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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Jurnal Media Wahana Ekonomika PREDIKSI 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 Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Tekno Kompak Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Jurnal Teknologi Informasi dan Multimedia Jurnal Abdidas Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA Journal of Electrical Engineering and Computer (JEECOM) Science in Information Technology Letters Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Silva Samalas: Journal of Forestry and Plant Science Jurnal Elkasista ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An 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 Jurnal Riset Rumpun Ilmu Pendidikan (JURRIPEN) Prosiding Seminar Nasional Unimus UPGRADE: Jurnal Pendidikan Teknologi Informasi Jurnal Ilmu Komputer dan Teknologi Informasi ABDIMASTEK 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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K-Nearest Neighbor Performance Optimization for Multiclass Imbalance of Intrusion Detection Data Using SMOTE and Distance Variation-Based Parameter Tuning Hairani Hairani; Christopher Michael Lauw; Sri Farida Utami; Afrig Aminuddin; Abu Tholib
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7489

Abstract

The increasing use of computer networks and internet-based services has made cybersecurity threats more complex. Intrusion Detection Systems (IDS) play a crucial role in identifying network attacks; however, conventional signature- or rule-based approaches are limited in handling novel attacks and dynamically changing attack patterns. Therefore, machine learning approaches are applied to enhance the adaptive capabilities of IDS. Nevertheless, the use of machine learning in IDS still faces a major challenge: data imbalance, where normal traffic significantly outweighs attack traffic. This condition biases models toward the majority class, leading to suboptimal detection of minority attacks. Based on this issue, this study aims to improve the performance of the K-Nearest Neighbor (KNN) method in network attack detection by applying the Synthetic Minority Over-sampling Technique (SMOTE) and parameter tuning. The study employs KNN with parameter tuning and SMOTE to address multiclass data imbalance in network attack detection. Parameter tuning is conducted to determine the optimal value of k and distance functions, including Euclidean, Manhattan, and Cosine Similarity. The results show that KNN with k = 3 and Manhattan distance on SMOTE-balanced data achieves the highest accuracy of 96.51%, outperforming Euclidean and Cosine Similarity distances. These findings conclude that applying SMOTE and appropriately selecting k and distance metrics significantly improve KNN performance in network attack detection and increase overall detection accuracy.
Analisis Pola Pembelian Konsumen Menggunakan Algoritma FP-Growth pada Data Transaksi Restaurant Burger Nindya Alifia Khumaira; Dadang Priyanto; Hairani Hairani; Galih Hendro Martono; Moch. Syahrir; Husain Husain
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 3 (2026): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i3.983

Abstract

Fast-food restaurants generate large volumes of transaction data that can be utilized to understand customer purchasing behavior and support business decision-making. However, transaction data are often used only for operational reporting, limiting their potential for identifying product association patterns. This study aims to apply the Frequent Pattern Growth (FP-Growth) algorithm to discover frequent itemsets and association rules from burger restaurant transaction data and implement the results in a web-based application. The dataset used consists of 2,001 burger restaurant transactions collected from Kaggle, covering the period 2021–2023. The research process included data preprocessing, transaction transformation, FP-Tree construction, frequent itemset extraction, and association rule generation using a minimum support threshold of 2 transactions and a minimum confidence threshold of 60%. The results revealed that the most frequent items were Save Point Sundae (191 transactions), Health Potion Smoothie (181 transactions), and Cheat Code Cookies (164 transactions). Several association rules achieved a confidence value of 100%, indicating a strong co-occurrence relationship between products. Furthermore, the rules Avatar Avocado -> Cosmic Rings and Cosmic Rings -> Avatar Avocado obtained a lift ratio of 1.50, demonstrating a positive association between the two items. These findings indicate that FP-Growth is effective in identifying customer purchasing patterns and can support promotional strategies, product bundling, and inventory management through data-driven decision-making.
SMOTE Variants and Random Forest Method: A Comprehensive Approach to Breast Cancer Classification Baiq Candra Herawati; Hairani Hairani; Juvinal Ximenes Guterres
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.147

