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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Informatika Pertanian Techno Nusa Mandiri : Journal of Computing and Information Technology ILKOM Jurnal Ilmiah KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) METIK JURNAL Jurnal Informatika Kaputama (JIK) Jurnal Mantik Jusikom: Jurnal Sistem Informasi Ilmu Komputer Mulia International Journal in Science and Technical JATI (Jurnal Mahasiswa Teknik Informatika) Science Midwifery JUKI : Jurnal Komputer dan Informatika Jurnal Sistem Informasi dan Sains Teknologi Jurnal Teknik Informatika (JUTIF) Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Arsitekno Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer Jurnal Tika Multica Science and Technology Andalasian International Journal of Applied Science, Engineering, and Technology Mejuajua Brilliance: Research of Artificial Intelligence AJAD : Jurnal Pengabdian kepada Masyarakat TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi International Review of Practical Innovation, Technology and Green Energy (IRPITAGE) Jurnal Ilmu Gizi dan Dietetik Journal Of Artificial Intelligence And Software Engineering Jurnal Malikussaleh Mengabdi Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Jurnal Solusi Masyarakat Dikara The Indonesian Journal of Computer Science Asian Journal of Science Education
Mutammimul Ula
Universitas Malikussaleh
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Implementasi Logika Fuzzy Dalam Optimasi Jumlah Pengadaan Barang Menggunakan Metode Tsukamoto (Studi Kasus : Toko Kain My Text) Teknik Informatika, Universitas Malikussaleh, Lhokseumawe, Aceh Utara, Mutammimul Ula,
JURNAL ILMIAH “ECOTIPE” JURUSAN TEKNIK ELEKTRO - FAKULTAS TEKNIK UNIVERSITAS BANGKA BELITUNG Vol 1, No 2 (2014): Jurnal “Ecotipe” Jurusan Teknik Elektro Fakultas Teknik Universitas B
Publisher : Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5.685 KB)

Abstract

Optimasi jumlah pengadaan barang dilakukan dengan menggunakan tiga variabel, yaitu penjualan, persediaan dan pengadaan. Variabel penjualan terdiri dari dua himpunan fuzzy, yaitu : turun dan naik, variabel persediaan terdiri dari dua himpunan fuzzy, yaitu : sedikit dan banyak, sedangkan variabel pengadaan  terdiri dari dua himpunan fuzzy, yaitu berkurang dan bertambah. Dengan mengkombinasikan semua himpunan fuzzy tersebut, diperoleh empat aturan fuzzy, yang selanjutnya digunakan dalam setiap inferensi. Pada tahap inferensi, dicari nilai keanggotaan anteseden (α) dan nilai optimasi perkiraan pengadaan (z) dari setiap aturan. Optimasi pengadaan barang (z) dicari dengan metode defuzzifikasi rata-rata terpusat. Analisa dengan menggunakan metode Tsukamoto menghasilkan kondisi optimum pengadaan barang mencapai 38 kain/bal, ini mendekati perhitungan yang dihasilkan oleh Toko My Text tanpa menggunakan metode Tsukamoto, yaitu 35 kain/bal. Analisa dengan menggunakan metode Tsukamoto ini memperlihatkan kondisi rill yang harus dijalankan pihak penjual barang di Toko My Text dalam melakukan proses pengadaan barang supaya lebih tepat sasaran. Kata kunci : Optimasi, Barang, Fuzzy, Metode Tsukamoto
IMPLEMENTASI SISTEM PAKAR PADA PASIEN PENDERITA TUBERKULOSIS POTENTIAL DROP OUT DI RUMAH SAKIT CUT MEUTIA ACEH UTARA Darnila, Eva; Ula, Mutammimul; Mauliza, Mauliza; Ermatita, Ermatita; Pahendra, Iwan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.968

