi inputan yang dibutuhkan dalam penghitungan metode ELM. Tahap kedua, pengolahan data, data dibagi menjadi data training dan data testing dengan komposisi data training sebanyak 80% (463 data) dari total 579 data dan 20% (116 data) sisanya sebagai data testing yang kemudian di normalisasi. Tahap ketiga, peramalan jumlah kunjungan pasien menggunakan metode ELM. Tahap terakhir, perancangan sistem menggunakan sysflow dan pembangunan sistem berbasis desktop serta evaluasi sistem. Hasil penelitian berupa aplikasi sistem pendukung keputusan untuk meramalkan jumlah kunjungan pasien. Dan melalui uji coba menggunakan 116 data testing berdasarkan fungsi aktivasi sigmoid biner dengan jumlah hidden layer sebanyak 7 unit dan Epoch 500 diperoleh hasil optimal MSE sebesar 0.027 Kata Kunci— Sistem Pendukung Keputusan, Peramalan, Jaringan Syaraf Tiruan, Extreme Learning MachineAbstract— In this research, a decision support system to predict the number of patients visit RSU Dr. Wahidin Sudiro Husodo Kota Mojokerto was designed and developed using Extreme Learning Machine (ELM) method which aims to assist director in making decision for the hospital, managing human and financial resource, as well as distributing material resource properly especially in the Department of Dentistry. The design of this decision support system to predict the number of patients visit with ELM method is divided into several stages. The first stage is to identify the input data collection needed in the calculation method of ELM. The next stage is processing the data; the data is divided into training data and testing data and then normalized, in which training data is 80% (452 data) and testing 579 data 20% (116 data). The third stage is problem solving using ELM. The last stage is the design and development of systems using sysflow and desktop-based system that includes the implementation and evaluation of the system. The result of this research is an application of decision supporting system to predict number of patients. By using 116 testing data based on the binary sigmoid activation function using 7 units of hidden layer and 500 Epoch then Optimal MSE value that was obtained is 0.027. Keywords— Decision Supporting System, Prediction, Artificial Neural Network, Extreme Learning Machine
Aplikasi Sistem Pakar Diagnosa Penyakit Pada Anak Bawah Lima Tahun Menggunakan Metode Forward Chaining Bagus Fery Yanto; Indah Werdiningsih; Endah Purwanti
Journal of Information Systems Engineering and Business Intelligence Vol. 3 No. 1 (2017): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.788 KB) | DOI: 10.20473/jisebi.3.1.61-67

Abstract

Abstrak— Anak-anak pada usia 2 bulan sampai 5 tahun (Balita) lebih rentan terkena penyakit. Lingkungan sangat mempengaruhi kesehatan Balita. Penelitian ini bertujuan untuk membuat sebuah aplikasi sistem pakar diagnosa penyakit pada Balita berbasis mobile. Penelitian ini terdiri dari tiga tahap. Tahap pertama adalah pengumpulan data dan informasi dari Manajemen Terpadu Balita Sakit (MTBS) dan wawancara dengan Bidan. Dari pengumpulan data dan informasi tersebut ditemukan fakta penyakit, keluhan, gejala dan saran penanganan. Tahap kedua adalah pembuatan rule dengan 18 penyakit. Tahap ketiga adalah implementasi aplikasi sistem pakar berbasis mobile dengan fitur diagnosa penyakit, riwayat diagnosa dan kumpulan penyakit. Aplikasi sistem pakar yang dibuat dapat mendiagnosa penyakit dan memberikan saran penanganan. Hasil evaluasi dari 50 data uji coba menghasilkan tingkat akurasi sebesar 82%, dimana 41 hasil diagnosa yang benar dan 9 diagnosa yang salah. Kata Kunci— Sistem Pakar, Forward Chaining, Diagnosa Penyakit, Manajemen Terpadu Balita Sakit, Knowladge BaseAbstract— Children at the age of 2 months to 5 years (toddlers) are more susceptible to disease contagious. Environmental condition significantly influences the children health. This  research aimed to create a mobile-based expert system application to diagnose disease in toddlers. This research consist of three stages. The first stage were data and information collection from Manajemen Terpadu Balita Sakit  (MTBS) and interview with medical staffs. From the first stage, we can discover the disease facts, signs, symptoms and treatment advices. The second stage was the construction of rules for 18 diseases. The third stage was the implementation of mobile-based expert system application with features of disease diagnosis, diagnosis history and collection of disease diagnosis. Expert system application made able to diagnose the disease and provide treatment advice. The results of evaluation using 50 testing data provides the level of accuracy of 82%, where 41 diagnosis result were true and 9 diagnosis were false. Keywords— Expert System, Forward Chaining, Disease Diagnosis, Manajemen Terpadu Balita Sakit, Knowledge Base
Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi di Sekolah Menengah Pertama dengan Metode VIKOR dan TOPSIS Rivanda Putra; Indah Werdiningsih; Ira Puspitasari
Journal of Information Systems Engineering and Business Intelligence Vol. 3 No. 2 (2017): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.173 KB) | DOI: 10.20473/jisebi.3.2.113-121