Abstract

This research focused on using machine learning methods for breast cancer diagnosis, considering that breast cancer is the scariest disease for women because it can cause mortality. Not only that, but there is also an increase in breast cancer death rates in women yearly.  Early prediction is the right solution to increase life expectancy and reduce mortality rates caused by breast cancer. However, breast cancer data has a problem, namely that the data is imbalanced, which harms the performance of the machine learning method itself. In the data, breast cancer had a Benign class (357 instances) more than the Malignant class (212 instances). Therefore, this study aimed to solve the problem of imbalanced data using the Smote variants and Random Forest approaches in breast cancer classification. The results of this study showed that the Smote approach with Random Forest had the best performance compared to Borderline Smote and Random Forest in the case of breast cancer data classification, where Smote with Random Forest produced an accuracy of 97.3%, sensitivity of 96.9%, and specificity of 97.8%. In comparison, Borderline Smote with Random Forest produced an accuracy of 96.4%, sensitivity of 95.6%, and specificity of 96.9%. The results of this study can contribute to predicting breast cancer using the proposed method, because it has been proven to have high accuracy.
Enhancing Hotel Recommendation Using Multi-Criteria Neural CollaborativeFiltering Abu Tholib; Fathorazi Nur Fajri; Ilham Saifudin; Hairani; Juvinal Ximenes Guterres
Upgrade : Jurnal Pendidikan Teknologi Informasi Vol 4 No 1 (2026): Agustus 2026 In-Press
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/upgrade.v4i1.6253

Abstract

The increasing volume of hotel information on online travel platforms made hotel selection more difficult for users because decision making had to consider multiple aspects simultaneously, including value, accessibility, service, room quality, cleanliness, and sleep quality. Conventional recommendation methods often depended on overall ratings and therefore were not sufficiently capable of representing the multidimensional nature of hotel preferences. This study proposed an improved multi-criteria neural collaborative filtering (MCNCF) model for hotel recommendation using the Bali Hotel Review dataset. The proposed model integrated user identity, hotel identity, and six structured hotel evaluation criteria to learn user preferences in a more detailed and preference-sensitive manner. The experimental design was also strengthened through a more reliable preprocessing and evaluation pipeline, including data splitting before scaling, training-based imputation for missing values, and user ranking evaluation. The model was implemented using embedding-based neural interaction learning to capture nonlinear relationships between users, hotels, and multi-criteria features. The results showed that the proposed approach achieved stable and competitive performance across testing splits of 10%, 20%, 30%, and 40%. On the original rating scale, the model produced the best Root Mean Square Error of 0.416400 and the lowest Mean Absolute Error of 0.351719. In addition, the ranking performance remained consistently high, with Normalized Discounted Cumulative Gain values ranging from 0.976540 to 0.996243. These findings demonstrated that the proposed approach provided an effective and robust solution for hotel recommendation by leveraging structured multi-criteria preference information within a neural recommendation framework.
Pemberdayaan Transmigran Melalui Penerapan Sistem Pertanian Adaptif Berbasis Padi Apung, Tata Air Mikro, Dan Pengelolaan Perikanan Di Lahan Tergenang Desa Papuyuan Kabupaten Balangan Firdaus, Adhitya; Adrianto, Muhammad Subhan Dwi; Nisa, Rahayu; Lestari, Jumiati Indah; Hasanah, Maulida; Febriana, Annisa Dwi; Hairani, Hairani; Fikrulia, Hidayah Jihan; Ghifari, Muhammad; Regandara, Ellysia Putri; Ekawati, Diah; Adawiyah, Rabi'atul; Hadi, Abdul; Mubarak, Ahmad Nazhif; Andani, Nazwa Putri
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 11 No. 3 (2026): September
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/linov.v11i3.4843