Abstract

The existence of a technology that identifies and controls patients with potential drop out TB disease which is increasingly rapid will be a top priority, especially for the health team in following up the success of treatment. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis by using a Case Based Reasoning model to see patients with potential Droup Out. For variable names used are pulmonary smear patients (+), new patients, pulmonary smear (-) / ro (+), new patients, extra pulmonary, relapsed patients, re-treatment, default patients, re-treatment patients, failed patients and others -other. The last detection process is taken from the highest value obtained in the diagnosis of all the symptoms that have been witnessed. Based on the results of the application of the Expert System on Potential Drop Out Tuberculosis Patients at Cut Meutia Hospital in North Aceh based on the case code 31 with a detection system for the AFB (+) Lung Patient with its detection symptoms, the patient coughs with phlegm for 2-3 weeks or more. the results of sputum examination, patients who have been treated with TB drugs less than 1 month and TB patients on sputum examination, patients who have been treated with TB drugs less than 1 month, TB patients stop the treatment and TB patients return to the facility health service facilities with the highest case value of 0.6111 of all detection systems that have been tested.Keywords: Expert system,  CBS, TB
Expert System Technology in Implementation of K-Means Clustering Algorithm in Patients with Tuberculosis at Cut Meutia Hospitals North Aceh Eva Darnila; Mutammimul Ula; Mauliza; Iwan Pahendra; Ermatita; Hardi, Richki
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

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Abstract

Technology in detecting potential drop out tuberculosis (TB) in Cut Meutia hospital and Health Office plays a great role and has been very important. This is seen from the increasing number of patients who could not be cured succesfully and who do not care about TB which will have fatal consequences on their health. In addition, the main cause of the increase in the number of potential drop out TB patients is because of the lack of awareness of the community, especially the middle economic level family of the danger of TB disease as seen from the irregular treatment that they have and the continued smoking habit. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis who were then diagnosed into the cluster of each TB patient using the K-Means algorithm. The system implementation in the expert system is that the initial symptoms include the question of whether the patient has cough with phlegm for 2-3 weeks or more (yes), has the patient been treated with TB drugs less than 1 month (no), experienced no appetite and nausea. From the results of these symptoms, there are diagnoses of New Patients, Pulmonary BTA (-) / Ro (+), with sub-acute level having moderate severity and duration, the severity can reduce the health status of the patient, the patient is eventually expected to recover and totally recovered the disease does not develop into a chronic disease. The results of this expert system would be entered into the K-Means clustering. The test results of the k-means clustering algorithm with K = 3 (C1, C2, C3). with initial centroid values of m1: C1, 5, 5, 5, 5, 5, 5 and m_2: C2, 3, 3, 3, 3, 3, with patient p1 with the value of each cluster (C1) = 6.928, ( C2) = 2.828, C3 = (4). For the closest cluster value is C2, then the BCV (Between Cluster Variation) calculation value is 19,596, and the WCV (Within cluster Variation) value is 144. Then the ratio value is 0.136. The result of the iteration -3 can be stopped because it does not experience the movement of the clusters and the clusters have been optimal. The results of this system can classify patients for each village and sub-district area so that the Hospital officials and the Health Office can directly monitor potential drop out TB patients and can facilitate the Head of Office/region in handling clustered TB patients using K-Means. Furthermore, in the coming years, it can be used as a tool in taking preventive measures.
Implementation of Clustering K-Means Algorithm classification of the need of Electricity power for each region at PT Lhokseumawe Muhammad Sadli; Wahyu Fuadi; Fajriana; Ermatita; Iwan Pahendra; Mutammimul Ula; Hardi, Richki
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

