Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

8.099

P-Index

This Author published in this journals

All Journal Jurnal Ilmu Komputer dan Informasi Jurnal F. Teknik : RESULTAN Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknik Komputer AMIK BSI Cakrawala : Jurnal Humaniora Bina Sarana Informatika Paradigma Jurnal Ilmiah FIFO Bina Insani ICT Journal Jurnal Pilar Nusa Mandiri Information System for Educators and Professionals : Journal of Information System Jurnal Mahasiswa Bina Insani Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) Jurnal Teknik Informatika STMIK Antar Bangsa Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Komtika (Komputasi dan Informatika) IKRA-ITH EKONOMIKA Jurnal ICT : Information Communication & Technology JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Kajian Ilmiah Jurnal Sistem Informasi Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Jurnal Sains Teknologi dalam Pemberdayaan Masyarakat Journal of Students‘ Research in Computer Science (JSRCS) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Pengabdian Masyarakat Information Technology (JPM ITech) INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Journal of Computer Science Contributions (Jucosco) Jurnal Komtika (Komputasi dan Informatika)

Herlawati Herlawati

Fakultas Ilmu Komputer, Universitas Bhayangkara Jakarta Raya

Author-ID : 280234

Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

Published : 159 Documents Claim Missing Document

Claim Missing Document

Articles

6 7 8 9 10

Sistem Informasi Penyewaan Lapangan Bulu Tangkis Berbasis Web Pada GOR Villa Mas Indah Bekasi Utara Tumbur Togu; Herlawati Herlawati; Adi Muhajirin
Journal of Students‘ Research in Computer Science Vol. 2 No. 1 (2021): Mei 2021
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/jsrcs.v2i1.656

Abstract Web-Based Badminton Court Rental Information System at GOR Villa Mas Indah, North Bekasi. Badminton GOR Villa Mas Indah is a business brand engaged in sports. However, the information system implemented in the company still tends to have many shortcomings and weaknesses by using a ledger, therefore the company needs a Web-Based Badminton Court Rental Information System Design at GOR Villa Mas Indah Bekasi Utara with the aim of helping in improving the business brand marketing strategy. and maximizing service with the aim of facilitating performance in data processing, changing data, viewing field schedule information, and data stored automatically and safely. The system development method uses Waterfall. Data collection methods are interviews, observation, literature study and questionnaires. The system design uses UML, the system is built using the PHP programming language, with MySQL database and application display using CSS Bootstrap. Testing the system using Blackbox Testing. Keywords: Booking, Information Systems, Rental, Waterfall, Web Based, Abstrak Sistem Informasi Penyewaan Lapangan Bulu Tangkis Berbasis Web Pada GOR Villa Mas Indah Bekasi Utara. GOR Bulu tangkis Villa Mas Indah adalah brand usaha yang bergerak di bidang olahraga. Namun sistem informasi yang di terapkan dalam perusahaan masih cenderung memiliki banyak kekurangan dan kelemahan dengan menggunakan buku besar, oleh karena itu perusahaan perlunya Perancangan Sistem Informasi Penyewaan Lapangan Bulu Tangkis Berbasis Web Pada GOR Villa Mas Indah Bekasi Utara dengan tujuan membantu dalam meningkatkan strategi marketing brand usaha dan memakasimalkan pelayanan dengan tujuan mempermudah kinerja dalam mengolah data, mengubah data, melihat informasi jadwal lapanagan, serta data tersimpan secara otomatis dan aman. Metode pengembangan sistem menggunakan Waterfall. Metode pengumpulan data yaitu Wawancara, Observasi, Studi Pustaka dan Kuesioner. Desain sistem menggunakan UML, sistem di bangun menggunakan bahasa pemograman PHP, dengan basis data MySQL dan tampilan aplikasi menggunkan CSS Bootstrap. Pengujian sistem menggunakan Blackbox Testing.. Kata kunci: Berbasis Web, Booking, Penyewaan, Sistem Informasi, Waterfall.

