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All Journal International Journal of Advances in Intelligent Informatics Knowledge Engineering and Data Science Jurnal Komputer Terapan International Journal of Computing and Informatics (IJCANDI) Indonesian Journal of Artificial Intelligence and Data Mining Jusikom : Jurnal Sistem Komputer Musirawas Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Journal of Robotics and Control (JRC) Just TI (Jurnal Sains Terapan Teknologi Informasi) J-Icon : Jurnal Komputer dan Informatika Journal of Informatics and Computing
Malani, Rheo
Politeknik Negeri Samarinda
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering

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KLASIFIKASI DOKUMEN LAYANAN SISTEM DAN DATA PRODUK MENGGUNAKAN FUZZY C-MEANS CLUSTERING Bedi Suprapty; Rheo Malani
Jusikom : Jurnal Sistem Komputer Musirawas Vol 6 No 2 (2021): Jusikom : Jurnal Sistem Komputer Musirawas DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v6i2.1329

Abstract

System Application and product (SAP) merupakan suatu produk perangkat lunak yang berguna untuk melakukan kontrol terhadap dokumen pelaporan kerusakan ataupun gangguan pada layanan yang di ajukan pada tiap unit departemen. Dalam penelitian ini di butuhkan solusi untuk melakukan pengelompokkan/clustering. Attribut yang digunakan pada penelitian ini berupa layanan aplikasi, dimana atribut 1 berisi SLA, atribut 2 berisi Maot. Cluster di bagi menjadi 4 level antara lain pada level 1 (Helpdesk TI), level 2 (Kasie layanan TI), level 3 (Kabag TI), dan level 4 (Manajer TI). Fuzzy C-Means (FCM) adalah metode yang digunakan dalam menyelesaikan solusi berupa hasil pengelompokkan layanan aplikasi. Penentuam centroid awal di lakukan dengan mengambil nilai rentang antara nilai Min dan Max pada data setiap attribut kemudian dibandingkan dengan jumlah cluster sehingga menghasilkan interval untuk setiap cluster. Adapun hasil dari penelitian ini pada cluster level 1 dan 2 tidak ada komplain dari pengguna masalah kerusakan ataupun gangguan pada layanan aplikasi tersebut. Di cluster level 3 terdapat 2 layanan aplikasi mengalami kerusakan ataupun gangguan. Jika layanan aplikasi tersebut tidak dapat diselesaikan pada batas waktu SLA yg ditentukan, maka pengguna tersebut berhak komplain ke Kabag TI. Begitu juga pada cluster level 4 sebanyak 22 layanan aplikasi mengalami kerusakan ataupun gangguan jika aplikasi tersebut belum dapat diselesaikan pada batas waktu SLA yg ditentukan maka pengguna tersebut juga berhak komplain ke Manajer TI. Rata – rata persentase MAPE pada keseluruhan clustering adalah 13,20%.
Pengurutan dan Pengelompokan Divisi Hasil Penerimaan Calon Karyawan Menggunakan Metode F-AHP dan K-Means Taufiqurrahman Taufiqurrahman; Rheo Malani; Abdul Najib
Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Vol 3, No 1 (2018): Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Informasi (SAKTI)
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (675.714 KB)

Abstract

Seiring berkembangnya SMK Negeri 7 Samarinda maka upaya meningkatkan mutu layanan kepada masyarakat terus dilakukan. Salah satu upaya yang dilakukan adalah dengan memilih tenaga Tata Usaha yang berkompeten yang dapat menyesuaikan dengan visi dan misi SMK Negeri 7 Samarinda, namun terdapat kendala yang muncul dalam penerimaan dengan calon karyawan tata usaha tersebut, salah satunya adalah jumlah pelamar kerja yang cukup banyak maka penentuan peserta calon karyawan Tata Usaha akan menjadi sulit dan memperlama proses penyeleksian, pengurutan sampai pengelompokan divisi bagi pelamar yang telah dinyatakan lulus seleksi. Untuk mengatasi masalah ini, perlu adanya sistem pengurutan dan pengelompokan divisi hasil seleksi penerimaan karyawan Tata Usaha pada SMK Negeri 7 Samarinda, dengan menggunakan metode Fuzzy Analytical Hierarchy Process (F-AHP) dapat diketahui bobot masing-masing kriteria, serta metode K-Means sebagai pengelompokan divisi hasil seleksi. Dengan adanya sistem pengurutan dan pengelompokan divisi ini dapat memudahkan kepala Tata Usaha SMK Negeri 7 Samarinda dalam menentukan karyawan yang sesuai bobot kriteria yang ada.
PENGELOMPOKAN SEBARAN TRANSFORMATOR DISTRIBUSI BERDASARKAN KAPASITAS DAYA MENGGUNAKAN METODE NAÏVE BAYES Studi Kasus: PT. PLN RAYON KOTA SAMARINDA Rheo Malani; Bedi Suprapty
J-Icon : Jurnal Komputer dan Informatika Vol 8 No 1 (2020): Maret 2020
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v8i1.2185

