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IDENTIFIKASI CITRA DAGING AYAM BERFORMALIN MENGGUNAKAN FITUR WARNA HUE SATURATION VALUE (HSV) DAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) Siti Nurhalisa, Waode; Mashur Sajiah, Adha; Adi Saputra, Rizal
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12444

Abstract

Sulawesi Tenggara merupakan salah satu provinsi penghasil daging ayam di Indonesia. Menurut data BPS, produksi daging ayam di Sulawesi Tenggara pada tahun 2023 mencapai 11.535.209 kg, meningkat 4,32% dari tahun 2021 sebesar 11.053.353 kg. Namun, isu penggunaan formalin pada daging ayam memerlukan solusi deteksi yang cepat, akurat, dan mudah. Salah satu alternatif alami, kertas tumerik dari cairan kunyit, meski ekonomis, hanya berfungsi sebagai kontrol positif dan negatif, sehingga kurang akurat. Penelitian ini bertujuan mengembangkan sistem identifikasi citra daging ayam berformalin menggunakan fitur warna Hue Saturation Value (HSV) dan algoritma K-Nearest Neighbor (K-NN). Proses deteksi meliputi pemasukan citra, pra-pemrosesan, ekstraksi ciri RGB ke HSV, pelatihan K-NN, dan identifikasi citra. Hasil pengujian menggunakan 150 citra daging ayam berformalin dan 150 citra tanpa formalin menunjukkan akurasi sistem sebesar 93,79%, dengan True Positive (TP) 145, False Negative (FN) 5, False Positive (FP) 4, dan True Negative (TN) 146. Nilai metrik meliputi Precision 97,32%, Recall 96,67%, Specificity 97,33%, Accuracy 97% dan F1-Score 96,99%. Sistem ini menunjukkan potensi sebagai metode deteksi formalin yang efektif dan andal.
IDENTIFIKASI KUALITAS IKAN CAKALANG SEGAR BERBASIS CITRA MATA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) DENGAN FUNGSI KERNEL RADIAL BASIS FUNCTION Adiningsi, Sri; Pramono, Bambang; Mashur Sajiah, Adha; Adi Saputra, Rizal
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12641

Abstract

Sulawesi Tenggara, yang mengalami peningkatan potensi perikanan dari 11,25% pada 2019 menjadi 11,60% pada 2021, memiliki kontribusi besar dalam komoditas seperti cakalang, dengan tangkapan sebesar 21.868 ton senilai Rp 501 miliar. Namun, tantangan utama yang dihadapi adalah jaminan mutu dan kualitas ikan untuk mempertahankan kepercayaan konsumen. Proses pendeteksian kesegaran ikan, yang umumnya dilakukan secara manual melalui indera manusia, menjadi tidak efektif untuk volume besar karena memakan biaya dan waktu yang tinggi. Penelitian ini bertujuan mengimplementasikan metode Support Vector Machine (SVM) dengan Kernel Radial Basis Function untuk mendeteksi kualitas ikan segar dan tidak segar berdasarkan citra mata ikan. Dataset yang digunakan sebanyak 1.830 citra, terdiri dari 1.050 citra ikan segar dan 870 citra tidak segar, yang dibagi 80% untuk pelatihan dan 20% untuk pengujian. Model yang dibangun mencapai akurasi sebesar 92,8% dan f1-score 93,4% berdasarkan confusion matrix. Pengujian menggunakan K-Fold Cross-Validation (K=10) menghasilkan akurasi tertinggi sebesar 94,54% dengan deviasi standar 1,69, menunjukkan kestabilan dan keandalan model. Hasil penelitian ini mendukung penerapan sistem deteksi otomatis berbasis citra mata ikan sebagai alat yang efisien dan akurat untuk menilai kualitas ikan, serta dapat meningkatkan daya saing produk perikanan di pasar global.
Klasterisasi Wilayah Kabupaten Di Sulawesi Tenggara Berdasarkan Produksi Bahan Pangan Menggunakan Algoritma K-Means Clustering Sawal, Mur; Saputra, Rizal Adi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i2.10437

