Article Per Year (5 Year)
p-Index From 2020 - 2025
9.132
P-Index
This Author published in this journals
All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) TEKNIK INFORMATIKA Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JurTI (JURNAL TEKNOLOGI INFORMASI) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Telematika JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH MIND (Multimedia Artificial Intelligent Networking Database) Journal CSRID (Computer Science Research and Its Development Journal) Building of Informatics, Technology and Science Jurnal Mantik Jurnal Manajemen, Ekonomi Sains Jurnal Varian JURNAL PIONIR INFOKUM Journal of Applied Data Sciences Jurnal Ipteks Terapan : research of applied science and education International Journal of Research in Vocational Studies (IJRVOCAS) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Jurnal Pengabdian Masyarakat dan Riset Pendidikan SISFOTENIKA Proceeding Of International Conference On Education, Society And Humanity
Wanayumini
Universitas Asahan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

Published : 53 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 53 Documents
Search

 1   2   3   4   5 
Penerapan Data Mining Pada Penerimaan Dosen Tetap Menggunakan Metode Naive Bayes Classifier dan C4.5 Sadikin, Muhammad; Rosnelly, Rika; Roslina, Roslina; Gunawan, Teddy Surya; Wanayumini, Wanayumini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2434

Abstract

Recruitment is an important step in creating professional HR (Human Resources). The application of classification methods such as the Naïve Bayes method and C4.5 can be used in the classification of potential lecturers and can be accepted by the campus by calculating the equations for each criterion. The difficulty experienced is the ineffective use of the method to generate the required lecturer acceptance so that it is not in accordance with the applicant's expertise. One of the classification methods applied to data mining is the naïve Bayes method and C4.5. The purpose of this study is to determine the level of accuracy of the two methods used by using the Weka 3.8 tool based on the calculation of Correctly Classified Instance and Incorrectly Classified Instance. The accuracy results obtained with the naïve Bayes method are 83.7838% and the C4.5 method is 91.8919% from 37 training data. So the C4.5 method is a more appropriate method to use than naïve Bayes.
Identifikasi Tanda Tangan menggunakan Metode Fitur Ekstrasi Biner dan K Nearest Neighbor Simanjuntak, Mutiara Sarahwaty; Rosnelly, Rika; Wanayumini, Wanayumini
CSRID (Computer Science Research and Its Development Journal) Vol 12, No 3 (2020): CSRID OKTOBER 2020
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.12.3.2020.191-200

Abstract

Tanda tangan mempunya pola yang unik berdasarkan fitur yang ditinjau. Penelitian ini mengindentifikasi tanda tangan secara otomatis dengan menggunakan fitur biner dari hasil tanda tangan scanner. Identifikasi tanda tangan penting dilakukan otentifikasi dokumen administrasi dan resmi dimana nilai akurasi hal yang diperlukan. Dalam pendekatan yang dilakukan, fitur tanda tangan diekstrak dengan menggunakan dua descriptor yaitu binary statistical image features (BSIF) dan local binary patterns (LBP). Penilaian menggunakan metode ini dengan melakukan percobaan dengan dua dataset yang sudah tersedia untuk umum yaitu database MCYT-75 dan GPDS-100. Dengan menggunakan metode klasifikasi KNN, mendapatkan nilai tertinggi masing-masing 96,7% dan 93,9%. Dalam verifikasi identifikasi tanda tangan akurasi klasifikasi diukur berdasarkan equal error rate (EER)yaitu 4.2% dan 5.33% pada GPDS-200 dan GPSD-150. Sehingga EER untuk database MCYT-75 sudah mencapau 7,78%. Nilai akurasi tersebut sudah dapat diketegorikan unggul.
PENERAPAN METODE NAÏVE BAYES DAN C4.5 PADA PENERIMAAN PEGAWAI DI UNIVERSITAS POTENSI UTAMA Lubis, Cindy Paramitha; Rosnelly, Rika; Roslina, Roslina; Situmorang, Zakarias; Wanayumini, Wanayumini
CSRID (Computer Science Research and Its Development Journal) Vol 12, No 1 (2020): CSRID FEBRUARI 2020
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (555.267 KB) | DOI: 10.22303/csrid.12.1.2020.51-62

