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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Artificial Intelligence and Data Mining International Journal of New Media Technology Jurnal Sinergitas PkM & CSR Jurnal ULTIMATICS JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI International Journal Of Science, Technology & Management (IJSTM) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Prosiding Konferensi Nasional PKM-CSR Aptekmas : Jurnal Pengabdian Kepada Masyarakat International Journal of Electrical, Computer, and Biomedical Engineering (IJECBE)
Marlinda Vasty Overbeek
Universitas Multimedia Nusantara
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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.
Ant Colony Optimization for Traveling Tourism Problem on Timor Island East Nusa Tenggara Yampi R Kaesmetan; Marlinda Vasty Overbeek
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.9274

Abstract

Timor island consists of five districts and one city, namely Kupang District, South Central Timor District, North Central Timor, Belu District, Malaka District, and Kupang City. On the Timor island, it has natural tourist destinations, culinary tours, cultural and historical attractions most on the island of Timor. The Ant Colony Optimization (ACO) Algorithm is very unique compared to the other nearby search algorithm, this algorithm adopted because of Ant Colony who were looking for food from the nest to food sources by leaving a footprint called Pheromone. Mapping system algorithm using ant, tourist sites can show the shortest route between two points is desired. Ants algorithm proved to be applied in determining the optimum route, but still has the disadvantage of dependence on the parameter value is not maximized. From the test results based on parameters of the cycle and the number of ants affects the simulation time, for ant algorithm parameters. From the test results based on the parameters, α and β affects, number of node, the simulation time and the shortest distance varying toward the destination even if the starting location and ending on the same location.
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 
PELATIHAN DASAR MEMBATIK DAN TIE DYE KEPADA DHARMA WANITA PERSATUAN (DWP) LEMBAGA PEMBINAAN KHUSUS ANAK (LPKA) KELAS II JAKARTA Fenina Adline Twince Tobing; Indiwan Seto Wahjuwibowo; Eunike Endariahna Surbakti; Marlinda Vasty Overbeek
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 4 (2021): Peran Perguruan Tinggi dan Dunia Usaha dalam Mewujudkan Pemulihan dan Resiliensi Masya
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37695/pkmcsr.v4i0.1266

Abstract

Kegiatan pelatihan membatik adalah salah satu wujud gerakan kembali mencintai batik yang merupakan seni tradisional asli Indonesia dan perlu untuk dilestarikan agar tidak punah. Dalam perkembangan potensi ketrampilan khusus tentunya seni kerajinan diharapkan juga megikuti kreatifitas yang tujuannya hasil karya pelatihan tidak berkesan hanya karya kreatifitas biasa atau stagnan saja, tetapi perlu melakukan pengembangan ide-ide yang fress, inovatif dan trend yang karya pelatihan bisa menjadi karya fungsional. Dalam pelatohan membati ini harapannya dapat menghasilkan karya produk unggulan sampai purna jual yang digandrungi. Pelatihan membatik ini bertujuan untuk menambah keterampilan anggota Dharma Wanita, dan diharapkan dapat mengembangkan batik menjadi ikon produk kerajinan didaerah kita. Selain itu, melalui pelatihan ini nantinya juga dapat menciptakan lapangan pekerjaan baru bagi kalangan perempuan dan diharapkan dapat menularkan ilmu yang didapat oleh anggota DWP LPKA Kelas II Jakarta. Diharapkan dengan adanya pelatihan Membatik dan Tie Dye ini, anggota DWP punya jiwa wirausaha dan wiraswasta membuat Membatik dan Tie Dye . Ini juga menjadi bagian kita untuk melestarikan produk batik dan pengembangannya seperti Tie Dye beserta tekniknya. Tidak masalah jika seseorang tidak memiliki latar belakang kerajianan membatik, namun tetap mampu mengikuti dan membuat Membatik dan Tie Dye yang baik dan indah. Kata Kunci : Membatik, Tie Dye, Pelatihan
Small Timescaled Data for Covid-19 Prediction with RNN-LSTM in Tangerang Regency Sagita Sasmita Wijaya; Marlinda Vasty Overbeek
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 1 (2023): Maret 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i1.21676

Abstract

Throughout the pandemic, many people have become familiarised with the new type of virus that has been spreading throughout the world, called the Coronavirus. On the 2nd of March, the year 2020, the Indonesian government had announced the identification of first Covid-19 case in Indonesia. With the arrival of Covid-19, and its spreading across all the provinces of Indonesia, the number of positive cases keeps growing even in the present day. Tangerang Regency is one of the areas that has opaqued citizens in the Banten Province. The purpose of this research is to discuss how to predict the sum of Covid-19 cases in the Tangerang Regency using the RNN-LSTM method. Although this method is very eloquent if used to perform a sequential task, its complexity and loss of gradient can make this model difficult to be trained, hence resulting in the use of the Long Short-Term Memory (LSTM) to reduce these weaknesses and help the RNN to look back on past data. This research uses Python as the programming language and Jupyter Notebook for the visualization of the results of the prediction. Therefore, the prediction model has been evaluated using various computational methods, such as RMSE with its error percentage of 0.05, and MSE and MAE with the same error percentage of 0.03 with the loss of their models being 9.6793e-04.
WEB-BASED DESIGN OF DHARMA WANITA ASSOCIATION (DWP) LPKA CLASS II JAKARTA FINANCIAL REPORT APPLICATION Fenina Adline Twince Tobing; Eunike Endariahna Surbakti; Marlinda Vasty Overbeek
Jurnal Sinergitas PKM & CSR Vol 6, No 2 (2022): OCTOBER
Publisher : Universitas Pelita Harapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19166/jspc.v6i2.6360

