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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Media Statistika Jurnal Studi Manajemen Organisasi Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jiko (Jurnal Informatika dan komputer) JURNAL PENDIDIKAN TAMBUSAI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Pendidikan dan Konseling bit-Tech JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) International Journal of Advances in Data and Information Systems Al-Mutharahah: Jurnal Penelitian dan Kajian Sosial Keagamaan Studies in Learning and Teaching Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Jurnal Bisnis Indonesia Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Community Service International Journal of Data Science, Engineering, and Analytics (IJDASEA) Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Inkofar Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Eksponensial Baitul Hikmah: Jurnal Ilmiah Keislaman STATISTIKA Kohesi: Jurnal Sains dan Teknologi Information Technology International Journal (ITIJ) Seminar Nasional Teknologi dan Multidisiplin Ilmu Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal ilmiah teknologi informasi Asia RAGAM: Journal of Statistics and Its Application Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Trimono, Trimono
Data Science Department, Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Analisis Pengaruh Tingkat Kriminalitas dan Kepadatan Penduduk Terhadap Indikator Kualitas Hidup Masyarakat melalui Pendekatan Two-Way MANOVA Dewi, Ni Luh Ayu Nariswari; Zalfa Assyadida, Azizah; Salma Namira, Alivia; Nasrudin, Muhammad; Trimono, Trimono
EKSPONENSIAL Vol. 16 No. 2 (2025): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/6ssnd846

Abstract

Quality of a population life is shaped by various social and structural conditions, including socioeconomic disparities, crime levels, and population pressure. Understanding how these factors interact is essential for evaluating regional welfare. Therefore, this study aims to examine the influence of crime rates and population density on the quality of life in Indonesia using a Two-Way Multivariate Analysis of Variance (MANOVA) approach. The dependent variables analyzed include the Human Development Index (IPM), the percentage of the poor population, and the open unemployment rate. The independent variables consist of categories of crime rates and population density levels. Prior to conducting the MANOVA, assumption tests were performed to ensure data adequacy, including multivariate normality testing using Mardia’s test, independence testing via Bartlett's Test of Sphericity, and homogeneity of variance testing with Box’s M Test. The analysis results indicate that neither crime rates nor population density levels significantly influence the three quality of life indicators simultaneously, as evidenced by the Wilks’ Lambda and Pillai’s Trace test outcomes. These findings suggest that policies aimed at improving quality of life should not solely focus on crime rates and population density but require a multidimensional approach encompassing other factors such as education, healthcare, and economic conditions. 
Implementasi Spatial Durbin Model Berbasis Data Science Untuk Analisis Kemiskinan Jawa Timur Arif, Farah Yusnaida; Mohammad Idhom; Trimono, Trimono
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol. 5 No. 1 (2025): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/9w9pye50

Abstract

Poverty remains a major development challenge that requires data-driven analysis to understand its variation across regions. This study focuses on East Java, where spatial interdependence is suspected to influence poverty distribution, making spatial analysis relevant for supporting regional policy design. The study examines determinants of poverty using the Spatial Durbin Model, which captures both direct effects and indirect spatial spillovers through lagged independent variables. The analytical workflow is implemented using a Python-based data science pipeline to ensure a systematic, transparent, and reproducible process, in line with current trends in technology-supported research. The dataset consists of 2024 secondary data from the Indonesian Central Bureau of Statistics. The analysis includes data preprocessing, construction of a Queen Contiguity spatial weight matrix, Moran’s I test to detect spatial autocorrelation, and SDM estimation. Results indicate significant positive spatial autocorrelation (I = 0.4099; p = 0.0008), showing that poverty is not randomly distributed. While the spatial lag of the dependent variable is not significant, an indirect spatial effect appears through the Gini Ratio (θ₄ = –39.42168; p = 0.03855). Moreover, the Human Development Index significantly reduces poverty. These findings highlight the roles of regional inequality and human development in shaping poverty dynamics and provide insights for more targeted policy interventions.
SOSIALISASI ORANG TUA TENTANG BAHAYA GADGET BAGI ANAK-ANAK Trimono, Trimono; Ningtiyas, Rona Wulan; Icha Rohmatul Jannah; Aliya Dasa Pramesthi; Putra, Andrawana; Wardah Ariij Adibah; Ade Irma Agustian
BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Vol. 5 No. 2 (2025): BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Desember 2025
Publisher : LPPM UNIKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/bhakti_nagori.v5i2.4773

