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Lindawati Lindawati
Program Studi Kepemerintahan, Fakultas Ilmu Sosial dan Ilmu Politik Universitas Medan Area
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Analisis Keberlanjutan Usahatani Andaliman di Kabupaten Toba Sitorus, Abdoni; Rauf, Abdul; Lindawati, Lindawati
Mimbar Agribisnis : Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Vol 11, No 2 (2025): Juli 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ma.v11i2.19754

Abstract

Andaliman as a typical biodiversity of North Sumatra that grows wild in the Toba and Tapanuli lake areas and is widely found in Toba Regency. Toba Regency is the largest producer of andaliman in North Sumatra with a planting area of 274 Ha and a production of 110.17 tons per year. Andaliman plants experience price fluctuations throughout the year ranging from Rp. 10,000 to Rp. 400,000. Andaliman plants are also quite difficult to cultivate so that Andaliman farming needs to be analyzed for Andaliman farming desires by lifting five dimensions of desire. The method used to analyze Andaliman is multidimensional scaling or MDS in a tool called Rapfish with the output of sensitive attribute data and the value of the desire index of each dimension. The results of the study showed that the value of the desire index for Andaliman farming and cultivation in the fairly sustainable category with a desire ordination value of 54.44 and 51.54. Sensitive attributes that affect the sustainability of andaliman farming are Planting materials for regeneration, Crop rotation, Sales system, Income/harvest, Selling price of andaliman, Tradition of using andaliman, Family participation in farming, Cooperation between andaliman farmers and UMKM managers, Role of agricultural extension workers, Access to agricultural roads, Post-harvest technology. Role of agricultural extension workers, Marketing information of andaliman and Management information of andaliman.
Peningkatan Kemampuan Guru-Guru SD Negeri 130 Palembang Dalam Menyajikan Presentasi Atraktif Melalui Pelatihan Microsoft Power Point Salamah, Irma; Lindawati, Lindawati; Asriyadi, Asriyadi; Kusumanto, RD
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2020): Februari
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v4i1.2197

Abstract

ABSTRAKPengembangan profesi guru adalah untuk menjaga dan meningkatkan kualitas guru agar semakin professional dalam melaksanakan tugasnya menggunakan media aplikasi Microsoft office power point. Ada beberapa faktor mengapa kegiatan ini diselenggarakan. Ada guru yang tidak terbiasa menggunakan teknologi sebagai media dalam pengajaran di kelas. Sekolah tidak menyediakan fasilitas yang memadai yang memungkinkan guru menciptakan media ajar mereka. Tidak adanya pembimbing dan pendampingan yang memberikan pendidikan singkat tentang bagaimana membuat media animasi untuk pengajaran di sekolah dasar. Dengan adanya pelatihan ini guru-guru SDN 130 Palembang diharapkan mampu menguasai dan memahami fitur dan fungsi yang ada pada Microsoft power point serta mampu membuat animasi untuk pembelajaran dengan menggunakan Microsoft power point.Kata kunci: animasi pembelajaran; pelatihan microsoft power point; presentasi atraktif. ABSTRACT Teacher professional development is to maintain and improve the quality of teachers to be more professional in carrying out their duties using Microsoft Office Power Point application media. There are several factors why this activity is held. There are teachers who are not used to using technology as a medium in classroom teaching. Schools do not provide adequate facilities that allow teachers to create their teaching media. The absence of mentors and mentors who provide short education about how to make animation media for teaching in elementary schools. With this training the SDN 130 Palembang teachers are expected to be able to master and understand the features and functions that exist in Microsoft power point and be able to create animations for learning using Microsoft power point.Keywords: attractif presentation; microsoft power point training; learning animation.
Analisis Faktor-Faktor yang Mempengaruhi Produktivitas Tenaga Kerja Pemanen Kelapa Sawit (Elaeis Gunieensis Jacq.) PT. Pekebunan Nusantara IV Regional II Ginting, Jonathan; Lindawati, Lindawati
Jurnal Ekonomi Pertanian dan Agribisnis Vol. 9 No. 3 (2025)
Publisher : Department of Agricultural Social Economics, Faculty of Agriculture, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jepa.2025.009.03.3