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Abstract

PLN (State Electricity Company) is in charge of providing stock of needs for the grouping of electrical power and classification for each region in Lhokseumawe City. The area that were grouped based on the amount of power consists of the four subdistricts, namely Banda Sakti, Blang Mangat, Muara Dua and Muara Satu, each of which is sourced from the village. The importance of clusters is to separate each data between data in the villages that will be input into sub-district data. Furthermore, the K-Means Clustering Classification was used in determining the grouping of electrical power needs in each region in the Lhokseumawe City where this system classify the electricity stock needs in each region categorized into a cluster. In this study, Clustering Classification of K-Means variables include job (V1), overall income (V2), house area (V3), number of rooms (V4), number of electronic equipment (V5) and total of power usage (V6). Results of grouping of C1 system = Subsidy R-1/450 VA, C2 = Subsidy R-1/900 VA, C3 = Non Subsidy R-1/900, C4 = Non Subsidy R-1/1300, C5 = Non Subsidy R- 1/2200 VA. The purpose of this study is to be able to predict the classification of each electric power requirement for each region based on the input data per district. This has an impact on the community and PLN's stock of electricity needs in order to remain stable. It is found out from the Clustering K-Means Classification that there is a new cluster for Banda Sakti. The last step in determining Clustering K- Means stopped at the the iteration 3 until the cluster is optimal. The results of this study are in the form of grouping of PLN Customers from each region displayed in the system in the form of classification of electrical power in each subdistrictdistrict. Furthermore, the grouping can be recommended to predict the power needs of each sub-district and belong to the cluster provided by the PLN.
Implementation of K-Modes Clustering in Predicting Electric Power Needs in Aceh Ula, Mutammimul; Hardi, Riyadhul Fajri; Hardi, Richki
Mulia International Journal in Science and Technical Vol 1 No 1 (2018): August
Publisher : Universitas Mulia

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Abstract

The State Electricity Company is tasked with providing a stock of electricity power grouping requirements and classification of classifications for each region in the city of Aceh. The area to be grouped is based on the amount of power consisting of four sub-districts namely Banda Sakti, Blang Mangat, Muara Dua and Muara Satu, each of which comes from Gampong. The importance of clusters to separate each data between gampong data that will be entered into each sub-district. Furthermore, the K-Means Clustering Classification is used in determining the grouping of electric power needs in each region in Aceh City, where the system classifies the electricity stock requirements in each region categorized into a clustering.
Introduction to the Map of Indonesia using interactive animation design in multimedia-based elementary schools Fathia; Mutammimul Ula; Riyadhul Fajri; Asmawi
Mulia International Journal in Science and Technical Vol 1 No 2 (2018): December
Publisher : Universitas Mulia

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Abstract

The use of technology automatically will provide convenience in the delivery of information. In this research, the use of technology can be done using animation to help and increase students' interest in participating in a more efficient learning process. This is done because some of the material learned is sometimes boring for students, especially in learning Geography science learning materials, even today students are less interested in studying Indonesian maps, because at this time the teacher only provides explanations through manual books and immovable drawings, in addition to lack of means and other information media such as pictures and encyclopedias supplied at school. From this problem, the author will research the design of interactive animations in the introduction of Indonesian state maps for multimedia-based school students. The software used in this research is Adobe Professional, Adobe Photoshop, and Wondershare Filmora. The method used in this study is a qualitative method, which is a research method that is more focused on the situation or phenomenon under investigation.
Realistic Texturing pada Objek 3-dimensi Menggunakan Model Tehnik Texture Mapping Ula, Mutammimul
Arsitekno Vol 6, No 6 (2015): Jurnal Arsitekno
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/arj.v6i6.1217

Abstract

Abstrak Tekstur merupakan karakteristik penting dari penampilan objek dalam pemandangan alam, dan merupakan syarat kuat dalam persepsi visual. Pemahaman tekstur merupakan bagian penting dari memahami visi manusia. Pada  objek 3-dimensi pemberian tekstur merupakan hal yang harus dilakukan agar objek terlihat lebih realistis. Maps berwujud gambar tekstur 2D dituangkan ke permukaan geometri/objek untuk membuat penampilan objek tersebut tampak halus untuk detail permukaannya. Pada pengembangan grafik realisme tingkat tinggi diperlukan lebih banyak lapisan tekstur, agar hasil mapping mendekati kesempurnaan. Sebuah tekstur maps yang diterapkan (dipetakan) biasanya dipakai untuk permukaan bentuk objek polygon, proses ini mirip dengan menerapkan texture pada kertas berpola kotak putih yang polo. Pada penelitian ini proses pemberian teksture pada objek 3-dimensi meliputi lantai, furniture dan gedung. Tekture yang digunakan didapat dari mengambil dari photo objek tersebut dalam dunia nyata.Kata Kunci: texturing, texture mapping,3-dimens,
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN JENIS TANAH YANG SESUAI UNTUK TANAMAN PANGAN MENGGUNAKAN METODE SMARTER DAN SAW Nurdin, Nurdin; Fahrozi, Fazar; Ula, Mutammimul; ., Muthmainah
Informatika Pertanian Vol 29, No 2 (2020): DESEMBER
Publisher : Sekretariat Badan Penelitian dan Pengembangan Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/ip.v29n2.2020.p83-94

