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All Journal Prosiding SNATIF Infotech Journal PROCEEDING IC-ITECHS 2014 JITEK (Jurnal Ilmiah Teknosains) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI INTECOMS: Journal of Information Technology and Computer Science IJISTECH (International Journal Of Information System & Technology) Indonesian Journal of Applied Informatics Jurnal Teras Kesehatan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Terpadu Journal of Information System, Applied, Management, Accounting and Research Jurnal ICT : Information Communication & Technology Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Manajemen Informatika dan Sistem Informasi Generation Journal JTIK (Jurnal Teknik Informatika Kaputama) G-Tech : Jurnal Teknologi Terapan Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Bumigora Information Technology (BITe) Journal of Advanced in Information and Industrial Technology (JAIIT) Infotek : Jurnal Informatika dan Teknologi Madaniya Tematik : Jurnal Teknologi Informasi Komunikasi Infotech: Journal of Technology Information Journal of Computer Networks, Architecture and High Performance Computing SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) IJISTECH Infotech: Jurnal Informatika & Teknologi Jurnal Pendidikan dan Teknologi Indonesia DEVICE International Journal Software Engineering and Computer Science (IJSECS) Jurnal Dinamika Informatika (JDI) Jurnal Teknik Informatika Jurnal Informatika Teknologi dan Sains (Jinteks) Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Asian Journal of Community Services (AJCS) Mafaza : Jurnal Pengabdian Masyarakat STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Proceeding of International Conference Health, Science And Technology (ICOHETECH) Journal Research of Social Science, Economics, and Management Adopsi Teknologi dan Sistem Informasi Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Innovative: Journal Of Social Science Research Journal of Software Engineering and Information System (SEIS) Journal Of Artificial Intelligence And Software Engineering SmartComp Jurnal Ilmu Komputer dan Sistem Informasi RESLAJ: Religion Education Social Laa Roiba Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) International Journal of Community Service Implementation Jurnal Teknik Silitek
Maulindar, Joni
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Sistem Peminjaman Alat Laboratorium Berbasis RFID dan IoT di Fakultas Kedokteran Gigi UMS Mulyanto, Hari; Maulindar, Joni; Lestari, Wiji
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30631

Abstract

Laboratories play a crucial role in supporting academic activities at health education institutions. However, inventory management at the Laboratory of the Faculty of Dentistry, Universitas Muhammadiyah Surakarta (UMS), is still conducted manually, leading to recording errors, service delays, and difficulties in real-time equipment monitoring. These issues hinder students from accessing information about the availability and location of equipment needed during practical sessions. This study aims to develop a laboratory equipment loan administration system using Radio Frequency Identification (RFID) technology integrated with the Internet of Things (IoT). The system was developed using the prototyping method, utilizing the ESP8266 and RFID RC522 sensor as the main components to support automated, contactless identification of equipment. The developed system is capable of digitally recording and monitoring the borrowing and returning of equipment in a structured and real-time manner. Testing results show that the system functions properly and meets user needs, although it has a limitation in RFID reading distance, with a maximum range of only 3 cm. This constraint presents a challenge for field implementation. Overall, the system has proven to improve efficiency, accuracy, and transparency in laboratory inventory management and supports the digitalization of technology-based equipment loan processes.
Training IoT Development for Enhancing Search and Rescue Tracking and Educational Tools Maulindar, Joni; Andrianto, Albertus Ari; Nandita Sekar Sukma Dewi
Asian Journal of Community Services Vol. 3 No. 8 (2024): August 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajcs.v3i8.10784

Abstract

The Internet of Things (IoT) Development Training at Universidade Oriental Timor Lorosa’e aims to address challenges in tracking search and rescue teams and enhance educational tools. This training is designed to provide an in-depth understanding of IoT technology and its applications in operational and educational contexts. The methods used include theoretical sessions, hands-on practice, and project evaluation. The evaluation results show a significant increase in participants' knowledge levels: understanding of IoT concepts increased from 40% to 85%, knowledge of IoT applications rose from 35% to 80%, the ability to use IoT devices improved from 30% to 75%, and skills in developing IoT systems advanced from 25% to 70%. The success of this training reflects the positive impact of IoT technology in enhancing participants' skills, potentially bringing long-term benefits to both fields discussed at Universidade Oriental Timor Lorosa’e.
PREDICTION AND PREVENTION OF DISEASE DIAGNOSIS DELAY USING DATA MINING METHODS IN HEALTHCARE QUALITY MANAGEMENT Maulindar, Joni; Guterres, Juvinal Ximenes; Rosita, Riska
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2023: Proceeding of the 4th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/icohetech.v4i1.3376