Abstract

Indonesia Merupakan Produsen Kelapa sawit terbesar di dunia dan memberikan kontribusi signfikan terhadap penerimaan devisa negara. PT. Perkebunan Nusantara IV Regional II merupakan salah satu perusahaan besar negara yang bergerak di bidang perkebunan dan pengolahan kelapa sawit dan teh. Produksi tandan buah segar kelapa sawit PT. Perkebunan Nusantara IV Regional II mengalami peningkatan dari tahun 2018 hingga 2021, tetapi mengalami penurunan pada tahun 2022. Adapun salah satu faktor yang mempengaruhi penurunan produksi tanda buah segar kelapa sawit adalah tenaga kerja. Pemanen kelapa sawit merupakan aset perusahaan dan berperan penting dalam mencapai tujuan perusahaan. Produktivitas pemanen kelapa sawit yang tinggi akan meningkatkan produksi perusahaan dan mencapai target. Perusahaan berupaya mendorong produktivitas tenaga kerj pemanen untuk mencapai target perusahaan. Faktor-faktor yang mempengaruhi produktivitas tenaga kerja antara lain usia, pengalaman kerja, tingkat pendidikan, premi, gaji, dan jumlah tanggungan keluarga. . Tujuan Penelitian ini untuk: 1) menganalisis produktivitas tenaga kerja pemanen kelapa sawit di PT. Perkebunan Nusantara IV Regional II Kebun Laras; 2) menganalisis faktor-faktor apa yang berpengaruh secara terhadap produktivitas tenaga kerja pemanen kelapa sawit di PT. Perkebunan Nusantara IV Regional II Kebun Laras. Metode yang digunakan dalam penelitian ini ini adalah analisis Regresi Linier Berganda. Hasil Penelitian diperoleh bahwa rata-rata produktivitas tenaga kerja pemanen PT.Perkebunan Nusantara IV Regional II Unit Kebun Laras adalah 1.643 Kg/Hari. Hal ini sudah tergolong tinggi, sebab produkivitas tenaga kerja pemanen sudah melebihi dari target yang sudah ditentukan oleh perusahaan; Variabel umur, Pendidikan, gaji, dan premi, berpengaruh secara positif dan signfikan terhadap produktivitas tenaga kerja pemanen sedangkan tanggungan keluarga, pengalaman dan masa kerja berpengaruh secara negatif dan signfikan terhadap produktivitas tenaga kerja pemanen
Development of a CNN-Based Mental Health Consultation Application Integrating Facial Expressions and DASS-42 Questionnaire Salsabila, Meidita; Lindawati, Lindawati; Fadhli, Mohammad
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37525

Abstract

Early detection of psychological disorders such as Depression, stress, and anxiety is still limited due to a lack of awareness and inadequate access to mental health consultation services. This study aims to develop a mental health consultation application that utilizes facial expressions and the Depression, Anxiety, and Stress Scale (DASS-42) questionnaire, employing a Convolutional Neural Network (CNN) algorithm. The CNN algorithm is used to detect and classify facial expressions into emotional categories, such as anger, sadness, disgust, and fear,  as early indicators of mental conditions. In addition, the DASS-42 questionnaire provides a structured psychological assessment to determine the severity of Depression, anxiety, and stress. This combination offers a more comprehensive and accurate evaluation, thus bridging the gap in early detection methods for mental health. Based on the development and testing results, a mental health consultation app utilizing facial expressions and the DASS-42 questionnaire was successfully created by using the CNN algorithm as a facial expression detector. The system can identify facial expressions such as sadness, anger, disgust, and fear with an accuracy of 81%, showing excellent performance in detecting early signs of mental disorders.
Evaluating Entropy-Based Feature Selection for Sales Demand Forecasting Using K-Means Clustering and Naive Bayes Classification Wulandari, Fadhilah Dwi; Lindawati, Lindawati; Fadhli, Mohammad
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 2 (2025): July 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i2.37046

