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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Robotics and Automation (IJRA) Techno.Com: Jurnal Teknologi Informasi Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Teknologi Informasi dan Ilmu Komputer Seminar Nasional Informatika (SEMNASIF) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika EMITTER International Journal of Engineering Technology Padjadjaran Journal of Dentistry Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization JURNAL INTEGRASI J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Mantik Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Indonesian Journal of Electrical Engineering and Computer Science GUYUB: Journal of Community Engagement Jurnal Rekayasa elektrika The Indonesian Journal of Computer Science Advance Sustainable Science, Engineering and Technology (ASSET)
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Segmentasi Pertumbuhan Padi berbasis Aerial Image menggunakan Fitur Warna dan Tekstur untuk Estimasi Produksi Hasil Panen Arifin, Muhammad Jainal; Basuki, Achmad; Dewantara, Bima Sena Bayu
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 1: Februari 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.0813438

Abstract

Pertumbuhan padi di daerah yang luas seringkali tidak ideal. Ini dapat disebabkan oleh faktor alam, jenis varietas padi, dan model perawatan yang digunakan. Ini juga akan mempengaruhi hasil panen. Luasnya lahan membuat petani sulit untuk memantau bagian yang tidak terjangkau. Seringkali pemantauan perkembangan padi dilakukan di tepi sawah tetapi tidak mencapai area tengah. Studi ini mengusulkan sistem pemantauan untuk pengembangan padi yang dapat menjangkau secara lebih luas dan memperkirakan hasil padi di setiap area lahan pertanian. Sistem ini menggunakan gambar udara untuk menjangkau area yang lebih luas dan kemudian memperkirakan produksi pertanian. Estimasi produksi dilakukan dengan mengelompokkan gambar kawasan pertanian menggunakan metode K-Means. Pengelompokan ini menggunakan parameter warna HSV dan tekstur Gabor sebagai fitur dari setiap bagian gambar. Hasilnya adalah segmen area padi berdasarkan pertumbuhannya. Jumlah segmen yang sesuai dengan usia Padi nyata akan menentukan nilai estimasi hasil. Penelitian menunjukkan bahwa tiga segmen pengembangan padi, dan memperkirakan produksi adalah 1.787 ton dengan perkiraan panen maksimum 1.924 ton dari data nyata 1,80 ton. Dan dengan skala kesalahan persentase rata-rata absolut 0,72% dan perbedaan 0,013 ton. AbstractPaddy growth in large areas is often not ideal. This can be caused by natural factors, types of rice varieties, and the treatment model used. This will also affect crop yields. The extent of land makes it difficult for farmers to monitor the unreachable part. Often monitoring of rice developments is done on the edge of the field but does not reach the middle area. This study proposes a monitoring system for rice development that can reach more broadly and estimate the yield of rice in every area of agriculture land. This system uses aerial images to reach a wider area and then estimates of agricultural production. Estimation of production is done by clustering images of agricultural areas using the K-Means method. This clustering uses HSV color parameters and Gabor textures as features of each part of the image. The result is a segment of the paddy area based on its growth. The number of segments corresponding to the age of the real Paddy will determine the estimated value of the yield. The research shows that three segments of rice development, and estimates the production is 1,787 tons with a maximum estimated harvest of 1,924 tons from the real data of 1, 80 tons. And with a mean absolute percentage error scale of 0.72% and a difference of 0.013 tons.
Studi Analisi Konsentrasi Warna Pada Cairan Pewarna Makanan Dengan Metode Pengukuran Optical Density Meiyanto, Onie; Gunawan, Agus Indra; Bayu Dewantara, Bima Sena
BRILIANT: Jurnal Riset dan Konseptual Vol 6 No 4 (2021): Volume 6 Nomor 4, November 2021
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1307.714 KB) | DOI: 10.28926/briliant.v6i4.718