Abstract

This study analyzes the issue of disease diagnosis delay in healthcare quality management using data mining methods. The aim is to understand the relationship between several key variables and diagnosis delay for various diseases. The study focuses on the variables of Age, Symptom Duration, Physician Experience, and Diagnosis Delay. Advanced data mining methods are employed to predict and prevent disease diagnosis delays. The results of this study present the findings from the analysis of the collected dataset. The dataset consists of patient information, including attributes such as Patient ID, Age, Symptom Duration, Physician Experience, Diagnosis Delay, and Treatment Initiation. Each attribute plays a crucial role in understanding and predicting diagnosis delay. The approach using linear regression yields coefficients [0.03260123, 0.24605912, 0.01765057, 1.09631713], indicating the influence of each variable on Diagnosis Delay. The Mean Squared Error (MSE) value of 0.7926 signifies the model's ability to predict Diagnosis Delay accurately. The scatter plot illustrates the linear relationship between actual Diagnosis Delay and predicted Diagnosis Delay. The Pearson's Correlation Coefficient of 0.5222 indicates a moderate positive correlation between the two. However, the residual plot indicates a tendency for underestimation of Diagnosis Delay for higher values.
Challenges in The Academic Promotion Process: Perspectives From Faculty Members Maulindar, Joni; Awang Long, Zalizah; Che Mustapha, Jawahir; Purnomo, Singgih
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2024: Proceeding of the 5th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/icohetech.v5i1.4127

Abstract

The academic promotion process faces various challenges that cause delays for faculty members in reaching higher ranks. This research aims to identify and analyze the factors contributing to delays in the academic promotion process. The research method used is a quantitative approach, with data collection techniques involving the distribution of questionnaires to faculty members who are currently undergoing or about to undergo the academic promotion process. The research results indicate that the lack of transparency in rules, policy changes, evaluation complexity, communication limitations, and institutional support all have a significant and equal impact on the challenges of academic promotion, with each factor having a coefficient of 0.2000. The R-squared and Adjusted R-squared values of 1.000 indicate that this model can explain the entire variation in academic promotion challenges. The high statistical significance of all coefficients suggests that these results are almost certainly not due to chance. Data analysis also shows that there is little autocorrelation in the model's residuals, and the residual distribution is nearly normal. These findings highlight the importance of transparency, policy consistency, effective communication, and institutional support in the academic promotion process. Improvements in these areas are expected to reduce the challenges faced by faculty members during the promotion process
Intelligent Traffic Sign Detection Using Yolov9 Pradana, Afu Ichsan; Harsanto, Harsanto; Maulindar, Joni
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2024: Proceeding of the 5th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/icohetech.v5i1.4205

Abstract

This research examines the automatic detection and classification of traffic signs using artificial intelligence (AI) and computer vision technologies. As urban traffic increases, quickly and accurately recognizing traffic signs becomes a challenge, especially under adverse conditions such as bad weather and limited visibility. Conventional technologies that rely on human vision are prone to errors, so an automated solution is needed. This research uses the YOLOv9 algorithm for real-time traffic sign detection, utilizing the Generalized ELAN (GELAN) architecture that combines the advantages of CSPNet and ELAN for efficiency and accuracy. The dataset used consists of 1924 images processed through various stages, including data augmentation and normalization. The model was trained for 15 epochs with fairly high accuracy results in the prohibitory, danger, and mandatory sign categories. However, there were still some misclassifications, especially in the prohibitory category which was sometimes mistakenly detected as another category or background. Overall, the model performed well in detecting traffic signs in various environmental conditions, but still needs improvement to increase accuracy in certain cases.
Sistem Rekomendasi Penentuan Majelis Hakim Perkara Tingkat Pertama Menggunakan Metode Support Vector Machine (SVM) pada Pengadilan Agama Sragen Shoffia Fajrin; Joni Maulindar; Afu Ichsan Pradana
IJAI (Indonesian Journal of Applied Informatics) Vol 10, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v10i1.103979

