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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Jurnal Kesehatan Lingkungan indonesia Media Statistika JURNAL SISTEM INFORMASI BISNIS Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Sains dan Teknologi Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika WARTA Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Information System E-Dimas: Jurnal Pengabdian kepada Masyarakat Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah KOMPUTIKA - Jurnal Sistem Komputer JTP - Jurnal Teknologi Pendidikan Indonesian Journal of Community Services Journal of Applied Data Sciences Jurnal Riset Teknologi Pencegahan Pencemaran Industri Indonesian Journal of Librarianship Proceeding Biology Education Conference Media Pustakawan STATISTIKA Journal of Bioresources and Environmental Sciences Scientific Journal of Informatics

Budi Warsito

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 413102

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

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Dinamika Literasi Masyarakat Salatiga: Perbandingan Indeks Pembangunan Literasi dan Indeks Literasi 2022 Budi Warsito; Harjum Muharam; Arief Rachman Hakim; Endang Fatmawati; Heriyanto; Yanuar Yoga Prasetyawan
Media Pustakawan Vol. 30 No. 1 (2023): April
Publisher : Perpustakaan Nasional

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

The examination of the Community Literacy Development Index (IPLM) juxtaposed with the Community Literacy Index (ILM) was undertaken as a foundational reference for the establishment of developmental policies and performance metrics. This research was driven by dual objectives: firstly, to ascertain the magnitude of the IPLM within the confines of Salatiga City, and secondly, to gauge the ILM within the same region. The analysis concerning the IPLM was executed to assess the state of libraries across Salatiga, encompassing facets such as spatial distribution of libraries, their respective collections, the competencies of library staff, and their patron demographics. The ILM investigation specifically narrowed its focus to the sub-district echelon, eliciting responses from 400 participants aged between 15 and 64 years. Emerging from the IPLM investigation, it was discerned that out of the 164 libraries included in the census, the composition was as follows: 20 public libraries, 129 school-affiliated libraries, 4 university libraries, and a further 10 specialized libraries. To further categorize by district, Argomulyo accounted for 32 libraries, Tingkir had 37, Sidomukti held 41, and Sidorejo hosted 53. Cumulatively, Salatiga City’s IPLM was determined to be 72.83, placing it within the moderate range (aligning with standard benchmarks). In parallel, the ILM analysis unveiled an overall score of 63.14 for Salatiga City, classifying it within the median spectrum. Within this, Argomulyo District took the lead with an ILM score of 66.30, while Tingkir District lagged with a score of 54.66.

Klasifikasi Penentuan skema Uji Sertifikasi di LSP UDINUS bagi mahasiswa Progrdi Sistem Informasi UDINUS dengan Algoritma Decision Tree (C4.5) Winarno, Agus; Warsito, Budi; Wibowo, Adi; Zeniarja, Junta
JOINS (Journal of Information System) Vol. 7 No. 2 (2022): Edisi November 2022
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v7i2.6429

AbstrakPenerapan Algoritma Decision Tree (C4.5) dan Eksperimen proses klasifikasi dilakukan menggunakan data nilai mahasiswa program studi S1 Universitas Dian Nuswantoro dengan 120.232 dataset menggunakan metode klasifikasi dengan Algoritma Decision Tree menghasilkan 99,99 % dan menghasilkan 7 klasifikasi dengan rekomendasi ntuk pelatihan dan uji sertifikasi di Lembaga sertifikasi profesi UDINUS pada 5 klasifikasi yaitu klasifikasi pred C sejumlah 2.355 data, pred BC sejumlah 4.633, pred B sejumlah 38.420 , pred AB sejumlah 33.414 dan pred A sejumlah 37.230 dan 2 klasifikasi yang tidak direkomendasikan yaitu klasifikasi pred D 1.440 dan pred E sejumlah 2.784 yang memberikan penyesuaian kurikulum pendidikan di Universitas Dian Nuswantoro dengan lembaga Sertifikasi dan Kebutuhan pekerjan. Kata Kunci: Sertifikasi, klasifikasi, mahasiswa, Tree Algorithm, rekomendasi