Sistem Informasi Pemilihan Peserta Program Indonesia Pintar (PIP) Dengan Metode K-Nearest Neighbor pada SD Negeri Pejuang V Kota Bekasi Sandy Satyo Prihatin; Prima Dina Atika; Herlawati Herlawati
Journal of Students‘ Research in Computer Science Vol. 2 No. 2 (2021): November 2021
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

The selection of participants for the Smart Indonesia Program (PIP) is an activity to determine students who are eligible for assistance. This study aims to create an information system for the Selection of Participants for the Smart Indonesia Program (PIP) which will assist Administrative Staff and SD Negeri Pejuang V Bekasi City in determining eligible and ineligible participants for assistance. The method used in this information system uses the K-Nearest Neighbor algorithm. The K-Nearest Neighbor process is carried out by giving weight to the student data attributes and looking for the Euclidean distance, then sorted from the smallest distance, after sorting the student data then looking for the closest distance to the training data. The K-Nearest Neighbor algorithm in data training is very fast, simple, easy to learn, effective with large training data and is resistant to data containing incorrect or anomalous values. The results of this study obtained student data as many as 77 students, there are True Positive (TP) data of 5 data, False Positive (FN) of 7 data, True Negative (TN) of 65 data and False Negative (FP) of 0. Results The accuracy obtained is 90.90% with a value of k=10. Keywords: Information System, K-Nearest Neighbor, KNN, Program Indonesia Pintar (PIP). Abstrak Pemilihan peserta Program Indonesia Pintar (PIP) merupakan kegiatan menentukan siswa yang layak untuk mendapatkan bantuan. Penelitian ini bertujuan membuat sistem informasi untuk Pemilihan Peserta Program Indonesia Pintar (PIP) yang akan membantu Staff Administrasi dan pihak SD Negeri Pejuang V Kota Bekasi dalam menentukan peserta yang layak dan tidak layak untuk mendapat bantuan. Metode yang digunakan pada sistem informasi ini menggunakan algoritma K-Nearest Neighbor. Proses K-Nearest Neighbor ini dilakukan dengan memberikan bobot pada atribut data siswa dan mencari jarak Euclidean, selanjutnya diurutkan dari jarak yang terkecil, setelah diurutkan data siswa tersebut maka dicari jarak terdekat terhadap data training. Algoritma K-Nearest Neighbor dalam pelatihan data sangat cepat, sederhana, mudah dipelajari, efektif dengan data pelatihan besar serta tahan terhadap data berisi nilai yang salah atau anomali. Hasil dari penelitian ini data siswa yang didapat sebanyak 77 siswa, terdapat data True Positive (TP) sejumlah 5 data, False Positive (FP) sejumlah 7 data, True Negative (TN) sejumlah 65 data dan False Negative (FN) sejumlah 0. Hasil akurasi yang diperoleh mendapatkan nilai 90.90% dengan nilai k=10. Kata kunci: K-Nearest Neighbor, KNN, Program Indonesia Pintar (PIP), Sistem Informasi.

ANIMASI INTERAKTIF PEMBELAJARAN TAJWID PADA TAMAN QUR'AN ANAK (TQA) AL WASHILAH CIREBON Abdul Kholis; Herlawati .
JURNAL TEKNIK KOMPUTER AMIK BSI Vol 1, No 2 (2015): Jurnal Teknik Komputer AMIK BSI
Publisher : Universitas Bina Sarana Informatika