Abstract

Bahan pangan merupakan bahan – bahan yang diproduksi dari hasil pertanian yang digunakan untuk membuat makanan .Bahan pangan tersebut terdiri dari sayuran , daging , kacang , ubi, dan lain sebagainya. Provinsi Sulawesi Tenggara menjadi salah satu provinsi yang memiliki jumlah produksi bahan pangan yang cukup tinggi di Indonesia . Penerapan algoritma K-Means clustering digunakan untuk mengelompokan wilayah kabupaten/kota yang ada di Sulawesi Tenggara berdasarkan hasil produksi bahan pangan. Metode yang digunakan dalam penelitian ini adalah CRISP-DM dengan algoritma K-Means clustering. Terdapat 17 kabupaten/kota di Sulawesi Tenggara yang digunakan dalam penelitian ini . Jenis bahan pangan yang akan digunakan dalam penelitian ada 7 yaitu padi , jagung , ubi kayu , ubi jalar , kacang tanah , kacang kedelai , dan kacang hijau . Hasil dari penelitian ini adalah 1 kabupaten/kota yang memiliki tingkat produksi bahan pangan yang tinggi , 4 kabupaten/kota memiliki tingkat produksi bahan pangan yang sedang , dan 12 kabupaten/kota yang memiliki tingkat produksi bahan pangan yang rendah. Hasil pengujian menggunakan Davies bouldin index adalah cluster 2 yang mempunyai kualitas cluster yang terbaik karena hasil yang didapat dari cluster 2 yaitu 0.30 yang dimana semakin kecil hasil yang didapatkan maka semakin baik clusternya.
Development of Anti-UAV System Using Visual Artificial Intelligence Sembiring, Javen; Prianggoro, Dimas; Saputra, Rizal Adi; Tarkono, Tarkono; Ummah, Khairul
International Journal of Aviation Science and Engineering - AVIA Vol. 5 No. 1: (June 2023)
Publisher : FTMD Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v5i1.83

Abstract

Unmanned Aerial Vehicles (UAV) was first developed as a tool for military purposes. Due to the rapid growth in technology, UAVs are now used in various applications including civil needs. Of course, there are consequences for this where UAVs can be misused by irresponsible parties. One example is the use of UAVs in airport fields which can disrupt the airport operations and possibly become a serious threat towards security and safety of flights in the airport. This paper will discuss the artificial intelligence (AI) modeling to detect UAVs. This AI modeling is the first step in designing counter unmanned aerial system (C-UAS). UAV detection will use deep learning using YOLOv4 (single-stage detection) for optimal detection speed and accuracy. There are a total of 500 image data processed and used in two AI modeling experiments in this study. Gaussian blur filter is used to create dataset variations so that the training can be processed more efficiently and the model can detect better. The results shows that the training dataset that has been processed with gaussian blur (filtered dataset) increases the AI model’s detection performance in rainy and clear conditions. Therefore, the model trained using filtered datasets is more suitable for use in detecting UAV objects in anti-UAV systems.
Aircraft Detection in Low Visibility Condition Using Artificial Intelligence Ummah, Khairul; Widyosekti, M. Dhiku; Arif, Yanuar Zulardiansyah; Saputra, Rizal Adi; Riszal, Akhmad; Sembiring, Javensius
International Journal of Aviation Science and Engineering - AVIA Vol. 5 No. 1: (June 2023)
Publisher : FTMD Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47355/avia.v5i1.84