Analisis Perbandingan SAW dan TOPSIS pada Sistem Pendukung Keputusan Karyawan Terbaik Firdonsyah, Arizona; Warsito, Budi; Wibowo, Adi
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11475

The decision-making process has many assessment criteria needed as the basis for its assessment. A large number of problems regarding the length of time required in the decision-making process require decision-makers to find solutions. Decision Support System is one option that can be developed by decision makers because it can help improve efficiency and accuracy in the decision-making process. The process of developing decision support requires certain calculation methods as part of the processing. The methods that are quite widely used to build a decision support system include the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. This research aims to analyze the accuracy of the cases raised as solutions to decision-making problems. A dynamic decision support system has been successfully created to design dynamics in the calculation of the SAW method and the TOPSIS method. The system is evaluated and analyzed for its accuracy level based on manual calculations. The results obtained are the SAW system has an accuracy value of 65% and the TOPSIS system is 100%. Furthermore, the calculation of the accuracy value of the SAW and TOPSIS methods in order to find out the best method to use by taking parameters in the form of the same value results generated from the calculations of the two methods. The results obtained are the accuracy value of the SAW method of 40% and the TOPSIS method of 100% based on testing using 60 employee data and 8 criteria used.

Measurement of Reading Level Index in Salatiga City Warsito, Budi; Hakim, Arief Rachman; Fatmawati, Endang
Indonesian Journal of Librarianship Indonesian Journal of Librarianship Vol. 4 No. 2 (2023)
Publisher : Department Library of Governance Institut of Home Affairs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33701/ijolib.v4i2.3581

Abstract Background: Concerning the increase in reading interest in Salatiga City, a scientific study is needed, which can become the basis for a policy decision so that the index will increase. Purpose: To measure the level of interest in reading people in Salatiga in 2023 comprehensively and precisely. Method: Methods using quantitative. This research was conducted using sampling techniques and research instruments, which have been determined by the National Library of Indonesia and have become national standards. The location of the research was carried out in the city of Salatiga, and sampling was done by simple random technique. Respondents amounted to 399 people with criteria aged 10-69 years. Measurements were made using five key performance indicators, namely reading frequency per week, duration of reading per day, amount of reading material per quarter, frequency of internet access per week, and duration of internet access per day. Result: The study results show that the value of the reading enthusiasm of the people in Salatiga City in 2023 is in the High category (62.13). Conclusion: Measurement of reading level index in Salatiga City to improving community reading literacy. The index value for the level of fondness for reading from the results of the 2023 study has decreased from the 2022 measurement, which had an index of 64.08. Keywords: Reading Frequency; Reading Duration; Reading Preferences; Reading Activity; Literacy Culture

Korelasi CO2 Terhadap Suhu dan kelembapan Dengan Multivariate Linear Regression Adhiwibowo, Whisnumurti; Warsito, Budi; Wibowo, Adi
Jurnal Transformatika Vol. 21 No. 2 (2024): Januari 2024
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v21i2.5230

Sekarang ini keadaan udara di daerah perkotaan sudah sangat tercemar oleh polusi. Semakin banyak gas CO2 yang mulai menyebar ke udara dapat menyebabkan meningkatnya suhu udara.. Hal ini dikarenakan bahwa CO2 dapat meningkatkan suhu di permukaan bumi. CO2 mempunyai peran yang dapat menyebabkan pemanasan global karena gas CO2 mempunyai di udara bebas dan dapat menyerap panas Matahari sehinggs suhu Bumi meningkat dampak pencemaran udara seperti asap kendaraan, asap rokok, asap dari pembakaran pabrik, dan kontribusi terbesar dalam pemanasan global mempunyai pengaruh sebesar 50% dan mempunyai lama hidup 50 200 tahun di atmosfer. Peningkatan suhu udara dan konsentrasi CO2 merupakan masalah yang sering terjadi pada daerah perkotaan dimana salah satunya adalah meningkatnya jumlah kendaraan bermotor sehingga konsentrasi CO2 juga ikut meningkat. Dengan melihat korelasi CO2 Terhadap Suhu dan kelembapan Dengan mengunakan Multivariate Linear Regression, kita dapat melihat bagaiman korelasi antara suhu serta kelembapan. Regresi linier multivariat merupakan model regresi linier dengan lebih dari satu variabel respon Y berkorelasi dan satu atau lebih variabel prediktor X. Hasil penelitian menunjukkan bahwa Dalam penelitian tersebut dikatakan bahwa terdapat korelasi antara CO2 suhu serta cahaya.

