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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Conference on Innovation and Application of Science and Technology (CIASTECH) JURTEKSI Jurnal Abdimas Mahakam METIK JURNAL Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jusikom: Jurnal Sistem Informasi Ilmu Komputer Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Indonesian Journal of Electrical Engineering and Computer Science Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Djtechno: Jurnal Teknologi Informasi Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Mechanical Engineering for Society and Industry Dirgamaya: Jurnal Manajemen dan Sistem Informasi J-Intech (Journal of Information and Technology) Automotive Experiences Journal of Informatics and Communication Technology (JICT) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Abdimas Journal International of Lingua and Technology Jurnal Komtekinfo Jurnal Buana Pengabdian Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Innovative: Journal Of Social Science Research JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Polimesin Journal of Informatics and Communication Technology (JICT) CSRID Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi Journal of Information Technology
April Lia Hananto
Universitas Buana Perjuangan Karawang, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Analisis Sentimen Aplikasi Bank Digital Pada Google Play Store Menggunakan Algoritma Naive Bayes Arkan Hilman Hakim; Hananto, April Lia; Nurapriani, Fitria; Huda, Baenil
Journal of Informatics and Communication Technology (JICT) Vol. 7 No. 1 (2025)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/jict.v7i1.405

Abstract

Pesatnya perkembangan teknologi perbankan digital telah mendorong munculnya beragam aplikasi perbankan yang tersedia di Google Play Store. Ulasan pengguna terhadap aplikasi-aplikasi ini menjadi sumber informasi yang berharga untuk menilai tingkat kepuasan mereka, yang kemudian dapat dianalisis melalui pendekatan sentiment analysis. Penelitian ini dilakukan untuk mengkaji kecenderungan sentimen pengguna terhadap beberapa aplikasi bank digital dengan memanfaatkan algoritma Naïve Bayes. Data yang dianalisis berasal dari 1.000 ulasan pengguna untuk masing-masing aplikasi, yaitu Seabank, Krom Bank, Bank Jago, Blu by BCA, dan Bank Saqu. Seluruh proses analisis dan pengolahan data dilakukan menggunakan platform Google Colab, dengan menerapkan metode Multinomial Naïve Bayes (MNB) untuk mengklasifikasikan sentimen ke dalam dua kategori, yaitu positif dan negatif. Hasil penelitian mengungkapkan bahwa Seabank menunjukkan performa tertinggi, dengan accuracy sebesar 94%, precision 93%, recall 100%, dan F1-score 97%, serta total 945 ulasan positif dan 55 ulasan negatif. Temuan ini memperlihatkan bahwa analisis sentimen dapat memberikan masukan yang bernilai bagi pengembang untuk meningkatkan kualitas aplikasi, sekaligus menjadi panduan bagi pengguna dalam memilih layanan perbankan digital yang sesuai dengan preferensi kebutuhan.
User Experience Design Analysis of the Karawang Job Vacancy Website using the User-Centered Design Method and System Usability Scale Sopian, Jajang; Huda, Baenil; Novalia, Elfina; Hananto, April Lia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5303

Abstract

An optimized User Experience (UX) design plays a significant role in creating a comfortable browsing experience, ensuring good accessibility, and enhancing user satisfaction. This study analyzes the UX design of the Info Loker Karawang website by applying the User-Centered Design (UCD) method and evaluating the resulting prototype using the System Usability Scale (SUS) to assess the website’s ease of use. The UCD method was selected because it places the user at the center of the design process, enabling the development of solutions that align closely with users’ needs, expectations, and characteristics. This approach has proven effective in producing relevant and intuitive interfaces through stages of analysis, design, and evaluation involving active user participation. Following the design phase, the prototype was tested using the SUS instrument to measure how well the design solution met usability and user satisfaction criteria. The evaluation results indicate that applying UCD in website design significantly improves usability, achieving a SUS score of 72.5, which falls into Grade B and is categorized as “Good” on the adjective rating scale. This research provides insights into the importance of user-centered approaches in website development and demonstrates the effectiveness of SUS in evaluating and measuring the success of UX design outcomes.
Penerapan Algoritma Apriori Dalam Menentukan Pola Pergerakan Kebutuhan Distribusi Pada PT. Satria Teknik Indonesia Yoviyardi, Rama; Lia Hananto, April; Nurapriani, Nurapriani; Huda, Huda
Jurnal PROCESSOR Vol 20 No 1 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.1.2207

