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All Journal International Journal of Artificial Intelligence Research Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Mantik Penusa JSiI (Jurnal Sistem Informasi) JURIKOM (Jurnal Riset Komputer) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH JOISIE (Journal Of Information Systems And Informatics Engineering) EDUMATIC: Jurnal Pendidikan Informatika Journal of Robotics and Control (JRC) Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi Jurnal Teknisi J-Com (Journal of Computer) Jurnal Algoritma Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat

Muhammad Ardiansyah Sembiring

Sekolah Tinggi Manajemen Informatika Dan Komputer Royal

Author-ID : 623335

Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences

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ANALISIS FAKTOR PREDIKSI DIAGNOSA TINGKAT SERANGAN JANTUNG MENGGUNAKAN METODE REGRESSION Sembiring, Muhammad Ardiansyah
JURNAL TEKNISI Vol 4, No 1 (2024): February 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v4i1.1800

Abstract: Heart disease, which is also known as cardiovascular, is a variety of conditions where there is narrowing or blockage of the blood vessels which can cause heart attacks, chest pain, stroke. Heart disease can occur in anyone of any age, gender, occupation, and lifestyle. In addition, heart disease cannot be cured. This condition requires careful treatment and monitoring throughout life. When this treatment fails, sufferers have to undergo surgical operations which are quite expensive and complicated. A report from WHO in September 2009 stated that this disease was the first cause of death to date. In 2004, an estimated 17.1 million people died from heart disease. This figure represents 29% of global causes of death, with details of 7.2 million people dying from heart disease and 5.7 million people dying from stroke. This can be prevented by reducing risk factors. The role of information technology can be realized by data retrieval techniques. research to shorten the time and selection of factors for early detection of heart attacks.Keywords: heart; regression; information Technology Abstrak: Penyakit jantung atau heart disease , yang juga dikenal dengan istilah kardiovaskuler adalah berbagai kondisi dimana terjadi penyempitan atau penyumbataan pembuluh darah yang dapat menyebabkan serangan jantung ,nyeri dada,stroke, Penyakit jantung dapat terjadi oleh siapapun disegala usia , jenis kelamin, pekerjaan , dan gaya hidup. Selain itu penyakit jantung tidak dapat disembuhkan .Kondisi ini membutuhkan pengobataan dan pemantauan hati-hati sepanjang hidupnya. Ketika pengobataan ini gagal , penderita harus melakukan operasi bedah yang cukup mahal dan rumit . Laporan dari WHO September 2009, menyebutkan bahwa penyakit tersebut merupakan penyebab kematian pertama sampai saat ini. Pada 2004, diperkirakan 17,1 juta orang meninggal karena Penyakit Jntung . Angka ini merupakan 29% dari penyebab kematian global, dengan perincian 7,2 juta meninggal karena penyakit jantung dan 5,7 juta orang meninggal karena stroke.Hal inni dapat dicegah dengan menggurangi factor- factor resiko .Peran teknologi informasi dapat diwujudkan dengan teknik mencari data riseet untuk mempersingkat waktu dan pemilihan fakto-faktor pendeteksi dini serangan jantung .Kata kunci: jantung; regresi; teknologi informasi

PENERAPAN METODE DOUBLE EXPONENTIAL SMOOTHING UNTUK MERAMALKAN ANGKA PENGANGGURAN Dari, Lisa Wulan; Syah, Arridha Zikrah; Sembiring, Muhammad Ardiansyah
JURNAL TEKNISI Vol 1, No 2 (2021): Agustus 2021
Publisher : Smart Education