Abstract

Lahan atau tanah merupakan sumber daya fundamental yang dimiliki manusia. Dengan adanya lahan, manusia dapat menghasilkan bahan pangan, sandang, papan, tambang, dan tempat dilaksanakannya berbagai aktivitas. Di satu sisi, kebutuhan lahan untuk pertanian terus meningkat. Di sisi lain, lahan subur makin terbatas karena digunakan untuk berbagai keperluan selain pertanian. Selain itu, petani umumnya kesulitan menentukan jenis tanaman yang tepat diusahakan pada tanah yang dimiliki. Penelitian ini bertujuan untuk menentukan jenis tanah yang sesuai bagi tanaman pangan menggunakan metode Simple Multi Attribute Rating Technique Exploiting Rank (SMARTER) dan metode Simple Additive Weighting (SAW). Kriteria dan perhitungan bobot untuk metode SMARTER dan SAW adalah kesuburan tanah (W1), unsur hara tanah (W2), kelembaban tanah (W3), tekstur tanah (W4), ketebalan gambut tanah (W5), reaksi (pH) tanah (W6), dan drainase tanah (W7). Hasil penelitian penerapan metode SMARTER dan SAW menghasilkan preferensi dengan nilai tertinggi 0,824286 pada jenis tanah Andosol untuk tanaman padi.
IMPLEMENTASI PEMODELAN CITRA MODEL SVM (SUPPORT VECTOR MACHINE) DALAM PENENTUAN PENGKLASIFIKASIAN JENIS SUARA KONTES BURUNG Rosdiana Rosdiana; Mutammimul Ula; Hafizh Al Kautsar Aidilof
Jurnal Informatika Kaputama (JIK) Vol 5, No 2 (2021): Volume 5, Nomor 2 Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v5i2.566

Abstract

Penelitian ini digunakan untuk klasifikasi pemodelan dengan citra model SVM (Support Vector Machine) dalam pengklasifikasian jenis suara burung yang telah dilatih dan hasil yang didapat berupa jenis suara burung yang telah diklasifikan dengan uji latih model SVM dihasilkan. Selanjutnya proses pada pengenalan suara burung yang dilakukan secara proses otomatis penggalian dan penentuan informasi linguistik yang disampaikan oleh sinyal suara atau sirkuit elektronik. Untuk masing-masing data latih memiliki tiap-tiap sample suara yang dihasilkan memiliki nilai energi masing-masing yang dipengaruhi oleh frekuensi, amplitudo dan phasa. Nilai energi dari masing-masing sample suara itu kemudian ditetapkan sebagai suatu ciri untuk dapat dikalsifikasi dengan sample suara lainnya. Metode support vector machine berperan dalam proses pengelompokan nilai energi suatu untuk menentukan ciri dari suatu sample suara. Setelah masing-masing sample suara memiliki identitas atau ciri masing-masing, maka dilakukanlah pengklasifikasian sample suara dimana dalam penelitian ini akan ditampilkan spesies dari suara burung yang diinputkan. dalam skema identifikasi jenis burung memiliku proses dengan tahap kenel 1 proses SVM dari masing-masing input file suara dan dilakukan kekernel uji dengan proses SVM yang hasilnya fungsi mapping, hasil uji, jarak cektor ciri spesies burung dan nilai grafik scope yang di latih. Persentase keakuratan sistem grafik dengan identifikasi false dan right berdasrkan sample pelatihan yang dilakukan.
IMPLEMENTASI MACHINE LEARNING DENGAN MODEL CASE BASED REASONING DALAM MENDIAGNOSA GIZI BURUK PADA ANAK” Mutammimul Ula; Ananda Faridhatul Ulva; Mauliza Mauliza
Jurnal Informatika Kaputama (JIK) Vol 5, No 2 (2021): Volume 5, Nomor 2 Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v5i2.570