Abstract

Penerapan metode Naïve Bayes dan C4.5 dibuat untuk digunakan terhadap seleksi dan klasifikasi calon pegawai yang berpotensi untuk masuk ke dalam kampus dengan cara membuat perhitungan dari persamaan pada setiap kriteria. Permasalahan yang sering ditemukan adalah tidak efektifnya penggunaan metode yang digunakan untuk menghasilkan penerimaan pegawai yang di perlukan sehingga belum sesuai dengan bidang keahlian bagi pelamar. Metode Naïve Bayes dan C4.5 tersebut merupakan metode klasifikasi yang diterapkan pada data mining. Tujuan dibuatnya penelitian ini untuk menentukan tingkat akurasi antara kedua metode tersebut berdasarkan ketepatan perhitungan Correctly Classified Instance  dan Incorrectly Classified Instance. Pengujian metode pada penelitian ini dilakukan dengan menggunakan tools Weka 3.8. Hasil yang didapat Pada metode Naïve Bayes tingkat akurasi yang didapat 77,7778% dan C4.5 memiliki tingkat akurasi 94,444% dari 36 data latih berhasil diuji. Sehingga hasil yang didapat C4.5 merupakan metode yang lebih tepat di gunakan dari pada Naïve Bayes.    
ANALISIS PENGARUH LOW-LIGHT IMAGE ENHANCEMENT PADA PENGENALAN WAJAH Rohima, Rohima; Wanayumini, Wanayumini; Rosnelly, Rika
CSRID (Computer Science Research and Its Development Journal) Vol 13, No 2 (2021): CSRID JUNI 2021
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.13.2.2021.118-129

Abstract

Sistem pengenalan wajah secara umum akan digunakan secara real time dalam mengenali individu, artinya noise tidak dapat terhindarkan. Salah satu masalah yang dianggap umum adalah kokndisi pencahayaan. Kondisi pencahayaan terjadi akibat pancaran yang diterima objek tidak mencukupi sehingga cenderung memiliki visibilat rendah, kontras berkurang, warna kabur, dan detail yang kabur. Maka low-light image enhancement dapat menjadi solusinya. Terdapat banyak sekali metode low-light image enhancement yang tersedia, namun mana teknik yang lebih baik dalam pengenalan wajah masih menjadi perdebatan. Untuk menemukan metode low light image enhancement yang baik maka pada penelitian ini dirancang beberapa sistem pengenalan wajah dengan PCA sebagai ekstraksi fitur serta menerapkan SSR, MSR, AMSR, Dong, HE dan BPDHE sebagai metode low-light image enhancement. Dataset SOF dipilih sebagai target pengujian dikarenakan berisi citra dengan kondisi pencahayaan berbeda. Sebagai tujuan, keseluruhan sistem pengenalan wajah akan dibandingkan tingkat pengenalannya untuk menemukan metode low-light image enhancement terbaik. Berdasarkan pengujian dan analisis, ditemukan bahwa mayoritas sistem mengalami peningkatan tingkat pengenalan dengan diterapkannya metode low-light image enhancement, dan sebagai metode terbaik HE (76,28866 %) menunjukkan hasil yang paling signifikan, disusul dengan AMSR (75,25773 %), MSR (74,2268 %), SSR (69,07216 %), BPDHE (67,01031 %) dan Dong (63,91753 %).
ANALISIS METODE DECISION TREE DALAM MEMPREDIKSI KELULUSAN MAHASISWA Wulandari, Wulandari; Rosnelly, Rika; Wanayumini, Wanayumini
CSRID (Computer Science Research and Its Development Journal) Vol 13, No 3 (2021): CSRID OKTOBER 2021
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid.13.3.2021.131-140

Abstract

Perguruan tinggi juga menjadi tolak ukur keberhasilan mahasiswa itu sendiri.Bagi mahasiswa yang tidak dapat menyelesaikan studinya, prestasi yang tinggi juga menjadi penyebab kegagalan mahasiswa, salah satunya mahasiswa yang kurang aktif di lingkungan kampus. . Selain itu, yang sering menjadi penyebab adalah nilai rata-rata indeks prestasi kumulatif (IPK) yang rendah, selain itu kegagalan mahasiswa juga dapat disebabkan oleh moralitas dan disiplin mahasiswa yang kurang. Perlu dilakukan penelitian untuk memprediksi kelulusan mahasiswa, dengan menggunakan input data yaitu berupa data mahasiswa yang meliputi nilai tiap semester, peminatan, PKL, Skripsi 1 dan Skripsi 2.
Determining Bullying Text Classification Using Naive Bayes Classification on Social Media Ade Clinton Sitepu; Wanayumini Wanayumini; Zakarias Situmorang
Jurnal Varian Vol 4 No 2 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v4i2.1086