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan metode VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) dan Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS). Sistem pendukung keputusan ini dibangun melalui 6 tahap. Tahap pertama adalah pengumpulan data dan informasi melalui wawancara dan analisis dokumen. Tahap kedua adalah pengolahan data dan informasi untuk mendapatkan rancangan sistem yang akan dibangun. Tahap ketiga adalah analisis sistem yang meliputi input data siswa, pembobotan kriteria dengan metode AHP, serta perankingan alternatif dengan metode VIKOR dan TOPSIS. Tahap keempat adalah perancangan sistem menggunakan konsep Object Oriented Design. Tahap kelima adalah implementasi sistem berbasis web. Tahap terakhir adalah evaluasi sistem dengan membandingkan tingkat akurasi antara metode VIKOR dan TOPSIS. Berdasarkan hasil uji konsistensi, terdapat 7 percobaan yang tidak konsisten dan 13 percobaan yang konsisten. Hasil yang diperoleh adalah tingkat akurasi yang tertinggi sebesar 80% dengan menggunakan TOPSIS. Berdasarkan hasil tersebut maka metode TOPSIS dapat digunakan pada kasus pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan derajat kepentingan antar kriteria adalah nilai aktivitas sedikit lebih penting dari nilai rapot, nilai aktivitas lebih penting dari nilai prestasi, nilai aktivitas sangat kuat penting dari nilai sikap, nilai rapot sedikit lebih penting dari nilai prestasi, nilai rapot lebih penting dari nilai sikap, dan nilai prestasi sedikit lebih penting dari nilai sikap.Kata Kunci— AHP, Pemilihan Siswa Berprestasi, Sistem Pendukung Keputusan, TOPSIS, VIKORAbstract— This research proposes a solution to create a decision support system of student achievement selection using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The decision support system would resolve the problem of big data processing which needs more effort and more time. The development of decision support system of student achievement selection consisted of 6 phases. The first phase was collecting the data and information via interviews and document analysis. The second phase was data processing to create system design. The third phase was analyzing the system that includes the input of student data, weighing the criteria using AHP method, and rank the alternatives using VIKOR and TOPSIS method. The fourth phase was designing the system using Object Oriented Design. The fifth phase was implementing the system using a web-based. The sixth phase was the evaluation of system by comparing the level of accuracy between VIKOR and TOPSIS methods. Based on the result of consistency test, there were 7 inconsistent experiments and 13 consistent experiments. The result obtained is the highest accuracy rate of 80% by using TOPSIS. Based on these results, TOPSIS method can be used in case of selection of outstanding students in SMP Taruna Jaya I Surabaya with degree of importance among the criteria is activity value was slightly more important than report value, activity value was more important than achievement value, activity value was very important from attitude value, report value was slightly more important than achievement value, report value was more important than attitude value, and achievement value was slightly more important than attitude value.Keywords— AHP, Decision Support System, Student Achievement Selection , TOPSIS, VIKOR
Decision Support System for Classification of Early Childhood Diseases Using Principal Component Analysis and K-Nearest Neighbors Classifier Damar Dananjaya; Indah Werdiningsih; Rini Semiati
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 1 (2019): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.065 KB) | DOI: 10.20473/jisebi.5.1.13-22

