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All Journal InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Rahmat Widia Sembiring
Politeknik Negeri Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

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Identifikasi Predikat Hasil Pengelompokan Data Kualitas Udara dengan Menggunakan Affinity Propagation dan Silhouette Coefficient Maulidya Rahmah; Ade Candra; Rahmat Widia Sembiring
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.4670

Abstract

Penelitian ini bertujuan untuk mengidentifikasi pengelompokan data kualitas udara dan mendapatkan predikat hasil pengelompokan kualitas data udara tersebut. Data yang digunakan adalah data kualitas udara Kota Pekanbaru yang diperoleh dari pengolahan data Laboratorium Udara Pemerintah Kota Pekan Baru dengan rentang waktu tahun 2014, 2015, dan 2016. Penulis menerapkan Affinity Propagation untuk melakukan klasterisasi pada data tersebut dan menghitung jumlah klaster yang dihasilkan. Berdasarkan penerapan Affinity Propagation pada data kualitas udara Kota Pekanbaru dengan pengujian nilai damping factor dari rentang 0.5 sampai 0.95 diperoleh 5 klaster saat damping factor bernilai 0.95. Sementara jumlah klaster terbanyak adalah 156 saat damping factor bernilai 0.55. Nilai rata-rata Silhouette Coefficient dari data yang diujikan adalah 0.264, dan jika dikategorikan maka kualitas klaster yang dihasilkan berdasarkan predikat nilai Silhouette Coefficient adalah Weak Structure.
Reverse Tracking Graph Based on Dynamic Path Planning Devanta Abraham Tarigan; Muhammad Zarlis; Rahmat Widia Sembiring
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 1 (2021): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i1.4355

Abstract

This paper gives substance to Dynamic Path Planning focusing on reverse tracking method. The development of this method are proposed and expected to reduce the algorithm scanning the whole graph repeatedly. In this paper, several approachment will be presented sequentially. First, analysis and modeling of the obstacle and environment, pre-path planning, Depth First Search for availability path planning, and improvement of the Dijkstra algorithm for the shortest path. There-in the proposed model is defined by adopting the reverse feature in the Depth First Search algorithm in the finding of the availability path on the graph.
Analisa Terhadap Perbandingan Algoritma Decision Tree Dengan Algoritma Random Tree Untuk Pre-Processing Data Saifullah Saifullah; Muhammad Zarlis; Zakaria Zakaria; Rahmat Widia Sembiring
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 2 (2017): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v1i2.41

Abstract

Preprocessing data is needed some methods to get better results. This research is intended to process employee dataset as preprocessing input. Furthermore, model decision algorithm is used, random tree and random forest. Decision trees are used to create a model of the rule selected in the decision process. With the results of the preprocessing approach and the model rules obtained, can be a reference for decision makers to decide which variables should be considered to support employee performance improvement
Analisa Terhadap Perbandingan Algoritma Decision Tree Dengan Algoritma Random Tree Untuk Pre-Processing Data Saifullah Saifullah; Muhammad Zarlis; Zakaria Zakaria; Rahmat Widia Sembiring
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 2 (2017): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (547.436 KB) | DOI: 10.30645/j-sakti.v1i2.41

Abstract

Preprocessing data is needed some methods to get better results. This research is intended to process employee dataset as preprocessing input. Furthermore, model decision algorithm is used, random tree and random forest. Decision trees are used to create a model of the rule selected in the decision process. With the results of the preprocessing approach and the model rules obtained, can be a reference for decision makers to decide which variables should be considered to support employee performance improvement
Co-Authors Ade Candra Devanta Abraham Tarigan Maulidya Rahmah Muhammad Zarlis Muhammad Zarlis Saifullah Saifullah Zakaria Zakaria