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Analisis Daya Tahan Keamanan Data Pada Steganografi Berbasis Teks Dalam Struktur Kalimat Bahasa Indonesia R. Fanry Siahaan; preddy marpaung; ibnu febrian; widia putri
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 22, No 2 (2023): Agustus 2023
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v22i2.8773

Data security in text-based steganography needs to be analyzed in depth to ensure the sustainability and security of the method. The purpose of this research is to analyze the durability of data security in text-based steganography. The analysis approach consists of steps to identify and evaluate the vulnerability of text steganography methods with Indonesian sentence patterns. The first step is to review previous relevant work in this field to understand the vulnerabilities that have been identified previously. The text insertion model carried out is dictionary-based as many as 1,929 words which are divided into seven-word classes that correspond to sentence patterns in Indonesian, namely adj (adjective), adv (adverb), nom (noun), num (numeral), par (particle), pro (pronominal) and ver (verb). Each word class is organized into sentence patterns and each has the same bit length of eight bits. The results of the durability analysis show that input data with a length of one word still can be hacked if the message insertion process with a choice of short sentence patterns. Whereas with a choice of sentence patterns that are more than two words it will start to be difficult to hack and even cannot be hacked because the number of possibilities is very large and even infinite or infinity.

PENERAPAN METODE MOORA DALAM MENENTUKAN PERUMAHAN SUBSIDI TERBAIK DI DAERAH SEI MENCIRIM Preddy Marpaung; Dedi Candro Parulian Sinaga; Baringin Sianipar; Muliati Laia
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i2.301

Perumahan subsidi merupakan program pemerintah sebagai salah satu alternatife untuk masyarakat yang berpenghasilan rendah supaya kebutuhan primer masyarakat seperti rumah terpenuhi terutama bagi masyarakat yang sudah berumah tangga. Menurut website penyedia informasi rumah bersubsidi, bahwa jumlah perumahan bersubsidi terus bertambah setiap tahunya. Salah satunya di daerah Sei Mencirim yang terdapat puluhan perumahan subsidi sebagai alternatife bagai masyarakat untuk memiliki rumah. Namun proses menentukan perumahan subsidi terbaik di daerah sei mencirim sangat sulit bagi masyarakat yang ingin mengambil rumah subsidi disana karena ketidak tahuan atau tidak adanya informasi mengenai perumahan subsidi terbaik disana. Oleh karena itu dibutuhkan sebuah metode dalam mendukung pengabilan keputusan menentukan perumahan subsidi terbaik bagi masyatakat yang ingin berdomesili di daerah Sei Mencirim. Peneliti menerapkan metode Multi-Objective Optimization by Ratio Analysis Atau biasa disingkat dengan metode MOORA dalam menentukan perumahan subsidi terbaik di daerah Sei Mencirim. Alasan peneliti menggunakan metode ini, karena beberapa peneliti terdahulu banyak menggunakan sistem pendukung keputusan dengan menggunakan metode moora dalam memecahkan permasalahan dalam pengambil keputusan.

Sistem pendukung keputusan penilaian kepuasan masyarakat terhadap pelayanan di pt. Putri manalu bersaudara menggunakan metode oreste Baringin Sianipar; Preddy Marpaung; Dedi Candro Parulian Sinaga; Murniati Laia; Muliati Muliati
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 6 No. 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v6i1.406

Sistem Pendukung Keputusan merupakan sistem yang mampu menyediakan dara informasi. Pengambilan keputusan dilakukan secara sistematis, mengumpulkan fakta-fakta, kemudian ada penentuan yang matang dari alternatif yang dihadapi, dan selanjutnya mengambil tindakan yang menurut perhitungan merupakan tindakan yang paling tepat. Sistem Pendukung Keputusan lebih ditujukan untuk mendukung manajemen dalam melakukan pekerjaan yang bersifat analitis dalam situasi yang kurang terstruktur dengan kriteria yang kurang jelas. Metode Oreste adalah salah satu metode pengambilan keputusan multi criteria atau yang lebih dikenal dengani stilah Multi Criteria Decision Making (MCDM). MCDM digunakan untuk menyelesaikan permasalahan dengan kriteria yang bertentangan untuk dapat mengambil keputusan untuk mencapai keputusan akhir.