Abstract

Bad weather often interferes with the functioning of the air transport system. One example is the frequent flight delays for commercial aircraft, resulting in losses for both the airline and passengers. Artificial Intelligence (AI) technology can now minimize delays caused by bad weather, especially in low visibility conditions. This paper discusses AI modeling that can detect aircraft in a low visibility weather condition, especially in the airport area. The employed method is the deep learning approach with the YOLOv4 algorithm (single-stage detection), which is regarded as one of the optimal platforms in this field. There are 600 images used in this work to create and train three different models. Image Dehazing filter is employed on the training data before it is trained to produce the detection model. The result shows that the model has a good performance in terms of performance metrices. Thus, this model is suitable to be used to detect aircraft in low visibility conditions.
Segmentasi Kematangan Pisang Raja Berbasis Fitur Warna HSV Menggunakan Metode KNN Aliansa, Warham; Ifayatin, Hadijah Nisa; Saputra, Rizal Adi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.669

Abstract

Taxonomically, the banana tree belongs to the Family Musaceae and the Genus Musa. The most widely cultivated species or type of banana worldwide is the wild banana. The ripeness classification of Raja bananas can be obtained through two methods: destructive and non-destructive. Destructive classification is performed through chemical analysis, but it can only be done by destroying the banana. On the other hand, non-destructive classification for Raja bananas can be done by observing the texture and color of the banana peel, which is the outermost part of the fruit, without the need to taste the flesh or peel it, thus keeping the fruit intact. In the classification of king bananas into three ripeness stages: unripe, ripe, and overripe, 150 test data and 15 training data are used. The HSV color feature is employed using the K-Nearest Neighbors (KNN) classification method with the assistance of MATLAB R2021a software, achieving 100% accuracy
Segmentasi Pada Plat Kendaraan Dinas dengan Metode Deteksi Tepi Canny, Prewitt, Sobel, & Roberts Saputra, Rizal Adi; Reskal, R; Wahyuni, Frida Mimi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.448

Abstract

In this day and age, technology is getting faster, making knowledge more advanced. Many people conduct research using various methods. With so many methods available, many will increasingly wonder which method to use. The author compared the official license plates using the Canny, Prewitt, Sobel, and Roberts edge detection methods. Segmentation is one of the important steps that can be used in the Number Plate Recognition system. Vehicle number plate segmentation is performed to compare four different edge detection methods, each with advantages and disadvantages. The samples we used were 28 test images consisting of 14 images at a distance of 1 meter and 14 images at a distance of 2 meters. From the test results using the canny, prewitt, sobel and roberts edge detection methods, the number of data tested is 28 images. The result is that the canny edge detection method is more accurate than the Prewitt, Sobel and Roberts edge detection method in segmenting official vehicle license plates.
Segmentasi Kematangan Pisang Raja Berbasis Fitur Warna HSV Menggunakan Metode KNN Aliansa, Warham; Ifayatin, Hadijah Nisa; Saputra, Rizal Adi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.669

Abstract

Taxonomically, the banana tree belongs to the Family Musaceae and the Genus Musa. The most widely cultivated species or type of banana worldwide is the wild banana. The ripeness classification of Raja bananas can be obtained through two methods: destructive and non-destructive. Destructive classification is performed through chemical analysis, but it can only be done by destroying the banana. On the other hand, non-destructive classification for Raja bananas can be done by observing the texture and color of the banana peel, which is the outermost part of the fruit, without the need to taste the flesh or peel it, thus keeping the fruit intact. In the classification of king bananas into three ripeness stages: unripe, ripe, and overripe, 150 test data and 15 training data are used. The HSV color feature is employed using the K-Nearest Neighbors (KNN) classification method with the assistance of MATLAB R2021a software, achieving 100% accuracy
Segmentasi Pada Plat Kendaraan Dinas dengan Metode Deteksi Tepi Canny, Prewitt, Sobel, & Roberts Saputra, Rizal Adi; Reskal, R; Wahyuni, Frida Mimi
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.448