Abstract

Cyber-bullying includes repeated acts with the aim of scaring, angering, or embarrassing those who are targeted Cyber-bullying is happening along with the rapid development of technology and social media in society. The media and users need to filter out bully comments because they can indirectly affect the mental psychology that reads them especially directly aimed at that person. By utilizing information mining, the system is expected to be able to classify information circulating in the community. One of the classification techniques that can be applied to text-based classification is Naïve Bayes. The algorithm is good at performing the classification process. In this research, the precision of the algorithm's has been carried out on 1000 comment datasets. The data is grouped manually first into the labels "bully" and "not bully" then the data is divided into training data and test data. To test the system's ability, the classified data is analyzed using the confusion matrix method. The results showed that the Naïve Bayes Algorithm got the level of precision at 87%. and the level of area under the curve (AUC) at 88%. In terms of speed of completing the system, the Naïve Bayes Algorithm has a very good rate of speed with completion time of 0.033 seconds.
Analisis Hasil Pendukung Keputusan Mendapatkan Rumah Dinas Perusahaan Menggunakan Metode Analytical Hierarchy Process (AHP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Andi Zulherry; T S Gunawan; Wanayumini Wanayumini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2976

Abstract

The Bridgestone company is a company engaged in the plantation sector, currently it has employees of 230 staff/employees, every employee is entitled to an official residence, This requires the company to conduct a decision analysis to determine the official residence for each employee who will apply for the official housing facility. to reduce the level of lack of transparency and accuracy of data that can cause turmoil and gaps for each employee. Then an analysis of the results of decision support for obtaining a company official residence was carried out using the Analytical Hierarchy Process (Ahp) and Technique For Order Preference By Similarity To Ideal Solution (Topsis). The final results of the AHP method trial evaluation result in accurate data where there are 5 employees who are truly in the very feasible category to get an official residence. Whereas in the AHP method there are differences in the results found, where it is found that the number of employees is 1 person who should be in the feasible category but belongs to the very feasible category, so that the number generated from the TOPSIS method is 6 people. With these 2 methods, it can produce an accuracy value of around 60% by entering all the specified criteria.
Analisis Peneriman Sistem Ujian CBT Menggunakan Metode UTAUT (Unified Theory of Acceptance and Use of Technology) di Lingkungan Kampus Arjuna Ginting; Roslina Roslina; Wanayumini Wanayumini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2924

Abstract

Information system technology has been applied to all organizations, both organizations and non-profits, even though the development of information technology has been felt by the education sector. Slowly technology began to replace some of the work and activities carried out by humans. However, today's technology is still not perfectly applied. This study tries to get an idea of how the participants respond using computer technology in carrying out their exam process or better known as the Computer Based Test (CBT) based exam. Respondents were selected as many as 100 people who are willing to fill out the research questionnaire. To get good analysis results, this study uses a problem-solving method, namely by using the Unified Theory Acceptance and Use of Technology (UTAUT) with various constructs. As a result, the UTAUT method explains the acceptance of CBT users with the business expectation performance (PE) construct which has a significant effect on the acceptance and use of a system (BIUS). To measure the level of variation in the change in the independent variable on the dependent variable or the highest R-Square value in the UTAUT method is 73%. From these results it can be concluded that the UTAUT method is the best method used in this case study research.
Uji Kemiripan Kalimat Judul Tugas Akhir dengan Metode Cosine Similarity dan Pembobotan TF-IDF Indra Mawanta; T S Gunawan; Wanayumini Wanayumini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2935