ewline"> Abstract — Media Limited cause children to become bored quickly,thereby reducing the child’s interest in learning. With theinnovation and development of technology combined between text,images, audio, music, animated images the support each other, cancause a sense of fun and enthusiasm for learning. So the child’smotivation for learning will increase and not saturated and isexpected to end up learning more. Animated interactive learningtajwid of this method will be a great learning fun and easy for boththe teacher and the student. By learning more interactive,instructor would always required to be creative and innovative inseeking a breakthrough study.Intisari — Media pembelajaran yang terbatas menyebabkananak menjadi cepat bosan sehingga mengurangi ketertarikananak pada pelajaran. Dengan inovasi dan perkembanganteknologi dipadukan antara text, gambar, audio, musik, animasigambar yang saling mendukung, mampu menimbulkan rasasenang dan semangat dalam proses belajar. Sehingga motivasianak selama proses belajar akan bertambah dan tidak jenuh dandengan ini diharapkan tujuan pembelajaran menjadi lebihmaksimal. Animasi Interaktif Pembelajaran Tajwid ini akanmenjadi metode pembelajaran yang amat menyenangkan danmemudahkan baik dari sisi pengajar ataupun siswa. Dengansistem pembelajaran yang lebih interaktif, pengajar akan selaludituntut untuk kreatif dan inovatif dalam mencari terobosanpembelajaran.Kata Kunci : Animasi Interaktif, Pembelajaran, Tajwid

PENERAPAN INFORMATION TECHNOLOGY ETHICS DALAM PROSES BELAJAR MAHASISWA Herlawati Herlawati
Cakrawala - Jurnal Humaniora Vol 10, No 1 (2010): Periode Maret 2010
Publisher : Universitas Bina Sarana Informatika

Many research on Information Technology (IT) Ethics for ethical guidance when students graduate or the technical delivery (asinkron or direct course). But in reality, sometimes we found confused students when implement IT ethic as a result of inconsistent thins when they learn. Ethics of copyright, for example, is the contrast in the library on campus copying without permission of books (most of the overseas issue). Or some professors who share module copyright campus when teaching at other colleges. Although the meaning of "in order to enlighten the people" but in terms of ethics of course that it violates. Most of this is happening due to the angle of view that distinguishes between the college campus with the professional world that sometimes allows things to happen on the campus ethical violation (the reason for the nations') as long as not done the work (the professional world). Moreover, the number of industrial policies (such as Microsoft ®) that does cut the price of its software with a particular reason (with a certain purpose, such as the introduction and strengthening brand products). Up to reinforce the reasons that campuses (including schools) different from the world of professional and community. In this paper will be presented several arguments that break the way the world should be distinguished college and the work with the principles of competency.Key Words : IT Ethics, Competency Based Curriculum, E-learning.

STRUCTURAL EQUATION MODELING DENGAN HUBUNGAN MODERASI PADA PENGARUH TINGKAT INTELEGENSI DENGAN KEBERHASILAN AKADEMIK Herlawati Herlawati
Paradigma Vol 13, No 1 (2011): Vol. 13 Nomor 1, Maret 2011
Publisher : LPPM Universitas Bina Sarana Informatika

Effect of level of intelligence as measured by the ability of logic (KL) and reasoning ability (KP) with academic success (as measured by GPA, there is a possibility that there could interact (measured by the friendliness of (KR) and proximity to the lecturer (KD )) can strengthen or weaken the relationship between the level of intelligence and academic success is. The possibility to interact is the moderating variable. moderating variables are variables that can strengthen or weaken the relationship between independent and dependent variables. Level of intelligence was a direct effect on academic success. Interaction does not directly influence academic success. To examine the relationship between the complex variables that both recursive and non-recursive to obtain the best overall picture of a model used structural equation modeling (SEM) with AMOS software version 16.0 Keywords: Intelligence, GPA, Structural Equation Modeling (SEM), Analysis of Moment Structure (AMOS)

Implementasi Support Vector Machine (SVM) dan Naïve Bayes untuk Analisis Sentimen Aplikasi KAI Access Muhammad Riky Sudrajat; Prima Dina Atika; Herlawati .
Jurnal ICT : Information Communication & Technology Vol 20, No 2 (2021): JICT-IKMI, Desember 2021
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v20i2.403

Google Play Store is one of the platforms on Android to download an application, Google Play also provides a feature for the public to be able to provide comments/reviews of the downloaded application. Reviews of the application are in the form of perception, both positive and negative, a review of one of the applications on google play, namely the KAI access application, can be used as research material to find information. The technique that can be used for this research is sentiment analysis, the classification method that will be used for this sentiment analysis is the support vector machine and naive Bayes as a comparison to find better accuracy of the two algorithms, this research can help developers to find out the shortcomings and advantages that must be improved on the application. The results of the study using the Support Vector Machine (SVM) classification obtained an accuracy rate of 93% while using the Naïve Bayes method that was 89%. So, the Support Vector Machine method provides a higher level of accuracy than the Naïve Bayes method.