Abstract

Background: Data on early childhood disease collected in clinics has accumulated into big data. Those data can be used for classification of early childhood diseases to help medical staff in diagnosing diseases that attack early childhoods.Objective: This study aims to apply Principal Component Analysis (PCA) and K-Nearest Neighbor (K-NN) Classifier for the classification of early childhood diseases.Methods: Data analysis was performed using PCA to obtain variables that had a major influence on the classification of early childhood diseases. PCA was done by observing the correlation between variables and eliminating variables that have little influence on classification. Furthermore, data on early childhood disease was classified using the K-Nearest Neighbor Classifier method.Results:  The results of system evaluation using 150 test data indicated that the classification system by applying PCA and KNN Classifier had an accuracy value of 86%.Conclusion: PCA can be used to reduce the number of variables involved so that it can improve system performance in terms of efficiency. In addition, the application of PCA and KNN can also improve accuracy in the classification of early childhood diseases.
Pelatihan dan Pendampingan Digital Marketing bagi UMKM Jasa Laundry menuju UMKM Go Digital Army Justitia; Indah Werdiningsih; Faried Effendy; Taufik Taufik
Jurnal Nasional Pengabdian Masyarakat Vol. 2 No. 2 (2021): Jurnal Nasional Pengabdian Masyarakat
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jnpm.v2i2.388

Abstract

The COVID-19 pandemic has had a significant impact on Micro Small Medium Enterprises (MSMEs), especially laundry services in Plosokandang, Tulungagung Regency. Their primary customers, college students, no longer use their services because of online teaching and learning. The use of social media digital marketing is one solution to promote products and services. Unfortunately, many MSMEs lack this skill. This community service project focuses on training and assisting MSMEs in designing digital marketing content and posting them on their official social media. Canva software was chosen as a tool for content creation because it is simple and quick to use, with minimal design capabilities. Canva offers ready-made templates, so users only need to add their own personal touches. Then, the content is shared on the official social media accounts (Instagram or Facebook Pages). Participants’ and partners’ knowledge and skills improved after following the training. The average increase in participant knowledge of Canva material is 18.62 points, while social media material is 10.79 points. These training and mentoring activities have a positive impact on skills and knowledge related to using Canva and social media for digital marketing. Another effect of digital marketing on social media is an increase in revenue turnover, customer numbers, customer reach, and market sectors.
Co-Authors Army Justitia Aulia Marcha Rizkasari Putri Bagus Fery Yanto Bambang Suwerda, Bambang Barry Nuqoba Damar Dananjaya Delia Putri Fardani Delia Putri Fardani, Delia Putri Dina Merlynaningrum, Dina Endah Purwanti Eto Wuryanto Eva Hariyanti Faried Effendy Firmansyah, Muhammad Andy Haryono Haryono Ibaneza Griffint Secoria Ira Puspitasari Kridanto Surendro Layly Aslinda Saraswati, Layly Aslinda Lucky Herawati Mardiyah, Binti Ainul muryoto muryoto, muryoto Nania Nuzulita Novitamala, Catur Bunga Purwanto Purwanto Rini Semiati Rivanda Putra Sardjito Eko Windarso, Sardjito Eko Sri Muryani, Sri Taufik Taufik Taufik Tri Wiji Wastiti, Tri Wiji Utami, Retno Arif Virgananda Ulfa Kharisma, Virgananda Ulfa Yunitasari, Metina Ayu