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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL MANAJEMEN BISNIS Jurnal Literasiologi Jurnal Tekno Kompak Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Jurnal Abdidas Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA Journal of Electrical Engineering and Computer (JEECOM) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Silva Samalas: Journal of Forestry and Plant Science Jurnal Elkasista ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Inovasi, Evaluasi dan Pengembangan Pembelajaran (JIEPP) Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An Jurnal Ilmiah Pendidikan Dasar (JIPDAS) Journal of Engineering, Technology and Computing (JETCom) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Journal of Management, Economic and Accounting (JMEA) Insand Comtech : Information Science and Computer Technology Journal International Journal of Engineering Continuity Valid Jurnal Pengabdian Journal of Economics and Management Scienties Prosiding Seminar Nasional CORISINDO Media Pendidikan Matematika
Hairani Hairani
Universitas Bumigora, Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Peningkatan Kinerja Metode SVM Menggunakan Metode KNN Imputasi dan K-Means-Smote untuk Klasifikasi Kelulusan Mahasiswa Universitas Bumigora Hairani, Hairani
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021843428

Abstract

Salah satu permasalahan utama Universitas Bumigora adalah rasio antara mahasiswa yang masuk dengan mahasiswa lulus tepat waktu  tidak seimbang, sehingga akan mengakibatkan penurunan penilaian akreditasi dikemudian hari. Salah satu indikator penilaian dalam proses akreditasi adalah rasio kelulusan mahasiswa. Data kelulusan mahasiswa yang tersimpan pada basisdata kampus, tetapi belum dimanfaatkan dengan maksimal. Dengan memanfaatkan data kelulusan mahasiswa dapat mengetahui pattern atau pola-pola mahasiswa yang lulus tepat waktu atau tidak, sehingga dapat minimalisir terjadinya mahasiswa yang drop out. Tidak hanya itu, pengambil keputusan dapat dimudahkan membuat kebijakan secara dini untuk membantu mahasiswa yang berpotensi drop out dan lulus tidak tepat waktu. Solusi yang ditawarkan pada penelitian ini adalah menggunakan teknik data mining. Salah satu metode data mining yang digunakan penelitian ini adalah metode SVM. Adapun tujuan penelitian ini adalah meningkatkan kinerja metode SVM untuk klasifikasi kelulusan mahasiswa Universitas Bumigora menggunakan metode KNN Imputasi dan K-Means-Smote. Penelitian ini terdiri dari beberapa tahapan yaitu pengumpulan data kelulusan mahasiswa, pra-pengolahan seperti penanganan nilai hilang menggunakan metode KNNI, penanganan ketidakseimbangan kelas menggunakan K-Means-Smote, klasifikasi menggunakan metode SVM. Tahapan terakhir adalah pengujian kinerja SVM berdasarkan akurasi, sensitivitas, spesifisitas, dan f-measure.  Berdasarkan hasil pengujian yang telah dilakukan, integrasi metode KNNI, K-Means-Smote, dan SVM mendapatkan akurasi 83.9%, sensitivitas 81.3%, spesifisitas 86.6%, dan f-measure 83.5%.  Penggunaan metode KNNI dan K-Means-Smote dapat meningkatkan kinerja metode SVM berdasarkan akurasi, sensitivitas, spesifisitas, dan f-measure. Abstract One of the main problems of Bumigora University is the ratio between incoming students and students graduating on time is not balanced, so that it will result in a decrease in accreditation assessment in the future. One of the assessment indicators in the accreditation process is the student graduation ratio. Student graduation data stored in the campus database, but has not been maximally utilized. By utilizing graduation data, students can find out patterns or patterns of students who graduate on time or not, so as to minimize the occurrence of students who drop out. Not only that, decision makers can make it easier to make policies early to help students who have the potential to drop out and not graduate on time. The solution offered in this research is to use data mining techniques. One of the data mining methods used in this study is the SVM method. The purpose of this study is to improve the performance of the SVM method for the classification of Bumigora University graduation students using the KNN Imputation and K-Means-Smote methods. This research consists of several stages, namely the collection of student graduation data, pre-processing such as handling missing values using KNNI method, handling class imbalances using K-Means-Smote, classification the SVM method. The last stage is testing SVM performance based on accuracy, sensitivity, specificity, and f-measure. Based on the results of test that have been carried out, the integration of the KNNI, K-Means-Smote, and SVM method get an accuracy of 83.9%, sensitivity 81.3%, specificity 86.6%, and f-measure 83.5%. The use of KNNI and K-Means-Smote method can improve the performance of the SVM method based on accuracy, sensitivity, specificity, and f-measure. 
Peningkatan Kinerja Metode Random Forest Berbasis Smote-Tomek Link Pada Sentimen Analisis Pariwisata Lombok Marzuki, Khairan; Rady Putra, Lalu Ganda; Hairani, Hairani; Mardedi, Lalu Zazuli Azhar; Guterres, Juvinal Ximenes
Jurnal Bumigora Information Technology (BITe) Vol 5 No 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v5i2.3166