Abstract

Metode Image Processing banyak diimplementasikan untuk mengidetifikasi suatu bentuk atau perubahan pada gambar untuk mendapatkan hasil identifikasi suatu percobaan. Dalam penelitian ini perpaduan Image Processing, optical density(OD) dan sensor rgb untuk menentukan kualitas campuran air yang didapatkan nilai komposisi cairan warna. Karakteristik warna dari sampel air diperoleh dari histogram pada gambar yang tertangkap oleh mikroskop digital, dari histogram warna dapat diperoleh nilai max dan mean dan hasil gambar dari difraksi oleh kamera digital serta nilai output sensor rgb. Dengan metode tersebut diperoleh hasil setiap sampel yang telah di encerkan memiliki karakteristik warna yang berbeda-beda, hal ini dapat dilihat dari setiap kanal warna dari output sensor. Pengolahan data dengan metode histogram untuk dilakukan proses pengambilan nilai rata-rata(mean) dan nilai maksimum(Max) diperoleh model untuk memprediksi jenis dan konsentrasi dari sampel, pengujian yang telah dilakukan, didapatkan hasil grafik yang sigifikan sesuai dengan komposisi kualitas air dengan pewarna makanan
Concept and Design of Anthropomorphic Robot Hand with a Finger Movement Mechanism based on a Lever for Humanoid Robot T-FLoW 3.0 Apriandy, Kevin Ilham; Ulurrasyadi, Faiz; Dewanto, Raden Sanggar; Dewantara, Bima Sena Bayu; Pramadihanto, Dadet
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1793

Abstract

This work described a concept and design of an anthropomorphic robot hand for the T-FLoW 3.0 humanoid robot, which featured a mechanism based on a lever as its finger movement. This work aimed to provide an affordable, modular, lightweight, human-like robot hand with a mechanism that minimizes mechanical slippage. The proposed mechanism works based on the push/pull of a lever attached to the finger to generate its finger flexion/extension movement. The finger’s lever is pushed/pulled through a servo horn and a rigid bar by the affordable TowerPro MG90S micro-servo. Our hand is developed only as necessary to become close to human hands by only applying five fingers and six joints, where each joint has its actuator. The combination of 3D printing technology with PLA filament accelerates and streamlines the manufacturing process, provides a realistic appearance, and achieves a lightweight, affordable, and easy maintenance product. Structural analysis simulations show that our finger design constructed with PLA material could withstand a load of about 30 N. We verified our finger mechanism by repeatedly flexing and extending the finger 30 times, and the results showed that the finger movements could be performed well. Our hand offered excellent handling for the mechanical issues brought on by finger movements, one of the issues that robot hand researchers have encountered. Our work could provide significant benefits to the T-FLoW 3.0 developers in enhancing the ability of humanoid robots involving hands, such as grasping and manipulating objects.
ANN-Based Mechanical Property Prediction of Bio-Fibre for Wind Turbine Blade Materials with FEM Validation Setia, Siaga Whiky; Arini, Nu Rhahida; Bayu Dewantara, Bima Sena
Advance Sustainable Science Engineering and Technology Vol. 8 No. 1 (2026): November - January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i1.2482

Abstract

The increasing demand for renewable energy highlights the need for sustainable materials in wind turbine blade design. Conventional fiberglass blades, while effective, present environmental and disposal challenges, motivating the exploration of bio-composites as greener alternatives. This study aims to develop and validate an integrated framework that combines experimental validation, Finite Element Method (FEM) pre-screening, Artificial Neural Networks (ANN), and Rule of Mixtures (RoM) validation to evaluate the feasibility of bio-fibre wind turbine blades Mechanical properties of flax, hemp, sisal, jute, pineapple fiber, and resin are obtained from previously published experimental studies available in the literature, with resin content fixed at 90% and permutations generated for ANN training. Experimental tensile testing on a 90% resin–10% pineapple fiber composite yields 131 MPa, closely matching the permutation prediction of 118.6 MPa, confirming dataset reliability. FEM simulations are then employed to pre-screen potential maximum performance values within the dataset range, ensuring the physical feasibility of ANN input properties. Using these validated inputs, the ANN predicts feasible bio-composite compositions, which are further compared against RoM estimations. The results show that ANN predictions remain within a 7% deviation from RoM values, demonstrating consistency with micromechanical theory. This integrated framework highlights that FEM-based input screening enhances ANN prediction reliability, and pineapple-based bio-composites can serve as sustainable and technically viable alternatives for wind turbine blade applications.
Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms Dewantara, Bima Sena Bayu; Miura, Jun
EMITTER International Journal of Engineering Technology Vol 2 No 2 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v2i2.27

Abstract

Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time.Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm
The Enhancement of 3 MHz Ultrasonic Echo Signal for Conversion Curve Development for Acoustic Impedance Estimation by Using Wavelet Transform Prastika, Edo Bagus; Gunawan, Agus Indra; Bayu Dewantara, Bima Sena; Hozumi, Naohiro; Prianto, Chandra Edy
EMITTER International Journal of Engineering Technology Vol 6 No 1 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1468.058 KB) | DOI: 10.24003/emitter.v6i1.245