Abstract

In this day and age, technology is getting faster, making knowledge more advanced. Many people conduct research using various methods. With so many methods available, many will increasingly wonder which method to use. The author compared the official license plates using the Canny, Prewitt, Sobel, and Roberts edge detection methods. Segmentation is one of the important steps that can be used in the Number Plate Recognition system. Vehicle number plate segmentation is performed to compare four different edge detection methods, each with advantages and disadvantages. The samples we used were 28 test images consisting of 14 images at a distance of 1 meter and 14 images at a distance of 2 meters. From the test results using the canny, prewitt, sobel and roberts edge detection methods, the number of data tested is 28 images. The result is that the canny edge detection method is more accurate than the Prewitt, Sobel and Roberts edge detection method in segmenting official vehicle license plates.
The Effect of Sintering Temperature on The Adhesion Quality of Hydroxyapatite on Porous Tantalum for Cancellous Bone Implant Application Saputra, Rizal Adi; Sukmana, Irza; Tarkono; Sugiri, Agus; Syazwani, Nur; Djuansjah, Joy
Jurnal Inovasi Teknologi Vol 5 No 2 (2024): October
Publisher : Engineering Forum of Western Indonesian Government Universities Board (Forum Teknik, BKS-PTN Wilayah Barat) Indonesia