Abstract

Background: Tourists visiting Lombok Island can access various sources of tourist information and can share their views and tourist experiences through social media such as positive and negative experiences. Objective: This research aims to analyze the sentiment of Lombok tourism reviews using the Smote-Tomek Link and Random Forest algorithms.Methods: The research was carried out in several stages, namely collecting the Lombok tourism dataset, text preprocessing, text weighting using the Term Frequency-Inverse Document Frequency (TF-IDF) method, data sampling using SMOTE-Tomek Link, text classification using Random Forest, and the final stage was performance testing based on accuracy. Result: The research results obtained using the Smote-Tomek Link and Random Forest methods in sentiment analysis analysis of tourist reviews about Lombok were 94%. Conclusion: The use of the Smote-Tomek Link and Random Forest methods in Lombok tourism sentiment analysis produces very good accuracy.
Electric Vehicle Sales-Prediction Application Using Backpropagation Algorithm Based on Web Ramadhanti Ramadhanti; Hairani Hairani; Muhammad Innuddin
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3388

Abstract

The accuracy of predicting future product sales is needed to minimize losses and gain profits. Inventory of goods carried out manually or improper product inventory planning causes the number of goods to accumulate due to the small number of requests, so the goods are damaged. Therefore, a sales prediction system with high accuracy is needed to assist in stocking electric vehicles. This research aimed to predict electric vehicle sales using the web-based backpropagation method. This study uses the backpropagation method to predict electric vehicle sales data from 2015 to 2022. The data is divided into 84 instances as training data and 12 instances as testing data. The result of this study was that the backpropagation method obtained a MAPE error rate of 6.25%. Thus, the backpropagation method can be used for predicting electric vehicle sales because it has a very accurate performance level.
Sosialisasi Peran Penggunaan Management Learning System sebagai Platform Pembelajaran Daring untuk Mendukung Pembelajaran Mandiri Aprianto, Dedi; Mardedi, Lalu Zazuli Azhar; Sutarman, Sutarman; Hendri, Wira; Hairani, Hairani; Innuddin, Muhammad; Rahmawati, Lela
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 5 No 2 (2025): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v5i2.4569

Abstract

keterbatasan kesadaran mahasiswa tentang optimalisasi penggunaan MLS sebagai media yang dapat menunjang belajar mandiri meskipun telah diterapkan sebagai media belajar komplementer, tetapi belum sepenuhnya efektif. Sehingga hal ini mengurangi potensi maksimal dalam mendukung proses belajar mereka. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk meningkatkan pemahaman dan kesadaran mahasiswa mengenai penggunaan Management Learning System (MLS) dalam mendukung pembelajaran mandiri. Isu yang diangkat adalah rendahnya kesadaran mahasiswa tentang MLS, yang berdampak pada efektivitas pembelajaran daring guna meningkatkan pembelajaran mandiri. Untuk mencapai tujuan tersebut, metode yang digunakan, yaitu sosialisasi; ceramah, diskusi, tanya-jawab, dan demonstrasi langsung. Kegiatan ini terdiri dari tiga tahapan: persiapan, pelaksanaan, dan evaluasi. Hasil kegiatan PkM ini menunjukkan bahwa bahwa (85%) peserta merasa lebih memahami cara menggunakan MLS setelah pelatihan, dan (78%) merasa siap untuk menerapkan MLS dalam pembelajaran mandiri. Selain itu, (90%) peserta menyatakan bahwa kegiatan ini bermanfaat bagi mereka. Kesimpulan kegiatann ini menunjukkan keberhasilan dalam memperkuat pemahaman mahasiswa tentang penggunaan MLS, sekaligus mendukung peningkatan pembelajaran mandiri dalam konteks pembelajaran daring.
KONSELING BEHAVIORISTIK TERHADAP PENCEGAHAN PRILAKU BULLYING DI SEKOLAH Amelia, Bengi; Ifnaldi, Ifnaldi; Hairani, Hairani
Primary Education Journals (Jurnal Ke-SD-An) Vol 4 No 3 (2024): NOVEMBER
Publisher : Universitas Islam Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36636/primed.v4i3.4882