Abstract

Ultrasonic technology has already been used for many applications. Most of them are mainly used for object measurement. Some techniques have been widely applied to particular measurement by utilizing a very specific component. In this research, the previous technique to develop a conversion curve to obtain the acoustic impedance of the target is adopted. Then, we propose a 3 MHz concave shaped ultrasonic transducer for measuring liquids and a confirmation is needed to confirm if the system used is correct. Therefore, several saline solutions which property has been known are used. A low voltage of 10 Volt pulse is used to trigger the transducer. The ultrasonic wave is then transmitted through the multilayered mediums, which is pure water, clear acrylic, and the target. The echo from the interface between the acrylic and the target is then received by the same transducer. Some parameters such as peak and RMS are used to develop the conversion curve. A peak detection and comparison between the original echo and the processed one by using Wavelet transform (UWT and DWT) is then performed. Some analysis of the echo signal by using multiresolution and time-frequency analysis is also proposed. The result obtained from the measurement is then compared to that from the theoretical calculation. Based on the result, in terms of developing the calibration graph, only the RMS value (UWT) which has the closest trend to the result of the calculation, with the mean percentage error of 0.65512%, which is the smallest value among all parameters.
Design and Implementation of Embedded Water Quality Control and Monitoring System for Indoor Shrimp Cultivation Natan, Oskar; Gunawan, Agus Indra; Dewantara, Bima Sena Bayu
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (724.62 KB) | DOI: 10.24003/emitter.v7i1.344

Abstract

Maintaining the water quality of a pond is one of the main issues on aquaculture management. Water quality represents the condition of a pond based on several water parameters such as dissolved oxygen (DO), temperature, pH, and salinity. All of these parameters need to be strictly supervised since it affects the life-sustainability of cultivated organisms. However, DO is said to be the main parameter since it affects the growth and survival rate of the shrimp. Therefore, a water quality control and monitoring system is needed to maintain water parameters at acceptable value. The system is developed on a mini-PC and microcontroller which are integrated with several sensors and actuator forming an embedded system. Then, this system is used to collect water quality data that is consisting of several water parameters and control the DO as the main parameter. In accordance with the stability needs against the sensitive environment, a fuzzy logic-based controller is developed to maintain the DO rate in the water. This system is also equipped with SIM800 module to notice the farmer by SMS, built-in wifi module for web-based data logging, and improved with Android-based graphical user interface (GUI) to perform user-friendly monitoring. From the experiment results, a fuzzy controller that is attached to the system can control the DO at the acceptable value of 6 ppm. The controller is said to have high robustness since its deviation for long-time use is only 0.12 ppm. Another test shows that the controller is able to overcome the given disturbance and easily adapt when the DO’s set point is changed.  Finally, the system is able to collect and store the data into cloud storage periodically and show the data on a website.
Analisis Kinematika Maju dari Tangan Robotik Berjari 4 yang Digunakan pada Robot Humanoid T-FLoW Kevin Apriandy; Bima Sena Bayu Dewantara; Raden Sanggar Dewanto; Dadet Pramadihanto
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3291