Abstract

Sales demand forecasting is crucial for inventory optimization in retail, especially for Micro, Small, And Medium Enterprises (MSMEs). This study examines the effect of entropy-based feature selection on the performance of a two-stage machine learning framework comprising K-Means clustering and Naive Bayes classification. The research was conducted on transactional data collected from a footwear MSME in Palembang, Indonesia, covering January to December 2024. Shannon Entropy and Information Gain were applied to identify and retain the most informative features before clustering and classification tasks. Two experimental scenarios were investigated: (1) using all features without selection and (2) applying entropy-based feature selection with Information Gain thresholds of 0.4 and 0.5 for category-based and quantity-based targets, respectively. The first scenario yielded moderate performance, with a Silhouette Score of 0.5747 and a classification accuracy of 96.97%. In contrast, the second scenario demonstrated superior results, achieving a Silhouette Score of 0.6261 and a classification accuracy of 99.49% when quantity sold was used as the target variable. These findings indicate that entropy-based feature selection reduces data dimensionality, enhances clustering compactness, and improves classification accuracy. This research contributes to the field by presenting a practical framework for sales demand forecasting in retail environments. Future work will focus on integrating additional contextual variables, such as seasonal trends and promotions, and validating the system in real-world retail settings
Optimasi Kendali PID berbasis IoT pada Oven Listrik untuk Pengeringan Rempah yang Presisi Pratama, Bambang; Salamah, Irma; Lindawati, Lindawati
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.30537

Abstract

Unstable spice drying can reduce active compound content by up to 30% and increase the risk of microbial contamination by up to 40%, while conventional temperature control does not ensure thermal stability. This study aims to develop an IoT-based drying system using a PID algorithm to maintain temperature stability and allow remote monitoring and control. The research followed the waterfall model, starting from needs analysis, hardware and software design, PID implementation using a trial-and-error approach, IoT application development with Kodular and Firebase, system integration, and full system performance testing. Key components include the DS18B20 temperature sensor, ESP32, heating element, and IoT platform. Software testing used the black box method, while hardware testing evaluated performance through overshoot, steady-state error, settling time, disturbance simulation, and comparison with the on-off control method. The resulting system automatically regulates temperature with a PID algorithm and enables real-time monitoring via mobile devices. Testing showed the PID system was more stable than the on-off method, with overshoot <4°C, steady-state error <1.5°C, settling time of ±750 seconds, and quick response to disturbances. The mobile application operated reliably without errors, enhancing the quality and precision of the spice drying process.
Pemasangan Panel Surya Sebagai Energi Alternatif di Pesantren Darul Hikmah, Kabupaten Aceh Besar Rahmawati, Cut; Muhtadin, Muhtadin; Mahyuddin, Mahyuddin; Lindawati, Lindawati; Effendy, Amalia; Noviandy, Teuku Rizky; Sufri, Rahmat; Anisah, Anisah; Faisal, Muhammad; Mutaqin, Raihan; Fatani, Muhammad; Alfharijy, Muhammad Daffa
ABDIMASKU : Jurnal Pengabdian Masyarakat UTND Vol 4 No 1 (2025): Edisi Januari 2025 - Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Tjut Nyak Dhien

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36490/jpmtnd.v4i1.1601

Abstract

This activity aims to provide students with an understanding of the importance of renewable energy usage and to raise awareness about sustainability. It took place at the Darul Hikmah Islamic Boarding School located in Geundring Village, Darul Imarah District, Aceh Besar Regency. The methodology employed included socialization, discussions, and practical training on solar panel installation. Participants comprised a team from the Faculty of Engineering at Abulyatama University and students from Darul Hikmah Islamic Boarding School.The outcomes of this initiative include the successful dissemination of information regarding the benefits of solar panels as an alternative energy source, as well as the installation of one solar-powered lamp that can provide lighting at night and enhance the quality of the boarding school’s facilities. The students gained a better understanding of renewable energy through socialization and discussions. They learned about the benefits and operation of solar panels and the significance of environmental sustainability. This activity contributed to raising the students' awareness of the need to transition to more environmentally friendly energy sources, thereby potentially stimulating further renewable energy initiatives.
The Influence of Corporate Social Responsibility, Fiscal Loss Compensation, and Executive Risk Preference on Tax Avoidance Lindawati, Lindawati; Putri, Wulandari Cahyani; Muarif, Syamsul
Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID) Vol. 4 No. 7 (2025): Jurnal Ilmiah Multidisplin Indonesia (JIM-ID), August 2025
Publisher : Sean Institute

