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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal CoreIT Dinamisia: Jurnal Pengabdian Kepada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL TEKNOLOGI DAN OPEN SOURCE Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JURTEKSI Zonasi: Jurnal Sistem Informasi Journal of Applied Engineering and Technological Science (JAETS) Jurnal Pengabdian Masyarakat Multidisiplin JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter IJISTECH Jutsi: Jurnal Teknologi dan Sistem Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat J-COSCIS : Journal of Computer Science Community Service Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat SATIN - Sains dan Teknologi Informasi JURNAL KARYA ILMIAH MULTIDISIPLIN INOVTEK Polbeng - Seri Informatika Edu Komputika Journal
Ahmad Zamsuri, Ahmad
Universitas Lancang Kuning
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Efektifitas Aplikasi RDBMS Sebagai Media Arsip Data Pada Kantor Kesehatan Pelabuhan Pekanbaru Berbasis Online Febriadi, Bayu; Zamsuri, Ahmad
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 2 (2017): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v1i2.43

Abstract

Kantor Kesehatan Pelabuhan Kelas II Pekanbaru is a government office that concerns about healthy, especially about environment health. There is a problem in case of saving electronic data, also in analyzing daily data both for internal and external data. The office has some computers and other tools that are useful in saving electronic data. In fact, the data are still saved in available cupboards and it is not efficient for an important data that is analyzed for more than one time. In other words, it is not good for a data is needed to be analyzed continuously. Rational Data Base Management System (RDBMS) application is an online based saving data and it uses System Development Life Cycle (SDLC) method. Hopefully, the application will be very useful for employees Kantor Kesehatan Pelabuhan Pekanbaru in managing their work.
SOSIALISASI ALGORITMA KEBANGSAAN GUNA PENINGKATAN PEMAHAMAN NILAI-NILAI KEBANGSAAN PESERTA DIDIK SEKOLAH MENENGAH KEJURUAN NEGERI 1 MINAS Djusar, Syahtriatna; Zamsuri, Ahmad; Elvira Asril
J-COSCIS : Journal of Computer Science Community Service Vol. 5 No. 1 (2025): J-COSCIS : Journal of Computer Science Community Service
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jcoscis.v5i1.21347

Abstract

Melalui sosialisasi Algoritma Kebangsaan, SMK Negeri 1 Minas berharap dapat membantu peserta didik memahami makna sebenarnya dari kebangsaan, memperkuat rasa persatuan dan kesatuan, serta menginternalisasi nilai-nilai Pancasila sebagai dasar negara. Dengan demikian, diharapkan generasi muda yang dihasilkan oleh SMK Negeri 1 Minas dapat menjadi generasi yang memiliki kesadaran nasional yang tinggi, serta siap untuk menghadapi dan mengatasi berbagai tantangan dalam memajukan bangsa dan Negara. Pengabdian yang dilakukan meliputi tiga tahapan, yaitu Tahap pertama yaitu fase persiapan, Tahap kedua yaitu fase penjelasan dan Tahap ketiga yaitu fase evaluasi. Kegiatan ini di ikuti oleh 25 orang siswa SMKN 1 Minas. Untuk mengukur pengetahuan, pemahaman dan peningkatanya setelah dilaksanakan kegiatan sosialisasi, digunakan kuisioner ysng meliputi 2 Tipe pertanyaan, yaitu Tipe Tipe A (Benar atau Salah) sebanyak 4 pertanyaan dan Tipe B (Pilihan Beberapa Jawaban) sebanyak 4 pertanyaan dengan total butir pertanyaan sebanyak 8. Hasil dari kegiatan yang telah dilakukan, menunjukkan adanya rata-rata peningkatan pengetahuan dari 25 orang peserta, dimana pada kuisioner awal, rata-rata pengetahuan dan pemahaman peserta berada pada penilaian Cukup (rata-rata nilai = 60), dan setelah dilaksanakan refleksi kegiatan dalam bentuk asesmen sumatif dengan pertanyaan lisan, didapatkan rata-rata pengetahuan dan keterampilan peserta berada pada penilaian Baik Sekali (rata-rata nilai = 90).
The Mitigating Overfitting in Sentiment Analysis Insights from CNN-LSTM Hybrid Models Susandri, Susandri; Zamsuri, Ahmad; Nasution, Nurliana; Efendi, Yoyon; Alwan, Hiba Basim
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 24 No 2 (2025)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4742