Jumlah pengangguran yang tinggi dapat menghambat proses pembangunan ekonomi, sehingga diperlukan sistem peramalan untuk mengetahui jumlah pengangguran di Asahan yang berpengaruh terhadap kebijakan pemerintah dalam pengambilan keputusan sebelum terjadinya peningkatan jumlah pengangguran. Peramalan pengangguran ini berdasarkan data aktual dalam kurun waktu 12 tahun menggunakan metode Double Exponential Smoothing (DES). Metode akurasi peramalan yang digunakan dalam peramalan pengangguran ini adalah Mean Absolute Percentage Error (MAPE) untuk menghitung persentase error pada nilai alpha. Hasil peramalan terbaik untuk data pengangguran terdapat pada nilai alpha 0,4 nilai MAPE sebesar 6,22%, sehingga jumlah pengangguran sebesar 6,22% untuk tahun 2021 dengan total pengangguran 22909,72 hasil perhitungan sebesar 22909,72 ± 6.22% = 22909,72 ± 1424,98. Dengan range prediksi 21484,74 – 24334,7.

PENGEMBANGAN PERMAINAN EDUKATIF ULAR TANGGA ALJABAR SEBAGAI STRATEGI ALTERNATIF PEMBELAJARAN MATEMATIKA SEKOLAH DASAR Sibuea, Mustika Fitri Larasati; Sembiring, Muhammad Ardiansyah; Adinda, Fitrah
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4379

Penelitian ini bertujuan untuk mengembangkan media pembelajaran ular tangga pada materi operasi hitung aljabar untuk siswa kelas III sekolah dasar dan mengetahui keefektifan rata-rata hasil belajar pada ujicoba terbatas. Penelitian ini merupakan penelitian pengembangan (Research and Development) menurut Borg dan Gall namun dibatasi sampai uji coba produk terbatas. Subjek dalam penelitian ini adalah 59 siswa kelas III SD Tamansiswa Sukadamai dan SDN 014682 Perhutaan Silau.Teknik pengumpulan data menggunakan metode observasi, wawancara, angket dan dokumentasi dengan teknik analisis data berupa deskriptif kuantitatif dan deskriptif kualitatif. Hasil pengembangan ini berupa media pembelajaran ular tangga aljabar dengan hasil penilaian akhir dari ahli media sebesar 92% termasuk kategori sangat baik dan hasil penilaian akhir dari ahli materi sebesar 90% termasuk kategori sangat baik. Hasil tes evaluasi siswa rata-rata sebesar 87,51. Hasil analisis tangggapan siswa terhadap media sebesar 93,52% dan pada angket keberterimaan media oleh guru sebesar 91%. Hal ini menunjukan bahwa media telah dinyatakan valid dan layak digunakan dalam pembelajaran di sekolah dasar. Kata Kunci: Pengembangan, Media Pembelajaran, Ular Tangga Aljabar

ANALISIS PERFORMANCE MODEL PREDIKSI HARGA JUAL MOBIL BEKAS MENGGUNAKAN MACHINE LEARNING Sembiring, Muhammad Ardiansyah; Sibuea, Mustika Fitri Larasati; elfina, Novita
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4378