Abstract

In an increasingly competitive business environment, companies are required to make more precise strategic decisions to enhance operational efficiency. The shift in customer demand trends has become a major challenge faced by PT Satria Teknik Indonesia, a goods distribution company. To address this challenge, the company can leverage transaction data to analyze customer purchasing patterns. By utilizing the results of this analysis, PT Satria Teknik Indonesia can improve the accuracy of customer demand predictions, accelerate data-driven decision-making, and optimize inventory management. One effective method for this analysis is the Apriori algorithm. The data used were obtained from the company's transaction recording system during the period from January 2023 to October 2024 and were analyzed to discover association rules in large datasets and identify relationships between products that are frequently purchased together. The results of this study reveal two items that are prioritized for ordering: Back Support and Safety Shoes Cheetah. If customers purchase Back Support, they are highly likely to also purchase Safety Shoes Cheetah, with a support value of 20.22% and a confidence level of 100%. Conversely, if customers purchase Safety Shoes Cheetah, they tend to also buy Back Support, with a support value of 20% and a confidence level of 94.74%. This study identifies a strong purchasing association pattern between Back Support products and Safety Shoes Cheetah, providing empirical evidence of the benefits of implementing data mining techniques to improve inventory management effectiveness and better respond to customer needs
Klasifikasi Sentimen Komentar Pengguna pada Aplikasi Ruangguru Menggunakan Algoritma Naive Bayes Yovika Aprianti; Tukino; Hananto, April Lia; Hilabi, Shofa Shofiah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1023

Abstract

The advancement of digital technology has encouraged the increasing use of online learning applications such as Ruangguru, while simultaneously fostering various innovations in the field of education. Ruangguru, as one of the most popular educational applications in Indonesia, receives thousands of user comments that can be analyzed to reflect user satisfaction and perception. This study aims to automatically classify user comments based on the sentiments they contain using the Naïve Bayes Classifier algorithm. This approach is expected to help Ruangguru developers better understand user needs and preferences, thereby improving service quality. The dataset was obtained from the Google Play Store platform, consisting of approximately 5,000 comments collected during the period from October 28 to December 31, using the google-play-scraper tool. The application of the Multinomial Naïve Bayes algorithm with TF-IDF weighting was employed to analyze the data, resulting in four sentiment categories: Baik Sekali, Baik, Cukup Baik, and Kurang Baik. Evaluation of the model was conducted using accuracy, precision, recall, and F1-score metrics. With an accuracy rate of 84.83%, the model correctly predicted the actual labels in approximately 85% of the test data. The model also achieved an F1-score of 85%, a precision of 86%, and a recall of 85%. The classification results revealed that the “Baik” category dominated with a proportion of 28.3%, followed by “Baik Sekali” at 24.3%, “Cukup Baik” at 24.0%, and “Kurang Baik” at 23.4%. These findings indicate that the model maintains a reasonable balance between sensitivity and accuracy in sentiment classification. Therefore, the Naïve Bayes Classifier method is capable of automatically identifying user opinions and has the potential to serve as a valuable tool in sentiment analysis for online learning services.
Klasterisasi Supplier Berdasarkan Kinerja Menggunakan Algoritma K-Means Afra, Alfina Fadhilah; Hananto, April Lia; Hananto, Agustia; Priyatna, Bayu
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 2 (2025): April 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i2.1935