ANALISIS SENTIMEN VAKSIN COVID-19 PADA TWITTER MENGGUNAKAN RECURRENT NEURAL NETWORK (RNN) DENGAN ALGORITMA LONG SHORT-TERM MEMORY (LSTM) Maharani, Chintya Ayu; Warsito, Budi; Santoso, Rukun
Jurnal Gaussian Vol 12, No 3 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.3.403-413

The Coronavirus, also known as the Covid-19 pandemic, has reached every country worldwide, including Indonesia. Covid-19 is still prevalent and has killed many people in Indonesia. This makes it impossible to stop Covid-19 from spreading. The government's attempt to stop the Covid-19 pandemic is acquiring the vaccine. The administration of the Covid-19 vaccine has generated much discussion on social media, particularly Twitter. Tweets displaying public opinion on Twitter can be used for sentiment analysis and categorizing public opinion on the Covid-19 vaccine. 20,000 tweets were collected by Twitter crawling between January 10 and January 15, 2022. 3.290 tweets were left after pre-processing and meaningless tweets were eliminated. The data were processed using the Recurrent Neural Network method with the Long Short-Term Memory algorithm to determine its accuracy and identify topics often discussed by the public on Twitter. The LSTM method is capable of storing old information/data. A model with 70% training data, a learning rate of 0.01, 100 LSTM units, 32 batch sizes, 100 epochs, a cross-entropy loss function, and Adam optimizers was used to build the classification in this study. The accuracy value obtained from the performance evaluation of the Long Short-Term Memory model research was 80.34%.

Comparative Analysis of Decision Tree and Logistic Regression Models in Employee Recruitment and Selection for Enterprise Success Khairina, Dyna Marisa; Wibowo, Adi; Warsito, Budi
Komputika : Jurnal Sistem Komputer Vol. 13 No. 2 (2024): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v13i2.11917

Enterprise success is determined by competent Human Resources (HR). The recruitment and selection process of employee candidates plays an important role in producing competent human resources as an effective initial selection increases the chances of finding the right candidate for a particular role. This research predicts the likelihood of a candidate being further selected in the interview phase based on behavioral and functional recruitment and selection which are important aspects of a candidate's potential fit and contribution to the enterprise. The research uses a comparison of decision tree analysis models and logistic regression to make predictions with several measurement metrics to see the accuracy and confusion matrix of each model used. Based on evaluation and validation, the decision tree analysis model is superior in prediction even though the results tend to be the same as the logistic regression model. The accuracy value of the classification using the decision tree model was 86.67% with correct prediction results of 78 data from 90 testing data and the accuracy value of the logistic regression model was 85.55% with correct prediction results of 77 data from 90 testing data. The results of the comparison of the two models show that the performance of the decision tree classifier model tends to be better.

Applied Data Science and Artificial Intelligence for Tourism and Hospitality Industry in Society 5.0: A Review Hartatik, Hartatik; Isnanto, R. Rizal; Warsito, Budi
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.300