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

Abstract

Porous tantalum has been recently recognized as a conventional orthopedic implant for bone substitute applications besides stainless steel, cobalt-chromium, titanium, and other metallic alloys. Porous tantalum has excellent mechanical and osseointegration properties similar to cancellous bone structure. To optimize the utilization, the dip coating technique was applied to coat porous tantalum with hydroxyapatite (HA). X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques investigate the coating characterization. HA is a bioceramic material that used for bone substitutes due to its chemical and structural similarity to bone minerals. Coated porous tantalum requires the sintering process of porous tantalum to adhere to HA. During the sintering process, various temperatures (650°C, 750°C, 850°C, 950°C, and 1100°C) were used to determine the optimum temperature for porous tantalum coated with HA. The heating rate is 1°C/1 min and the holding time is 60 minutes. The result shows that the optimum temperature of HA-coated porous tantalum is at 850°C. The morphology structure of the HA-coated porous tantalum shows that the adhesion between porous tantalum and HA is in good condition. The element in the HA-coated porous tantalum shows that the existence of HA is high.
Co-Authors , Jumadil Nangi -, Findriyani -, Safal A.Yudi Eka Risano Ababil Azies Sasilo Abbas, Muhammad Akram Abdillah, Muh Ade Sitti Nur Zainab Adha Mashur Sajiah Adiningsi, Sri Afifah Hakim, Auliyah Agsaria, Fabelina Agus Sugiri Agus Sugiri, Agus Ahmad Fadli Ramadhan Ahmad Fadli Ramadhan Ahmad Riszal Ahmad Sipa, Alfriyanti Akmal Rahman Aksara, L.M. Bahtiar Akyar, Faisal Al Qadri, Muhammad Vannes Algazali, Muhammad Aliansa, Warham Alma Fisabillah Amaliya Nurani Basyarah Andi Juliardi Abdillah Andi Maghfirah Parenrengi, Andi Maghfirah Andi Tenriawaru Angga Darma Prabowo Anisa suci Pratiwi Anshari, Erwin Anwar, Syaipudin Apriansyah, Muhammad Fiqih Aprilyani S, Lily Arif, Yanuar Zulardiansyah Arif, Zainal Arifin Kusumo Wicaksono Arinal Hamni Asa Hari Wibowo Asa Hari Wibowo, Asa Hari Asdar Asdar Asdar Asri Wido Mukti Asriani, Risky Nur Asrumin Asti Rahayu Asti Rahayu Auliya Afifah Adnan Hakim Awaliah, Wd. Rizky Ayu Pratiwi Ndibola Ayu, Nurfatzma Az'zahra Tarimana, Annisa Azriel Saktiawan, Muhammad Badarudin, Ade Syifa Bagus Rifaldi Bambang Pramono Bambang Pramono Bambang Pramono Bambang Pramono Billa, Nabilla Salsa Billah, Khaerunni Salsa Chintya Mawadhah Sumitro Chintya Mawadhah Sumitro Dewi Perwito Sari Dewi Titania Randa Diah A.P, Zahwa Dian Trianita Lestari Dilla, Farah Dini Fadilah Djuansjah, Joy Djuansjah, Joy R P Dwi Tsunami, Widya Dwina Angelina Sipayung Edi Syah Mihrad Eko Wahyu Saputra Eko Yohanes Elfiani Eriyadi, Riko Ermila Ermila Etrilian Tongalu Fa, Nur Fadhilah, Ghefira Zahra Nur Fadilah, Muh. Bayanudin Fahrul Ardian Nugroho Fani Fadilah fauzi, fitya aulia Fazilah, Nurul Febryanti, Wa Ode Ika Fifi Nirmala G Fildzah Khalishah Ghassani Findry, Findriyani Florencia Virgiane Evalyn Padang Ghefira Zahra Nur Fadhilah Gusti Putu Pupaningrum Hadi Prayitno Hafiizah, Nur Hardani, Prisma Trida harnelia, harnelia Harnowo Supriadi, Harnowo Hashimatul Zaria Hasna Anggin Tri Muslimin Hassanah, Waode Siti Nurul Hayara Octaviani Hendriyanto, Agus Herlambang, Ian Herry Wardono HERU WAHYUDI Hidayat, Wahyu Al Hidayatunnikmah, Nina Hidjriani Ibrahim, Fauzi Ifayatin, Hadijah Nisa Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum Ika Purwanti Ningrum, Ika Purwanti Ikhwanul Uzlah, Laode Iklil Awalda Tariza Inda Asriyanti Lauto Indri Indri Indriyani Nur Indriyani Nur Intan Ayu Kusuma Pramushinta Ira Purbosari Irsyad, Akhmad Irza Sukmana Irza Sukmana, Irza Ishak Jaelani, Muhammad Isnawaty Isnawaty Isnawaty Isnawaty Isnawaty Isnawaty, Isnawaty Iza, Abdillah