Abstract: Cars are a very popular four-wheeled means of transportation today, so that many consumers or buyers are interested in buying new or used cars depending on their respective economies. One factor that influences consumer interest in buying a car is price. Price greatly influences the sustainability of consumers in buying a car. It is necessary to estimate the estimated price of a used car based on criteria such as mileage, taxes, fuel consumption, and engine capacity. Estimation using regression method where in regression method there are 7 more methods including (1) Linear Regression, (2) Support Vector Regression – Linear, (3) Support Vector Regression – RBF, (4) Decision Tree Regression, (5) Random Forest Regressor, (6) Gradient Boosting Regression, (7) NLP Regressor applied in this research. Based on the 7 regression methods, the best method with the best accuracy value will be sought which will be used in the deployment processing process to determine the price of used cars with a ratio of 90:10, 80:20 and 70:30 producing the best estimated value is decision tree regression. Each method has a high level of accuracy including in the 90:10 ratio decision tree regression as the best method in the ratio has an accuracy level of 99%, and in the 80:20 ratio decision tree regression has an accuracy value of 99%, then the 70:30 ratio decision tree regression again becomes the best method with an accuracy level of 99%. Keyword: Machine Learning; Used Car Price Prediction; Regression; Performance Model Abstrak: Mobil merupakan sebuah alat transportasi kendaraan roda empat yang sangat populer saat ini, sehingga banyak sekali minat konsumen atau pembeli yang ingin membeli mobil baru maupun bekas tergantung dari ekonomi nya masing-masing Salah satu yang mempengaruhi minat konsumen dalam membeli mobil yaitu harga. Harga sangat berpengaruh dalam keberlangsungan konsumen dalam membeli suatu mobil Perlunya upaya estimasi untuk mengetahui perkiraan harga mobil bekas dengan berdasarkan kriteria seperti jarak tempuh, pajak, konsumsi bahan bakar, serta kapasitas mesin. Estimasi menggunakan metode regresi dimana dalam metode regresi terdapat 7 metode lagi meliputi (1) Linear Regression, (2) Support Vector Regression – Linear, (3) Support Vector Regression – RBF, (4) Decision Tree Regression, (5) Random Forest Regressor, (6) Gradient Boosting Regression, (7) NLP Regressor yang diterapkan dalam penelitian ini. Berdasarkan 7 metode regresi tersebut akan dicari 1 metode terbaik dengan nilai akurasi paling terbaik yang akan digunakan dalam proses pengolahan deploy untuk menentukan harga mobil bekas dengan rasio yaitu 90:10, 80:20 dan 70:30 menghasilkan nilai estimasi terbaik adalah decision tree regression. Masing – masing metode memiliki tingkat akurasi yang tinggi diantaranya dalam rasio 90:10 decision tree regression sebagai metode terbaik dalam rasio tersebut memiliki tingkat akurasi sebesar 99%, dan pada rasio 80:20 decision tree regression tersebut memiliki nilai akurasi sebesar 99%, selanjutnya rasio 70:30 decision tree regression kembali menjadi metode terbaik dengan tingkat akurasi sebesar 99%. Kata kunci: Machine Learning; Prediksi Harga Mobil Bekas; Regresi; Performance Model

ANALISA KINERJA MODEL REGRESI DALAM MACHINE LEARNING UNTUK MEMPREDIKSI HARGA BERAS Sembiring, Muhammad Ardiansyah; Sembiring, Febby Wulandari
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 8 No 1 (2024)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v8i1.3902

Sektor perdagangan saat ini mengalami kenaikan atau penurunan harga yang sangat signifikan. Hal ini menyebabkan beras menjadi salah satu faktor penunjang keberlangsungan hidup masyarakat. Kenaikan harga beras dapat mengakibatkan penurunan daya beli masyarakat terhadap kebutuhan lainnya. Sehingga untuk mengantisipasi adanya kenaikan harga beras dilakukannya prediksi menggunakan machine learning dengan menggunakan perbandingan 7 metode. Tujuan penelitian ini adalah untuk menganalisa kinerja model-model regresi terbaik dalam machine learning yang dapat digunakan untuk memprediksi harga beras. Nantinya akan diperoleh metode manakah yang menghasilkan nilai akurasi yang paling akurat dalam memprediksi harga beras. Estimasi menggunakan metode regresi dimana dalam metode regresi terdapat 7 metode lagi meliputi (1) Linear Regression, (2) Support Vector Regression Linear, (3) Support Vector Regression RBF, (4) Decision Tree Regression, (5) Random Forest Regressor, (6) Gradient Boosting Regression, (7) MLP Regressor. Adapun model terbaik yang dari hasil analisa penelitian ini yaitu metode Decision Tree Regression dengan pengujian akurasi model yaitu paa rasio pengujian data 80:20 sebesar 100%, 100% pada rasio pengujian data 70:30 dan pada rasio 60:40 adalah 100%.