The primary purpose of this research is to delve into the emerging trends of artificial intelligence and data science with a specific focus on the tourism and hospitality sectors. A comprehensive methodology used to conduct this research includes collecting article data, conducting analysis and then conducting a review study on data science and artificial intelligence trends. These articles were selected based on metadata sourced from web of science and Scopus metadata. In particular, the research scrutinized and assessed the evolving trends in data science and artificial intelligence within the hotel and tourism category. This analysis drew data from two prominent databases, Web of Science and Scopus, obtained a total of 4155 articles identified using the software and generated 124 terms in the articles with at least ten co-occurrence relationships. The findings of this study explain the huge potential, namely the trend of data application of science and artificial intelligence in the tourism sector which is categorized in five distinct areas: forecasting tourist demand, implementing customized service recommender systems for the tourism industry, classifying tourist behavior patterns in automation, analyzing and understanding tourist behavior, developing tourist destinations, and planning itineraries. Additionally, the research anticipates a heavy emphasis on future studies on predicting travel demand. Looking ahead, this research extends the foundations laid by previous review studies primarily focusing on knowledge and forecasting methodologies in the tourism sector. The conclusions drawn in this research are well-supported by the evolving landscape of knowledge in this field. Furthermore, contributions of this research it offers valuable insights into the future directions of apllied data science and artificial intelligent research are represents the pioneering effort to analyze of applying machine learning to advance artificial intelligence and big data within the hotel and travel industries. The authors propose several avenues for future research in this domain based on the data unearthed.Additionally, the research anticipates a heavy emphasis on future studies on predicting travel demand. Looking ahead, this research extends the foundations laid by previous review studies primarily focusing on knowledge and forecasting methodologies in the tourism sector. The conclusions drawn in this research are well-supported by the evolving landscape of knowledge in this field. Furthermore, it offers valuable insights into the future directions of sentiment analysis research. Notably, this paper represents the pioneering effort to comprehensively analyze the methodology of applying machine learning to advance AI and big data within the hotel and travel industries. The authors propose several avenues for future research in this domain based on the data unearthed.

Kinetika Degradasi Air Limbah Menggunakan Media Tutup Botol Plastik PET dengan Reaktor Aerobik MBBR Muliyadi, Muliyadi; Purwanto, Purwanto; Sumiyati, Sri; Budiyono, Budiyono; Sudarno, Sudarno; Warsito, Budi
Jurnal Kesehatan Lingkungan Indonesia Vol 24, No 1 (2025): Februari 2025
Publisher : Master Program of Environmental Health, Faculty of Public Health, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkli.24.1.59-67