Abstract

Khasus bullying banyak terjadi di Indonesia, hal tersebut dapat menghambat proses belajar siswa disekolah. Penelitian bertujuan untuk mengetahui pengertian, dampak, dan cara menanggulangi bulyying dengan konseling. Penelitian ini menggunakan pendekatan studi literature tentang teori, dampak,dan cara menanggulanginya dengan konseling. Olweus (1999) mendefinisikan bulyying sebagai masalah psokososial dengan menghina dan merendahkan orang lain secara berulang-ulang dengan dampak negatif terhadap pelaku mempunyai kekuatan yang lebih dibandingkan korban. Beberapa hal dalam pendidikan yang dapat menanggulangi bulyying yaitu dengan melibatkan orang tua, teman sebaya, guru, konselor sekolah, serta seluruh warag sekolah.
THE USE OF LOCAL HERBAL IN ALTERNATIVE AND COMPLEMENTARY THERAPIES AS MIDWIFERY CARE SYNERGISTIC THERAPY IN SASAK ETHNIC Triandini, I Gusti Agung Ayu Hari; Hairani, Hairani
Jurnal Silva Samalas Vol 7, No 2 (2024): Desember 2024
Publisher : Universitas Pendidikan Mandalika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jss.v7i2.14226

Abstract

Traditional healers are still the main choice of the Sasak tribe to assist with childbirth. The city of Mataram ranks second lowest in terms of the percentage of births assisted by health workers and the third lowest in the West Nusa Tenggara region in terms of the percentage of births in health service facilities because of holistic service experience, culture, education, and outreach to health facilities factors. Traditional health services have been proven for a long time and are used by the community in preventive, promotive, curative, and rehabilitative efforts. This is very useful, especially in areas where access to health services is limited. The term "integrative medicine" in synergistic therapy is used to refer to the combination of conventional and alternative medicine practices that meet the requirements of scientific evidence, safety, and effectiveness. A descriptive, cross-sectional, quantitative method was used to assess 30 traditional healers in the Mataram city area. The complementary therapies in midwifery care help to reduce symptoms such as nausea vomiting and lower back pain, prepare for labor and increase the chances of an uncomplicated birth, increase milk production or reduce pain in perineum wounds, and also to accelerate the recovery of postpartum maternal health conditions using traditional herbal therapy such as pilis, parem, tapel, serbat, boreh. It has many benefits and needs to be introduced to midwives to be more optimal in providing holistic midwifery services.
Edukasi Pencegahan Pernikahan Dini dan Anemia untuk Menurunkan Risiko Stunting di Desa Cikawao Isviyanti, Isviyanti; Triandini, I Gusti Agung Ayu Hari; Hairani, Hairani; Gumangsari, Ni Made Gita; Hidayati, Diana; Gustiya, Sherly Dwi
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 9 No. 4 (2024): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/linov.v9i4.2172