Factors Analysis And Profit Achievement For Trading Company By Using Rough Set Method Sembiring, Muhammad Ardiansyah; Azhar, Zulfi
International Journal of Artificial Intelligence Research Vol 1, No 1 (2017): June 2017
Publisher : Universitas Dharma Wacana

This research has been done to analysis the financial raport fortrading company and it isÂ intimatelyÂ relatedÂ toÂ someÂ factorsÂ whichÂ determineÂ the profit of company. The result of this reseach is showed aboutÂ New Knowledge and perform of the rule. InÂ discussion, by followed data mining process and using Rough Set method. Rough Set is to analyzed the performance of the result. This Â reseach will be assist to the manager of company with draw the intactandobjective. Rough set method is also to difinedÂ the rule of discovery process and started the formation about Decision System, Equivalence Class, Discernibility Matrix,Â Discernibility Matrix Modulo D, Reduction and General Rules. Rough set method is efective model about the performing analysis in the company.Â Keywords : Data Mining, General Rules, Profit,. Rough Set.

Determining Citizens Eligibility for Cash Assistance Using the BORDA Method Putra, Andriansyah; Sembiring, Muhammad Ardiansyah; Mardalius
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8854

The Bandar Lama Village Head Office has implemented a Direct Cash Assistance distribution system as an effort to help underprivileged people meet their daily needs. However, the selection process for aid recipients is still carried out manually and conventionally, which has the potential to cause inaccuracy in targeting, human error, and low time efficiency and accuracy of decision making. The absence of an integrated digital system and the use of selection methods that are not yet based on criteria weighting have caused inequality in the distribution of aid, leading to complaints from community members and ineffective program implementation. To overcome these problems, this study proposes the implementation of a web-based Decision Support System using the BORDA method. The BORDA method is a multi-criteria decision-making approach that allows for systematic evaluation of multiple criteria simultaneously, providing more objective and consistent results in the selection process. This system incorporates various socio-economic indicators such as income level, family size, housing conditions, and employment status to ensure comprehensive assessment of each applicant's eligibility. Based on the results of the BORDA method calculation on 30 tested resident data, it was obtained that a resident named Tomy had the highest score of 70, followed by Ranto Simanjuntak with a score of 70, and Marianik with a score of 67. With this BORDA method-based system, aid distribution in Bandar Lama Village can be carried out more accurately, fairly, and transparently, ultimately improving the effectiveness of social assistance programs and ensuring that aid reaches those who need it most.

Seasonal Pattern Analysis In Bolu House Sales Using Seasonal Adjustment Method Andrean, Stefhany; Sembiring, Muhammad Ardiansyah; Sena, Maulana Dwi
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8937

Rumah Bolu is a business engaged in the sale of sponge cakes located on Jalan Perumahan Duta Mas 9, Sei Kamah II, Kec. Sei Dadap, Asahan Regency, North Sumatra 21263. The problems faced by Rumah Bolu include if the stock decreases, Rumah Bolu risks losing sales and customer trust, while if the stock is excessive but sales are low it can cause wasteful costs, decreased product quality and financial losses that hinder maximum profits. During certain seasons such as weekends or big celebrations, the demand for sponge cakes can increase drastically which risks causing shortages of raw material stock and delays in marketing. Conversely, on Monday to Friday, sales tend to decrease which can result in stock piling up and increase the risk of loss. With the need for a forecasting system, Rumah Bolu can adjust sales based on seasonal demand patterns so as to avoid the risk of shortages or excess stock, optimize operational costs and increase profits to the maximum. To predict the sale of sponge cake, a forecasting method is applied, namely the Seasonal Adjustment method, which is used when the time series data pattern obtained has a seasonal pattern. The seasonal pattern is a fairly unique sales pattern because it can be seen when there is a certain increase in a certain season. The purpose of this study is to design a sponge cake stock forecasting application with the Seasonal Adjustment method and to apply a forecasting method to predict the stock of sponge cakes at Rumah Bolu using PHP and its MySQL database. The research method used in this study is a quantitative research method. The results of the Seasonal Adjustment calculation prediction on banana sponge cakes for the January 2025 period were 424 with a MAPE of 5.53%. Then the results of the Seasonal Adjustment calculation prediction on pandan sponge cakes for the January 2025 period were 73.67 with a MAPE of 3.84% and the results of the Seasonal Adjustment calculation prediction on birthday sponge cakes for the January 2025 period were 142.67 with a MAPE of 3.03%.

