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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) Pro Bisnis Telematika Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology

Imam Tahyudin

STMIK AMIKOM Purwokerto

Author-ID : 2377793

Astronomy 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 9 Documents Claim Missing Document

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Articles

Improved optimization of numerical association rule mining using hybrid particle swarm optimization and cauchy distribution Imam Tahyudin; Hidetaka Nambo
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Particle Swarm Optimization (PSO) has been applied to solve optimization problems in various fields, such as Association Rule Mining (ARM) of numerical problems. However, PSO often becomes trapped in local optima. Consequently, the results do not represent the overall optimum solutions. To address this limitation, this study aims to combine PSO with the Cauchy distribution (PARCD), which is expected to increase the global optimal value of the expanded search space. Furthermore, this study uses multiple objective functions, i.e., support, confidence, comprehensibility, interestingness and amplitude. In addition, the proposed method was evaluated using benchmark datasets, such as the Quake, Basket ball, Body fat, Pollution, and Bolt datasets. Evaluation results were compared to the results obtained by previous studies. The results indicate that the overall values of the objective functions obtained using the proposed PARCD approach are satisfactory.

Prediction of Daily Network Traffic based on Radial Basis Function Neural Network Haviluddin Haviluddin; Imam Tahyudin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

This paper presents an approach for predicting daily network traffic using artificial neural networks (ANN), namely radial basis function neural network (RBFNN) method. The data is gained from 21 – 24 June 2013 (192 samples series data) in ICT Unit Universitas Mulawarman, East Kalimantan, Indonesia. The results of measurement are using statistical analysis, e.g. sum of square error (SSE), mean of square error (MSE), mean of percentage error (MPE), mean of absolute percentage error (MAPE), and mean of absolute deviation (MAD). The results show that values are the same, with different goals that have been set are 0.001, 0.002, and 0.003, and spread 200. The smallest MSE value indicates a good method for accuracy. Therefore, the RBFNN model illustrates the proposed best model to predict daily network traffic.

Decision Support System using Data Mining Method for a Cross Selling Strategy in Retail Stores Imam Tahyudin; Mohammad Imron; Siti Alvi Solikhatin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 3, No 3: December 2014
Publisher : Institute of Advanced Engineering and Science

A sales transaction dataof a retail company which is collect edevery day is enormous. Very large data will bemore meaning fultoin crease the company’s profitsif itcanbe extracted properly. Based on the research resultsof Andhika, et al[1], ZhangandRuan[6], Herera et al [7], Witten [11], explained that one of the methods that can gather information from the transaction data is the method of association. With this method it can be determined the patterns of transactions performed simultaneously and repeatedly. Thus, it can be obtained amodel that can be used as a reference for cross selling sales strategy. The purpose of this research is to apply data mining association methods of data mining by using apriori algorithm to create a new sales strategy for cross selling. Based on calculations, Association Rule is implemented by applying Confidence value=0.8while the value of Support=0.1 of the defined minimum value, the total result are 77 rules.Keywords: Data Mining, Association, Apriori Algorithm, Cross Selling, Retail Stores

MODEL REGRESI PARTIAL LEAST SQUARES (PLS) (Studi Kasus : Kinerja Satuan Kerja Sekretariat Daerah Kabupaten Tegal) Imam Tahyudin
Pro Bisnis Vol 2, No 2: Agustus (2009)
Publisher : Universitas Amikom Purwokerto

Metode regresi kuadrat terkecil parsial atau Partial Least Squares (PLS) adalah pemodelan ‘lunak’ yang bebas asumsi sebaran. PLS dilakukan secara iteratif menggunakan algoritma NIPALS dan proses pendugaannya melibatkan variansi variabel Y dan variansi variabel X pada setiap iterasinya. Berdasarkan hasil analisis menggunakan bantuan Matlab versi 7 diperoleh model regresi PLS pada studi kasus kinerja satuan kerja Sekretariat Daerah Kabupaten Tegal yaitu 'ˆY=TBQdengan jumlah komponen maksimum delapan ( = 0.10). Model ini dapat memberikan informasi bahwa total variansi variabel Y yaitu volume pekerjaan, produktivitas dan kecepatan dapat dijelaskan oleh variabel X yaitu ketepatan, ketelitian, efektifitas, kemitraan, kerja tim, pendelegasian, keuletan, kehandalan dan kemandirian sebesar 60,46%

INOVASI PROMOSI OBYEK WISATA MENGGUNAKAN TEKNOLOGI AUGMENTED REALITY (AR) MELALUI LAYAR BERBASIS ANDROID Imam Tahyudin; Nur Atikah Fitriyanti; Nur Dewiyanti; Muhammad Syaiful Amin; Muhammad Yanuar Firdaus; Fahmy Putra Nahri Utama
Telematika Vol 8, No 1: Februari (2015)
Publisher : Universitas Amikom Purwokerto

Peningkatan inovasi dan kreativitas pada sebuah produk adalah suatu kewajiban. Salah satunya adalah inovasi media promosi brosur obyek wisata.Inovasi terbaru yang diharapkan dapat menarik perhatian masyarakat adalah penerapan Teknologi Augmented Reality (AR) pada brosur obyek wisata melalui layar. Teknologi AR atau dapat disebut juga sebagai Realitas Tertambah merupakan integrasi elemen digital yang ditambahkan ke dalam dunia nyata dan mengikuti keadaan lingkungan yang ada. Aplikasi ini dapat diterapkan padaperangkat mobile berbasis android. Dengan demikian, pada layar ponsel akan menghadirkan keterangan tentang objek wisata tersebut bahkan menampilkan suara dan video. Media promosi melalui brosur obyek wisata berbasis AR sebagai solusi pintar, mudah, cepat untuk mengetahui objek wisata di Kabupaten Banyumas secara menarik. Melalui sebuah brosur AR, setiap orang dapat mengetahui objek wisata di Kabupaten Banyumas secara nyata