Abstract

Penggunaan gawai yang berlebihan pada anak-anak kini menjadi perhatian serius karena dapat memengaruhi perkembangan fisik, kognitif, dan sosial mereka. Kegiatan pengabdian kepada masyarakat ini dilaksanakan untuk meningkatkan kesadaran orang tua dan pengasuh mengenai risiko penggunaan gawai yang tidak terkontrol, sekaligus mendorong terciptanya kebiasaan digital yang lebih sehat dalam lingkungan keluarga. Program ini menggunakan pendekatan partisipatif melalui edukasi langsung, diskusi kelompok, serta pemanfaatan media interaktif seperti poster informatif dan video edukatif singkat agar materi lebih mudah dipahami oleh peserta. Kegiatan dilaksanakan di lingkungan masyarakat setempat dan melibatkan orang tua, guru, serta tokoh masyarakat yang memiliki peran penting dalam pengawasan anak. Selama pelaksanaan, peserta diberikan pemahaman mengenai dampak jangka panjang penggunaan gawai berlebihan, termasuk gangguan tidur, penurunan konsentrasi, dan rendahnya interaksi sosial anak. Hasil kegiatan menunjukkan peningkatan yang signifikan, di mana 85% peserta menyadari bahaya paparan gawai berlebihan, sementara 90% lainnya menyatakan kesediaan untuk meningkatkan kontrol terhadap penggunaan gawai di rumah. Melalui evaluasi pra-tes dan pasca-tes, terlihat peningkatan skor pengetahuan peserta sebesar 40%. Program ini diharapkan mampu menjadi upaya preventif dalam mengurangi risiko kecanduan digital pada anak usia dini
Prediksi Hasil Produksi Beras di Kabupaten Lamongan Menggunakan Stochastic Frontier Analysis (SFA) Imelda Widya Ningrum; Dwi Arman Prasetya; Trimono
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i1.15556

Abstract

The agricultural sector plays a crucial role in the Indonesian economy, especially in maintaining food estate and economic stability. This study aims to identify and improve the technical efficiency of rice production in Indonesia using Stochastic Frontier Analysis (SFA). Agricultural data were analyzed through validation, cleaning, feature selection, and modeling with a log-linear Cobb-Douglas production function estimated using Maximum Likelihood Estimation (MLE). Model performance was evaluated on training and test data using Log-likelihood, R-squared, and Mean Absolute Percentage Error (MAPE). The results showed good model prediction performance on test data (R-squared = 0.6658 and MAPE = 14.34%). Technical inefficiency analysis indicated that the level of inefficiency among farmers in Lamongan Regency was relatively low and homogeneous. However, the efficiency frontier analysis identified significant opportunities to increase rice yields through more efficient management of production factors and reduction of inefficiencies
Prediksi Harga Saham Menggunakan ARIMA Outlier sebagai Pendekatan Awal Menuju Analisis AI Keuangan Adam, Cindi; Idhom, Mohammad; Trimono, Trimono
Elkom: Jurnal Elektronika dan Komputer Vol. 18 No. 2 (2025): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v18i2.3314

Abstract

Perkembangan kecerdasan buatan (AI) mendorong inovasi dalam analisis keuangan, termasuk prediksi harga saham yang fluktuatif. Penelitian ini bertujuan memprediksi harga saham PT Garudafood Putra Putri Jaya Tbk menggunakan model ARIMA dengan penanganan Outlier sebagai pendekatan awal menuju sistem prediksi yang lebih adaptif. Data harga penutupan harian dari Yahoo Finance dianalisis melalui uji stasioneritas, identifikasi model ARIMA, deteksi Outlier berbasis log-return, serta evaluasi performa menggunakan RMSE, MAE, dan MAPE. Hasil penelitian menunjukkan bahwa ARIMA Outlier memberikan performa lebih baik dibandingkan ARIMA dasar. ARIMA standar menghasilkan MAPE 1.32% dan AIC –899.46, sedangkan ARIMA dengan tiga dummy Outlier mencapai MAPE 1.16% dan AIC –900.37. Peramalan 14 hari ke depan menunjukkan pola yang stabil pada kisaran Rp 370–371. Pada data uji, ARIMA dasar memberikan akurasi terbaik pada pertengahan Agustus, sedangkan ARIMA Outlier mencapai akurasi tertinggi pada akhir Agustus dengan prediksi Rp 370.2 yang sangat dekat dengan harga aktual Rp 370.4. Hasil ini menunjukkan bahwa penanganan Outlier meningkatkan ketepatan model, sehingga ARIMA Outlier dapat digunakan sebagai fondasi awal menuju pengembangan sistem prediksi keuangan berbasis AI.
Natural Mosquito Repellet Socialization for Dengue Prevention in Rural Areas: Sosialisasi Semprotan Anti Nyamuk Alami untuk Pencegahan Demama Berrdarah M Zufar Irhab S Putra; Sekar Arum Melati; Dinda Putri Arnindi; Desy Miftachul Ilmi Arifin Putri; Trimono
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 9 No. 3 (2025): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