Abstract

Abstrak : Penetapan majelis hakim secara manual di Pengadilan Agama Sragen sering kali memerlukan waktu hingga tiga hari dan berisiko menimbulkan ketidakefisienan, terutama ketika jumlah perkara tinggi dan ketua pengadilan berhalangan hadir. Penelitian ini bertujuan mengembangkan sistem rekomendasi susunan majelis hakim perkara tingkat pertama dengan metode Support Vector Machine (SVM) untuk memberikan rekomendasi yang lebih cepat dan efisien kepada Ketua Pengadilan Agama Sragen. Sistem dibangun menggunakan pendekatan hybrid, menggabungkan model klasifikasi SVM untuk perkara umum dan rule-based untuk perkara khusus seperti ekonomi syariah dan dispensasi kawin. Dataset yang digunakan terdiri atas 1.428 data perkara dan delapan profil hakim, yang diproses melalui tahap pembersihan teks, ekstraksi kata kunci, transformasi fitur dengan TF-IDF dan one-hot encoding, serta balancing data menggunakan SMOTE. Model dilatih dengan kernel RBF dan divalidasi melalui 5-fold cross-validation. Hasil pengujian menunjukkan model ketua majelis mencapai F1-score 64%, akurasi 63%, presisi 66%, dan recall 63%. Sementara model anggota 2 memperoleh F1-score 56%, dan anggota 1 sebesar 36%. Confusion matrix memperlihatkan bahwa sistem dapat mengenali pola penugasan hakim dominan namun masih kesulitan menangani kelas minoritas. Sistem ini menunjukkan potensi sebagai alat bantu rekomendasi yang mampu meningkatkan efisiensi, akurasi, dan konsistensi dalam penetapan majelis hakim.=================================================Abstract :Manual assignment of judicial panels at the Sragen Religious Court often takes up to three days and poses a risk of inefficiency, especially when the case load is high and the chief judge is unavailable. This study aims to develop a recommendation system for composing first-instance judicial panels using the Support Vector Machine (SVM) method, in order to provide faster and more efficient recommendations to the Chief Judge of the Sragen Religious Court. The system is built using a hybrid approach, combining an SVM classification model for general cases and a rule-based approach for special cases such as Islamic finance and marriage dispensation. The dataset used consists of 1,428 case records and eight judge profiles, processed through text cleaning, keyword extraction, feature transformation using TF-IDF and one-hot encoding, and class balancing using SMOTE. The model is trained with the RBF kernel and validated using 5-fold cross-validation. Evaluation results show that the model for the chief judge achieved an F1-score of 64%, accuracy of 63%, precision of 66%, and recall of 63%. Meanwhile, the model for member 2 reached an F1-score of 56%, and member 1 only 36%. The confusion matrix reveals that the system can recognize dominant judge assignment patterns, although it still struggles with minority classes. This system demonstrates strong potential as a recommendation tool that can enhance efficiency, accuracy, and consistency in judicial panel assignments.
Sistem Rekomendasi Kuliner Karanganyar Menggunakan Metode Hybrid Recommendation Radya Prameswari Putri; Joni Maulindar; Afu Ichsan Pradana
Progresif: Jurnal Ilmiah Komputer Vol 21, No 2 (2025): Agustus
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i2.3105

Abstract

Karanganyar has many culinary tourist destinations, but the number of diverse choices often makes it difficult for users to choose where to eat according to their preferences. Therefore, this research aims to help users find culinary places based on special menus. The recommendation system will be developed using a hybrid approach by combining content-based filtering and collaborative filtering. The content-based method matches the special menu with user input using cosine similarity, while collaborative filtering calculates the score from the normalized rating and the number of reviews using the weighted sum. A weight of 0.6 is given for content-based and 0.4 for collaborative because direct preference for menus is considered more dominant. The test was carried out using 5 different menus using precision and recall, with the test results for 100% recall, and the precision got a score of 75.42% because there are still recommendations displayed in the system that only have similar characteristics but are not really relevant to the user's preferencesKeywords: Collaborative filtering; Content-based filtering; Hybrid recommendation; Culinary recommendation; Recommendation system. AbstrakKaranganyar memiliki banyak destinasi wisata kuliner, namun jumlah pilihan yang beragam sering menyulitkan pengguna dalam menentukan tempat makan sesuai preferensi. Oleh karena itu, penelitian ini bertujuan untuk membantu pengguna menemukan tempat kuliner berdasarkan menu spesial. Sistem rekomendasi yang akan dikembangkan menggunakan pendekatan hybrid dengan menggabungkan content-based filtering dan collaborative filtering. Metode content-based mencocokkan menu spesial dengan input pengguna menggunakan cosine similarity, sedangkan collaborative filtering menghitung skor dari rating yang dinormalisasi dan jumlah ulasan dengan menggunakan weighted sum. Bobot 0,6 diberikan untuk content-based dan 0,4 untuk collaborative karena preferensi langsung terhadap menu dinilai lebih dominan. Pengujian dilakukan dengan menggunakan 5 menu yang berbeda menggunakan precision dan recall, dengan mendapatkan hasil pengujian untuk recall 100%, dan precision mendapatkan nilai 75,42% karena masih ada rekomendasi yang ditampilkan disistem yang hanya mirip karakteristiknya tetapi tidak benar-benar relevan dengan preferensi penggunaKata Kunci: Collaborative filtering; Content-based filtering; Hybrid recommendation; Rekomendasi kuliner; Sistem rekomendasi 
Desain Prototipe Pemberi Pakan Otomatis Untuk Kucing Peliharaan Berbasis Internet of Things (IOT) dengan Fitur Monitoring Real Time Hani Rifdah Azizah; Joni Maulindar
Reslaj: Religion Education Social Laa Roiba Journal Vol. 7 No. 10 (2025): RESLAJ: Religion Education Social Laa Roiba Journal
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/reslaj.v7i10.9345