Abstract

Model kinematika merupakan bagian penting dalam pengembangan robot humanoid karena dapat merepresentasikan karakteristik dari robot, membuat pemahaman tentang robot menjadi lebih mudah. Mengingat perkembangan robot humanoid T-FLoW yang saat ini dilengkapi dengan sepasang tangan baru, maka perlu dibangun model kinematika untuk memahami lebih lanjut tentang tangan robot baru tersebut. Oleh karena itu, dalam pekerjaan ini, disajikan sebuah analisis kinematika maju untuk memperoleh model kinematika dari tangan berjari 4 baru robot humanoid T-FLoW. Dengan menggunakan pendekatan matriks transformasi homogen, model kinematika tangan robot diturunkan berdasarkan perkalian beberapa matriks rotasi dan matriks translasi yang tersusun dari frame koordinat pangkal ke frame koordinat tujuan. Model kinematika yang diturunkan disimulasikan dalam tugas gerak dasar tangan: menggenggam sebuah benda, dihitung dengan bantuan MATLAB, dan divisualisasikan menggunakan fitur plot 3D MATLAB. Hasil menunjukkan bahwa model tersebut memberikan berbagai karakteristik tangan robot seperti konfigurasi, posisi sendi, dan posisi end-of-effector, yang kemudian dapat divisualisasikan menjadi kerangka tangan. Kedepannya, pekerjaan kami dapat memfasilitasi pengembang T-FLoW dalam membangun pergerakan tangan dengan sistem umpan balik, yang kemudian dapat digunakan untuk menyelesaikan berbagai permasalahan desain gerakan tangan. Kinematics models are important part of humanoid robot development as they can represent the characteristics of the robot, making understanding the robot easier. Given the development of the T-FLoW humanoid robot which is currently equipped with a new pair of hands, it is necessary to build a kinematics model to understand more about the new robot hands. Therefore, in this work, a forward kinematics analysis is presented to derive the kinematics model of the new 4-fingered T-FLoW humanoid robot hand. Using a homogeneous transformation matrix approach, the kinematics model of the robot hand is derived based on the multiplication of several rotation and translation matrices arranged from the base coordinate frame to the goal coordinate frame. The derived kinematics model is simulated in a basic hand motion task: grasping an object, calculated with the help of MATLAB, and visualized using MATLAB's 3D plot feature. The results show that the model provide various characteristics of the robot hand such as configuration, joint positions, and end-of-effector positions, which then be visualized into a hand skeleton. In the future, our work can facilitate T-FLoW developers in building hand movement and feedback systems, which then can be used to solve various hand motion design problems.
Pengenalan Wajah 3D dengan menggunakan PointNet Arif Hidayah; Bima Sena bayu Dewantara; Dadet Pramadihanto
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3294

Abstract

Pengenalan wajah tiga dimensi (3D) telah menjadi topik penelitian yang menarik karena mampu mengatasi keterbatasan pengenalan wajah dua dimensi (2D) dalam menghadapi perubahan pose, pencahayaan, dan pemalsuan. Penelitian ini mengusulkan sebuah pipeline pengenalan wajah 3D yang invarian terhadap perubahan cahaya, dengan menggunakan teknik segmentasi euclidean clustering dan Convolutional Neural Network (CNN) PointNet. Data wajah diambil menggunakan kamera Time-of-Flight yang menghasilkan titik awan (point cloud). Proses segmentasi euclidean clustering berhasil memisahkan area wajah dengan akurat, membantu dalam pengenalan wajah 3D. Melalui pelatihan dengan 217 dataset dan 2048 titik per wajah, sistem mencapai akurasi pelatihan sebesar 99% dan akurasi validasi sebesar 84,4%, dengan loss pelatihan sebesar 1% dan loss validasi sebesar 15,6%. Evaluasi pada tiap kelas menunjukkan rata-rata akurasi 0.9887471867966992, presisi 0.8255813953488372, recall 0.8255813953488372, dan F1-score 0.8255813953488372. Hasil menunjukkan bahwa pipeline pengenalan wajah 3D ini memiliki potensi besar dalam aplikasi keamanan, pengawasan, dan pengenalan objek di lingkungan yang kompleks. Three-dimensional (3D) face recognition has emerged as an intriguing research topic, addressing the limitations of two-dimensional (2D) face recognition in handling pose variations, lighting changes, and spoofing. This study proposes an illumination-invariant pipeline for 3D face recognition, utilizing the euclidean clustering segmentation technique and Convolutional Neural Network (CNN) PointNet. Facial data is captured using a Time-of-Flight camera, generating point clouds. The euclidean clustering segmentation effectively isolates facial regions, aiding in 3D face recognition. After training with 217 datasets and 2048 points per face, the system achieved 99% training accuracy and 84.4% validation accuracy, with 1% training loss and 15.6% validation loss. Class-wise evaluation yielded an average accuracy of 0.9887471867966992, precision of 0.8255813953488372, recall of 0.8255813953488372, and F1-score of 0.8255813953488372. The results highlight the significant potential of this 3D face recognition pipeline in security, surveillance, and object recognition in complex environments.
Deteksi Kondisi Gigi Manusia pada Citra Intraoral Menggunakan YOLOv5 Ahmad Fauzi Makarim; Tita Karlita; Riyanto Sigit; Bima Sena Bayu Dewantara; Arya Brahmanta
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3355