Abstract

Lembaga Pembinaan Khusus Anak (LPKA)Class II Jakarta, there is a Dharma Wanita Association (DWP) Jakarta Class II LPKA organization whose members are all the wives of civil servants and also female civil servants who serve in that place. One of the keys to the success of an organization is being able to manage finances well, one of which is reflected in routinely making financial reports every month. Not only important for large companies, financial reports that are compiled and updated regularly are also important for MSME businesses, online businesses or organizations. It doesn't matter if someone doesn't have an educational background in accounting, but is still able to make complete financial reports.Technological advances encourage DWP LPKA Class II Jakarta to be able to carry out their work in terms of financial reporting to make it easier and more efficient by using applications that we have researched and implemented through the Multimedia Nusantara University (UMN) Community Service Program (PKM) in 2022 and DWP LPKA Class II Jakarta members received this form of community service with great enthusiasm. Through this PKM activity it is hoped that there will be an increase in the application of science and technology in society (mechanisms, IT, management) and for improving community values from a social and financial management perspectiveabstract in bahasaLembaga Pembinaan Khusus Anak (LPKA) Kelas II Jakarta, terdapat organisasi Dharma Wanita Persatuan (DWP) LPKA Kelas II Jakarta yang beranggotakan seluruh Istri PNS dan juga PNS wanita yang bertugas di tempat tersebut. Salah satu kunci sukses sebuah organisasi adalah mampu mengelola keuangan dengan baik, salah satunya tercermin dari rutin membuat laporan keuangan setiap bulan. Tidak hanya penting bagi perusahaan besar, laporan keuangan yang disusun dan diperbaharui secara berkala juga penting dilakukan oleh bisnis UMKM, usaha online atau organisasi. Tidak masalah jika seseorang tidak memiliki latar belakang pendidikan akuntansi, namun tetap mampu membuat laporan keuangan yang lengkap.Kemajuan Teknologi mendorong untuk membantu DWP LPKA Kelas II Jakarta untuk dapat melaksanaan pekerjaan mereka dalam hal pelaporan keuangan agar lebih mudah dan efisien dengan menggunakan aplikasi yang telah kami teliti dan kami implementasikan melalui Program Pengabdian Kepada Masyarakat (PKM) Universitas Multimedia Nusantara (UMN) tahun 2022 dan anggota DWP LPKA Kelas II Jakarta memerima bentuk pengabdian masyarakat yang kami lakukan dengan sangat antusias. Melalui kegiatan PKM ini diharapkan adanya peningkatan penerapan IPTEK di masyarakat (mekanisme, IT, manajemen) dan untuk perbaikan tata nilai masyarakat dari segi sosial dan manajeme keuangan.
Innovations in Software Configuration: Introducing a Data Comparison Tool Based on the Myers Diff Algorithm Augustino, Lorentzo; Kusnadi, Adhi; Vasty Overbeek, Marlinda
International Journal of Science, Technology & Management Vol. 4 No. 6 (2023): November 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i6.974

Abstract

In the realm of software project development, it's not uncommon for changes to emerge at various stages of a project's lifecycle. Such alterations can manifest in virtually every facet of the software development process, from conceptual design decisions down to the minutiae of the source code. To proficiently manage and track these dynamic changes, professionals turn to a specialized toolset known as Software Configuration Management (SCM). One of the standout features that SCM tools bring to the table is the 'diff' capability. This functionality allows developers to identify and review the disparities between two versions of source code. Recognizing the importance and utility of this feature, the primary objective of this research is to create an advanced diff application. This application, by leveraging the Myers Diff algorithm, is meticulously designed to pinpoint and showcase differences in characters between two sets of text-based data. Moreover, it accentuates these differences by visually highlighting the contrasting characters between the two datasets. To ensure the reliability and accuracy of this newly developed tool, we undertook a series of validation tests. We juxtaposed the results from our application against those from a comparable existing tool. Impressively, the discrepancies in results were minimal, with a marginal difference of just 1%. This suggests not only the utility but also the precision of our application in real-world software development scenarios.
Co-Authors Abigail, Tesalonika Adhi Kusnadi Aditiya, Yoga Alex Kurniadi Augustino, Lorentzo Dennis Gunawan, Dennis Erasmus Ndolu, Fajar Henri Eunike Endariahna Surbakti Feliana, Ferlinda Fenina Twince Tobing Glennardy, Bryan Hin, Alexander Moya Kaesmetan, Yampi R Khaeruzzaman, Yaman kusnadi, adhi Mediyawati, Niknik Moeljono Widjaja Ni Made Satvika Iswari Nusantara, Samiaji Bintang Pomalingo, Suwito Prasetya, Syarief Gerald Prawira, Oqke Remerta Noni Naatonis Ruki Harwahyu Sagita Sasmita Wijaya Suryadibrata, Alethea Sutomo, Rudi Tobing, Fenina Adline Twince Wahjuwibowo, Indiwan Seto Yaman Khaeruzzaman