Abstract

This study aims to improve sentiment analysis accuracy and address overfitting challenges in deep learning models by developing a hybrid model based on Convolutional Neural Networks and Long Short-Term Memory Networks. The research methodology involved multiple stages, starting with preprocessing a dataset of 5,456 rows. This process included removing duplicate data, empty entries, and neutral sentiments, resulting in 2,685 usable rows. To overcome data quantity limitations, data augmentation expanded the training dataset from 2,148 to 10,740 samples. Data transformation was carried out using tokenization, padding, and embedding techniques, leveraging Word2Vec and GloVe to produce numerical representations of textual data. The hybrid model demonstrated strong performance, achieving a training accuracy of 99.51%, validation accuracy of 99.25%, and testing accuracy of 87.34%, with a loss value of 0.56. Evaluation metrics showed precision, recall, and F1-Score values of 86%, 87%, and 86%, respectively. The hybrid model outperformed individual models, including Convolutional Neural Networks (70% accuracy) and Long Short-Term Memory Networks (81% accuracy). It also surpassed other hybrid models, such as the multiscale Convolutional Neural Network-Long Short-Term Memory Network, which achieved a maximum accuracy of 89.25%. The implications of this study demonstrate that the hybrid model based on Convolutional Neural Networks and Long Short-Term Memory Networks effectively improves sentiment analysis accuracy while reducing the risk of overfitting, particularly in small or imbalanced datasets. Future research is recommended to enhance data quality, adopt more advanced embedding techniques, and optimize model configurations to achieve better performance.
SOSIALISASI BRANDING PRODUK USAHA MIKRO, KECIL DAN MENENGAH (UMKM) DI KELURAHAN SIALANGMUNGGU Arini; Ahmad Zamsuri; Aprilia Milanda Putri; Sahrul Saputra; Andi Zahran Budiman
J-COSCIS : Journal of Computer Science Community Service Vol. 5 No. 1 (2025): J-COSCIS : Journal of Computer Science Community Service
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jcoscis.v5i1.22632

Abstract

Usaha mikro kecil dan menengah memiliki peran dalam mempertahankan roda perekonomian nasional. Branding merupakan istilah dari sebuah nama, symbol dan perancangan sebuah desain pada produk (Irawan & Affan, 2020). UMKM harus berinovasi agar dapat bersaing secara global. UMKM di kelurahan Sialangmunggu memiliki berbagai latar belakang usaha baik kuliner, produk, dan kerajinan. Berdasarkan hasil survey yang telah dilakukan oleh tim PPK Ormawa HMJ Manajemen Universitas Lancang Kuning salah satu masalah yang dialami oleh mayoritas UMKM di Kelurahan Sialangmunggu adalah kurang memahami branding sebagai fungsi untuk menjaga sustainability usahanya. Kebanyakan para pelaku UMKM masih berfokus pada trading dan melupakan sisi branding. Hal ini dapat disebabkan karena ketidaktahuan, ego, atau sifat tertutup mereka atas ide baru, dan merasa cepat puas. Oleh karena itu sangat masuk akal untuk kita pahami bahwa branding bukan hanya membuat target pemasaran kita memilih kita didalam pasar yang penuh kompetensi ini tetapi juga membuat prospek-prospek pemasaran kita melihat kita sebagai satu-satunya yang dapat memberikan solusi kepada kebutuhan ataupun masalah mereka.
Synthetic Minority Oversampling Technique for Efforts to Improve Imbalanced Data in Classification of Lettuce Plant Diseases Nurliana Nasution; Feldiansyah Feldiansyah; Ahmad Zamsuri; Mhd Arief Hasan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 6 No. 1 (2023): Jurnal Teknologi dan Open Source, June 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i1.2883

Abstract

In this study we classified lettuce plant diseases. These plant diseases are available in the form of images that have been converted in .csv format to be classified. These plant diseases are available in the form of images that have been converted in .csv format to be classified. Image These plant diseases have been divided into several classes or categories. Then we determine the features of each row and column of the dataset. Each line in the CSV file represents one image, and each column represents one feature Each line in the CSV file represents one image, and each column represents one feature. Then a label is made for each line in the CSV file, namely the class or category where the images are grouped. Thus, so that we get datasets that are ready to be processed with machine learning. However, in processing the dataset, we get imbalanced data. So we added the Synthetic Minority Over-sampling Technique (SMOTE) method to overcome the imbalance that occurs. So that the data can be classified using several algorithms to find the best accuracy.
The Mitigating Overfitting in Sentiment Analysis Insights from CNN-LSTM Hybrid Models Susandri Susandri; Ahmad Zamsuri; Nurliana Nasution; Yoyon Efendi; Hiba Basim Alwan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4742