Abstract

Artikel ini melaporkan hasil dari sebuah program pengabdian masyarakat yang bertujuan untuk mengurangi risiko stunting melalui edukasi pencegahan pernikahan dini di Desa Cikawao tepatnya di SMPN 2 Pacet dengan menggunakan pendekatan partisipatif. Program ini memberikan informasi tentang dampak pernikahan dini terhadap kesehatan ibu dan anak serta menawarkan solusi untuk mengatasi masalah stunting dengan mengkonsumsi tablet Fe dan edukasi kesehatan reproduksi untuk pencegahan pernikahan dini. Penilaian dilakukan melalui survei awal dan akhir program untuk mengukur perubahan pengetahuan remaja. Dari hasil perbandingan pre-test dan post-test menunjukkan adanya peningkatan pengetahuan sebelum dan sesudah edukasi sebesar 16.83%. Terdapat perbedaan yang signifikan antara tingkat pengetahuan sebelum dan sesudah penyuluhan pada siswa pada materi yang diberikan. Dengan demikian edukasi dinilai efektif dalam mengubah persepsi tentang pernikahan dini. Education on the Prevention of Early Marriage and Anemia to Reduce the Risk of Stunting in Cikawao Village Abstract This article reports the results of a community service program which aims to reduce the risk of stunting through education on preventing early marriage in Cikawao Village, specifically at SMPN 2 Pacet using a participatory approach. This program provides information about the impact of early marriage on maternal and child health and offers solutions to overcome the problem of stunting by consuming Fe tablets and reproductive health education to prevent early marriage. Assessments are carried out through surveys at the beginning and end of the program to measure changes in youth knowledge. From the results of the pre-test and post-test comparison, it shows that there is an increase in knowledge before and after education (16,83%). There is a significant difference between the level of knowledge before and after counseling students on the material provided. Thus, education is considered effective in changing perceptions about early marriage.
Sistem Pakar Diagnosa Penyakit THT Menggunakan Inferensi Forward Chaining dan Metode Certainty Factor Dirgantara, Bhintang; Hairani, Hairani
Jurnal Bumigora Information Technology (BITe) Vol 3 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.1241

Abstract

Currently, Ear, Nose, and Throat (ENT) has become a disease that is quite common in the world. In Indonesia, people with ENT disease are around 190-230 per 1000 population. The types of diseases studied in this study were Serous Orthitis Media, Nasal Polyps, Acute Pharyngitis, Retrofaryngeal Abscess, and Nafosaryngeal Carcinoma. The purpose of this study was to make an application of an expert system for the diagnosis of ENT diseases using forward chaining inference and certainty factors that can facilitate medical personnel to diagnose types of ENT diseases. The stages of developing an expert system in this study consisted of problem identification for problem domain, knowledge acquisition was used to obtain the MB and MD value of each symptom in ENT disease with the interview method, the design was used to design knowledge representations such as decision tables and inference engine. With the expert system of ENT disease diagnosis, it can make it easier for doctors to make decisions, or the right diagnosis of a symptom that arises in ENT, so that proper treatment is obtained and minimizes the occurrence of misdiagnoses
Thesis Topic Modeling Study: Latent Dirichlet Allocation (LDA) and Machine Learning Approach Hairani, Hairani; Janhasmadja, Mengas; Tholib, Abu; Ximenes Guterres, Juvinal; Ariyanto, Yuri
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4375

Abstract

The thesis reports housed in the campus repository have yet to be analyzed to reveal valuable knowledge patterns. Analyzing trends in thesis research topics can facilitate the selection of research topics, aid in mapping research areas, and identify underexplored topics.Therefore, this research aims to model and classify thesis topics using Latent Dirichlet Allocation (LDA) and the Naïve Bayes and Support Vector Machine (SVM) methods. This study employs the LDA method for thesis topic modeling, while SVM and Naïve Bayes are used for classifying these topics. The research results show that LDA successfully modeled five of the most popular thesis topics, namely two related to computer networks, two on software engineering, and one on multimedia. For thesis topic classification, the SVM method demonstrated higher accuracy than Naïve Bayes, reaching 92.80% after the data was balanced using Synthetic Minority Oversampling Technique (SMOTE). The implication of this study is that the topic modeling approach using LDA is able to identify dominant thesis topics. In addition, the SVM classification results obtained better accuracy than Naïve Bayes in the thesis topic classification task.
Enhancing Mental Illness Predictions: Analyzing Trends Using Multiple Linear Regression and Neural Network Backpropagation Riosatria, Riosatria; Hairani, Hairani; Anggrawan, Anthony; Syahrir, Moch.
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 2 (2024): September 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i2.4391

