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All Journal Teknika: Jurnal Sains dan Teknologi JAIS (Journal of Applied Intelligent System) OPERATION EXCELLENCE: Journal of Applied Industrial Engineering JOIN (Jurnal Online Informatika) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT Indonesian Journal of Business Intelligence (IJUBI) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) J-SAKTI (Jurnal Sains Komputer dan Informatika) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Journal of Practical Computer Science (JPCS) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Teknologi dan Manajemen Industri Terapan Jurnal Teknik Industri Jurnal Manajemen Informatika dan Bisnis Digital Journal Industrial Engineering and Management (JUST-ME) Journal of Artificial Intelligence and Digital Business Jurnal Lentera Pengabdian VIDHEAS: Jurnal Nasional Abdimas Multidisiplin SAINTEK Cahaya Pengabdian

Ikhsan Romli

Universitas Pelita Bangsa

Author-ID : 1471156

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Penentuan Kepuasan Pelanggan Terhadap Pelayanan Kantor Pelayanan Pajak Menggunakan C4.5 dan PSO Ikhsan Romli; Fairuz Kharida; Chandra Naya
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Tax Service Office is a work unit of the Directorate General of Taxation that carries out services in the field of taxation to the public, both registered and unregistered taxpayers, within the working area of the Directorate General of Taxes. The number of Primary Tax Service Offices in Indonesia, one of which is the Primary Tax Service Office in Bekasi, has various ways to increase the satisfaction of taxpayers for the services provided. This study aims to determine the accuracy of taxpayers' satisfaction using data mining techniques using the Decision Tree C4.5 Algorithm with Particle Swarm Optimization (PSO) feature selection, validation uses cross validation techniques while accuracy is measured by the confussion matrix, which is to determine the level of service satisfaction conducted by distributing questionnaires to taxpayers in the Primary Tax Service Office in Bekasi as many as 500 questionnaires. The results show the accuracy value of Taxpayers' service satisfaction at the Pratama Tax Service Office using the Decision Tree C4.5 Algorithm with a feature selection of Particle Swarm Optimization (PSO) of 98,85%, Precission of 98,85% and Recall of 100%.

Sistem Informasi Pergudangan Pada Cv. Cokro Dengan Model Pengembangan Sistem Waterfall Ikhsan Romli; Ikfal Setiawan
Jurnal SIGMA Vol 9 No 1 (2018): September 2018
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.353 KB)

Abstraksi Di zaman yang semakin modern ini, perkembangan ilmu pengetahuan dan teknologi semakin pesat, apalagi informasi sekarang ini sangat cepat menyebar ke penjuru dunia. Sejalan dengan hal tersebut permasalahan yang ada pada perusahaan juga semakin kompleks dalam kehidupan sehati-hari. Dengan kenyataan ini kita dituntut untuk menyelesaikan permasalahan yang ada dengan memanfaatkan kecanggihan teknologi serta kecepatan, ketepatan dan keakuratan dalam memberi informasi sehingga dalam melaksanakan pekerjaan kita mendapatkan hasil yang optimal. Salah satunya adalah pemanfaatan teknologi komputer. Penjualan merupakan salah satu aktivitas bisnis penting yang dilakukan oleh perusahaan untuk dapat memperoleh laba yang merupakan tujuan utama dari sebagian besar perusahaan. Untuk dapat melaksanakan kegiatan penjualan dengan baik, setiap pemilik usaha perlu memiliki sebuah sistem yang baik dan terkendali dengan alur yang jelas. Maka berdasarkan uraian diatas, sangat menarik untuk melakukan sebuah penelitian terhadap toko ibu sum guna mendukung dan meningkatkan kinerja dan efisiensi dalam melakukan penjualan produknya Kata kunci: PHP, MySQL , Point Of Sales

Optimalisasi Support Vector Machine Menggunakan Particle Swarm Optimization Untuk Mendiagnosa Penyakit Kanker Payudara Ari Maulana; Agung Nugroho; Ikhsan Romli
Journal of Practical Computer Science Vol 1 No 2 (2021): November 2021
Publisher : DPPM Universitas Pelita Bangsa

Kanker payudara adalah kanker yang paling umum pada wanita dan penyebab utama kematian kanker di seluruh dunia. Klasifikasi dalam data mining merupakan dua bentuk proses analisis data yang digunakan untuk mengekstraksi model yang menggambarkan kelas data atau untuk memprediksi tren data di masa depan. Support Vector Machine (SVM) dikenal juga dengan support vector network yang merupakan metode supervised terkait dengan learning algorithm untuk analisa pola data yang digunakan untuk klasifikasi dan regresi. Seleksi fitur banyak digunakan untuk mengatasi fitur yang tidak relevan dan berlebihan. Seleksi fitur menyederhanakan sekumpulan data dengan mengurangi dimensi dan mengidentifikasi fitur yang relevan tanpa mengurangi akurasi prediksi. Penelitian ini mengguanakan algoritma Support Vector Machine dengan Particle Sarm Optimization untuk mendiagnosa penyakit kanker payudara. Hasil dari penelitian ini adalah accuracy sebesar 97.61%, precision sebesar 99.21% dan recall 96.94%. Penggunaan Particle Swarm Optimization bekerja secara efektif dalam meningkatkan nilai akurasi. Kata kunci: Kanker payudara, klasifikasi, support vector machine, particle swarm optimizatiom.