COMPARING THE WMA AND SES METHODS FOR FORECASTING STOCK PRODUCT OF MS GLOW PUTRI Nurhamidah, Nurhamidah; Sembiring, Muhammad Ardiansyah; Lubis, Iin Almeina
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 4 (2024): September 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i4.3322

Abstract: Ms Glow Putri Shop is a business that operates in the beauty sector, selling beauty products, namely skincare and bodycare, which are useful for maintaining healthy body and facial skin. However, Ms Glow Putri currently often experiences problems, namely tight competition and inventory management that is less effective in terms of sales numbers. Every month reaching ±1300 products, Ms Glow Putri also often experiences shortages and build-ups in skincare and bodycare stocks. This can reduce customer confidence so that Ms Giow Putri often experiences losses in the form of finance and other things, so this method is needed to predict some skincare and other stock supplies. bodycare provided in the following month. This method uses the Weighted Moving Average and Single Exponentiation Smoothing methods to predict supplies of skincare and bodycare stocks. The results of research on Ms GIow daughter using the Weight Moving Average Method with a weight of 5 with a MAPE of 1.08% and the SingIe Exponentiation Smooting Method with an Alpha of 0.1, namely 0.84%, then the comparison between the two methods can be stated that the SES method is the best method good, because it has the lowest error. Keywords: forecasting; ms glow putri; ses and wma Abstrak: Toko Ms Glow Putri adalah usaha yang bergerak di bidang kecantikan, menjual produk kecantikan yaitu skincare dan bodycare berguna untuk menjaga agar kesehatan kulit tubuh dan wajah tetap terjaga. Namun Ms Glow Putri saat ini sering kali mengalami permasalahan yaitu persaingan yang ketat dan manajemen persediaan yang kurang efektif dengan jumlah penjualanan. Setiap bulan mencapai ±1300 produk maka Ms Glow Putri juga sering mengalami kekurangan dan penumpukan pada stok skincare dan bodycare ini dapat mengurangi kepercayaan pelanggan sehingga Ms Glow Putri sering mengalami kerugian berupa finance dan lainnya maka perlu metode ini untuk memprediksi beberapa persediaan stok skincare dan bodycare yang disediakan pada priode di buIan berikutnya. Metode ini menggunakan metode Weighted Moving Averege dan Single Exponential Smoothing untuk memprediksi persediaan pada stok skincare maupun bodycare. HasiI penelitian pada Ms GIow Putri dengan mengggunakan Metode Weight Moving Averege dengan bobot 5 dengan MAPE 1,08% dan Metode Single Exponential Smooting dengan Alpha 0,1 yaitu 0,84% maka perbandingan antara dua metode tersebut dapat dinyatakan bahwa metode SES adaIah metode paling baik karena memiliki error terendah. Kata kunci: ms glow putri; peramalan; ses dan wma

IMPLEMENTATION OF E-SCM AS A SOLUTION TO OPTIMIZE SHOE STOCK SUPPLY CHAIN IN GASTI JAYA STORE Siregar, Sindi Fatika Sari; Sembiring, Muhammad Ardiansyah; Ananda, Ricki
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 3 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i3.3770