Abstract

Desa Pupuyuan memiliki karakteristik lahan rawa dengan kondisi jenuh air yang membatasi produktivitas pertanian padi konvensional. Kondisi ini juga menyimpan potensi sumber daya perikanan dan tanaman lokal. Program pemberdayaan masyarakat ini bertujuan untuk mengoptimalkan potensi lokal melalui penerapan sistem padi apung, pengolahan ikan dan genjer menjadi produk bernilai ekonomi. Metode pelaksanaan meliputi survei kebutuhan, sosialisasi, pelatihan, praktik langsung, serta monitoring dan evaluasi dengan pendekatan partisipatif. Kegiatan melibatkan masyarakat, perangkat desa, dan mahasiswa sebagai pendamping. Pendekatan partisipatif digunakan agar masyarakat dapat memahami dan menerapkan teknologi yang diperkenalkan secara mandiri. Hasil dan pembahasan menunjukkan bahwa tingkat penerimaan masyarakat terhadap program tergolong tinggi, dengan 90% responden menyatakan puas dan tertarik. Sistem padi apung dinilai sesuai dengan kondisi lahan tergenang karena mampu mengatasi masalah banjir. Selain itu, pengasapan ikan dan pengolahan genjer menjadi keripik mampu meningkatkan nilai tambah dan memperpanjang masa simpan hasil produksi. Kendala yang dihadapi meliputi keterbatasan biaya awal, partisipasi masyarakat yang belum merata, serta kendala logistik dan infrastruktur. Berdasarkan hal tersebut, teknologi sederhana berbasis potensi lokal efektif meningkatkan pengetahuan, keterampilan, dan ekonomi masyarakat. Keberlanjutan program memerlukan pendampingan berkelanjutan dan keterlibatan aktif masyarakat. Increasing the Capacity of Transmigrants Through an Adaptive Farming System Based on Floating Rice and Fish Smoking in Flooded Land in Pupuyan Village, Balangan Regency Abstract Pupuyuan Village is characterized by swampy, water-saturated conditions that limit the productivity of conventional rice farming. These conditions also hold potential for local fisheries and plant resources. This community empowerment program aims to optimize local potential through the implementation of a floating rice system, processing  fish and genjer into economically valuable products. Implementation method include  needs surveys, outreach, training, hands-on practice, and monitoring and evaluation using a participatory approach. Activities involve the community, village officials, and students as facilitators. A participatory approach is used to  enable the community to understand and independently implement the introduced technology. Results and discussions indicate a high level of community acceptance of the program, with 90% of respondents expressing satisfaction and interest. The floating rice system is considered suitable for inundated land conditions because it can address flooding issues. In addition, smoking fish and processing genjer into chips can increase added value and extend the shelf life of produce. Challenges faced include limited initial costs, uneven community participation, and logistical and infrastructure constraints. Based on this, simple technology based on local potential is effective in improving community knowledge, skills, and economics. The program’s sustainability requires ongoing mentoring and active community involvement.
UTILIZATION OF FREE ENERGY FOR POWER CHARGING USING MAGNETIC GENERATORS IN MILITARY OPERATIONS IN REMOTE AREAS Rian Putra Eka Setiawan; Kasiyanto Kasiyanto; Hairani Hairani
Elektronika Sistem Senjata Vol 6 No 1 (2025): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v5i2.522