PENERAPAN DATA MINING MENGGUNAKAN ALGORITMA K-MEANS UNTUK KLASIFIKASI PENYAKIT ISPA Ikhsan Romli
Indonesian Journal of Business Intelligence (IJUBI) Vol 4, No 1 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i1.1727

With the rapid development of technology in all fields, from the government, education, agriculture and especially in the health sector, technology can provide fast and accurate information for health teams, doctors, nurses and even patients themselves to make it easier to control their own health. Acute Respiratory Infections (ARIs) are diseases of the upper or lower respiratory tract, usually contagious, that can cause a wide spectrum of diseases ranging from asymptomatic illness or mild infections to severe and deadly illness, depending on the causative pathogen, environmental factors and factors host. The purpose of this study was to apply the K-Means method to classify ARI diseases and to obtain accurate and fast accuracy in classifying symptoms of ARI using the K-Means method. The method used is data mining techniques using the K-Means algorithm. This process resulted in 3 clusters, namely cluster C1 (Regular ISPA) with 81 members, cluster C2 (moderate ISPA) with 103 members, and cluster C3 (Heavy ISPA) with 66 members. It can be seen that the largest number of ARI patients are patients with mild ARI symptoms. Based on the results of the percentage analysis for each cluster, the first cluster has a percentage of 35% of data, the second cluster is 45% of data and the third cluster is 20% of data. Testing using the DBI (Davies Bouldin Index) validation obtained values for each cluster. Testing cluster 1 produces DBI value -0.244, cluster 2 DBI value -0.250, cluster 3 DBI value -0.239. Because the DBI value of cluster 3 is smaller, the cluster can be called optimal.

PERANCANGAN DAN IMPLEMENTASI SMART GARDEN BERBASIS INTERNET OF THINGS (IOT) PADA PERUMAHAN CENTRAL PARK CIKARANG Ikhsan Romli; Kristoforus Lensiprimo Nong Hugo; Irfan Afriantoro
Indonesian Journal of Business Intelligence (IJUBI) Vol 4, No 2 (2021): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v4i2.1974

Technological developments, especially in agriculture and plantations in era 4.0, have greatly increased over time. One of them is in terms of plant care. Plant care is one of the activities carried out to keep plants fertile and healthy. Moreover, in the dry season plant care is very important to do such as, doing watering periodically in accordance with the right time, and also light lighting must be in accordance with the needs of the plant. In this writing, researchers designed a tool that can respond to and work on commands that have been sent, and also reply to messages about the information displayed on the blynk application. Smart Garden Tools It uses NodeMCU 8266 as a controller as well as a soil moisture sensor as a soil moisture detector, and DHT11 as a temperature and humidity sensor. The results of this study are to minimize the occurrence of damage to plants, make it easier for residents to control and monitor the condition of the house in real time, and also to improve the quality of plants in order to grow properly.

Implementasi Sistem Pakar menggunakan Metode Certainty factor Untuk Mendiagnosa Penyakit Herpes Zoster Ikhsan Romli; E Romansyah; Andika Permana
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 4 No 2 (2020): JULY-DECEMBER 2020
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v4i2.158

Herpes Zoster is a skin disease that is very difficult to treat and everyone can certainly experience it, the characteristics of this disease are characterized by unilateral vesicles in groups with pain characterized by radicular around the dermatome. This study aims to establish a Web-based Certainty factor method as a tool to diagnose skin diseases. With this application, it doesnâ€™t need long time to find out what type of herpes zoster is suffering. To use this applicationÂ is that the patient answers the questions which are provided by the system, then the system will process all the patient answers using the certainty factor method, after that, the system will produce output as the results of the diagnosis of the type of shingles. The system built can help patients to know the type of disease that is being suffered by the patients and in accordance with expert analysis of skin diseases.

Sistem Pendukung Keputusan Menentukan Siswa Yang Menerima Beasiswa Menggunakan Metode SAW Jamaludin Jamaludin; Agung Nugroho; Ikhsan Romli
Prosiding SISFOTEK Vol 4 No 1 (2020): Vol 4 No 1 (2020): SISFOTEK 2020
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.588 KB)

The number of schools that are growing steadily, making the school is required to implement a better strategy. For that reason, the school must observe all the activities that exist in the school environment to be able to attract the attention of parents so that their children attend school. Decision Support System is basically to facilitate the school in selecting candidates who will receive scholarships, to get more accurate results, and apply the Simple Additive Weighting method. At SD Negeri Singajaya 03 the process of determining students who receive scholarships uses several criteria, namely Parental Income, Semester, Parental Dependency, Number of Brothers, and Value. In building this system the author uses the System Development Life Cycle (SDLC) development method, and for system design using the Unified Modeling Language (UML). For making the application the author uses PHP programming language and MYSQL database testing using the Black Box Testing method. The results of this study are an application of decision support to determine prospective scholarship recipients using the method Simple Additive Weighting (SAW). In conclusion, this Decision Support System is more convincing than the old method. Because the calculation results are faster, more efficient, and more accurate.