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

Abstract

Dengue fever remains a significant public health concern, necessitating comprehensive prevention strategies, including vector control. This community engagement study explores the implementation of natural mosquito repellent spray production using lemongrass as a strategic approach to mitigate dengue transmission in Lontar Village. The research aims to analyze the impact of this natural repellent on community health, identifying challenges and opportunities associated with its adoption and sustainable production. Employing a mixed-methods approach, the study incorporates community surveys, interviews with local residents and health officials, and direct observation during the socialization and production phases. Findings indicate that the provision of natural mosquito repellent significantly enhances community participation in dengue prevention, offering an accessible and environmentally friendly alternative to chemical repellents. Key challenges include initial awareness dissemination regarding the benefits of natural repllents and ensuring consistent home-based production. However, the benefits demonstrate substantial potential for improving local health outcomes, fostering self-reliance in disease prevention, and promoting the use of local resources. The study suggests targeted support mechanisms, including continuous education, hands-on workshops, and simplified production guidelines to maximize the benefits of this natural repellent. These findings contribute to understanding the role of community-based interventions in local health development and provide practical insights for supporting disease prevention efforts in rural contexts. The research highlights the importance of strategic interventions that can empower communities to adopt sustainable health practices.
ARIMA-TGARCH Model for Return Prediction and Risk Estimation with VaR Imanta Ginting; Trimono Trimono; Kartika Maulida Hindrayani
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3090

Abstract

Investment activity in the Indonesian capital market has experienced significant growth, driven by increasing public awareness and accessibility to financial instruments. Stocks remain the most favored investment tool due to their potential for high returns, though they come with higher risks. Accurate modeling of return dynamics and risk estimation is thus crucial for informed investment decisions. This study analyzes the return and volatility of PT Telekomunikasi Indonesia Tbk (TLKM) stock using a hybrid time series approach that combines the Autoregressive Integrated Moving Average (ARIMA) model and the Threshold Generalized Autoregressive Conditional Heteroskedasticity (TGARCH) model. The analysis uses daily closing price data from 2020 to 2024, with 1,210 observations. The best-fitting model, ARIMA(2,0,2)–TGARCH(1,1), resulted in low Root Mean Squared Error (RMSE) values of 0.0188 for both training and testing datasets, indicating strong prediction accuracy. Forecasting over a five-day horizon revealed fluctuating returns and a decreasing trend in volatility, from 0.0230 to 0.0198. Additionally, the study utilized the Value at Risk (VaR) method to estimate potential losses under normal market conditions. At a 95% confidence level, the predicted daily loss for a capital investment of IDR 50,000,000 ranged between IDR 1,633,108 and IDR 1,859,355. The combination of ARIMA and TGARCH, integrated with VaR, provides a comprehensive framework for capturing both linear return trends and asymmetric volatility, offering investors a robust quantitative tool for managing risks and optimizing strategies.
KLASTERISASI TINGKAT KESEJAHTERAAN MASYARAKAT MENGGUNAKAN METODE SELF ORAGNIZING MAPS DENGAN PARTICLE SWARM OPTIMIZATION Afidria, Zulfa Febi; Trimono, Trimono; Prasetya, Dwi Arman
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7752