Abstract

Penelitian ini bertujuan mambantu tugas pokok TNI-AD menggunakan Generator magnet yang memiliki konsep free energy sebagai solusi untuk penyediaan energi dalam operasi militer, terutama di wilayah terpencil di mana sumber energi konvensional kurang dan sulit dijangkau. Generator magnet yang dirancang untuk dapat beroperasi pada kecepatan rendah dapat mengisi perangkat militer dengan generator magnet yang memiliki konsep free energy. Dengan desain, pengujian, dan analisis generator magnet yang dioptimalkan untuk pengisian daya pada kecepatan rendah. Penelitian ini adalah bertujuanagar generator magnet menghasilkan energy yang dapat digunakan di medan operasi militer terpencil. Hasil pengujian menunjukkan bahwa generator ini mampu menghasilkan energi yang tinggi dengan efisiensi mencapai 82,3% pada kecepatan 200 RPM. Energi yang dihasilkan cukup untuk mengisi daya perangkat militer dan menyediakan cadangan daya yang stabil. Dengan kemampuan ini, generator magnet yang dirancang dapat menjadi sumber daya yang cukup untuk mendukung operasi militer di medan yang sulit dijangkau.
ANALYSIS OF THE KALMAN FILTER METHOD ON A GYROSCOPE TO REDUCE NOISE TO IMPROVE RESPONSIBILITY IN A SHOOTING Dekki Widiatmoko; Rian Putra Eka Setiawan; Hairani Hairani; rokhim utomo
Elektronika Sistem Senjata Vol 6 No 2 (2025): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v6i2.671

Abstract

This study aims to analysis how effective the Kalman Filter method is in reducing noise in gyroscope signals to improve the responsiveness of a shooting simulator. By using the Kalman Filter, the data from the gyroscope becomes more accurate, leading to a more realistic shooting simulation experience. The clearer signal not only improves orientation accuracy but also reduces the system's response time, making the simulator faster and more precise in reacting to user inputs. The results show that the Kalman Filter significantly enhances the performance of the shooting simulator, which is crucial in military and security settings where accuracy and quick response are essential.
Optimasi Artificial Intelligence Sebagai Sistem Tutor Cerdas Pada Pembelajaran di SMA Muhammadiyah 1 Rambipuji Ilham Saifudin; Rohmad Wahid Rhomdani; Dudi Irawan; Hairani; Salahudin Robo; Yuri Ariyanto
ABDIMASTEK Vol. 4 No. 2 (2025): Desember
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Latar Belakang program pengabdian masyarakat ini adalah belum meratanya pengetahuan dan praktik penggunaan AI (Artificial Intelligence) di sekolah SMA Muhammadiyah 1 Rambipuji Jember. Tujuan program ini mendapatkan pengetahuan dalam membuat media pembelajaran menarik dengan menggunakan AI dan menggunakan AI dalam membuat media pembelajaran, seperti: video pembelajaran, slide presentasi, hiburan, dan lain-lain. Metode yang digunakan adalah program penyediaan buku panduan praktik dalam mempraktekkan AI sebagai tutor cerdas. Target luaran yang akan dihasilkan adalah mengenal atau memiliki pengetahuan lebih dan media pembelajaran berbasis AI. Hasil dari program ini diantaranya: Guru-guru SMA Muhammadiyah 1 Rambipuji dapat memiliki pengetahuan dan keterampilan dalam membuat media pembelajaran berbasis AI. Kesimpulan, program ini berhasil mencapai tujuan dengan memberikan dampak positif bagi guru-guru dalam penggunaan AI dalam pembuatan media pembelajaran di sekolah.
Pelatihan dan Pendampingan Digital Marketing untuk Meningkatkan Daya Saing UMKM Binaan BRIDA Provinsi Nusa Tenggara Barat Bukran Bukran; Muhammad Tahir; Muhamad Wisnu Alfiansyah; Miftahul Madani; Mudawil Qulub; Hairani Hairani
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 7 No. 1 (2026): ADMA: Jurnal Pengabdian dan Pemberdayaan Mayarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v7i1.6503