Abstract

Deli Husada Health Institute is a health campus that has been established for 34 years, currently it has 30000 students, each student at the final level will submit a final project of study program every year, each student before doing his final project report must provide the title of an assignment report. Finally, to the study program, to reduce the level of similarity in the title of the student's final report, the study program usually conducts a manual check, the result that appears is that it is not effective in determining the title of the final project for students, so that it creates quite a lot of similarities between students. So that many final project reports look the same. With the above conditions, the Sentence Similarity Test of the Final Project Title was carried out with the Cosine Similarity Method and TF-IDF Weighting at the Deli Husada Delitua Health Institute Campus. At the end of the test results on the training data against the training data, the results obtained were 43% of the titles in Submitted is not eligible to be submitted again and 53% is eligible to be submitted as the title of the final project because it has high similarities to the title of the final project report. And get the average time 0.12117 in minutes
Penentuan Kelas Menggunakan Algoritma K Medoids Untuk Clustering Siswa Tunagrahita Husin Sariangsah; Wanayumini Wanayumini; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2547

Abstract

So far, the class placement of mentally retarded students is based on the age of entering the child when registering at SLB C Muzdalifah, the Intelligence Quotient (IQ) test has not been tried for mentally retarded students in classifying student classes. It is important to group mentally retarded children to make it easier for teachers to prepare programs and implement educational services. It is important for the school to understand that in mentally retarded children there are individual differences with very large variations. That is, being at almost the same age level (calendar age and mental age) and the same education level, in fact individual abilities differ from one another. Thus, of course, special strategies and programs are needed that are adapted to individual differences. This research was made to classify and analyze data mining for class clustering students with the K-Medoids algorithm to help group students who want to occupy classes according to their level of intellectual disability. From the grouping results obtained 3 clusters, which have the highest number of students is the moderate mental retardation class and the lowest cluster is mild mental retardation, the Muzdalifah special school can prepare classes based on grouping for teaching and learning activities.
Co-Authors Ade Clinton Sitepu Ade Clinton Sitepu Adelina, Mimi Chintya Alfitra, Andra Amanda, Windi Winona Andi Zulherry Annas Prasetio Annas Prasetio Ardana, Abdul Aziz Arjuna Ginting ayadi, B. Herawan H B. Herawan Hayadi Dedy Hartama Dedy Hartama Desi Irfan Desi Irfan Devy Pratiwi Dini Farhatun Doughlas Pardede Elisabeth S, Noprita Erica Rian Safitri Erlina Erlina Gea, Muhammad Nasri Hanani Hutabarat, Jamina Harahap, Sarwedi Hartama, Dedy Hartono Hartono Hasibuan, Cici Cahyati Husin Sariangsah Ichsan Firmansyah Indra Mawanta Indra Swanto Ritonga Irfan Sudahri Damanik Ismail, Juni isnaini, fitri JAKA KUSUMA Juni Ismail Karina Andriani Khoirunsyah Dalimunthe Lili Tanti Lili Tanti Lubis, Cindy Paramitha lvindra, Farhan A M yoggi saputra M. Ari Iskandar Margolang, Khairul Fadhli Masri Wahyuni Mhd Fauzan Yafi Miftahul Jannah Muhammad Azwar Al Ayyub Muhammad Fachrurrozi Nasution Muhammad Nasri Gea Muhammad Sadikin Muhammad Sayid Amir Ali Lubis Muhammad Zarlis Mutiara S. Simanjuntak Nasution, Ammar Yasir Novendra Adisaputra Sinaga NURLIANA NURLIANA P.P.P.A.N.W. Fikrul Ilmi R.H. Zer Prasetya, Hardi Rahma, Intan Dwi Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly RIKA ROSNELLY Rika Rosnelly Rika Rosnelly Rika Rosnelly, Rika Roesnelly, Rika Rohima, Rohima Roslina Roslina, Roslina Roslina, Roslina Sartika Mandasari Satria, Habib Selase, Septinur Sihombing, Rotua Simangunsong, Dame Lasmaria Sri Ayu Rosiva Srg Sugeng Riyadi Sugeng Riyadi Sumantri, Ekoliyono Wahyu T S Gunawan Tambunan, Fazli Nugraha Tammamah Lubis, Hartati Teddy Surya Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Triana Puspa handayani Triwanda, Eri Vicky Rolanda Wardana, Revo Wulandari, Wulandari Yuni Franciska Br Tarigan Zakarias Situmorang Zer, P.P.P.A.N.W. Fikrul Ilmi R.H.