Abstract

Pulau Jawa juga merupakan salah satu pulau yang masih menjadi kontributor terbesar dalam pertumbuhan ekonomi Indonesia. Kontribusi Pulau Jawa diperkirakan akan menyentuh porsi hingga 58,75 persen pada tahun 2023. Namun, di balik pertumbuhan ekonominya yang pesat, Pulau Jawa masih menghadapi tantangan kesejahteraan seperti tingginya pengangguran, kemiskinan, serta rendahnya kualitas sumber daya manusia dan pendidikan. penelitian ini bertujuan untuk mengelompokkan tingkat kesejahteraan Masyarakat di Pulau Jawa menggunakan metode Self Organizing Maps dengan Particle Swarm Optimization. Metode ini dipilih karena SOM juga sangat efisien dalam mengelola data yang mengandung noise, outlier, serta nilai yang hilang karena ukuran sampelnya tidak memiliki batasan. Akan tetapi SOM juga memiliki kelemahan yaitu jumlah cluster perlu ditentukan secara spesifik dan untuk mendapatkan batas cluster peneliti harus melakukan inspeksi manual atau menggunakan algoritma cluster hierarki atau partisi. Penentuan batas cluster pada metode SOM dapat menggunakan metode Particle Swarm Optimization(PSO). Kebaruan dari penelitian ini adalah penerapan kombinasi metode SOM dan PSO dalam analisis kesejahteraan masyarakat di Pulau Jawa, yang masih jarang digunakan pada studi serupa. hasil penelitian ini menunjukkan model terbaik membentuk 3 cluster dengan nilai silhouette coefficient tertinggi sebesar 0.7293 Nilai tersebut menunjukkan bahwa struktur cluster yang terbentuk termasuk dalam kategori baik.
Rice Price Forecasting Using an Ensemble GRU–SVR Model with Enhanced Feature Engineering Faizi, Dandi Nur; Trimono, Trimono; Saputra, Wahyu Syaifullah Jauharis
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3532

Abstract

Rice price volatility significantly impacts economic stability and food security in Indonesia, particularly in East Java, where fluctuations in staple food prices affect household purchasing power and inflation management. This study addresses the limitations of existing rice price forecasting models, which often struggle to capture the complex, nonlinear dynamics of agricultural prices influenced by multiple factors such as climate variability and market conditions. Accurate and reliable price forecasting is essential to support effective policy formulation, market intervention, and food price stabilization strategies. This research develops an ensemble forecasting framework integrating Gated Recurrent Unit (GRU) and Support Vector Regression (SVR) with enhanced feature engineering to predict daily medium rice prices using historical price and weather data. The dataset comprises daily observations from 2021 to 2025, including rice prices, average temperature, relative humidity, rainfall, and sunshine duration. In this framework, GRU serves as a temporal feature extractor to learn complex temporal dependencies, while enhanced feature engineering generates complementary statistical features from sliding windows to enrich GRU's output. The combined feature set is provided to an SVR model with a Radial Basis Function kernel for final regression. Experimental results show that the proposed model achieves a high forecasting accuracy with an MAPE of 0.109%, demonstrating stable predictive behavior and making it a valuable tool for monitoring rice prices. The model's effectiveness in capturing temporal dependencies and nonlinear patterns suggests potential applicability beyond East Java, offering broader insights for agricultural price forecasting in other regions.
Implementation of Multiplex Leiden Algorithm for Clustering Ancol Visitors Wardani, Ajeng Puspa; Trimono, Trimono; Nasrudin, Muhammad
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3608