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kapasitas pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) dalam memanfaatkan digital marketing sebagai strategi peningkatan daya saing usaha di era ekonomi digital. Mitra kegiatan adalah pelaku UMKM binaan Badan Riset dan Inovasi Daerah (BRIDA) Provinsi Nusa Tenggara Barat. Permasalahan yang dihadapi mitra meliputi rendahnya literasi digital, keterbatasan pemanfaatan media sosial sebagai media promosi, serta belum optimalnya penggunaan marketplace dan platform digital untuk pemasaran produk. Metode pelaksanaan dilakukan melalui sosialisasi, pelatihan, praktik langsung, pendampingan, dan evaluasi. Materi yang diberikan meliputi penyusunan strategi pemasaran digital, pembuatan konten promosi menggunakan aplikasi Canva, optimalisasi media sosial, pemanfaatan marketplace, serta pengenalan Google Business Profile. Hasil kegiatan menunjukkan adanya peningkatan pemahaman peserta mengenai strategi pemasaran digital serta meningkatnya kemampuan peserta dalam membuat konten promosi dan memasarkan produk secara digital. Peserta juga menunjukkan antusiasme tinggi selama sesi praktik dan diskusi. Kegiatan ini diharapkan mampu mendorong transformasi digital UMKM sehingga mampu meningkatkan daya saing serta memperluas jangkauan pasar.
A Comparison of Logistic Regression, Random Forest, and XGBoost Based on Feature Importance in Heart Failure Prediction M. Thoriq Panca Mukti; Hairani Hairani; Djoko Rahardjo; M. Rizki
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 5 No. 2 (2026): September 2026 (In Press)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v5i2.6583