Latar belakang: Tujuan penelitian adalah untuk menganalisis laju kinetika degradasi pengolahan air limbah biologi menggunakan model Michaelis-Menten dan regresi linier.Metode: Jenis penelitian ini adalah eksperimen. Sampel diambil dengan teknik grab sample dan diambil pada 4 titik dengan jumlah 70 liter yang dibagi sama rata pada tiap titik. Penentuan model dilakukan dengan menggunakan persamaan Michaelis-Menten dan regresi linier. Reaktor terbuat dari fiberglass, berukuran panjang 40 cm, lebar 40 cm, tinggi 50 cm, dan tebal 4 mm. Reaktor memiliki kapasitas 80 L. Inlet dan Outlet air limbah dirancang dengan menggunakan pipa PVC. Percobaan dijalankan selama 30 hari. Total luas permukaan semua media adalah 14.130 cm2. Analisis data menggunakan uji regresi linear dan persamaan michaelis-menten.Hasil: Hasil pemodelan persamaan Michaelis-Menten menunjukkan nilai R2 mendekati sempurna, yang menunjukkan kedekatan dengan kondisi lapangan sebenarnya. Kondisi aerobik berlangsung lebih lama dan memungkinkan terjadinya degradasi BOD, COD, dan TSS. Konstanta Menten untuk menghilangkan BOD, COD, dan TSS masing-masing adalah 17,7, 80,5, dan 135. Nilai R2 yang diperoleh dengan menggunakan model regresi linier mendekati angka sempurna, yaitu untuk parameter BOD (0,995), COD (0, 9934), dan TSS (0,9665). dengan nilai y masing-masing -0,0613, -0,0467, -0,042. Persamaan yang diperoleh dari hasil pemodelan regresi adalah Y = 31,245-0,030X1 + 0,015X2 + 0,044X3 + e.Simpulan: Model yang digunakan mampu memprediksi secara akurat degradasi BOD, COD, dan TSS dalam kondisi aerobik. Studi ini menyarankan pengoptimalan kondisi aerobik dalam praktik pengolahan air limbah untuk meningkatkan efisiensi penghilangan BOD, COD, dan TSS, menggunakan model Michaelis-Menten untuk pengurangan polutan yang efektif. Besarnya gelembung udara yang dihasilkan aerator tidak dikontrol sehingga tidak dapat dimaksimalkan laju aliran udara yang masuk pada reaktor yang mungkin akan berpengaruh pada hasil kerja reaktor. Penelitian ini meningkatkan pengetahuan pengolahan air limbah dengan menunjukkan efektivitas model Michaelis-Menten dalam menganalisis laju degradasi dan menekankan penggunaan media plastik, sehingga menawarkan wawasan berharga untuk penelitian masa depan. Title: Wastewater Degradation Kinetics Using PET Plastic Bottle Capping Media with MBBR Aerobic ReactorBackground: The purpose of this study was to analyze the rate of degradation kinetics of biological wastewater treatment using the Michaelis-Menten model and linear regression.Method: This type of research is experimental. Samples were taken using the grab sample technique and taken at 4 points with a total of 70 liters divided equally at each point. Model determination was carried out using the Michaelis-Menten equation and linear regression. The reactor was made of fiberglass, measuring 40 cm long, 40 cm wide, 50 cm high, and 4 mm thick. The reactor has a capacity of 80 L. The wastewater inlet and outlet were designed using PVC pipes. The experiment was run for 30 days. The total surface area of all media was 14,130 cm2. Data analysis used linear regression tests and the Michaelis-Menten equation.Results: The results of the Michaelis-Menten equation modeling showed an R2 value close to perfect, which indicated closeness to actual field conditions. Aerobic conditions lasted longer and allowed for degradation of BOD, COD, and TSS. Menten's constants for removing BOD, COD, and TSS were 17.7, 80.5, and 135, respectively. The R2 value obtained using the linear regression model approached the perfect number, namely for the parameters BOD (0.995), COD (0.9934), and TSS (0.9665). with y values of -0.0613, -0.0467, -0.042, respectively. The equation obtained from the results of the regression modeling is Y = 31.245-0.030X1 + 0.015X2 + 0.044X3 + e. Conclusion: The model used is able to accurately predict the degradation of BOD, COD, and TSS under aerobic conditions. This study suggests optimizing aerobic conditions in wastewater treatment practices to improve the efficiency of BOD, COD, and TSS removal, using the Michaelis-Menten model for effective pollutant reduction. The size of the air bubbles produced by the aerator is not controlled so that the rate of air flow entering the reactor cannot be maximized, which may affect the results which could minimize the reactor's working time. This study enhances the knowledge of wastewater treatment by demonstrating the effectiveness of the Michaelis-Menten model in analyzing degradation rates and emphasizing the use of plastic media, thus offering valuable insights for future research.

Domestic wastewater treatment system using waste plastic bottle caps as biofilter media Muliyadi, Muliyadi; Purwanto, Purwanto; Sumiyati, Sri; Budiyono, Budiyono; Utomo, Sudarno; Warsito, Budi
International Journal of Advances in Applied Sciences Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i1.pp235-246

The increasing lack of clean water has created a paradigm for treating wastewater directly from the source. This study aimed to determine the effectiveness of processing domestic waste using plastic bottle caps in the anaerobe and aerobe reactor system by measuring several key parameters in wastewater. Experimental study on on-site wastewater treatment system using two bioreactors, a biodegradation made from fruit and vegetable peel waste, and local microorganisms. Domestic wastewater was used in this study. The wastewater treatment system's performance was monitored using parameters like pH, temperature, total suspended solids (TSS), chemical oxygen demand (COD), and biochemical oxygen demand (BOD), collected daily at 9 am during peak wastewater generation. The wastewater treatment system using aerobe and anaerobic reactors with plastic bottle cap media and microorganism biodegradation effectively reduced the TSS, COD, and BOD. The anaerobe reactors were more effective at removing these pollutants, with a maximum TSS reduction of 81.1%, COD removal efficiency of 90.1%, and BOD removal efficiency of 80.2%. The longer acclimatization time of the anaerobe reactor may make it more efficient after acclimatization compared to the aerobe reactor. Although the anaerobe reactor may require a longer acclimatization time, it ultimately results in a higher efficiency in terms of TSS, COD, and BOD reduction compared to the aerobe reactor.

