Article Per Year (5 Year)
p-Index From 2019 - 2024
1.376
P-Index
This Author published in this journals
All Journal Indonesian Journal of Artificial Intelligence and Data Mining Jurnal ULTIMATICS JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Aptekmas : Jurnal Pengabdian Kepada Masyarakat International Journal of Electrical, Computer and Biomedical Engineering
Marlinda Vasty Overbeek
Universitas Multimedia Nusantara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry 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 Transportation Veterinary Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
APLIKASI MOBILE LAYANAN ADMINISTRASI DESA/KELURUHAN UNTUK LAYANAN DI ERA PANDEMI COVID 19 Yaman Khaeruzzaman; Adhi Kusnadi; Marlinda Vasty Overbeek; Moeljono Widjaja; Dennis Gunawan; Ni Made Satvika Iswari
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 5 No 2 (2022): APTEKMAS Volume 5 Nomor 2 2022
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v5i2.4721

Abstract

Administrative services are a routine activity carried out by village and/or sub-district offices andallow for mobility and crowding of residents which should be avoided during the current pandemic.The administrative service procedure requires a series of approvals from the head of the RT, headof the RW, the apparatus and the head of the village/kelurahan so it takes time. Administrativeservices will be very good if they can be carried out electronically using devices that are commonlyowned by citizens such as smart cell phones so that they can be carried out faster, complying withrecommendations to avoid mobility and crowds and the slogan "stay at home" can be implemented.The stages of community service activities carried out started from needs analysis and systemdesign using the waterfall model development method. This activity will be continued at theimplementation stage so that it can be used widely for the community. The development andinstallation of village administration service applications is planned to be based on Android withcentralized data in the cloud. The system design is then verified and validated by a number of users,especially from the kelurahan because those parties are the ones who know the existing serviceprocess. The verification test states that the service process is in accordance with what is neededand the validation test states that the design is in accordance with the user's needs.
Peningkatan Kemampuan Membuat Surat dan Laporan Menggunakan Ms.Word pada Siswa MA Raudatul Irfan Adhi Kusnadi; Marlinda Vasty Overbeek; Yaman Khaeruzzaman; Moeljono Widjaja; Alethea Suryadibrata
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol 1 No 2 (2020)
Publisher : Politeknik Dharma Patria

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v1i2.341

Abstract

Kegiatan pelatihan ini bertujuan untuk meningkatkan kemampuan siswa/siswi MA Raudatul Irfan dalam penggunaan MS.Office, terutama MS.Word. Peningkatan kemampuan siswa/siswi akan meningkatkan peluang mereka untuk memasuki jenjang pendidikan lebih tinggi dan dunia kerja. Kegiatan ini dilaksanakan selama dua hari dimulai dari pagi jam 8.00 WIB sampai selesai. Banyaknya jumlah siswa/siswi yaitu berjumlah 80 orang ditambah staf dan guru sebanyak 10 orang, maka untuk meningkatkan efektifitas dalam pelatihan di laboratorium Kampus UMN, peserta dibagi dua kelompok sebanyak 40 orang untuk setiap kelasnya. Metode yang digunakan dalam pelatihan ini adalah demontrasi dan contoh. Pada awal sesi peserta akan diperkenalkan pada komputer, sistem operasi, dan MS.Office, kemudian diakhiri dengan evaluasi dan latihan. Dengan mengikuti pelatihan ini, siswa/siswi akan meningkat kemampuannya dalam menggunakan komputer terutama MS.Office dengan tujuan utama membuat surat dan laporan menggunakan MS.Word. Secara keseluruhan kegiatan ini berlangsung dengan lancar dan baik, dan hasil latihan/evaluasi yang baik dengan rata-rata indeks prestasi 2,7 dari skala 1-4
Digital Image Processing using Texture Features Extraction of Local Seeds in Nekbaun Village with Color Moment, Gray Level Co Occurance Matrix, and k-Nearest Neighbor Yampi R Kaesmetan; Marlinda Vasty Overbeek
Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i2.2038

Abstract

The problem in determining the selection of corn seeds for replanting, especially maize in East Nusa Tenggara is still an important issue. Things that affect the quality of corn seeds are damaged seeds, dull seeds, dirty seeds, and broken seeds due to the drying and shelling process, which during the process of shelling corn with a machine, many damaged and broken seeds are found. So far, quality evaluation in the process of classification of the quality of corn seeds is still done manually through visible observations. Manual systems take a long time and produce products of inconsistent quality due to visual limitations, fatigue, and differences in the perceptions of each observer. The selection of local maize seeds in Timor Island, East Nusa Tenggara Province, especially in Nekbaun Village, West Amarasi District with feature extraction with a color moment shows that the mean, standard deviation and skewness features have an average validation of 88% and use the GLCM method which shows the neighbor relationship. Between the two pixels that form a co-occurrence matrix of the image data, namely GLCM, it shows that the features of homogeneity, correlation, contrast and energy have an average validation of 70.93%. The k-Nearest Neighbor (k-NN) algorithm is used in research to classify the image object to be studied. The results of this study were successfully carried out using k-Nearest Neighbor (k-NN) with the euclidean distance and k = 1 with the highest extraction yield of 88% and the results of GLCM feature extraction for homogeneity of 75.5%, correlation of 78.67%, contrast of 65.75 % and energy of 63.83% with an average accuracy of 70.93%.
Classification of Metagenome Fragments With Agglomerative Hierarchical Clustering Alex Kurniadi; Marlinda Vasty Overbeek
Ultimatics : Jurnal Teknik Informatika Vol 13 No 2 (2021): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v13i2.2180