Abstract

Heart failure is a cardiovascular disease with a high mortality rate, requiring a prediction system capable of assisting in faster and more accurate early detection. This study aims to compare the performance of Logistic Regression, Random Forest, and XGBoost in predicting heart failure, with a focus on feature importance. The dataset is a public Kaggle dataset, consisting of 918 patient records with 11 features and 1 target attribute. The research stages include exploratory data analysis (EDA), data preprocessing, anomaly handling, label encoding, data standardization, model training, model evaluation, and feature importance analysis. Model evaluation was conducted using accuracy, precision, recall, and F1-score. The results indicate that Random Forest achieved the best performance, with an accuracy of 86.96%, a precision and recall of 88.24%, and an F1-score of 88.24%. Meanwhile, XGBoost achieved an accuracy of 85.87%, and Logistic Regression achieved 84.78%. The feature importance analysis revealed that the ST_Slope attribute was the most dominant feature across all three models in predicting heart failure. This study demonstrates that the Random Forest method provides superior classification performance compared to the other models, and feature importance analysis can aid in interpreting the clinical attributes that influence heart failure prediction.
Co-Authors Abdillah, Mokhammad Nurkholis Abdul Hadi Abdurraghib Segaf Suweleh Abdurraghib Segaf Suweleh Abu Tholib Adam, M. Awaludin Adawiyah, Rabi'atul Adrianto, Muhammad Subhan Dwi Afrig Aminuddin Ahmad Ahmad Ahmad Fathoni Ahmad Zuli Amrullah Aleeka Jasmine Amelia, Bengi Ameylan Verina Tabun Amin, Farda Milanda Andani, Nazwa Putri Andi Sofyan Anas Andi, Moh syaiful Andini, Nisha Anggarawan, Anthony Anthony Anggrawan Arfa, Muhammad Arifah Ulayya Ashadi, Diki Astuti, Ni Luh Budi Ayu Dasriani, Ni Gusti Bukran Bukran Candra, M. Ade Christine Eirene Christopher Michael Lauw Christopher Michael Lauw Dadang Priyanto Dedi Aprianto Dedy Febry Rachman Dedy Febry Rahman Dekki Widiatmoko Deny Jollyta Diah Ekawati Dian Syafitri Didik Dwi Prasetya Diki Ashadi Dirgantara, Bhintang Djoko Rahardjo Donny Kurniawan Dyah Susilowati Dyah Susilowaty ED. Yunisa Mega Pasha ED. Yunisa Mega Pasha Efendi, Muhamad Masjun Eka Setiawan, Rian Putra Ezra Azzahra Fahry, Fahry Fathorazi Nur Fajri Fatimatuzzahra Fatimatuzzahra Febriana, Annisa Dwi Fikrulia, Hidayah Jihan Firdaus, Adhitya Fitra Rizki Ramdhani Galih Hendro Martono Gede Yogi Pratama Gibran Satya Nugraha Gibran Satya Nugraha Guntara, Muhammad Gusti Ayu Diah Gita Kartika Santi, I Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasanah, Maulida Hasbullah Hasbullah Herawati, Baiq Candra Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila Husain Husain I Gusti Agung Ayu Hari Triandini I Nyoman Switrayana Ida Putu Andika Ifnaldi Ifnaldi Iis Sopiah Suryani Ilham Saifuddin Indah Puji Lestari Indradewa, Rhian Irawan, Dudi 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 Kasiyanto, Kasiyanto Khairan marzuki Khairil Ihsan Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lalu Zazuli Azhar Mardedi Lestari, Jumiati Indah Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho M. Rizki M. Thoriq Panca Mukti M.Khaerul Ihsan M.Khaerul Ihsan Maariful Huda, Muhammad Malika, Riwayati Mamay Maulana Mamay Maulana Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Melati Rosanensi Mia Nisrina Anbar Fatin Michael Lauw, Christopher Miftahul Madani Mubarak, Ahmad Nazhif Mudawil Qulub Muhamad Azwar Muhamad Azwar, Muhamad Muhamad Reza Pahlevi Muhamad Reza Pahlevi Muhamad Wisnu Alfiansyah Muhammad Arfa Muhammad Fahmi Muhammad Ghifari, Muhammad Muhammad Innuddin Muhammad Maariful Huda Muhammad Ridho Akbar Muhammad Ridho Hansyah muhammad Syahbudi, muhammad Muhammad Tahir Muhammad Turmuzi Muhammad Zulfikri Muhammad Zulfikri Muhammad Zulkarnaen Haris Mujahid Mujahid Neny Sulistianingsih Ni Made Gita Gumangsari Nindya Alifia Khumaira Nisa, Rahayu Noor Akhmad Setiawan Novitasari Tsamrotul Fuadah Nur Intan Hayati Nur Intan Hayati Nurhayati, Lilik Nurul Azmi Nurvianti, Nurvianti Nuzululnisa, Bq Nadila Pahrul Irfan Pratama, Gede Yogi Putu Tisna Putra Qososyi, Sayidina Ahmadal Rahayun Amrullah Husaini Rahman, Mochamad Farhan Caesar Rahmawati, Lela Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rangga Wijaya Regandara, Ellysia Putri Rhomdani, Rohmad Wahid Rian Putra Eka Setiawan Rifqi Hammad Rio Riswanto Simanjuntak Riosatria, Riosatria Riwayati Malika Rizki Wahyudi Robo, Salahudin rokhim utomo Rosyda, Miftahurrahma RR. Ella Evrita Hestiandari Saifuddin Zuhri Saifuddin, Ilham Saifudin, Ilham Samsul Hadi Santoso, Heroe Shudiq, Wali Ja'far Soepriyanto, Harry Sofiansyah Fadli Soni Muhsinin Sri Farida Utami Sri Winarni Sofya Sri Winarni Sofya Sudi Prayitno Sukron, Moh Sutarman Sutarman Syahrir, Moch. tadianta m., Winardi aries Teguh Bharata Adji Tri Nur Jayanti Tri Nur Jayanti Triwijoyo, Bambang Krismono Triyanna Widiyaningtyas Umi Hanifah Vidiasari, Herlita Vidiasari, Viviana Herlita Vina Vitniawati Wahyuningsih, Rr. Sri Handari Wangiyana, I Gde Adi Suryawan Wening Asih Sutrisno Wening Asih Sutrisno Widhya Aligita Widhya Aligita Widiatmoko, Dekki Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Yuri Ariyanto Zilullah Nazir Hadi