Abstract

Untuk memastikan efisiensi operasional dan kualitas produk, evaluasi kinerja supplier sangat berperan penting dalam bidang perindustrian. PT Percetakan masih menggunakan penilaian subjektif dalam menilai kinerja supplier. Variabel dalam data ini yaitu Supplier, Jumlah Pesanan, Harga Satuan dan Rentang Pengiriman yang dapat dianalisis untuk meningkatkan penilaian kinerja supplier. Penelitian ini menggunakan algoritma K-Means untuk mengklasterisasikan supplier berdasarkan kinerja. Algoritma K-Means dipilih karena dapat mengolah data dalam jumlah besar dan efisien, hasil yang didapat lebih objektif dibanding pendekatan subjektif. Hasil Penelitian ini diharapkan dapat memberikan kontribusi dan solusi yang praktis bagi PT Percetakan untuk menentukan mitra kerja sama melalui penerapan algoritma K-Means. Hasil klasterisasi menunjukkan bahwa terdapat perbedaan yang signifikan antara supplier dalam setiap klaster. Supplier dengan performa terbaik (Klaster 1) cenderung memiliki jumlah pesanan yang tinggi, harga satuan lebih kompetitif, dan waktu pengiriman lebih cepat. Sementara itu, supplier dengan performa rendah (Klaster 3) memiliki harga lebih tinggi dan rentang pengiriman yang lama, yang dapat mempengaruhi efisiensi operasional perusahaan.
Web-Based Warehouse Inventory System Using the Waterfall Method: A Case Study at Satria Wholesale Mart Melisa; Tukino; Agustia Hananto; April Lia Hananto
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.610

Abstract

In the digital era, manual warehouse inventory management is still challenging for many business people, including Satria Wholesale Mart. The main problems also faced are irregularities in recording incoming and outgoing goods, low accuracy of stock data, delays in reporting, and difficulties in tracking stock in real time. This finding aims to design and build an efficient and effective web-based warehouse inventory system using the Waterfall method. The finding method used is applied findings with a descriptive qualitative approach, which also aims to describe in detail and systematically the phenomena that also occur in the field and how new systems can be developed to solve these problems. The findings show that applying the waterfall method in developing a web-based inventory information system at PT Herso Ticep Indonesia has also yielded satisfactory results. The system that has also been developed has succeeded in meeting the needs of companies in inventory management, improving operational efficiency, and optimizing inventory management. These findings imply that companies can improve their operational efficiency and optimize inventory management by implementing this information system. The findings could also guide other companies that want to develop similar systems.
Development of Geolocation-Based Employee Attendance Application on Android Mobile Kurnia, Nisa; Hananto, April Lia; Tukino, Tukino; Hilabi, Shofa Shofiah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1890

Abstract

The development of mobile-based systems in Indonesia has provided innovative solutions to improve the efficiency of conventional administrative processes, especially in employee attendance. This research aims to develop an Android-based employee attendance application that is integrated with geolocation technology to enable accurate and real-time attendance monitoring. This system is built using the Waterfall method, which includes the stages of needs analysis, system design, implementation using Flutter and Dart programming language, and testing using black box testing techniques. Black-box testing was conducted on six main functions, resulting in a 94% overall success rate. Most functions achieved a 100% pass rate, but two test cases for attendance check in/out failed due to GPS location inaccuracies, highlighting the impact of device and environmental factors. The average response time was 1.28 seconds, and the average GPS delay was 2.1 seconds. The implementation of real-time notifications and admin verification improved transparency and minimized attendance fraud. The results demonstrate that the application provides an effective and efficient solution for employee attendance management. Future work should focus on enhancing location accuracy, conducting non-functional testing, and expanding features to ensure broader adoption and system robustness.
Analisis Status Pembayaran Group Order NooBlue Menggunakan Algoritma XGBoost Surala, Lyvia; Tukino; April Lia Hananto; Elfina Novalia; Fitria Nurapriani
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 4 (2025): EDISI JULI 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i4.11279