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

Abstract

Tax avoidance remains a critical issue for governments and businesses, as it directly impacts state revenue, corporate reputation, and public trust. In Indonesia’s food and beverage industry, the complexity of regulations and diverse corporate strategies create opportunities for tax avoidance that warrant closer examination. This study analyzes the influence of corporate social responsibility, fiscal loss compensation, and executive risk preference on tax avoidance among food and beverage companies listed on the Indonesia Stock Exchange during 2018–2022. Using a quantitative approach, the research employs secondary data from annual financial reports and applies panel data regression analysis. The results show that, simultaneously, all three variables significantly affect tax avoidance. However, partially, corporate social responsibility and fiscal loss compensation have no significant effect, while executive risk preference has a significant negative impact, indicating that risk-averse executives are less inclined to adopt aggressive tax strategies. These findings provide empirical evidence on behavioral and institutional factors shaping corporate tax behavior and highlight the role of executive characteristics in tax policy. The study is limited by its sector-specific sample and selected variables, suggesting opportunities for broader research in the future.
A Comparative Study of Machine Learning Classifiers with SMOTE for Predicting Purchase Intention Khairunnisa, Khairunnisa; Soim, Sopian; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7615

Abstract

The rapid growth of e-commerce has made it increasingly important for online platforms to understand user behavior, particularly in predicting purchasing intention. This study examines the implementation of three machine learning models: Logistic Regression, Random Forest, and Gradient Boosting, to classify purchase intention using real transaction session data. One of the primary obstacles confronted in this investigation is the matter of class imbalance found in the dataset, where 10422 records indicate no purchase while only 1908 indicate a completed purchase. This disparity may result in a biased model performance that prioritizes the dominant class and limits the ability to accurately detect minority class behavior, which in this case is the actual purchase. To resolve this matter, During the data preprocessing phase, the Synthetic Minority Over-sampling Technique (SMOTE) was implemented. Accuracy, precision, recall, and F1-score metrics were implemented to assess each model's functionality. The results indicate that following the implementation of SMOTE, the Random Forest model attained the best accuracy of 93%, succeeded by Gradient Boosting at 90% and Logistic Regression with 84%. These findings demonstrate that the use of SMOTE significantly improves model sensitivity and balance. This study provides useful insights into designing fairer and more effective predictive systems in the field of e-commerce.
Pengembangan Algoritma Convolutional Neural Network dalam Menganalisis Emosi Suara Menggunakan Mel-Spektogram Zakka, Iqlima Sabila; Rakhman, Abdul; Lindawati, Lindawati
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.7875