Abstract

ABSTRACT Human needs for energy are mostly obtained from electrical energy, both for daily needs and for industrial needs. PT. PLN (Persero) is one of the state electricity companies that serves the community's need for electricity. Transformer or better known as "transformer" or "transformer" is actually an electrical device that converts AC power at one voltage level to one voltage level based on the principle of electromagnetic induction without changing its frequency. Because of the lack of distribution of transformers around the Samarinda area, it can result in electricity demand services to the community. Therefore we need a method that can facilitate the distribution of PT. PLN Rayon Kota Samarinda, one of the methods is by applying Naïve Bayes. The purpose of this study is to facilitate the distribution in each region and the type of transformer used. The results of calculations using the Naïve Bayes method, obtained the probability of grouping the training data is P (160) = 0.006441224, P (100) = 0.016304348, P (80) = 0.001610306, P (50) = 0.001610306, P (40) = 0.000402576, P P (20) = 0,000679348. From the calculation results, it appears that the probability value P (100) is more dominant, then 100 is recommended for real consumption which is used as training data. The Naïve Bayes method produces an accuracy rate of 92%.
Implementation Of Augmented Reality At State Polytechnic Of Samarinda Building Using Marker Based Tracking Method Sianipar Yosephine Yulietayanti Natalia; M. F. Andrijasa; Rheo Malani
Journal of Informatics and Computing Vol. 1 No. 1 (2022): Journal of Informatics and Computing
Publisher : Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (377.117 KB) | DOI: 10.31884/random.v1i1.13

Abstract

Augmented Reality (AR) is increasingly used in the industrial revolution 4.0 as it is today, one of which is as a medium for information and learning. Currently, the Samarinda State Polytechnic (POLNES) is one of the universities located in Samarinda and has buildings as a place for lecture activities. The campus introduction media used today is to use miniatures and this is still not effective in providing the right information results. The research with the title "Implementation of Augmented Reality in the Samarinda State Polytechnic building using the Marker Based Tracking Method", aims to help introduce buildings that are used as places for student lecture activities. The benefits of this study can provide convenience to students and the general public who want to know the building plan in the POLNES campus environment. The research method uses the waterfall method with observation and literature data collection techniques. The results of this study are in the form of an android mobile application with Augmented Reality technology that can display the plan of the Samarinda State Polytechnic building along with its information.
Inter-Frame Video Compression based on Adaptive Fuzzy Inference System Compression of Multiple Frame Characteristics Arief Bramanto Wicaksono Putra; Rheo Malani; Bedi Suprapty; Achmad Fanany Onnilita Gaffar; Roman Voliansky
Knowledge Engineering and Data Science Vol 6, No 1 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v6i12023p1-14

Abstract

Video compression is used for storage or bandwidth efficiency in clip video information. Video compression involves encoders and decoders. Video compression uses intra-frame, inter-frame, and block-based methods.  Video compression compresses nearby frame pairs into one compressed frame using inter-frame compression. This study defines odd and even neighboring frame pairings. Motion estimation, compensation, and frame difference underpin video compression methods. In this study, adaptive FIS (Fuzzy Inference System) compresses and decompresses each odd-even frame pair. First, adaptive FIS trained on all feature pairings of each odd-even frame pair. Video compression-decompression uses the taught adaptive FIS as a codec. The features utilized are "mean", "std (standard deviation)", "mad (mean absolute deviation)", and "mean (std)". This study uses all video frames' average DCT (Discrete Cosine Transform) components as a quality parameter. The adaptive FIS training feature and amount of odd-even frame pairings affect compression ratio variation. The proposed approach achieves CR=25.39% and P=80.13%. "Mean" performs best overall (P=87.15%). "Mean (mad)" has the best compression ratio (CR=24.68%) for storage efficiency. The "std" feature compresses the video without decompression since it has the lowest quality change (Q_dct=10.39%).
Optimization of Humanoid Robot Leg Movement Using Open CM 9.04 Wajiansyah, Agusma; Malani, Rheo; Supriadi, Supriadi; Gaffar, Achmad Fanany Onnilita
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.15071

Abstract

The Indonesian Robot Dance Contest (KRSTI) is a branch of the Indonesian Robot Contest (KRI) with the theme of dance. The robot used is a humanoid robot that can dance. Every year at the event, the provisions for robots constantly change, both the type of dance being demonstrated and the requirements for the robot's height. The taller the robot, the more difficult it is to control its walking movements because of the load it carries. This study uses a suitable algorithm to make the walking movement more natural and minimize the robot's falling. Human ROM data is used as a parameter for the range of motion of the servos that act as joints in the robot's legs. The algorithm created serves to determine the initial position of the angle on the servo to avoid the wrong initial movement position between one servo and another. The robot used is the Bioloid Robot’s leg Type A and uses OpenCM 9.04-A as the controller. The results showed that ROM on human feet could not be fully implemented on robot legs due to the robot's structure and the need for a robot that only relies on an algorithm to find the correct fulcrum to maintain balance. The comparison results show that the movement when walking on the ankle (ID servo 15) ranges from 749-567, while the ROM range is only between 580-512. When walking (servo ID 16), movement ranges from 460-291, while the ROM range ranges from 580-512.
Co-Authors Abdul Najib Achmad Fanany Onnilita Gaffar Agusma Wajiansyah, Agusma Alfiansyah, M Nur Ananda, Roni Arrosied, Harun Bedi Supriaty Bedy Suprapty Gusti G N Haviluddin Haviluddin M. F. Andrijasa Muhammad Soleh Muhammad Trisna Aryuna Mulyanto Mulyanto Mulyanto Mulyanto Oki Dwi Nurhayati Purba, Muren Fiatra Denata Purnawansyah Purnawansyah Roman Voliansky Sianipar Yosephine Yulietayanti Natalia Suprapty, Bedi Supriadi Supriadi Taufiqurrahman Taufiqurrahman Wikarno, Wikarno