Javensius Sembiring, Javensius Jayanti Yusmah Sari Jelyzer Patanan Judanto, Nurendro Hardjo Jumadil Nangi Jumadil Nangi Jumadil Nangi Jumadil Nangi, Jumadil Kaimuddin, Sitti Mikarna Kasim, Nurdian Kayla, Mutmainnah Putri Khairul Ummah Khamil, Muhammad Raihan Putra Khrysna Dwipangga, Ageng Arya Kurniawan, Dondi L.M. Bahtiar Aksara L.M. Fid Aksara, L.M. Fid La ode Muhammad Bahtiar Aksara La Ode Rahmat Andre Pratama La Ode Santiaji Bande La Ode Sukriman La Ode, Abdul Azis Syah La Surimi La Surimi La Surimi La Surimi, La Lestari, Dian Trianita Lestari, Yunda Puji Lily Aprilyani Linda Saputri LM Tajidun LM Tajidun, LM M. Rangga Saputra Maharani Hasan, Puspita Mahruri Arif Wicaksono Marni Mulyani Marsita Harim Martinus Martinus, Martinus Mashur Sajiah, Adha Maulivia Idham Choliq Mayang Putri Khairunnisa Mihrad, Edi Syah Mochammad Imron Awalludin Mochammad Resha Mubaraq, Muh. Falah Muh. Ikbal, Muh. Muhaimin Hamzah Muhaimin Hamzah Muhaimin Zain, Al MUHAMAD FADLI Muhamad Faza Almaliki Muhamad Handoyo Sahumena Muhamad Handoyo Sahumena Muhamad Ilham, La Ode Muhamad, Ngawal Muhammad Abdillah Rahmat Muhammad Ikhwan Muhammad Irsyad Muhammad Nabil Afkar Muhammad Ricky Aryansah. B Muhammad Yusril Muhammad, Zahir Mundeh, Marianne Mursalim Mursawal, Mursawal Mustarum Musaruddin Mutmainnah Muchtar Mutmainnah Putri Kayla Nabila Saskia Arham nabilla, putri Nadaa Qur’atul‘Ain Nadya Ambarwati Nadya Elfareta Azarin Nafrizal Natalis Ransi Natalis Ransi, Natalis Nathania, Meutya Nazarrudin, Rizal Ni Made Sri Ulandari Ni Wayan Erdiani Ningrum, Ika Purwati Ningsih, Lilis Sugi Nono Satria Noviana Saputri, Kiki Nugraha, Nurcahya Nur Fadillah, Nur Nur Rahma Sela Nur, Indriyani Nurhafni A, Syarifah Nurhafni Ahmad, Syarifah Nurmaladewi Nurmaladewi Nurmaladewi, Nurmaladewi Nurtiani, Devy Natalia Ode Yamin Arsy Fadillah Mbota, La Panaungi, Fajar Pratiwi Aprilya Wahid, Dwi Prianggoro, Dimas Purbosari, Ira Putri Arafa, Ninis Putriani, Ananda Putu Arimbawa Putu Arimbawa Putu Arimbawa, Putu Qubra, Rama Rafi Iyad Madani Chaidir rahayu ningsih, Lilis sugi Rahma Basri, Siti Rahmad Akbar Rahman, Nur Syazwani Binti Ab Rahmat Hidaya Karismadi, Nur Rahmat Karim Rahmat Saputra, La Ode Alvin Raiya, Muhammad Saharullah Ramadana, Alvianto Ramadhan, Abdul Fath Ramadhan, Muh. Akbar Perdana Ramadhan, Muhammad Afin Ramadhani, Annisa Auliya Ramadhani, Dwi Hikmah Ratnasari Ratnasari Rayadin, Muhamad Amhar Reskal, R Resti Ajeng Sutiani Rifaldi, Dwi Rina Rina Riofasesi, Daffa Risano, Yudi Eka A Riskan Riszal, Akhmad Rizaldy Setiawan Hasanuddin Rizkah Nurhasanah Rizki Eka Sakti Octaviani Roy Pane Ryan Septian Fajar, Muhammad Sabiqunassabiqun Sahera, Nelti Juliana Saleh Badawi, Muh Samudin, Ayustina Saputra, Eko Wahyu Saputra, Muh. Farhan Saputri, Shinta Arjunita Sari, Dewi Perwito Sarita, Ihsan Saudi, Septiyani Bayu Sawal, Mur Sembiring, Javen Shinta Arjunita Saputri Shirley Savetlana Shirley Savetlana, Shirley Silfi, Silfi Siti Nurhalisa, Waode Sitti Aisyah Sri Adiningsi SRI ADININGSI ERNI ALBAKIA Sri Ayu Ningsih Srikandi, Raya Statiswaty Subardin Subardin Suci Oktavia Rahmadani SUGIYANTO Sugiyanto - Sulastri Apridayanti Sultrayansa Sumarni Sumarni Sumitro, Dewi Sari Suria, Fellonnisa Suryadiwansa Harun Sutardi Sutardi Sutardi Sutardi Sutiyana Fachruddin Syahidatul Islamiyah Syam, Nurhana Syazwani, Nur Tarkono Tarkono Tarkono Thalib, La Ode Jafar Umar Trihapsari, Argitha Tunda, Amin Usman, Yusril Wa Ode Ika Febryanti Wa Ode Yatni Yansari Wahyuni, Frida Mimi Waode Siti Nurul Hassanah Weka Gusmiarty Abdullah Weka GUSMIARTY ABDULLAH Weka Gusmiarty Abdullah, Weka Gusmiarty Wibowo, Bayu Adi Wicaksono, Mahruri Arif Widyosekti, M. Dhiku Wildayanti Yanuar Burhanuddin Yolanda Camelia Imelda Yunda Puji Lestari Yurika Sastyarina Yurika Sastyarina Yusup Hendronursito, Yusup Yuwanda Purnamasari Pasrun Zahro Al Maulidiyah Zulhanif Zulhanif, Zulhanif