MULTIMEDIA PEMBELAJARAN LARUTAN ELEKTROLIT DAN TATANAMA HIDROKARBON (Studi Kasus: Mata Pelajaran Kimia kelas XI dan XII SMK HKTI 2 KLAMPOK) Imam Tahyudin
Telematika Vol 4, No 2: Agustus (2011)
Publisher : Universitas Amikom Purwokerto

Tujuan penelitian ini untuk membuat metode MULTIMEDIA PEMBELAJARAN di SMK HKTI 02 Klampok. Metode yang digunakan untuk mendapatkan informasi adalah Metode pengumpulan data yang terdiri dari observasi, interview, dan dokumentasi. Metode pengembangan sistem yang digunakan adalah analisis sistem, desain sistem, coding, testing, implementasi dan pemeliharaan. Berdasarkan hasil penelitian, telah dibuat sebuah MULTIMEDIA PEMBELAJARAN “larutan elektrolit dan tatanama senyawa hidrokarbon”. Penelitian ini berhasil dibuat dengan menggunakan software ADOBE PHOTOSHOP CS2, ADOBE AUDITION 1.5, dan MACROMEDIA FLASH 8.

SISTEM PENDUKUNG KEPUTUSAN SELEKSI BEASISWA PENDIDIKAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING Ita Yulianti; Imam Tahyudin; Nurfaizah Nurfaizah
Telematika Vol 7, No 1: Februari (2014)
Publisher : Universitas Amikom Purwokerto

Tujuan penelitian ini adalah untuk membangun sebuah aplikasi sistem pendukung keputusan seleksi beasiswa pendidikan di SMK Negeri 3 purbalinggayang nantinya dapat mempermudah pekerjaan dan meminimalisir kesalahan yang dilakukan oleh panitia penyeleksian beasiswa di SMK Negeri 3 Purbalingga dalam mengambil keputusan seleksi beasiswa pendidikan. Metodologi yang digunakan dalam proses sistem pendukung keputusan menggunakan model perhitungan SAW (Simple Additive Weighting) Hasil Penelitian ini berupa Aplikasi Sistem Pendukung Keputusan seleksi Beasiswa Pendidikan di SMK Negeri 3 Purbalingga

An Interactive Mobile Augmented Reality for Tourism Objects at Purbalingga District Imam Tahyudin; Dhanar Intan Surya Saputra; Haviluddin Haviluddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 1, No 2: February 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v1.i2.pp375-380

This paper presents the development of an interactive mobile Augmented Reality (AR) for tourism promotion with eXtreme programming (XP) at Purbalingga district, Central Java that has many places of tourism attractions such as Owabong, Purbasari Pancuran Mas, Sanggaluri Park and BuperMunjuluhur. By applying the AR concept, it is expected the tourism objects could be enhanced by augmenting the virtual brochures which could be viewed over a mobile device. In this study, mobile device Android platform is used to display interactive brochures of tourism promotioncontaining 3D models, animations, and sounds. The brochure provides information in of real attractions of the tourism objects in Purbalingga district.

Analysis of Delivery Data by Medical Staff Using The K-Means Algorithm in Sleman District Sefitriani Khasanah; Adinda Rifi Yanti; Dwi Puspa Sari; Imam Tahyudin; Dhanar Intan Surya Saputra
International Journal of Engineering, Science and Information Technology Vol 2, No 4 (2022)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v2i4.330

The process of childbirth has many factors that result in the death of the baby and the mother during the delivery process, namely the lack of medical staff or health workers (midwife, doctor, or another paramedic). There needs to be an analysis of the delivery process assisted by medical staff. This analysis maps the readiness of medical staff with the needs in the field. Both natural and cesarean births have the same main goal, to make labor run smoothly and ensure that the mother and baby are safe. Deliveries assisted by health workers use secure, clean, and sterile equipment to prevent infection and other health hazards. The hope is to minimize the number of mothers who are not helped during childbirth. This study aims to analyze data on deliveries assisted by medical staff for case studies in Sleman District, Province of Yogyakarta Special Administrative Region, Indonesia, with the K-Means Algorithm. K-means is an unsupervised learning algorithm that has a function to group data into data clusters. This algorithm can accept data without any category labels, the learning process requires a relatively fast time, is quite easy to understand and implement, and the algorithm is quite popular. The research used 13,869 data in 2018. In 2019, the decrease in the number of mothers giving birth from 13,470 who were rescued was 13,469. The 2018 data produced 3 (three) clusters. In 2019 data produced 4 (four) clusters. With different levels of levels assisted by medical staff starting from the high, medium, and low groups.

Co-Authors Adinda Rifi Yanti Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Dwi Puspa Sari Fahmy Putra Nahri Utama Haviluddin Haviluddin Hidetaka Nambo Ita Yulianti M. Syaiful Amin Mohammad imron Muhammad Yanuar Firdaus Nur Atikah Fitriyanti Nur Dewiyanti Nurfaizah Nurfaizah Sefitriani Khasanah Siti Alvi Solikhatin

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