Abstract

Ancol is the largest recreational destinations, attracting visitors from diverse backgrounds. However, in 2024 the company experienced an 11.96% decline in visitor numbers. This condition highlights the urgent need for more accurate customer segmentation to support targeted and effective marketing strategies. Accordingly, this study investigates whether a Multiplex Leiden can produce coherent visitor segments, while also examining the relative contribution of each layer to community formation. Unlike prior multilayer segmentation studies, this study leverages the Multiplex Leiden algorithm, which guarantees well-connected communities and has been shown to achieve higher modularity. This is among the first applications of Multiplex Leiden for visitor segmentation, offering improved community coherence and interpretability in a multi-layer behavioral network. To balance network structures and reduce cross-layer density bias, kNN backbone preprocessing was applied before community detection. The results reveal 18 distinct visitor communities with substantial variation in size. Layer-wise quality analysis shows that the socioeconomic status layer contributes the strongest influence on the detected communities, followed by spending behavior and experiential preferences. The clustering quality was evaluated using multiple metrics. An Adjusted Rand Index (ARI) of 0.617 indicates a stable, non-random visitor segmentation, while a positive total quality score of 1.086 reflects strong cross-layer community structure. A mean conductance value of 0.548 suggests moderately well-separated yet realistically overlapping communities. Overall, the findings empirically confirm the effectiveness and interpretability of the Multiplex Leiden algorithm with backbone preprocessing for visitor segmentation in multi-layer networks. Future research may extend this framework by incorporating additional behavioral or temporal data.
Co-Authors Abda Abda Abdullah Abdullah Adam, Cindi Ade Irma Agustian Adelia Adelia, Adelia Adiwidyatma, Afdhal Reshanda Afidria, Zulfa Febi Aliya Dasa Pramesthi Amanillah, Rahmatul Amri Muhaimin Andreas Nugroho Sihananto Ardiani, Ardia Eva Arif, Farah Yusnaida Arifta, Septia Dini Asfiani, Ilil Musyarof Aurelia, Cenditya Ayu Aviolla Terza Damaliana Aviolla Terza Damaliana Aviolla Terza Damaliana Awang, Wan Suryani Wan Azni Aisyah Azzahra, Adelia Ramadhina Bainar Bainar, Bainar Bey Lirna, Cagiva Chaedar Carissa, Savvy Prissy Amellia Damaliana, Aviolla Terza Desy Miftachul Ilmi Arifin Putri Dewi, Ni Luh Ayu Nariswari Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diash, Hakam Dzakwan Dinda Putri Arnindi Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Edi Sugiyanto Fahrudin, Tresna Maulana Fairuz Luthfia Winoto Putri, Maretta Faizi, Dandi Nur Farkhan Febri Giantara Febriyanti, Alvi Yuana Febyanti, Iin Hadi, Surjo Hadiyan Pradipta, Alvino Hasan Hendri Prabowo Herlina Herlina Hervrizal, Hervrizal I Gede Susrama Mas Diyasa I Gede Susrama Mas Diyasa I Gusti Putu Asto Buditjahjanto Icha Rohmatul Jannah idhom, Mohammad Ikaningtyas, Maharani Ikaningtyas, Maharani Imanta Ginting Imelda Widya Ningrum Insania, Nichlata Irawan, Tanaya Anindita Irma Amanda Putri Kartika Maulida Hindrayani Kartika Maulida Hindrayani Kartini Kartini Kassim, Anuar bin Mohamed Khairunisa, Adenda Khosyi, Hanun Aufa Nur Kusdani, Kusdani Kuswardana, Dendy Arizki Linggasari, Dienna Eries Lisanthoni, Angela M Zufar Irhab S Putra Maharani Ikaningtyas Maruddani, Di Asih Mas'ad Mas'ad Maulana Pasha, Naufal Ricko Maulidiyyah, Nova Auliyatul Mohammad Idhom Mohammad Idhom Muhaimin, Amri Muhammad Muharrom Al Haromainy Munoto Nabila, Nasywa Azzah Nabilah Selayanti Nafiah, Fajria Ulumin Nariyana, Calvien Danny Nasution, Baktiar Nathania, Vannesa Ningrum, Imelda Widya Ningtiyas, Rona Wulan Nova Auliyatul Maulidiyyah Novita Anggraini Nugraheni, Setiawati Oktaviani, Sheny Eka Panglima, Talitha Fujisai Prisma Hardi Aji Riyantoko Prismahardi Aji Riyantoko Putra, Andrawana Putri, Irma Amanda Putri, Milla Akbarany Baktiar Putri, Nabila Rizky Amalia Putri, Shafira Amanda Rafiqah, Lailan Rafli Feandika Nugroho, Muhammad Ratna Yulistiani Renaldi, Sahat Rhomaningtias, Lina Riswanda, Mohammad Nizar Riyantoko, Prismahardi Aji Rizkiyah, Selly Rizqin, Indira Zein Ryan Dana, Alvin Sabela, Sefilah Naurah Safira Devi, Arsita Safira, Alya Mirza Salma Namira, Alivia Saputra, Wahyu Syaifullah Jauharis Sekar Arum Melati Sihananto, Andreas Sonhaji, Abdulah Sugiarti, Nova Putri Dwi Suprapto, Rheinka Elyana Susrama Mas Diyasa , I Gede Syamsul Rizal Tarno Tarno Taufik, Ikbar Athallah Terza Damaliana, Aviolla Tresna Maulana Fahrudin Utami, Rianti Siswi Utriweni Mukhaiyar Valentina, Tiara Wardah Ariij Adibah Wardah, Salsabila Wardani, Ajeng Puspa Wibowo, Muhammad Bagas Satrio Widayawati, Eny Widayawati, Eny Widison, Daffin Tanjiro Yuciana Wilandari Zalfa Assyadida, Azizah