Abstract

Unlike genomics which study specifically culturable microorganisms, metagenomics is a field that studies microorganic samples retrieved directly from the environment. Such samples produce widely varying fragments when sequenced, many of which are still unidentified or unknown. Assembly of these fragments in the goals of identifying the species contained among them are thus prone to make said goals more difficult, so it becomes necessary for binning techniques to come in handy while trying to classify these mixed fragments onto certain levels in the phylogenetic tree. This research attempts to implement algorithms and methods such as k-mers to use for feature extraction, linear discriminant analysis (LDA) for dimensionality reduction, and agglomerative hierarchical clustering (AGNES) for taxonomic classification to the genus level. Experimentation is done across different objective measurements, including the length of the observed metagenome fragment that spans from 0,5 Kbp up to 10 Kbp for both the 3-mer and 4-mer contexts (k = 3 and k = 4). The averaged validity scores of the resulting data clusters generated from both the training and test sets, computed with the silhouette index metric, are 0.6945 and 0.0879 for the 3-mer context, along with 0.5219 and 0.1884 for the 4-mer context.
Data Train Reduction on Data Image With K Support Vector Nearest Neighbor (Case Study : Maize Leaf Image) Marlinda Vasty Overbeek; Yampi R Kaesmetan
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 2 (2020): Spetember 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i2.10451

Abstract

In this study, we applied the K Support Vector Nearest Neighbor algorithm to reduce data train on data image. The data image that we used is the maize leaves image infected with fungi and healthy maize leave. The aim of data train reduction in this study is to get faster and more accurate prediction results. This because by using the K Support Vector Nearest Neighbor algorithm, a support vector that is formed from the algorithm really characterize the objective function of the problem. The accuracy obtained from this study is 0.20 or 20% mean error for the value of nearest neighbor K  = 3 and using K Nearest Neighbor as a model construction algorithm. The error value is smaller than when we compared to the construction of the model without performing data train reduction. The error value if not doing any reduction is 0.209 or 20.9%. Whereas in terms of time efficiency, working with the K Support Vector Nearest algorithm is 24 seconds faster than without performing data train reduction 
Sistem Identifikasi Titik Kritis Halal Menggunakan Algoritma Forward Chaining Alexander Moya Hin; Adhi Kusnadi; Marlinda Vasty Overbeek; Oqke Prawira; Yaman Khaeruzzaman; Syarief Gerald Prasetya
JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Vol 8, No 1 (2023): Januari 2023
Publisher : Universitas Al Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/sst.v8i1.1285

Abstract

Halal products are obligatory to be used by people who are Muslim. When viewed in terms of the number of the Muslim population in the world and Indonesia, halal products have very potential economic opportunities. However, halal products have the risk of becoming non-halal if the accompanying process and storage do not follow halal rules. Therefore, it is necessary to identify the critical halal point, the point where the potential for such change occurs. So far, identification is made manually, of course there will be opportunities for identification errors to happen and it will take a relatively long time. To overcome these problems, identification can use a computer-based system. Forward chaining is an algorithm that is suitable for identifying halal points, because in SJH LPPOM MUI there is a decision tree for identifying halal critical points which is carried out in the same forward sequence as the forward chaining algorithm process flow. The development of a halal critical point identification system is carried out using the Software Development Life Cycle V-model method, the PHP programming language and the MySQL Database Management System. The system was successfully tested using Whitebox testing, including unit testing, integration testing, and overall system testing. Then testing using Blackbox testing techniques by comparing the results of identifying critical points using the system with the results of identifying critical points manually producing the same results. User satisfaction testing was also carried out using the End User Computing Satisfaction method and obtained an average satisfaction score of 86.53%Keywords – halal products, critical halal point, AI, forward chaining
Multichannel Slotted ALOHA Simulator Design for Massive Machine-Type Communication (mMTC) on 5G Network Ferlinda Feliana; Ruki Harwahyu; Marlinda Vasty Overbeek
International Journal of Electrical, Computer, and Biomedical Engineering Vol. 1 No. 2 (2023)
Publisher : Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62146/ijecbe.v1i2.8

Abstract

Massive Machine-type Communication (mMTC) is one of the main service scenarios in 5G. At the time of initializing the connection to the base station, the MTC machines will make a connection request via the random access procedure. One of the schemes of random access procedure for handling this connection request is similar to how multichannel slotted ALOHA works. Multichannel slotted ALOHA itself is a development of the slotted ALOHA scheme which originally has only a single channel. At the initial state of mMTC, there will be an explosion of the number of demands to the available channels. Given the number of machines that will be connected, the likelihood of a collision on the same channel increases. As a result, the probability of failure also increases. The system's configuration has an impact on the likelihood of success and the time it takes to achieve it. The number of channels influences the likelihood of collisions, the backoff window influences the transmission distribution in each slot, and the maximum transmission limits the ability of device retransmission. These three arrangements have an impact on one another. The simulator build in this research is expected to make it easier for researchers to optimize multichannel slotted ALOHA configurations in 5G to handle the surge in access demands from mMTC devices.
Co-Authors Adhi Kusnadi Alethea Suryadibrata Alex Kurniadi Alexander Moya Hin Dennis Gunawan Ferlinda Feliana Harwahyu, Ruki Kaesmetan, Yampi R Moeljono Widjaja Ni Made Satvika Iswari Oqke Prawira syarief gerald prasetya Yaman Khaeruzzaman