Abstract

Pertumbuhan pesat ekonomi digital telah mendorong meningkatnya penggunaan layanan transaksi daring, termasuk sistem pemesanan kelompok. Namun, tantangan baru turut muncul, khususnya dalam hal keandalan informasi terkait status pembayaran pelanggan. Permasalahan seperti keterlambatan atau kegagalan pembayaran dapat memengaruhi kestabilan keuangan bisnis. Oleh karena itu, penelitian ini bertujuan untuk membangun model prediksi status pembayaran pelanggan menggunakan algoritma Extreme Gradient Boosting (XGBoost). Data yang digunakan berasal dari transaksi NooBlue Shop pada Maret 2025, yang terdiri dari 403 entri. Proses analisis mencakup tahapan pra-pemrosesan data, pembagian data menjadi data latih dan uji dengan rasio 60:40, serta pelatihan model XGBoost. Model dievaluasi menggunakan metrik klasifikasi seperti akurasi, precision, recall, F1-score, dan confusion matrix. Hasil pengujian menunjukkan bahwa model mampu mengklasifikasikan status pembayaran dengan tingkat akurasi mencapai 90%. Nilai precision dan recall masing-masing berada pada kisaran 0.89–0.93, sedangkan F1-score menunjukkan performa yang seimbang untuk kedua kelas. Analisis lebih lanjut menunjukkan bahwa fitur total pembayaran dan uang muka merupakan kontributor utama dalam proses prediksi. Temuan ini menunjukkan bahwa penerapan XGBoost dapat memberikan solusi yang efektif dalam membantu perusahaan memantau status pembayaran pelanggan secara otomatis dan responsif, serta mendukung pengambilan keputusan berbasis data secara lebih tepat dan efisien di tengah dinamika ekonomi digital.
Perancangan Website E-commerce Menggunakan Metode Waterfall pada Penjualan Alat Komputer Hibatullah, Muhammad Hafizh; Tukino; Hananto, April Lia
Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi Vol. 2 No. 3 (2025): SINTA: JULI
Publisher : Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/sinta.v2i3.61

Abstract

Perkembangan teknologi informasi telah mendorong perusahaan untuk memanfaatkan internet sebagai media penjualan melalui e-commerce. Artikel ini membahas perancangan website e-commerce bernama NATIVE STORE yang fokus pada penjualan handphone, hardware komputer, dan laptop. Penelitian ini bertujuan untuk membantu perusahaan memperluas jangkauan pemasaran dan memudahkan konsumen dalam melakukan transaksi secara online. Metode yang digunakan adalah Waterfall, sebuah pendekatan SDLC (System Development Life Cycle) klasik yang terdiri dari tahapan: analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Website dibangun menggunakan bahasa pemrograman PHP dan database MySQL. Hasil pengujian menggunakan metode Blackbox menunjukkan bahwa seluruh fitur berjalan sesuai harapan. Website ini diharapkan mampu menjadi solusi efektif dalam meningkatkan efektivitas penjualan dan kemudahan akses bagi konsumen.
KLASIFIKASI ULASAN APLIKASI KOPI KENANGAN PADA GOOGLE PLAYSTORE MENGGUNAKAN ALGORITMA NAIVE BAYES Fadli, Muhammad Abil; tukino, Tukino; Novalia, Elfina; Hananto, April Lia
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7037