Pencarian Stasiun Kereta Terdekat dengan Algoritma A Star Berbasis Android di Bekasi Ikhsan Dwikurniawan; Herlawati Herlawati; Robertus Suraji
Jurnal ICT : Information Communication & Technology Vol 20, No 2 (2021): JICT-IKMI, Desember 2021
Publisher : STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36054/jict-ikmi.v20i2.401

Transportation has become one of the most important needs in daily activities in social life. Advances in information technology that exist today, can be used as a means to improve public services, one of which is in the railway sector. With advances in information technology can make it easier for people to find information quickly and easily. There are several obstacles, namely the lack of information about the nearest station route. This study aims to create an android-based nearest station search application with the shortest route to the destination station using the A STAR Algorithm. The A STAR algorithm is an algorithm that looks for the shortest route to reach the expected destination. In this study Kranji Station, Bekasi Station, East Bekasi Station, Tambun Station, Cibitung Station, Telaga Murni Station, Cikarang Station. With tests carried out from 7 times of testing, it can be ensured that 4 times the A STAR algorithm is successful in the shortest distance, 1 time the results of the A STAR algorithm are the same as Google Maps, and 2 times the A-Star algorithm shows a longer distance than Google Maps.

Prediksi Kelas Jamak dengan Deep Learning Berbasis Graphics Processing Units Rahmadya Trias Handayanto; Herlawati Herlawati
Jurnal Kajian Ilmiah Vol. 20 No. 1 (2020): Januari 2020
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

For the first time, machine learning did the classical classification process using two classes (bi-class) such as class -1 and class +1, 0 and 1, or the form of categories such as true and false. Famous methods used are Artificial Neural Networks (ANN) and Support Vector Machine (SVM). The current development was a problem with more than two classes, known as multi-class classes. For SVM sometimes the plural classes are overcome by doing a gradual process like a decision tree (DT) method. Meanwhile, ANN has experienced rapid development and is currently being developed with a large number of layers with the new activation functions, i.e. the rectified linear units (ReLu), and the probabilistic-based activation, i.e. softmax, including its optimizer methods (adam, sgd, and others). Then the term changed to Deep Learning (DL). This study aimed to compare two well-known methods (DL and SVM) in classifying multiple classes. The number of DL layers was six with the neuron composition are 128, 64, 32, 8, 4, and 3, while SVM uses a radial kernel base function with gamma and c respectively 0.7 and 5. Besides, this study intends to compare the use of the Graphics Processing Unit (GPU) available on Google Interactive Notebook (Google Colab), an online Python language programming application. The results showed that DL accuracy outperformed SVM but required large computational resources, with the accuracy for DL and SVM are 99% and 98%, respectively. However, the use of the GPU can overcome these problems and is proven to increase the speed of the process as much as 47 times. Keywords: Artificial Neural Networks, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine. Abstrak Di awal perkembangannya mesin pembelajaran melakukan proses klasikfikasi menggunakan dua kelas (bi-class) misalnya kelas -1 dan kelas +1, 0 dan 1, atau bentuk kategori seperti benar dan salah. Metode terkenal yang digunakan adalah Jaringan Syaraf Tiruan (JST) dan Support Vector Machine (SVM). Perkembangan selanjutnya adalah problem dengan kelas yang lebih dari dua kelas, dikenal dengan istilah kelas jamak (multi-class). Untuk SVM terkadang kelas jamak diatasi dengan melakukan proses berjenjang mirip pohon keputusan (decision tree). Sementara itu JST telah mengalami perkembangan yang pesat dan saat ini sudah dikembangkan dengan jumlah layer yang banyak disertai dengan fungsi-fungsi aktivasi terkini seperti rectified linear unit (ReLu), dan softmax yang berbasis probabilistik, termasuk juga metode-metode optimizernya (adam, sgd, dan lain-lain). Kemudian istilahnya berubah menjadi Deep Learning (DL). Penelitian ini mencoba membandingkan dua metode terkenal (DL dan SVM) dalam melakukan klasifikasi kelas jamak. Jumlah layer DL sebanyak enam dengan masing-masing neuron sebesar 128, 64, 32, 8, 4, dan 3, sementara SVM menggunakan kernel radial basis function dengan gamma dan c berturut-turut 0.7 dan 5. Selain itu penelitian ini bermaksud membandingkan penggunaan Graphics Processing Unit (GPU) yang tersedia di Google Interactive Notebook (Google Colab), sebuah aplikasi online pemrograman bahasa Python. Hasil penelitian menunjukan akurasi DL unggul tipis dibanding SVM namun memerlukan sumber daya komputasi yang besar masing-masing dengan akurasi 99% dan 98%. Namun penggunaan GPU mampu mengatasi permasalahan tersebut dan terbukti meningkatkan kecepatan proses sebanyak 47 kali. Kata kunci: Jaringan Syaraf Tiruan, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine.