Abstract

Upaya pencegahan permasalahan stunting kepada masyarakat khususnya pada ibu-ibu dengan pemberian masukan khususnya masyarakat aceh utara akan pentingnya pemenuhan gizi pada balita agar terhindat dari stunting. Kekurangan gizi menjadi pokok permasalahan yang dialami balita di Indonesia. Peran Rumah Sakit dan Dinas Kesehatan diperlukan dalam melihat jumlah gizi buruk pada balita khususnya di Aceh. Dalam penelitian ini penting dilakukan implementasi machine learning dengan model case based reasoning dalam mendiagnosa gizi buruk pada anak dalam melihat pengelompokkan balita yang teridentifikasi stunting atau tidak dengan menggunakan teknologi system pakar Case Based Reasoning yang dimodelkan dalam dalam mesin learning yang dilihat dari data riwayat gizi yang kemudian dimasukkan kedalam model pengujian Machine Learning dalam mendeteksi gizi buruk pada balita. Hal ini dapat mengurangi stunting yang ada di setiap wilayah, gampong dan kecamatan dari tiap Puskesmas yang ada di kabupaten aceh utara. Tujuan Penelitian ini adalah Untuk mengetahui pendeteksian gizi buruk balita pada Rumah Sakit Cut Meutia Kab. Aceh Utara. Hasil penelitian ini adalah dapat mendiagnosa gizi buruk pada balita dengan menggunakan metode casedbase reasoning dan hasil sistem yang dibangun dapat digunakan sebagai acuan untuk memantau tumbuh kembangnya bayi/balita. adapun variabel yang dimasukkan adalah nama, umur balita, jenis kelamin, tinggi badan dan berat badan, kemudian machine learning mencari kasus yang terdekat untuk melihat nilai yang paling mendekati dalam problem stunting. hasil nya adalah Nilai nya adalah Similarity (x, K001) 1,00, Similarity (x, K008), 0,66Similarity (x, K010), 0,64.
Co-Authors - Fakhrurrazi -, Badriana -, Bakhtiar ., Muthmainah Abdi Zulfikri Achmad Rizal, Reyhan Ade Irfan Ade Luky Setiawan Agi Ayu Nurdianta Barus Akbar, Muhammad Zulfat Amri, Fajar Ananda Faridhatul Ulva Andik Bintoro Angga Pratama Angga Pratama Ar Razi Arief Rahman Arnawan Hasibuan Arpika, Asma Mauli Arya Wiyangga Pradana Asma Mauli Arpika Asmawi Asran Asrianda Asrianda Azhari SN Badriana, Badriana Bakhtiar Bakhtiar Bambang Suhendra Barus, Agi Ayu Nurdianta Budi Setiawan Burhanuddin Burhanuddin Burhanuddin Burhanuddin Burhanuddin Burhanuddin Bustami Bustami Bustami Cut Agusniar Cut Dewi Aida Soraya Cut Ita Erliana Dewi, Apriandini Sri Difa Angelina Edi Yusuf Adiman Elfiana Emi Maulani Eri Saputra Ericky Benna Perolihin Manurung Ermatita - Ermatita Ermatita Eva Darnila Eva Darnila eva darnila, eva darnila Ezwarsyah Ezwarsyah Fachrurrazi Fachrurrazi Fadillah, Tengku Farhan Fadliani Fadlisyah Fadlisyah Fadlisyah Fahrizal, Effan