Abstract

Proses identifikasi dan pencatatan rekam medis pada praktik kedokteran gigi masih dilakukan secara manual. Akibatnya, proses tersebut memakan waktu yang cukup lama. Pada penelitian ini metode deteksi objek dimanfaatkan untuk membantu dokter melakukan identifikasi pada gigi pasien. YOLOv5 dipilih untuk dilatihkan pada dataset citra intraoral dengan lima kelas kondisi gigi (normal, karies, tumpatan, sisa akar, dan impaksi). Dataset yang digunakan berjumlah 1.767 data citra intraoral yang diambil dan dilabeli oleh dokter gigi. Dataset dibagi menjadi tiga bagian, 10% digunakan untuk data testing dan 90% digunakan untuk data training dan validation. Dilakukan komparasi performa berdasarkan nilai metrik evaluasi terhadap tiga jenis model YOLOv5 (S, M, L). Dari hasil pelatihan, YOLOv5 M sebagai model terbaik mendapatkan nilai mAP sebesar 84%, dan 82% nilai akurasi testing. Penelitian ini telah memenuhi tujuan utama untuk membangun sebuah model deep learning yang robust untuk mendeteksi dan mengklasifikasi beberapa kondisi gigi pada manusia.
Co-Authors Achmad Basuki Achmad Basuki Achmad Basuki Afifah, Izza Nur Agus Indra Gunawan Ahmad Fauzi Makarim Alfan Rizaldy Pratama Pratama Ali Ridho Barakbah Alif Wicaksana Ramadhan Amang Sudarsono, Amang ANUGERAH WIBISANA Anwar Anwar APRIANDY, KEVIN ILHAM Arif Hidayah Arifin, Muhammad Jainal Arini, Nu Rhahida Arna Fariza Arya Brahmanta Arya Brahmanta, Arya Ashadi, Imam Asmarany, Anja Aulia Dwi Maharani Aulia, Fira Bagus Nugraha Deby Ariyadi Bambang Sumantri Bambang Sumantri Catoer Ryando Dadet Pramadihanto Dadet Pramadihanto Dadet Pramadihanto Daffa, Muhammad Fariz Dewanto, Raden Sanggar Dewi Mutiara Sari Djoko Purwanto Endra Pitowarno Fadhillah, Excel Daris Ferry Astika Saputra Fikri Aulia Fikri Aulia Fildzah Aure Gehara Zhafirah Fithrotul Irda Amaliah Gunawan, Agus Indra Gunawan, Agus Indra Hamida, Silfiana Nur Hary Oktavianto Hozumi, Naohiro Hozumi, Naohiro Huda, Achmad Thorikul Huda, Achmad Torikul Husein Aji Pratama Idris Winarno Idris Winarno Ihwan Dwi Wicaksono Ilham Iskandariansyah Imam Ashadi IMANUDDIN, ACHMAD ILHAM Insivitawati, Era Iwan Syarif iwan Syarif Jun Miura, Jun Junaedi Ispianto Kamaluddin, Muhammad Wafiq Kevin Apriandy Kisron Kisron Linda Indrayanti Lusiana Lusiana M Udin Harun Al Rasyid, M Udin Harun Makarim, Ahmad Fauzi MARTINI, NI PUTU DEVIRA AYU Meiyanto, Onie Mohamad Walid Asyhari Mohamad Walid Asyhari Muhammad Abdul Haq Muhammad Anwar Sanusi Muhammad Faiz Oskar Natan Prastika, Edo Bagus Prastika, Edo Bagus Pratama, Ariesa Editya Prianto, Chandra Edy Prianto, Chandra Edy Prima Kristalina Puspasari Susanti Rabbani, Fahmi Muhammad Rabbani Rachmawati, Oktavia Citra Resmi Raden Sanggar Dewanto Ricky Afiful Maula Rifqi Amalya Fatekha Rika Rokhana Riyanto Sigit Riyanto Sigit, Riyanto Romadhon, Nur Rizky Rudi Kurniawan Sanusi, Muhammad Anwar Sesulihatien, Wahjoe Tjatur Setia, Siaga Whiky Setiawardhana Setiawardhana Setiawardhana Setiawardhana Setiawardhana, Setiawardhana Sholahuddin Muhammad Irsyad Sigit Riyanto Susanti, Puspasari Taufiqurrahman Taufiqurrahman Tessy Badriyah Tessy Badriyah, Tessy Tita Karlita Tita Karlita Titon Dutono Tri Harsono Tri Harsono ULURRASYADI, FAIZ Wahjoe Tjatur Sesulihatien Wahjoe Tjatur Sesulihatien Wibowo, Iwan Kurnianto