Penggunaan Matlab dan Python dalam Klasterisasi Data Herlawati Herlawati; Rahmadya Trias Handayanto
Jurnal Kajian Ilmiah Vol. 20 No. 1 (2020): Januari 2020
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Abstract Organizations need to dig through the data clustering process, both past data and data from the internet. Sometimes the data has to be re-clustered to match the actual conditions. Therefore, it is necessary to prepare clustering support equipment. In this study the K-Means method was chosen for comparing two technical computational languages, i.e. Matlab and Python which are currently in great demand by researchers and can be used by organizations for a clustering process. This study showed both Matlab and Python have enough libraries (libraries) and toolboxes to help users in data clastering as well as graphics presentation. The test results show that the two programming languages are capable of carrying out the clustering process with two clusters; cluster 1 with a center point at coordinates (1.24, 1.34) and cluster 2 with a center point at coordinates (3.1, 3.07) and are presented by a cluster distribution plot. Keywords: Clusterization, K-Means, Matlab, Python. Abstrak Organisasi perlu menggali data lewat proses klasterisasi data, baik data lampau maupun data dari internet. Terkadang data harus dilakukan klasterisasi ulang untuk mencocokan dengan kondisi yang sebenarnya. Oleh karena itu perlu dipersiapkan peralatan pendukung klasterisasi. Dalam penelitian ini metode K-Means dipilih untuk membandingkan dua bahasa komputasi teknis yaitu Matlab dan Python yang sekarang ini banyak diminati para peneliti yang dan dapat digunakan oleh organisasi yang membutuhkan proses klasterisasi. Hasil dari penelitian ini menunjukan baik Matlab maupun Python memiliki cukup pustaka (library) dan toolbox dalam membantu pengguna mengklasterisasi data, mempresentasikan grafik. Hasil pengujian menunjukan kedua Bahasa pemrograman mampu menjalankan proses klasterisasi berupa klaster 1 yang memiliki titik pusat yang berada pada koordinat (1.24, 1.34) dan klaster 2 dengan titik pusat yang berada pada koordinat (3.1, 3.07) disertai dengan plot sebaran klasternya. Kata kunci: Klasterisasi, K-Means, Matlab, Python.

Efektifitas Pembatasan Sosial Berskala Besar (PSBB) di Kota Bekasi Dalam Mengatasi COVID-19 dengan Model Susceptible-Infected-Recovered (SIR) Rahmadya Trias Handayanto; Herlawati Herlawati
Jurnal Kajian Ilmiah Vol. 20 No. 2 (2020): Mei 2020
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