Abstract

This study aims to improve sentiment analysis accuracy and address overfitting challenges in deep learning models by developing a hybrid model based on Convolutional Neural Networks and Long Short-Term Memory Networks. The research methodology involved multiple stages, starting with preprocessing a dataset of 5,456 rows. This process included removing duplicate data, empty entries, and neutral sentiments, resulting in 2,685 usable rows. To overcome data quantity limitations, data augmentation expanded the training dataset from 2,148 to 10,740 samples. Data transformation was carried out using tokenization, padding, and embedding techniques, leveraging Word2Vec and GloVe to produce numerical representations of textual data. The hybrid model demonstrated strong performance, achieving a training accuracy of 99.51%, validation accuracy of 99.25%, and testing accuracy of 87.34%, with a loss value of 0.56. Evaluation metrics showed precision, recall, and F1-Score values of 86%, 87%, and 86%, respectively. The hybrid model outperformed individual models, including Convolutional Neural Networks (70% accuracy) and Long Short-Term Memory Networks (81% accuracy). It also surpassed other hybrid models, such as the multiscale Convolutional Neural Network-Long Short-Term Memory Network, which achieved a maximum accuracy of 89.25%. The implications of this study demonstrate that the hybrid model based on Convolutional Neural Networks and Long Short-Term Memory Networks effectively improves sentiment analysis accuracy while reducing the risk of overfitting, particularly in small or imbalanced datasets. Future research is recommended to enhance data quality, adopt more advanced embedding techniques, and optimize model configurations to achieve better performance.
Optimization Of Social Media Phishing Detection Models Syafitri (Scopus ID: 57200085316), Wenni; Guntoro, Guntoro; Zamsuri, Ahmad; Waldelmi, Idel
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 1 (2025): June 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i1.37602

Abstract

Phishing is one of the most dangerous attacks in the cyber world. Very few researchers have focused on social media phishing, although SMS phishing can be related to the messaging features available on various social media platforms. This study will utilize PSO and PCA techniques to optimize the performance of RF in social media phishing. This study will compare the performance of PSO and RF with that of PCA and RF. An optimized phishing message detection model was built using NLP, incorporating TF-IDF for feature extraction, PCA and PSO for feature optimization, and Random Forest as a classifier to distinguish phishing messages from normal messages. The RF model optimized by PSO produces nearly balanced metrics: precision (0.9877), recall (0.9728), and F1 (0.9802), all of which are high. The RF model with PCA optimization achieves a slightly lower Accuracy (0.9639) and the lowest Precision (0.9585). Although there were no significant differences in the classification process, PSO and PCA made a real contribution to future research development.
PELATIHAN DESAIN MEDIA DENGAN APLIKASI CANVA UNTUK SISWA MADRASAH ALIYAH MA'ARIF NU PEKANBARU Zamsuri, Ahmad; Susandri, Susandri; Pane, Eddissyah Putra; Feldiansyah, Feldiansyah; Fajrizal, Fajrizal; Herlina, Sari
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.3022