Abstract

                The need for regular feeding of pets, especially cats, presents a challenge for owners with busy schedules. Irregular feeding can negatively impact the animal's health. This research aims to design a prototype of an automatic pet feeder based on the Internet of Things (IoT) with real time monitoring and control features. The system is developed using an ESP32 microcontroller, HX711 load cell sensor, servo motor, RTC DS3231 real time clock module, vibration sensor, and the Blynk application as a remote interface. The method used is the Prototype model. The system operates in two modes: automatic mode using the schedule from the Blynk app and offline automatic mode using a default schedule from the RTC when not connected to the internet. Additionally, a manual mode is available via a physical button. The system is tested for both hardware and software functionality, as well as automation performance. Results show the system can dispense food on schedule with good accuracy and display real time status via an OLED screen and the Blynk app. This system is expected to be an efficient and flexible solution for pet owners in managing automated feeding..
SISTEM MONITORING KUALITAS AIR BERBASIS INTERNET OF THINGS DI DESA WONOSARI Gibran Arya Pradana; Joni Maulindar; Agustina Srirahayu
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.417

Abstract

Di daerah-daerah yang masih menggunakan inspeksi manusia sebagai norma, kesehatan masyarakat sangat berisiko akibat air berkualitas rendah. Dengan latar belakang tersebut, tujuan penelitian ini adalah untuk mengembangkan dan meluncurkan sistem pemantauan kualitas air di Desa Wonosari yang memanfaatkan Internet of Things (IoT). Untuk lebih melindungi penduduk dari bahaya kesehatan, sistem ini dimaksudkan untuk memberikan data akurat secara real-time tentang suhu air, kekeruhan, total padatan terlarut (TDS), pH, dan karakteristik lainnya. Teknik penelitian meliputi pengumpulan persyaratan, konstruksi prototipe, evaluasi sistem, dan pengujian. Berdasarkan hasil, sensor pH, kekeruhan, suhu air, dan total padatan terlarut (TDS) masing-masing memiliki akurasi 99,22% dan 98,26%. Perangkat tersebut juga lulus uji ketahanan dengan tingkat keberhasilan 96,66% dan margin kesalahan 3,33%. Hasil ini menunjukkan bahwa metode yang diusulkan meningkatkan efektivitas pemantauan kualitas air dan dapat meningkatkan aksesibilitas air, yang pada gilirannya meningkatkan kesehatan masyarakat. Hasilnya, teknologi ini memberikan pendekatan baru terhadap pemantauan kualitas air masyarakat yang aman dan efisien.
Implementation of the Threshold Method in an IoT-Based Monitoring System for Temperature, Humidity and Feed in Broiler Chicken Houses Febryan Djastin Arya Raharja; Joni Maulindar; Arif Setiawan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 8 No. 3 (2026): Research Paper July 2026
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v8i3.8808