To overcome the COVID-19 outbreak, the government did not carry out the lockdown policy (regional quarantine policy) but implemented the Large-Scale Social Restrictions (PSBB) policy. Starting from the capital city of Jakarta, this policy was followed by other regions. Bekasi City as a buffer zone of Jakarta immediately implemented the PSBB policy since this area is close to Jakarta and is feared to be affected by the Jakarta region which is a red zone with almost half of Indonesian COVID-19 cases are in the Jakarta area. Many people do not agree with the PSBB, but in order to keep the economic growth as well as to overcome the outbreak, the government does not adopt a regional quarantine policy. To determine the effectiveness of PSBB in the city of Bekasi, this study tried to use the Susceptible-Infected-Recovered (SIR) model to measure the spread rate of COVID-19. The results showed a decrease in the number of infected cases with beta and gamma were 0.071 and 0.05, respectively, and the epidemic was predicted to end in June 2020. Keywords: coronavirus, epidemic, pandemic, regional quarantine policy, Bekasi City Abstrak Dalam mengatasi wabah COVID-19, pemerintah tidak melakukan karantina wilayah (lock down) tetapi menggunakan kebijakan Pembatasan Sosial Berskala Besar (PSBB). Dimulai dari ibukota Jakarta, kebijakan ini diikuti oleh wilayah lainnya. Kota Bekasi sebagai wilayah penyangga Jakarta segera menerapkan kebijakan PSBB mengingat wilayah ini berdekatan dengan Jakarta dan dikhawatirkan terpengaruh dengan kota Jakarta yang merupakan zona merah dengan hampir separuh kasus COVID-19 ada di wilayah Jakarta. Banyak pihak yang mendukung dan juga kurang setuju dengan PSBB, namun agar perekonomian tetap berjalan dan wabah dapat diatasi, pemerintah tidak mengambil kebijakan karantina wilayah. Untuk mengetahui efektifitas PSBB di kota Bekasi, penelitian ini mencoba menggunakan model Susceptible-Infected-Recoverd (SIR) untuk mengukur laju penyebaran COVID-19. Hasilnya menunjukan adanya laju penurunan kasus terinfeksi dengan beta dan gamma beruturut-turut sebesar 0,071 dan 0,05 dan diprediksi akan berakhir di bulan Juni 2020. Kata kunci: virus corona, epidemik, pandemik, karantina wilayah, Bekasi City