Penerapan Data Mining Untuk Pengelompokan Kepadatan Penduduk Kabupaten Deli Serdang Menggunakan Algoritma K-Means Preddy Marpaung; Ibnu Pebrian; Widia Putri
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 6 No. 2 (2023): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar

Kepadatan penduduk diberbagai besar seperti Kabupaten Deli Serdang akan mengakibatkan banyak dampak yang akan dialami oleh masyarakat. Namun sering kali masyarakat baik individu atau kelompok yang ingin betempat tinggal maupun berdomisili di Kabupaten Deli Serdang memilih lokasi tempat tinggalnya semaunya tanpa mengetahui klasifikasi kepadatan penduduk yang ada, sehingga bisa mendapatkan dampak masalah yang besar bagi masyarakat tersebut atau cenderung berada dilingkaran permasalahan yang begitu besar yang akan dihadapinya jika tidak tahu memilih lokasi tempat tinggal yang akan ditempati masyarakat tersebut. Ketidaktahuan masyarakat akan lokasi kepadatan penduduk yang ada di kabupaten Deli Serdang karena tidak adanya pengetahuan atau informasi tentang pengelompokan kepadatan penduduk. Maka perlu dilakukan pengelompokan kepadatan penduduk sebagai pengetahuan baru kepada masyarakat untuk menghidari maupun mengurangi dampak yang akan dialami bagi masyarakat yang ingin bertempat tinggal di daerah Deli Serdang. Pengelompokan kepadatan penduduk ini akan dikelompokan kedalam 3 kelompok (cluster) menggunkan algoritma K-Means , yaitu sangat padat (cluster1), Padat (cluster2), dan sedang (cluster3). Dengan hasil penerapan algoritma K-Means dapat menghasilkan, bahwa dari 22 kecamatan yang ada, terdapat 3 kecapatan Sangat Padat (cluster1), 4 kecamatan padat (cluster2), dan 15 kecamatan sedang (cluster3). Sehingga dengana adanya cluster kepadatan penduduk ini akan memberikan pengetahuan baru kepada masyarakat baik secara individu maupun kelompok yang melakukan urbanisasi, transmigrasi, dan imigrasi karena faktor pekerjaan, faktor ingin menetap, maupun faktor lainnya , sehingga menghindari atau meminimalisi dampak permasalahan karena faktor kepadatan penduduk.

SOSIALISASI DAN BIMBINGAN PEMBUATAN LAPORAN KEUANGAN PERHOTELAN BERBASIS KOMPUTERISASI Preddy Marpaung; R.Fanry Siahaan; Arta Putri Simalanggo; Daniel Pariang
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2023): Volume 4 Nomor 3 Tahun 2023
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v4i3.17354

Perkembangan zaman dewasa ini yang sudah serbah digital atau serba komputerisasi harus bisa dimanfaatkan semua kalangan mempercepat segala pekerjaan baik dipemerintahan, akademisi, maupun bidang usaha atau perusahan. Namun belum semua pihak usaha melakukan hal itu, salah satunya hotel halay inn dalam pembuatan laporan keuangan. Dimana pihak keuangan mereka masih melakukan pembuatan laporan keuangan secara manual atau tulis tangan.Oleh karena itu, melalui pengabdian kepada masyarakat ini dibuatlah sosialisasi dan bimbingan pembuatan laporan keuangan perhotelan berbasis komputerisasi dalam hal ini penggunaan aplikasi Microsoft Excel untuk hotel halay inn, Deli Serdang.. Dengan adanya sosialisasi dan bimbingan pembuatan laporan keuangan perhotelan berbasis komputer dengan cara pengenalan aplikasih, melakukan pelatihan, bimbingan dan pengujian, pihak hotel sudah memiliki ketrampilan dalam pembuatan laporan keuangannya dengan baik. Sehingga sangat efektif dalam mendukung penyelesaian tugas kedepannya secara khusus bagian keuangan hotel halay inn..

MOORA Method Analysis For Decision Support System Determining the Best Subsidized Housing in Tanjung Morawa Marpaung, Preddy; Suci Amalia Sari; Fadya Larasati; Pasaribu, Sutrisno Arianto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.702

Subsidized housing is a government program as an alternative for low-income communities so that the primary needs of the community such as housing are met, especially for people who are already married. One of the areas where subsidized housing is located is the Tanjung Morawa area, Deli Serdang, North Sumatra. However, the problem for the community or employees who want to find a residence to live in the Tanjung Merowa area is the difficulty in determining a subsidized house that suits their wishes, such as comfort, housing price, house model, strategic location. The factor that makes it difficult for people to determine a residential house is because there is no knowledge or information about which subsidized house is the best according to the criteria to be occupied. Therefore, it is necessary to apply a method to analyze to determine the best subsidized house, the Objective Optimization on the basis of Ratio Analysis Simple (MOORA) method is applied to analyze the decision support system to determine the best subsidized house in Tanjung Morawa, where the MOORA method is able to produce the best subsidized house based on the highest value or ranking, where the highest value is ranking 1 alternative 6, Mulia Residence housing.