Abstract

Broiler chickens require optimal house management to maintain productivity, particularly in terms of temperature, humidity, and feed availability. Monitoring that is still done manually can potentially cause delays in detecting changes in environmental conditions and feed stock, which can hinder the chickens’ growth. This study aims to implement a threshold method in an Internet of Things (IoT)-based monitoring system for temperature, humidity, and feed levels in broiler chicken houses. The study employed the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model, utilizing an ESP32 microcontroller, a DHT22 sensor to measure temperature and humidity, an HC-SR04 sensor to detect feed levels, a 4-channel relay module to control fans and incandescent lights, and a web dashboard connected to a Supabase database for real-time monitoring. The system applies threshold values adjusted to the broiler chickens’ growth phases so that the actuators can operate automatically to maintain optimal coop conditions. Test results show that the system is capable of monitoring temperature, humidity, and feed levels in real time, transmitting data to the web dashboard, and controlling lights and fans according to threshold values specifically, lights turn on when the temperature is below 31°C and fans turn on when the temperature is above 31°C. The implementation of this system improves the effectiveness of monitoring and controlling coop conditions and has the potential to support poultry farm productivity. The system applies threshold values adjusted to the growth phase of the broiler chickens so that the actuators can operate automatically to maintain optimal conditions in the coop. Test results show that the system is capable of monitoring temperature, humidity, and feed levels in real time, transmitting data to a web dashboard, and controlling lights and fans according to threshold values specifically, lights turn on when the temperature is below 31°C and fans turn on when the temperature is above 31°C. The implementation of this system improves the effectiveness of monitoring and controlling coop conditions and has the potential to support broiler farm productivity. Further development can be pursued by adding automatic notification features, improving sensor accuracy, and integrating an automatic feeding system.
Co-Authors Abdullah Abdullah Syaifudin Aditya Rachman Putra Afu Ichsan P Afu Ichsan Pradana Agil Husnul Khotimah Agustina Srirahayu Ahmad Qashid H Ahmad Setiawan Aji, Sindhu Purnomo Akbar Galih Saputra Akbar Akbar, Akbar Galih Saputra Akbar, Reza Maulana Aldin Fathiray Aliefian Hendra Wardana Ananda, Naufal Choirul Andreas Abi Permana Andrianto, Albertus Ari Anggit Hardiyanto Anggita, Febri Arif Anisatul Farida Anisatul Farida Annas Setiawan Prabowo Anugrah Putra, Muhammad Ardani, Hasby Arif Ardhianto, Aan Ardiyanto, Kevin Ardiyanto, Marta Arif Eko Fitrianto Arif Setiawan Arif Setiawan Arif Wicaksono Septyanto Arnan Dwi Arsandy, Noelino Grevansha Avianto Adi Pratama Awang Long, Zalizah Azza Al Abbas, Abdullah A’an Jati Susilo Badrudin, Muhamad Bagas Mutaqqi Bagaskara, Ikrar Bagos Erwanto bagus esti tomo Bagus Prakoso, Ahmad Bahrul Aziz Rifai BAHTIAR, YUSUF Bangun Prajadi Cipto Utomo Bayu Tri Pramono Berlian Agustina, Anggun Bondan Wahyu Pamekas brigitta harlim Che Mustapha, Jawahir Christopher Jody Widiyono Da Costa, Alexandre Daffa Ebtra Satria Dewi, Nandita Dewi, Nandita Sekar Sukma Dhimas Arya Rakadipa Didik Kurniawan Difan Agra Susilo Dika Adi Pratama Dimas Abimanyu Sutrisno Putro Dimas Cahyo utomo Dimas Galuh Pratama Dison Librado