Abstract

Abstract: The Canva application is an application that can be used in creating banner designs. With the utilization and development of techniques in making banner designs. In this case, the use of attractive and appropriate media in the process of making training banners will have a positive impact that will have the potential to greatly improve students' ability to create banners with the Canva application. Students and students really need knowledge in making media design with the aim of providing provisions in making media design even though students at Madrasah Aliyah Ma'arif NU Pekanbaru are quite many who want trainings to improve students' soft skill knowledge. Community Service offers a solution in the form of media design making training with the Canva application for students of Madrasah Aliyah Ma'arif NU Pekanbaru. Where this program is expected to be a forum and inspiration for students to increase their knowledge in making Media Design with the canva application. Where this program is expected to be able to be a forum and inspiration for students to be able to increase their knowledge in making Media Design with the great canva application that students and students of Madrasah Aliyah Ma'arif NU Pekanbaru hope for. As a speaker, he provided socialization and at the same time assistance on how to make Media Design with an interesting and certainly very useful application for students of Madrasah Aliyah Ma'arif NU Pekanbaru. Keyword: Media Design, Canva, Students of Madrasah Aliyah Ma'arif NU Pekanbaru  Abstrak: Aplikasi canva merupakan aplikasi yang dapat digunakan dalam pembuatan desain spanduk. Dengan pemanfaatan dan pengembangkan teknik dalam pembuatan desain spanduk. Dalam hal ini, pemanfaatan media yang menarik dan tepat guna dalam proses pembuatan spanduk pelatihan akan memiliki dampak positif yang akan sangat berpotensi meningkatkan kemampuan siswa dalam membuat spanduk dengan aplikasi canva. Para siswa dan siswi sangat membutuhkan pengetahuan dalam membuat desain media dengan tujuan memberikan bekal dalam pembuatan desain media walaupun siswa di Madrasah Aliyah Ma'arif NU Pekanbaru cukup bayak yang menginkan pelatihan-pelatihan untuk meningkatkan pengetahuan softskill siswa. Pengabdian Kepada Masyarakat menawarkan solusi berupa pelatihan pembuatan desain media dengan aplikasi canva untuk siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Di mana program ini diharapkan mampu menjadi wadah dan inspirasi bagi para siswa dapat menambah pengetahuan dalam membuat Desain Media dengan aplikasi canva besar harapan siswa dan siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Sebagai pemateri memberikan sosialisasi dan sekaligus pendampingan mengenai bagaimana pembuatan Desain Media dengan aplikasi canva yang menarik dan pastinya sagat dapat bermanfaat bagi siswa Madrasah Aliyah Ma'arif NU Pekanbaru. Kata kunci: Desain Media, Canva, Siswa Madrasah Aliyah Ma'arif NU Pekanbaru
PENINGKATAN KREATIVITAS DIGITAL MELALUI PELATIHAN PEMBUATAN KARAKTER AI MENGGUNAKAN MIDJOURNEY PADA SISWA SMK NEGERI 8 PEKANBARU Fajrizal, Fajrizal; Zamsuri, Ahmad; Hasan, Mhd Arief; Fajar, Muhammad Al
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 1 (2025): April 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i1.2814

Abstract

Abstract: This program aimed to introduce and enhance students' understanding of artificial intelligence (AI), with a focus on using MidJourney in digital character creation. The training, attended by 10 students and 1 teacher, covered material from basic to advanced levels regarding AI technology and its application in creative industries. The training methodology included theory introduction, MidJourney tool demonstrations, and hands-on practice in creating digital characters. Evaluation was conducted through pre-test and post-test questionnaires, showing significant improvement in participants' understanding of AI and MidJourney. The pre-test results indicated that 70% of participants had limited foundational knowledge of AI, while the post-test results revealed a 40% increase, with participants now able to create more effective prompts for generating digital characters. Additionally, a post-training satisfaction survey showed high satisfaction levels regarding the delivery of material and the overall quality of the training. This training successfully improved the participants' technological literacy and prepared them for the challenges of the creative industry, which increasingly relies on AI technology. Overall, this activity made a positive contribution in enhancing students' skills in AI-based digital design. Keyword: training; artificial intelligence; midjourney; character design; SMK Negeri 8 pekanbaru; creative technology  Abstrak: Program ini bertujuan untuk memperkenalkan dan meningkatkan pemahaman siswa tentang kecerdasan buatan (AI) dengan fokus pada penggunaan MidJourney dalam pembuatan karakter digital. Peserta pelatihan, yang terdiri dari 10 siswa dan 1 guru pendamping, diberikan materi dari dasar hingga mahir mengenai teknologi AI dan penerapannya dalam dunia kreatif. Metode pelatihan meliputi pengenalan teori, demonstrasi penggunaan MidJourney, serta sesi praktik pembuatan karakter digital. Evaluasi dilakukan menggunakan kuesioner pre-test dan post-test yang menunjukkan peningkatan signifikan dalam pemahaman peserta terhadap AI dan MidJourney. Hasil pre-test menunjukkan bahwa 70% peserta memiliki pemahaman dasar yang terbatas tentang AI, sementara hasil post-test menunjukkan peningkatan sebesar 40% dengan peserta mampu menyusun prompt yang lebih efektif untuk menghasilkan karakter digital. Selain itu, survei kepuasan yang dilakukan setelah pelatihan juga menunjukkan tingkat kepuasan yang tinggi terhadap penyampaian materi dan kualitas pelatihan. Pelatihan ini tidak hanya berhasil meningkatkan literasi teknologi peserta, tetapi juga mempersiapkan mereka untuk menghadapi tantangan dunia kerja di industri kreatif yang semakin bergantung pada teknologi AI. Secara keseluruhan, kegiatan ini memberikan kontribusi positif dalam mengasah keterampilan peserta didik di bidang desain digital berbasis AI.. Kata kunci: pelatihan; kecerdasan buatan; midjourney; desain karakter; SMK Negeri 8 pekanbaru; teknologi kreatif 
PENINGKATAN KETERAMPILAN DESAIN GRAFIS BERBASIS AI MELALUI PELATIHAN PENGGUNAAN MIDJOURNEY PADA SISWA JURUSAN REKAYASA PERANGKAT LUNAK DI SMK NEGERI 8 PEKANBARU Fajrizal; Ahmad Zamsuri; Mhd Arief Hasan
J-COSCIS : Journal of Computer Science Community Service Vol. 5 No. 2 (2025): J-COSCIS : Journal of Computer Science Community Service
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/np1yqq20