Abstract

Speech Emotion Recognition (SER) still faces challenges in accuracy, especially in distinguishing acoustically similar emotions. Conventional approaches such as MFCC (Mel Frequency Cepstral Coefficients) are often ineffective in capturing the emotional nuances of voice. To address this, this study aims to develop a Convolution Neural Network (CNN) model based on the Spec-ResNet architecture that uses Mel-Spectrogram as input to improve the system's ability to extract and recognize emotional signatures from speech signals. Another objective is to evaluate the performance of primary emotion classification in the RAVDESS dataset and measure model consistency through 5-fold cross-validation. The model used, Spec-ResNet, is an adaptation of the ResNet architecture equipped with residual learning to maximize the multi-stage feature extraction process. Experiments were conducted with the RAVDESS dataset containing 1,440 voice samples from six primary emotions: neutral, happy, sad, angry, afraid, and surprised. The test results showed a significant increase in accuracy, with a macro score reaching 92%, up from the MLP/SVM baseline of 83%. Neutral and happy emotions were classified very well (F1-scores of 93% and 90%), but emotions such as fear and surprise remained difficult to distinguish due to the similarity of their vocal patterns. Validation through 5-fold cross-validation yielded an average accuracy of 91.5% ± 0.8%. This study demonstrates the great potential of Mel-spectrograms in SER, while also underscoring the need for advanced approaches such as attention mechanisms to handle ambiguous emotions.
Co-Authors -, Angelina . Zulfan A Halim Abdul Rakhman Abdul Rauf Abelia, Dinda Dwi Ade Silvia Handayani Adeliana, Adeliana Adelita Lubis, Adelita Adriani, Silfia Afdhal Afdhal Affrylia, Gita Afkar, Mufidul Afridayani, Afridayani Afridon, Afridon Agatha, Adelia Agustiar agustiar Ahmad Syai Ahmad Taqwa Ahmadin Ahmadin Akmalia, Alfi Alaisyi, Alaisyi Aldo, Ketut Alfharijy, Muhammad Daffa Alfiansyah, Ikhwan Alfiatun, Alfiatun Alfirdaus, Muhammad Farrel ali khaeri, imam Alliya, Annisa Ul Alvionita, Gusni Am, Zakiati Amalia Amalia Amelianda, Amelianda Amiza, Ibel Dwi Amri Amin Andi Andi Andila, Tria Anggraini, Anggun Anisah Ardelia, Naila Arifani, Rizka Arifin Soenggono, Arifin Arlinda, Sari ARMEN ZULHAM Arsella, Shendy Aryanti Aryanti Asep Irfan Asmaul Husna Asriyadi Asriyadi Asrul Asrul Astari, Devina Atminingsih Atminingsih, Atminingsih Audina, Reka Aulia, Muhammad Rafi Awalia Gusti Awaluddin Awaluddin Az-zahra, Maudhy Azizah, Nur Putri Azwandi Azwandi Azzahra, Siti Azzahrah, Ladysa Bakhir , Norfarizah Mohd Bambang Pratama, Bambang Baso Intang Sappaile, Baso Intang Bunyamin Bunyamin Chairunnisaak, Mariam Cucu Atikah Cut Rahmawati Cut Zuriana Damiati, Tri Darus, Mozard Bahauddin Darwel, Darwel Deddy Junaedi Dewi Maya Sari Dharmalau, Andy Diana Chalil Didit Haryadi Dina Mayadiana Suwarma Effendy, Amalia Eka Pradani, Rizki Febri Eka Putri, Yuliantini Eka Susanti Eka Susanti, Eka Susanti Eko Sugiarto Elmerillia, Elmerillia Elvina, Aminah Enda Kartika Sari, Enda Kartika Enda, Enda Kartika Sari Endang Larasati Eri Yusni Ermawati Ermawati Ermawati, Yuli Fadhli, Mohammad Fadmawati, Any Fadmawaty, Any Faisal Ahmadi Fatani, Muhammad Fatimatuzzahra Fatimatuzzahra Febriani, Dina Fitra, Miladil Fitri Wardani, Erika Fitri, Aida Fitriadi, Nuzuli FITRIYANTI, RAMADHINA Frenica, Agnes Gameli, Cahyani Rahmi Garnita, Ria Ghodina, Aurina Willy Ghufran S., Mufti Miadi Ginanjar, Seandy Grenaldo Ginting Gusdi Sastra, Gusdi Hadir Hudiyanto, Hadir Hafsaridewi, Rani Hanah, Siti Handayani, Sri Hardi Siswo, Hardi Hasmawaty, Hasmawaty Hedra Bayu, Hendi Hesniati, Hesniati Hidayah, Hidayah Hidayat, Sholeh Hikmah Hikmah Holiawati, Holiawati HS, Alicia