Dita Putra Pratama Divangga Revansa Arya Pradhana Dwi Hartanti Dwi Hartanti Dwi Hartanti Dwi Hartanti Dwi Kurniawan Saputro Dwi Resty Kartika Dwiirawan, Ridwan Dyah Aprimavista Cahyani Edy Kurniawan Ega Fuad Ibrahim Eko Purwanto Em Sutrisna Enggar Wijaya Putra Ery Permana Yudha Ery Permana Yudha Ester Anugrayningtyas Fachruddin Edi Fandi Aziz Pratama Fathur Iqbal Hilmi Ulhadi FAULINDA ELY NASTITI Febryan Djastin Arya Raharja Firdaus, Azkha Brilliant Fitria Eko Nurjanah Fitroh Ahmad Abdul Aziz Frisca Tri Arumsari Galang Prambudi Raka Kusuma Gibran Arya Pradana Guterres, Juvinal Ximenes Hafid Affan Wahid Hamna Zakiya , Nasywa Hani Rifdah Azizah Hanif Hilmi, Muhammad Hanif Nur Ahmad Hari Windiyastuti Harsanto Harsanto, Harsanto Hartanto, Didik Mayur Hasanah, Herliyani Hidayat, Almaranda Aisyanissa Hiyarunnisa Kahes Waypi Ibnu Bagus Setiawan Ichwani, Achmad Ila Aulia Rahmah immaculata yolia dewi Widayanti Indah, Ratna Puspita Indrastata, Ilham Buyung Indriyas Kukuh Wijayanti Intan Oktaviani Intan Oktaviani Iqbal Hanan Junaidi Irawan, Egie Irawan, Ridwan Dwi Irfan Ramadhan Istiana Hanifah Istiqomah, Yasinta Jawahir Che Mustapha Yusuf Jawahir Che Mustapha Yusuf Jofan Fathurahman Juvinal Ximenes Guterres Karlina Kusuma Ningrum Kevin Yoga Ananta Kurniawan, Daniel Ade Leny Monica Lidia Earlene Rendhiva Lintang Surya Lola Sekar Arum Lufti Puspitasari Margaretha Evi Yuliana Margaretha Evi Yuliana Mashkul Ryan Ibrahim Matin Muhith Meraldy Fiko Rastio Ajie Mink Poo Lexy Utomo Mink Poo Lexy Utomo Mira Erlinawati Moh Muhtarom Moh. Muhtarom Moh. Muhtarom Moh. Mutarom Muhammad Daivany Nur Auliya Saleh Muhammad Nur Ikhsanudin Mulyanto, Hari Munawaroh, Maysani Mustapha, Jawahir Che Nadia Hepyntha Nailurrizqi, Adistya Nanda Ramadhani, Fikko Nandita Sekar Sukma Dewi Nibras Faiq Muhammad Ningrum, Karlina Kusuma Nugroh, Heri Nur Auliya Saleh, Muhammad Daivany Nur Cahyo Nugroho Nurchim Nurdina Aulia Agustina Nurfadilah Nurfadilah Nurlaili, Dewi Nurohman Nurohman, Nurohman Nurrohman Oktaviyana Dwi Hendra Jati Permatasari, Hanifah Pipin Widyaningsih, M.Kom. Praba M.A.R.K Pramoedya Ananta Dzikri Pramono Pramono Pramono prastiwi, yuyun Prastya, Alvian Bagus Prastyo, Okik Dwi Pratiwi, Dinita Christy Pujiati Edy Santoso, Elysa Mei Puput Dwi Mandiri Puput Dwi Mandiri Putra Pradana, Gibrand Putra, Hadi Widya Nugraha Surya Raafika Studiviani Dwi Binuko Raditya Koesyan Dipo P Radya Prameswari Putri Rais Suryo Wahono Ramasya Alief Islami Raihan Ratna Puspita Indah Rendi Enggar Bintang Pratama Restu Gilang Wijanarko Reza Mar Hendra Putra Ridzkyan Buti Pratama Rifa'i, Rifan Rifan Amirul Hafizh, Muhammad Rifqi Firdausi Arafad Riska Rosita Rizki Hendra Rizqy Mahendra Abdul Rahman Romy Rajawali Nusantara Saifullah Rudi Susanto Saifudin Umar Sandy Yustisio O Sandy Yustisio Okta Viandra Saputra, Muchammad Yoga Setiawan, Gilang Setya Pradhana, Wahyudi Shelvi Azizah Shoffia Fajrin Sindhu Purnomo Aji Singgih Purnomo SRI SUMARLINDA Suci Bunga Pritalina Sudarminingsih Sudarminingsih Sulistyo Adi Prasetyo Syahrul Agung Fathoni Tasya Mutiara Diva Tasya Mutiara Diva Tesalonika, Angel Tigar Riski Septiono Titi Jayanti Tiur Bunga Gadissa Tory, Alfa Rado Andre Yusa Saka Tri Endah Purnamawati Vihi Atina Vita Sofia Prihatini Wahyu Adi Pratama Wahyu Aji Saputro, Lintang Wahyu Kuncoro Warihaji, Wijasena Warta, Danu Widayanti, immaculata yolia dewi Wihan Perkasa Nugraha Putra Wijayanti, Indriyas Kukuh Wijayanti, Sefi Ayuk WIJI LESTARI Wiji Lestari Wijiyanto Yafa Arsyida Aulia Rakhma Yasinta istiqomah Yeyen Santi Putri Yoma Patria Risky, Satya Yusuf Bahtiar Zaenuar Erfandi Zalizah Binti Awang Long