Abstract

Penelitian ini bertujuan untuk mengimplementasikan pelatihan penggunaan teknologi MidJourney berbasis AI dalam pembuatan desain grafis di SMK Negeri 8 Pekanbaru, khususnya untuk siswa jurusan Rekayasa Perangkat Lunak. Analisis situasi menunjukkan bahwa peserta didik memiliki keterbatasan dalam memahami dan mengaplikasikan teknologi AI dalam desain grafis. Solusi yang ditawarkan adalah pelatihan penggunaan MidJourney untuk meningkatkan kreativitas dan keterampilan teknis peserta dalam desain. Pelatihan dilakukan dengan pendekatan praktikal, mencakup pengenalan platform, pembuatan desain berbasis prompt, serta praktik mandiri dengan pendampingan. Hasil dari kuisioner yang dibagikan sebelum dan sesudah pelatihan menunjukkan peningkatan signifikan dalam keterampilan peserta. Sebelum pelatihan, pemahaman peserta mengenai AI berada pada 50%, namun setelah pelatihan meningkat menjadi 86%. Kemampuan menggunakan MidJourney meningkat dari 44% menjadi 80%, dan kreativitas peserta mengalami peningkatan dari 56% menjadi 84%. Umpan balik dari peserta menunjukkan kepuasan terhadap materi yang diberikan, meskipun ada saran terkait durasi pelatihan dan penyediaan materi lanjutan. Secara keseluruhan, pelatihan ini berhasil memperkenalkan teknologi AI kepada peserta didik dan memberikan dampak positif terhadap pengembangan keterampilan desain grafis berbasis digital.
Co-Authors Abini, Eka Yestira Nita Alkhairi, Putrama Alwan, Hiba Basim Anam, M Khairul Anam, M. Khairul Andi Zahran Budiman Andre Armada Aprilia Milanda Putri Arini Arita Fitri, Triyani Arpan Asparizal, Asparizal Bayu Febriadi, Bayu Dafwen Toresa Deni Iskandar Eko Sediyono Elvira Asril, Elvira Elvira Elvira Fadly Suandi Fajar, Muhammad Al Fajrizal Fajrizal Fajrizal, Fajrizal Febrizal Alfarasy Syam Febrizal Alfarasy Syam Febrizal As-Syam Feldiansyah Feldiansyah Feldiansyah, Feldiansyah Fitri Juliani Gunadi Widi Nurcahyo Guntoro, Guntoro Hamdani Hamdani Hazira, Nadila Hendrawan, Riki Hiba Basim Alwan idel waldelmi, idel Keumala Anggraini Khairani Djahara, Khairani Lisnawita Lisnawita Loneli Costaner Mariza Devega Mhd. Arief Hasan, Mhd. Arief Muhamad Sadar, Muhamad Muzdalifah, Indah Nurfika Sari Nurliana Nasution Nurliana Nasution, Nurliana Nuroini, Indi Pandu Pratama Putra, Pandu Pratama Pane, Eddissyah Putra Pardede, Akim Manaor Hara Rahmiati Rahmiati Ramadani, Indah Ramadhani, Maya Roki Hardianto Sahrul Saputra Saputra, Eko Ikhwan Sari Herlina Sari Herlina Sari Herlina Sarjon Defit Shelydia Martha Sumijan , Sumijan Susandri, Susandri Susi Handayani Sutejo Sutejo Syafitri (Scopus ID: 57200085316), Wenni Syahtriatna D Syahtriatna Djusar Syahtriatna Djusar Syam, Salmaini Safitri Tintien Koerniawati Triyani Arita Fitri Turnandes, Yogo Vebby Vebby Vebby Walhidayat Walhidayat Walhidayat Wenni Syafitri, Wenni Wirta Agustin Yenni, Heda Yogi Yunefri, Yogi Yogo Turnandes Yogo Turnandes Yoyon Efendi Yoyon Efendi Yuhelmi Yuhelmi Yuvi Darmayunata Zamzami, Zamzami