Fahrozi, Fazar Fahrozi, Mahlil Fajar Tri Tri Anjani Fajriana, Fajriana Fakhrurrazi Fakrurrazi Fakrurrazi Fakrurrazi Fasdarsyah Fathia Fauzi, Sri Wahyuni Febryanda, Inne Fidyatun Nisa Fitriana Fitriana Fitrianti, Uli Fuadi, Wahyu Fyanda, Dwi Auji Gita Perdinanta Hadi Riyadi Hafizh Al Kautsar Aidilof Harun, Rofiq Hasbi, Maulida ilham - sahputra Ilham Sahputra Ilham Sahputra Ilham Sahputra Ilham Sahputra Ilham Saputra Ilham Saputra Ilham Saputra Ilham Saputra Ilham Saputra Iramadhani, Dwi Irhamna, Ayu Irma Yurni Irma Yurni Irwansyah, Defi Iswadi Iswadi Ivan Maulana Iwan Pahendra Iwan Pahendra Iwan Pahendra Anto Saputra Juandana, Rio Adian Juniwan Ginting Laila, Dwi Nur'aini Mahdaliana, Mahdaliana Maryana Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza, Ade Mauliza, Mauliza Mochamad Ari Saptari Muarif Qumar Muhammad Abdullah Ali Muhammad Abdullah Ali Muhammad Danil Muhammad Fauzan Muhammad Ichwan Muhammad Ikhsan Muhammad Ikhwani Muhammad Muhammad Muhammad Rahmad Zainal Muhammad Rizka, Muhammad Muhammad Sadli Muhammad, Muhammad Multazam, T Mulyadi Mulyadi Munirul Ula Muthmainnah Muthmainnah Mutmainnah Mutmainnah Nadya Hayana Nasriah Nasriah Nasriah Nasriah Nayla Husna, Siti Nur Faliza Nur Hafni Nurdin Nurdin Nurfebruary, Nanda Sitti Nuri Aslami Nurmalina Nurmalina, Nurmalina Pahendra, Iwan Purba, Nur Alfi Rahma Fitria, Rahma Rahmat Kurniawan Rayhan Rahul Mutuahmi Razif Razif Renardi, Renardi Reyhan Achmad Rizal Reyhan Achmad Rizal Reyhan Achmad Rizal Ria Zulhusna Richki Hardi Ridha Maulana Ridwan Ridwan Risawandi, Risawandi Riyadhul Fajri Rizal Tjut Adek Rizal, Reyhan Achmad Rizki Putra Fhonna Rizky Putra Fhonna Rizky Putra Phonna Rizky Zuliyansyah Rosdian dian rosdian rosdian, Rosdian dian Rosdiana Rosdiana Rosdiana Rosdiana Rosya Afdelina Rozzi Kesuma Dinata Safriana Safriana Sahputra, Ilham Salahuddin Salahuddin Salahuddin Salamah Salamah Salamah Salamah Salamah Saptari, Mochamad Ari Satriawan, Ivan Sayed Fachrurrazi Sayed Fachrurrazi Setiawan, Ade Luky Shayravi Shayravi Shayravi, Shayravi Siregar, Dinda Saima Agustina Siti Aminah Siti Atikah Nabila Suheri Sujacka Retno Suriyanto Suriyanto Susanti Susanti syarifah asria nanda, syarifah asria Syibral Malasyi Syukriah Syukriah Syukriah Syukriah Tengku Farhan Fadillah Teuku Zulkarnaen Tiara Razaqa Sakinah Tsania Asha Fadilah Daulay Ulva , Ananda Faridhatul Umaruddin Usman Vera Novalia Veri Ilhadi Wahyu Fuadi Yella Cinni Ujung Yuli Asbar Yulisda, Desvina Yumna Rilasmi Said Yumna Rilasmi Said Yusniar Yusniar Zahratul Fitri Zahratul Fitri Zahratul Fitri, Zahratul Zainal Abidin Zikrina Zikrina Zul Akli Zulfikri, Abdi Zuraida Zurhijjah Zurhijjah