Abstract

The increasing number of mental health cases caused by various factors such as social changes, economic pressures, and technological advancements has made it difficult to accurately predict the number of cases, hindering prevention and early intervention efforts. Therefore, developing more accurate, data-driven predictive models is necessary to improve the effectiveness of prevention and intervention. This study aims to develop a predictive model for the number of mental health cases using Multiple Linear Regression and Neural Network Backpropagation methods. The study employs two predictive methods, Multiple Linear Regression and Neural Network Backpropagation to forecast future trends in the number of mental health cases. The findings reveal that the Neural Network Backpropagation method provides more accurate predictions than Multiple Linear Regression in forecasting mental health case trends. Specifically, the Neural Network Backpropagation method resulted in an MAE of 111.39 and a MAPE of 1.77%, while the Multiple Linear Regression method produced an MAE of 115.24 and a MAPE of 1.83%. Thus, the implication of this study is that the Neural Network Backpropagation method can be utilized to predict trends in the number of mental health cases due to its ability to provide highly accurate predictions.
Co-Authors Abdillah, Mokhammad Nurkholis Abdurraghib Segaf Suweleh Abdurraghib Segaf Suweleh Abu Tholib Adam, M. Awaludin Afrig Aminuddin Ahmad Ahmad Ahmad Fathoni Ahmad Zuli Amrullah Amelia, Bengi Amin, Farda Milanda Andi Sofyan Anas Andi, Moh syaiful Andini, Nisha Anggarawan, Anthony Anthony Anggrawan Arfa, Muhammad Ashadi, Diki Astuti, Ni Luh Budi Ayu Dasriani, Ni Gusti Candra, M. Ade Christine Eirene Christopher Michael Lauw Dadang Priyanto Dedi Aprianto Dedy Febry Rachman Dedy Febry Rahman Deny Jollyta Dian Syafitri Didik Dwi Prasetya Diki Ashadi Dirgantara, Bhintang Donny Kurniawan Dyah Susilowati Dyah Susilowaty Edddy, Syaiful Eka Setiawan, Rian Putra Fahry, Fahry Fatimatuzzahra Fatimatuzzahra Fitra Rizki Ramdhani Gede Yogi Pratama Gibran Satya Nugraha Gibran Satya Nugraha Gumangsari, Ni Made Gita Guntara, Muhammad Gusti Ayu Diah Gita Kartika Santi, I Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasbullah Hasbullah Herawati, Baiq Candra Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila Husnul Madihah, Husnul I Gusti Agung Ayu Hari Triandini I Nyoman Switrayana Ida Putu Andika Ifnaldi, Ifnaldi Ilham Saifuddin Indah Puji Lestari Indradewa, Rhian Isviyanti, Isviyanti Janhasmadja, Mengas Jauhari, M. Thonthowi Jupriadi, Jupriadi Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Kandisa, Amelia Kasiyanto Kasiyanto, Kasiyanto Khairan marzuki Khairil Ihsan Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lalu Zazuli Azhar Mardedi Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho M.Khaerul Ihsan Maariful Huda, Muhammad Malika, Riwayati Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Melati Rosanensi Michael Lauw, Christopher Miftahul Madani Muhamad Azwar Muhamad Azwar, Muhamad Muhammad Arfa Muhammad Innuddin Muhammad Maariful Huda Muhammad Ridho Akbar Muhammad Ridho Hansyah muhammad Syahbudi, muhammad Muhammad Zulfikri Muhammad Zulfikri Muhammad Zulkarnaen Haris Mujahid Mujahid Neny Sulistianingsih Noor Akhmad Setiawan Nurhayati, Lilik Nurul Azmi Nurvianti, Nurvianti Nuzululnisa, Bq Nadila Pahrul Irfan Putu Tisna Putra Qososyi, Sayidina Ahmadal Rahman, Mochamad Farhan Caesar Rahmawati, Lela Rahmi, Agustina Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rifqi Hammad Riosatria, Riosatria Riwayati Malika Rizki Wahyudi RR. Ella Evrita Hestiandari Saifuddin Zuhri Saifuddin, Ilham Samsul Hadi Santoso, Heroe Shudiq, Wali Ja'far Soepriyanto, Harry Sofiansyah Fadli Sri Winarni Sofya Sri Winarni Sofya Sudi Prayitno Sukron, Moh Sutarman Sutarman Syahrir, Moch. tadianta m., Winardi aries Teguh Bharata Adji Tri Widayatsih, Tri Triwijoyo, Bambang Krismono Triyanna Widiyaningtyas Umi Hanifah Vidiasari, Herlita Vidiasari, Viviana Herlita Wahyuningsih, Rr. Sri Handari Wangiyana, I Gde Adi Suryawan Widiatmoko, Dekki Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Zilullah Nazir Hadi