Abstract

Aplikasi Kopi Kenangan merupakan aplikasi yang digunakan untuk pemesanan minuman secara online milik perusahaan PT Bumi Berkah Boga. Selain hal tersebut aplikasi ini juga membantu perusahaan menerima ulasan terkait pengalaman pelanggan dalam menggunakan layanan aplikasi kopi kenangan. Namun ulasan pelanggan di Google Playstore memiliki jumlah data yang banyak sehingga sulit dianalisis secara manual. Tujuan penelitian ini melakukan klasifikasi ulasan pelanggan pada aplikasi Kopi Kenangan mempergunakan algoritma Naïve bayes. Metode penelitian ini meliputi pengumpulan data, preprocessing, pemodelan dan evaluasi. Data yang dipergunakan dalam penelitian ini yaitu sebesar 1000 data dengan lima kategori yaitu promo, pelayanan, performa aplikasi, transaksi dan kualitas produk. Hasil penelitian menunjukkan bahwa kategori ulasan terbanyak adalah tentang performa aplikasi dengan persentase 45% dari total 1000 data ulasan. Hasil akurasi penelitian yaitu sebesar 85% yang menunjukkan bahwa model dapat melakukan klasifikasi data kategori sentimen dengan cukup baik.
Co-Authors - Faqih AA Sudharmawan, AA Abdullah Abdullah Abdullahi Tanko Mohammed Abdullahi Tanko Mohammed Adittia Agustian Afra, Alfina Fadhilah Agneresa Agneresa Ahmed Sule Ahnaf, Naufal Zubdi Ajie, Prasetyo Alparizi, Muhamad Iqbal Alpian, Yayan alzahra, alika aziza Anthony Chukwunonso Opia Aprilia Putri Nardilasari Arkan Hilman Hakim Asep Haris Atmaja, Rashelin Zahra Aulia, Aldi Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Baenil Huda Baenil Huda Baenil Huda Baenil Huda Bagus Setyawan Baihaqi, Kiki Ahmad Bayu Priyatna Bayu Priyatna Bayu Priyatna Berkah*, Kamila Candra Zonyfar Catur Nugroho Danny Manongga Dean Ariesta Aziz Deddy Prihadi Detrie Noviani Dhany Hermansyah Dien Noviany Rahmatika Edrina Christine, Natalie Eichler, Luiz Eko Pramono Eko Sediyono Esam Abu Baker Ali Fadli, Muhammad Abil Fatlun, Aulia Fatmanisa Mumpuni Delta Maharani Fauzi Ahmad Muda Firdaus, Mohamad Ricky Firman Nurdiansyah Firman Nurdiyansyah Fitri Nur Masruriyah, Anis Fitria Nur Apriani Fitria Nurapriani Guntur, Muhamad Hananto, Agustia Hanny Hikmayanti Handayani Hayati, Cucu Hendry Henry Adam Hibatullah, Muhammad Hafizh Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Hindriyanto Dwi Purnomo Huda Huda Huda, Baenil Ihsan, Mohammad Maftuh Ihwan Ghazali Indra Kurniawan Indri Oktapiani Irawan, Bei Harira Irwan Sembiring Istiadi Isyanto, H. Puji Iwan Setiawan Iwan Setyawan Joko Purwanto Kadori, Ilman Kamila Berkah* Kurnia, Nisa Lutfiah, Siti Mega Tri Kurnia Melisa Miswadi Miswadi Moh Hasan Basri Mohamad Ricky Firdaus Mubarok, Piky Muhamad Djaka Permana Muhammad Idris Muhammad Idris Muhammad Idris Muhammad Nova Muhammad Zacky Asy'ari Muthia Nur Rizky Fitriani Nisa Kurnia Novalia, Elfina Novia Cahya Utami Nurapriani, Fitri Nurapriani, Fitria Nurapriani, Nurapriani Nurfajria, Dera Paryono, Tukino Permana Andi Paristiawan Permana Andi Paristiawan Pradana Rizki Maulana Prasetya, Rafli Pratama, Daffa Agung Priatna, Bayu Priyatna , Bayu Priyatna, Bayu Purnomo, Hendryanto Dwi Putri Indraswari Reformasi, Era Rieke Retnosary Rosalina, Elsa Rukmanta Jayawiguna Ruliansyah Ruliansyah Ruliansyah Ruliansyah, Ruliansyah Saepul Aripiyanto Safarudin Gazali Herawan Sari, Nurnilam Sarina Sulaiman Sarina Sulaiman Setiawan, Feddy Wanditya Setiawan, Pratama Wahyu Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Sofiah Hilabi Shofiah Hilabi, Shofa Shuaibu Alani Balogun Sigit Widiyanto Silva, Tiago Siti Masruroh Soleman, Soleman Sopian, Jajang Sri Mumpuni Ngesti Rahaju Sudrajat, Deden Renhad Suhada, Karya Surala, Lyvia Susilawati, Agnes Dwita Syah Alam Tita Puspita Sari Tukino Tukino Tukino Tukino Tukino Tukino, Tukino tukino, tukino Tukino, Tukino Wahiddin, Deden Yazid, Muhammad Abi Yovika Aprianti Yoviyardi, Rama yuwono, Fuad anwar