Co-Authors A.A. Ketut Agung Cahyawan W Abd Rohman Abdul Kholis Achmad Wira Wiguna Adam Adam Adam Fajariansyah Adi Muhajirin Adi Supriyatna admin admin Aera Santiana Agus Hidayat Agustin, Syafira Cessa Ajie Prasetya Ajif Yunizar Pratama Yusuf AlHakim, Abdu Malik Andy Achmad Hendharsetiawan Anggaini, Meri Anisa Feby Yana Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anita Setyowati Srie Gunarti Anton Anton Ardiansyah, Muhamad Arrasyid, Rizky Maulana Asmoro Bangun Priambodo Atika , Prima Dina Ayu Afidarisa Rahma Bangga Tua Siregar Bayu Andriansyah Ben Rahman Beno Aditya Sanusi Beno Aditya Sanusi Benrahman Bhagaskara Farhan Wiguna Binu Nuryadi Budi Santoso Bunga Pratiwi Cahyaaty, Tata Arya Christhover , Robbie Dadan Irwan Dani Dani Daniel Jhon Rosinton Hutauruk Desi Puspasari Diah Putri Ramadhani Dicki Rizki Amarullah Didik Setiyadi Dinda Mutiara Hanum Dwi Budi Santoso Dwi Budi Srisulistiowati Eka Puspita Sari Eka Suryani Pratiwi Ekawati, Inna Endang Retnoningsih Erene Gernaria Sihombing, Erene Gernaria Ervan Dwi Kurniawan Fachrullyanta Adi Saputra Fadilah, Naufal Arif Fahrika, Andi Ika Faisal Adi Saputra Fandiansyah, Rafly Fata Nidaul Khasanah Feni Meilan Tasiba Firyal Rosiana Dita Frieyadie Galih Apriansha Pradana Gedhe Hilman Wakhid Gilby Lionska Wenas Gymnastiar, Muhammad Handry Hartino Haris, Syamsul Alam Harviansyah, Muhammad Haryono Haryono Haryono Hendharsetiawan , Andy Achmad Hendharsetiawan, Andy Achmad Heri Prabowo Hero Suhartono Hero Suhartono, Hero Hutauruk , Daniel Jhon Rosinton Icah Fitri Yani Idaul Hasanah Ikhsan Dwikurniawan Ikhsan Dwikurniawan Ira Wardani Irham Cahya Nugraha Irwan Raharja Ivan Nur Firdaus Izdihar, Zalfa Jaja Jaja JAJA, JAJA Joko Dwi Hartanto Juandika Shevani Julaiwa, Siti Hawa Karnita Afnisari, Karnita Krisendo Setiawan Kukuh Dwi Prasetyo Kurniawan, Ervan Dwi Kustanto , Prio Ladyana Suciani Syafitri Lestari, Tyastuti Sri Lubis, Riski Aditya Magdalena, Caroline Julyana Maimunah Maimunah Maimunah Maimunah Maimunah Maimunah, Maimunah Malikus Sumadyo Mardi Yudhi Putra Mayora Lolly Ishimora Merza Dheo Prakoso Muhamad Ardiansyah Muhammad Harviansyah Muhammad Muharrom Muhammad Riky Sudrajat Muhammad Zidan Al Faiq Nabila , Marsyanda Salsa Ningrum, Mirza Cahya Nita Merlina Nita Merlina, Nita Nitin Kumar Tripathi Noer Hikmah Novaldi Nur Pratama Novianto, Krisna Nunung Hidayatun Nur Amanda Pratiwi Nurchayati Nurchayati Nurcholis Nurcholis Oriza Sativa Dinauni Silaen Pahrizal, Pahrizal Popy Purnamasari Wahid Suyitno Pradana , Galih Apriansha Pramuhesti, Salwa Nabiila Priatna , Wowon Prihatin, Sandy Satyo Prima Dina Atika Purnama, Putra Aldi Purnomo, Rakhmat Purwanti, Santi Rachmatin, Nida Rafika Sari RAFIKA SARI Rahmadya Trias Handayanto Raihan Nurfaidzi Ramadhan, Sahara Ramadhani, Diah Putri Rasim Rasim Rasim, Rasim Rejeki , Sri Retno Nugroho Whidhiasih Retno Sari Riska Utami Dewi Rismayana, Raka Rizki Aulianita, Rizki Robbie Christhover Robertus Suraji Rosliana, Siti Rusdiansyah Rusdiansyah Salwa Nabiila Pramuhesti Samsiana , Seta Sandy Satyo Prihatin Santoso , Muhammad Reinaldy Sanusi, Beno Aditya Saputra , Faisal Adi Saputra, Fachrullyanta Adi Sari , Rafika SATRIYAS ILYAS Septi Eka Hardyana Septia, Dwi Yoga Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Seta Samsiana Setiawan, Andy Achmad Hendhar Setyowati Srie Gunarti, Anita Shadriyah , Shadriyah Silaen, Oriza Sativa Dinauni Siti Masripah, Siti Siti Rosliana SITI SETIAWATI Sohee Minsun Kim Solikin Solikin Solikin Solikin Sri Rejeki Sri Sureni Sugeng Murdowo Sugiyatno , Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sugiyatno Sunandar Sunandar Syadhaffa Gedriyansah Syafina, Prilia Hashifah Syahbaniar Rofiah Syahfitri, Intan Cahya Tambun, Jerisman Jhon Wesli Tia Monisya Afriyanti Trisumeikra, I Komang Arya Tumbur Togu Tyastuti Sri Lestari Tyastuti Sri Lestari Umi Salamah Wicaksono, Naufal Eka Wida Prima Mustika Wiguna, Bhagaskara Farhan Wijaya, Indra Yana, Anisa Feby Yessi Rahmawati Yugo Bhekti Utomo Yusuf, Ajif Yunizar Pratama

Title

Found 159 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 159 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 159 Documents
Search