Penentuan Kriteria Dalam Penilaian Sub-Kontraktor Untuk Proses Blackening Dengan Pendekatan Analytical Hierarchy Process (AHP) Di PT. TKI Andreamara Andreamara; Ikhsan Romli; Andriani Andriani
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

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

TKI is a company in the manufacturing industry, with the main job of machining processes for motor vehicle components. PT. TKI has 2 sub-cons for blackening work and intends to evaluate those sub-cons. The method used to determine the assessment criteria using Analytical Hierarchy Process method (AHP). The results of the criteria research using the AHP method obtained 5 criteria, namely quality, price, delivery, flexibility, and responsiveness (QCDFR) with the weight of each criterion: quality = 0.48, price = 0.13, delivery = 0.31, flexibility = 0.05, and responsiveness = 0.03. These five criteria will then be used to evaluate the sub-contractors to be implemented at the end of the year. Keywords: AHP, Sub-Contractor, Criteria, Industry, Blackening

Penerapan Algoritma Fuzzy C-Means Untuk Pengelompokan Data Penduduk Miskin Di Indonesia Berdasarkan Kabupaten dan Kota Ayu Indriyanti; Agung Nugroho; Ikhsan Romli
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.141146

Poverty is a central issue for every country in the world, especially for developing countries. In Indonesia, poverty has become a phenomenon and fact, one of the problems that has not been resolved until now by both the central government and the regional government. Difficulties in determining which regions experience the highest and normal poverty levels and areas with low poverty levels, a method is needed to help this problem. One of them is data mining using clustering techniques. Clustering is a method used to group data based on the similarity of the data. In analyzing partition-based clusters, the Fuzzy C-Means (FCM) algorithm is an algorithm that has been widely used to solve data clustering problems. The variable in this study is the number of poor people based on regencies and cities in Indonesia from 2015 to 2017. These variables are used to obtain categories from each cluster formed. From the results of the analysis carried out, it can be concluded that three regencies and cities can be grouped: cluster 1 consisting of 39 districts / cities with high poverty levels, cluster 2 consisting of 368 districts / cities with low poverty level categories, and cluster 3 having members 107 districts / cities with moderate poverty levels. And from the DBI value obtained in the FCM algorithm is equal to 0.524 which means that with this value the cluster in the algorithm that is formed can be said to be good or optimal because the DBI value is close to 0. Keywords: Clustering, Poverty Data, Fuzzy C-Means, Davies-Bouldin Index

Klasifikasi Kerusakan Barang Dengan Menggunakan Komparasi Algoritma C4.5 Dan Naive Bayes Romli, Ikhsan; Kurniawan, M Edi
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 1 No. 1 (2022): Mei 2022
Publisher : Yayasan Literasi Sains Indonesia

Process control is needed to prevent goods from being damaged both in the production and delivery processes. Therefore, in this study, a classification of conditions was carried out whether the goods that experienced the incident could still be used or not. This study uses a classification model with the C4.5 and Naïve Bayes algorithms, by evaluating using the confusion matrix method, the best accuracy in the C4.5 algorithm is 73.9% recall 72.9% and 88% precision, with these results it can be said that algorithm C 4.5 is good to be implemented in this decision support system model

Co-Authors Abdul Mazid Adi Rusdi Adi Rusdi Widya Agung Nugroho Agus Suwarno, Agus Ahmad Rifai Alfian Nur Alim Andika Permana Andre Amara Andreamara Andreamara Andriani Andriani Andriani Andriani Andriani Andriani Antika Zahrotul Kamalia Antoni, Andi Ari Maulana Ayu Indriyanti Butsianto, Sufajar Candra Naya Candra Naya Chandra Naya E Romansyah Effendi Listyanto, Rudy Elkin Rilvani Ermanto Fachrial Banyu Asmoro Fairuz Kharida Hendi Herlambang Herlambang, Hendi Ikfal Setiawan Irfan Afriantoro Jamaludin Jamaludin Kinantaka, Rizky Budiyasa Kristoforus Lensiprimo Nong Hugo Kurniawan, M Edi Mardiyana, Mohamad Maulana, Donny Muhammad Arif Hidayat Muhammad Fatchan Muhammad Ihsan Aprilianto Muhammad Irfan Ngudi Wiyatno, Tri Nugroho, Agung Nurhidayanti, Nisa Permana, Andika Prabowo, Yohanes Fernando Anom Prameswari R, Shanti Priatna , Wowon Putra, Boy Manggala Rizki, Rafli Ardian Romansyah, E Saputro, Rian Ngesti Sasongko, Ananto Tri Siswandi, Arif Siti Rahayu Supriadi, Asmadi Supriadi, Asmadi Supriyati . Surojudin, Nurhadi Tri Ngudi Wiyatno Ucok Darmanto Soer Widya, Adi Rusdi Wiyanto - Yoga Religia Zy, Ahmad Turmudi

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