Penerapan Algoritma K-Means Clustering Untuk Pemetaan Kepadatan Penduduk Berdasarkan Jumlah Penduduk Kota Medan Marpaung, Preddy; Siahaan, R. Fanry
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.343

Population density in a large city such as Medan will have many impacts on the community. However, often people, either individuals or groups who want to live or live in the city of Medan, choose their location at will without knowing the existing population density classification, so that they can have a big problem impact on the community or tend to be in a circle of huge problems they will face. if you do not know, choose the place of residence that the community will occupy. The community's ignorance of the location of population density in the city of Medan is due to the absence of knowledge or information on population density mapping. So it is necessary to map the population density as new knowledge for the community to avoid or reduce the impact that will be experienced by people who want to live or reside in the city of Medan. This population density mapping will be grouped into 3 groups (clusters) using the K-Means Cluster algorithm, namely very dense (cluster1), dense (cluster2), and medium (cluster3). The results of population density mapping in the city of Medan, namely the very densely populated area of 121 kelurahan, the densely populated area is 30 sub-districts, and areas are no longer found in the city of Medan.

Pemilihan Calon Manager Dari Pegawai Berprestasi Menggunakan Metode Profile Matching Pada CV. Glofacia Oceanic Parulian Sinaga, Dedi Candro; Sianipar, Baringin; Marpaung, Preddy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.256

At this time, the company CV. Glofacia Oceanic in Medan City is looking for employees to be appointed as Managers and for the Selection of Candidates for Managers who have difficulties in selecting employees who have good work performance within the company, then based on work goals and attendance, which are evaluation materials for employee appraisals to become managers. For employees who are elected will be managers in the CV. Glofacia Oceanic. The number of employees becomes the owner of difficulties for company owners in selecting employees who are appointed to become managers, so it cannot be denied that in the selection of outstanding employees at CV. Oceanic Glofacia is often done not objectively. To find out which internal employees of the company are performing well, it is necessary to assess the performance of the employees. At the time of an assessment in choosing a prospective manager, including using a decision support system to help solve a problem. The method that will be used to select prospective internal managers is the Profile Matching method with the application of this method in selecting prospective managers, so there are no errors in decision making. So it is hoped that the Profile Matching Method can provide value objectively to employees and assist the company's director in providing employee performance appraisals.

Penerapan Algoritma K-Means Clustering Untuk Pemetaan Kepadatan Penduduk Berdasarkan Jumlah Penduduk Kota Medan Marpaung, Preddy; Siahaan, R. Fanry
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.343

Population density in a large city such as Medan will have many impacts on the community. However, often people, either individuals or groups who want to live or live in the city of Medan, choose their location at will without knowing the existing population density classification, so that they can have a big problem impact on the community or tend to be in a circle of huge problems they will face. if you do not know, choose the place of residence that the community will occupy. The community's ignorance of the location of population density in the city of Medan is due to the absence of knowledge or information on population density mapping. So it is necessary to map the population density as new knowledge for the community to avoid or reduce the impact that will be experienced by people who want to live or reside in the city of Medan. This population density mapping will be grouped into 3 groups (clusters) using the K-Means Cluster algorithm, namely very dense (cluster1), dense (cluster2), and medium (cluster3). The results of population density mapping in the city of Medan, namely the very densely populated area of 121 kelurahan, the densely populated area is 30 sub-districts, and areas are no longer found in the city of Medan.

Pemilihan Calon Manager Dari Pegawai Berprestasi Menggunakan Metode Profile Matching Pada CV. Glofacia Oceanic Parulian Sinaga, Dedi Candro; Sianipar, Baringin; Marpaung, Preddy
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.256

At this time, the company CV. Glofacia Oceanic in Medan City is looking for employees to be appointed as Managers and for the Selection of Candidates for Managers who have difficulties in selecting employees who have good work performance within the company, then based on work goals and attendance, which are evaluation materials for employee appraisals to become managers. For employees who are elected will be managers in the CV. Glofacia Oceanic. The number of employees becomes the owner of difficulties for company owners in selecting employees who are appointed to become managers, so it cannot be denied that in the selection of outstanding employees at CV. Oceanic Glofacia is often done not objectively. To find out which internal employees of the company are performing well, it is necessary to assess the performance of the employees. At the time of an assessment in choosing a prospective manager, including using a decision support system to help solve a problem. The method that will be used to select prospective internal managers is the Profile Matching method with the application of this method in selecting prospective managers, so there are no errors in decision making. So it is hoped that the Profile Matching Method can provide value objectively to employees and assist the company's director in providing employee performance appraisals.

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