Husin, M. Husna, Ainul Ida Zulfida, Ida Iif Rahmat Fauzi, Iif Rahmat Ikhsan Yuda Pratama Indah Sari, Dewi Indawati, Indawati Iqbal Iqbal Iqmy, Ledy Oktaviani Irfan, Basuki Ario Seno Irma Salamah Irma Suryani Ironia Vivie Susanti, Ironia Vivie Ismawan Ismawan, Ismawan Iswanda, Odi Ivan Suaidi Iwan Setiawan Jaifan, Muhammad Jamjuri, Endi Jamratul Ula Jannah, Syifaul Joey, Joey Jonathan Ginting juliana, Nanin Khairunnisa Khairunnisa Khairunnisya, Aqilla Khie, Sak Komariah, Eneng Kurnita, Taat Lanza Pahlevi, Muhammad Lase, Yolanda Leni Marlina Lestari, Khotifah Puji Leuwol, Ferdinand Salomo Lili Dianah Lina Lina Linda Junia Ningsih Listiorini, Dewi Lucyana Lucyana, Lucyana Lukman Hakim M. Ridha Madiyoh, Abdulhakim Maharani, Ullya Dwi Mahaza Mahyuddin Mahyuddin Maisun, Maisun Maizal, Ilham Mamusung, Robby Tanod Mardiana, Dinny Mardikawati, Budi Margie, Lyandra Aisyah Marietta Shanti Marita, Tia Martianingsih, Baiq Lilik Martinus Mujur Rose Marur, Muhammad Marza, R. Firwandri Maulida, Putri Maulidin, Aula Maulin, Siti Maulisa, Ella Mayanda, Afrida Rizki Mediana, Salwa Deta Meliyana Meliyana, Meliyana Mirdayanti, Rina Monika, Sinar Monika, Sinar Mu'arif, Syamsul Muchlis, Yusrizal Muhammad Alwi Muhammad Faisal Muhammad Iqbal Muhtadin Muhtadin Mukhlis Mukhlis Mulyani, Riri Muniroh, Leny Muslim, Burhan Muslimah, Rina Mutaqin, Raihan Muthaharah, Muthaharah Mutmainnah Mutmainnah Na:am, Muh Fakhrihun Nahdudin, Nahdudin Nasution, Siti Khadijah Hidayati Novarijah, Syarifah Novianda, Nabila Rizqi Novianda, Nabila Rizqia Noviani, Fadiah Nur, Erdi Nurfi, Nurfi Nurhajar Anugraha Nurhanifa, Nurhanifa Nurjihan, Nisrina Nurlaili Nurlaili Nurwijayanti Onasis, Aidil Palawi, Ari Palin T, Yona Paryanto, Alfin Dwi Ponimin Purnamarini, Tri Ratna Putri Vandalis, Yoke Annisa Putri, Wulandari Cahyani Rabbani, Ali Rabiah, Nur Nabila Radifan, Hadyan Hilman RADITE TISTAMA Rahmanta Rahmanta, Rahmanta Rahmanta`, Rahmanta Rahmawati, Cut Raihan, Ahmad Raihanah, Adinda Rajes Ikhlas Rosaguna, Rajes Ikhlas Ramadhan, Andi Ramadhan, Muhammad Fadli Ramdiana , Ramdiana Ramdiana, Ramdiana Ratna Novita Punggeti RD Kusumanto Reo, Petrus Renol Rida Safuan Selian Rina Herawati, Augustin Riswanto, Muhammad Riviwanto, Muchsin Riviwanto, Muchsin` Rizka Fadli Wibowo, M. Roiyan, Lalu Muhammad Rosini, Iin Rudiyanto Rudiyanto, Rudiyanto Rukiyanto Rukiyanto, Rukiyanto Safitry, Yuwaffy Safriyani, Lia Saharani, Saharani Salsabila, Meidita Salsabila, Raina Saptanto, Subhechanis Saptanto, Subhechanis Sarhindi, Sarhindi Sari Wardani Sari, Rani Purnama Sari, Tengku Dede Rachma Sarjana Sarjana Sarjono Sarjono, Sarjono Sasrita, Bysmira Septiana, Ardilla Septiani, Rizka Ayu Septina, Phuja Tawilla Sholihin Sholihin Silfia Silfia, Silfia Silviana, Mery Sipasulta, Grace Carol Siregar, Nur Mawaddah Siti Hawa Sitorus, Abdoni Sopian Soim, Sopian Sopian, Adi Sri Wahyuni Suandari, Fitri Sufri, Rahmat Suksmerri Suksmerri Sume, Syahlan A. Sumilat, Rohyani Rigen Is Supadmi, Tri Suryani Suryani SURYANI, TRIA ANANDA Suyuti, Suyuti suzan zefi Syahardi, Amri Syahbana, Mahdi Syahril Syahril syakir syakir Syamsul Muarif Tengku Hartati Tengku Riza Zarzani N Tetep Tety Sriana Teuku Rizky Noviandy Tiurma, Tiurma Triani, Susi Trianov, Rilky Triasensi, Sherlya Tumilantouw, Kireina Gabriela Ul Karimah, Lulu Ummir, Badril UTAMI, FUTRI Utami, Futri Valerie, Michelle Viviani, Viviani Wahyudin, Mokhammad wahyudin, mukhammad Wardani, Happy Kusuma Wardani, Sari Wasludin, Wasludin Wibowo, Rulianda P. Widianty, Anggie Wijayantono, Wijayantono Wilyuza, Wilyuza Witomo, Cornelia Mirwantini Wulandari, Fadhilah Dwi Wulandari, Widyana Wusqa, Asy Syifa Urwatul Yanti Yanti Yulianto Yulianto Yuliasari, Dewi Yusnita, Emilia Yusrizal Yusrizal Zakka, Iqlima Sabila Zamakhari, Ahmad Zardi, Muhammad Zulprianto Zulprianto