Co-Authors . Widayat Abdul Hoyyi Adi Waridi Basyirudin Arifin Adi Wibowo Adi Wibowo Agus Rusgiyono Agus Winarno, Agus Ahmad Lubis Ghozali Ahmed, Kamil Alan Prahutama Anindita Nur Safira Arafa Rahman Aziz Arbella Maharani Putri Arief Rachman Hakim Arief Rachman Hakim Arief Rachman Hakim Aris Sugiharto Arsyil Hendra Saputra Atmaja, Dinul Darma Atur Ekharisma Dewi Aurum Anisa Salsabela Bagus Dwi Saputra Bayastura, Shahnilna Fitrasha Bayu Surarso Bimastyaji Surya Ramadhan Budiyono Budiyono Calvin, Esagu John Catur Edi Widodo Chrisna Suhendi Cintika Oktavia Di Asih I Maruddani Di Mokhammad Hakim Ilmawan Dian Mariana L Manullang Dinar Mutiara Kusumo Nugraheni Dwi Ispriyanti Dyna Marisa Khairina eka rahmawati Ekky Rosita Singgih Wigati Endang Fatmawati Endang Fatmawati Fachry Abda El Rahman Faisal Fikri Utama Faliha Muthmainah Fath Ezzati Kavabilla Fatiya Nur Umma Ferry Hermawan Fiqria Devi Ariyani Firdonsyah, Arizona Gayuh Kresnawati Gertrude, Akello Ghifar Rahman Handayani, Sri Hanif Kusumasasmita Haritsa, Rifda Tsaqifarani Harjum Muharam Hasbi Yasin Hendri Setyawan Henny Widayanti, Henny Heriyanto Hizkia Christian Putra Setiadi Indra Jaya Infan Nur Kharismawan Intan Monica Hanmastiana Jafron Wasiq Hidayat Junta Zeniarja Kadarrisman, Vincensius Gunawan Slamet Kiswanto Kiswanto M. Afif Amirillah M. Andang Novianta Maharani, Chintya Ayu Mahrus Ali Maori, Nadia Annisa Maryono Maryono Maryono Maryono Masruroh, Fitriana Maulida Najwa, Maulida Mifta Ardianti Moch. Abdul Mukid Mochamad Arief Budihardjo Moh Ali Fikri mohamad jamil muhammad shodiq Muliyadi Muliyadi Munji Hanafi Mustafid Mustafid Mustaqim Mustaqim, Mustaqim Nisa Afida Izati Noor Azizah Nur Fitriyah Nurcahyanti, Tri Meida Nurul Hidayati Oktavia, Cintika Oky Dwi Nurhayati Pandu Anggara Paul, Gudoyi M Perdana, Ery Purwanto Purwanto Puspita Kartikasari Putri, Nitami Lestari R Rizal Isnanto R. Rizal Isnanto Rachmat Gernowo Rachmat Gernowo Rahmat Gernowo Rahmatul Akbar Ratna Kencana Putri Rini Nuraini Rita Rahmawati Rita Rahmawati Riva Amrulloh Riza Rizqi Robbi Arisandi Royani, Noorhanida Rukun Santoso Rully Rahadian Safitri, Adila Salma Farah Aliyah Sang Nur Cahya Widiutama Sari, Juwita Dwinda Silvia Elsa Suryana Siti Fadhilla Femadiyanti Sri Endah Moelya Artha Sri Sumiyati Sudarno Sudarno Sudarno Sudarno Sudarno utomo Sugito Sugito Sulardjaka Sulardjaka Suparti Suparti Syafrudin Syafrudin Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Ta’fif Lukman Afandi Tri Yani Elisabeth Nababan Ummayah, Putri Qodar Vincensius Gunawan Slamet Kadarrisman Wahyul Amien Syafei Whisnumurti Adhiwibowo Wibowo, Catur Edi Widiyatmoko, Carolus Borromeus Winahyu Handayani Yanuar Yoga Prasetyawan Yundari, Yundari

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