Abstract: In the retail industry, effective supply chain management is essential to ensure stock availability aligns with market demand. Gasti Jaya Store, a growing shoe retailer, faces challenges in optimizing inventory management, often leading to stock surpluses or shortages. These issues can impact operational efficiency and customer satisfaction. To address this problem, this study the implementation of Electronic Supply Chain Management (E-SCM) as a solution to optimize supply chain management. E-SCM enables the integration of technology-based systems for real-time stock monitoring, procurement, and distribution. Using a case study method and a qualitative approach, this research evaluates the effectiveness of E-SCM in enhancing operational efficiency, reducing excess stock, and accelerating the distribution process at Gasti Jaya Store. The findings indicate that E-SCM implementation improves data transparency, speeds up decision-making, and enhances customer satisfaction. Additionally, the system helps reduce operational costs by optimizing inventory management and minimizing the risk of stock imbalances. In conclusion, the adoption of E-SCM can serve as an effective strategy for mid-sized retail businesses to improve their competitiveness and supply chain efficiency.Keywords: E-SCM; inventory stock; operational efficiency. Abstrak: Dalam industri ritel, manajemen rantai pasok yang efektif sangat diperlukan untuk memastikan ketersediaan stok sesuai dengan permintaan pasar. Toko Gasti Jaya sebagai salah satu toko sepatu yang berkembang menghadapi tantangan dalam mengelola persediaan secara optimal, yang sering kali menyebabkan kelebihan atau kekurangan stok. Permasalahan ini dapat berdampak pada efisiensi operasional dan kepuasan pelanggan. Untuk mengatasi masalah tersebut, penelitian ini mengusulkan penerapan Electronic Supply Chain Management (E-SCM) sebagai solusi dalam mengoptimalkan manajemen rantai pasok. E-SCM memungkinkan integrasi sistem berbasis teknologi dalam proses pemantauan stok, pengadaan barang, hingga distribusi secara real-time. Dengan metode studi kasus dan pendekatan kualitatif, penelitian ini mengevaluasi efektivitas E-SCM dalam meningkatkan efisiensi operasional, mengurangi kelebihan stok, serta mempercepat proses distribusi di Toko Gasti Jaya. Hasil penelitian menunjukkan bahwa implementasi E-SCM mampu meningkatkan transparansi data, mempercepat pengambilan keputusan, dan meningkatkan kepuasan pelanggan. Selain itu, sistem ini membantu mengurangi biaya operasional dengan mengoptimalkan manajemen persediaan dan meminimalkan risiko ketidakseimbangan stok. Kesimpulannya, penerapan E-SCM dapat menjadi strategi yang efektif bagi bisnis ritel skala menengah untuk meningkatkan daya saing dan efisiensi rantai pasok mereka.Kata Kunci: E-SCM; efisiensi operasional; persediaan stok.

Co-Authors Adinda, Fitrah Agus, Raja Tama Andri Akmal Akmal Amalia Andhini Asri Awaliyah Arifin Andika Nanda Manurung Andrean, Stefhany Andrew Ramadhani Arridha Zikra Syah Bachtiar Efendi Balqis, Nur Chitra, Latiffani Cici Santika Putri Dari, Lisa Wulan Dedi Setiawan Dedi Setiawan Dina Pertiwi elfina, Novita Fahriza Khoirani Febby Madonna Yuma Firdha Agis Utami Batu Bara Hazrina, Umi Indah Hommy Dorthy Ellyany Sinaga Iin Almeina Ika Rahmanda Sitorus Ishak Ishak Ishak Ishak Julita, Rina Lubis, Iin Almeina Manurung, Silpany Mardalius Marhama, Siti Marpaung, Nasrun Maysaroh, Maysaroh Mhd Istaufa Arif Sinaga Muhammad Iqbal Muhammad Istaufa Arib Sinaga Mustika Fitri L Sibuea Mustika Fitri Larasati Sibuea Nurhamidah Nurhamidah Nurhasanah Nurhasanah Nuriadi Manurung panjaitan, widia fahwana br PuspitaSari, Dinda Tri Putra, Andriansyah Rahayu, Elly Raja Tama Andri Agus Ramadhani, Andrew Ricki Ananda Rizky Ardiansyah Rohminatin Rohminatin Sapta, Andy Sastria Sandy Utama Selvi, Diana Sembiring, Febby Wulandari Sena, Maulana Dwi Siregar, Sindi Fatika Sari Siti Ramadani Sri Rezki Maulina Azmi Sri Wahyuni Sudarmin Sudarmin Sulistiani, Indah Wiwin Handoko Yessica Siagian Yunita

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