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All Journal Jurnal Ilmiah KOMPUTASI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal of Information System, Applied, Management, Accounting and Research Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Indonesian Journal of Business Intelligence (IJUBI) bit-Tech Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JISA (Jurnal Informatika dan Sains) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Ilmiah Wahana Pendidikan Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science Formosa Journal of Computer and Information Science Jurnal Lentera Pengabdian International Journal of Applied Research and Sustainable Sciences (IJARSS) International Journal of Sustainable Applied Sciences (IJSAS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian JPM MOCCI : Jurnal Pengabdian Masyarakat Ekonomi, Sosial Sains dan Sosial Humaniora, Koperasi, dan Kewirausahaan SAINTEK International Journal of Integrated Science and Technology Jurnal Indonesia : Manajemen Informatika dan Komunikasi Welfare: Jurnal Pengabdian Masyarakat
Wahyu Hadikristanto
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Comparative Analysis of Support Vector Machine and Random Forest Algorithms in Indonesian Batik Classification Oktavianto, Rainal Zulian; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Sustainable Applied Sciences Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijsas.v2i6.2072

Abstract

This study compares the performance of Support Vector Machine (SVM) and Random Forest (RF) algorithms in Indonesian batik image classification. Data collected from four batik categories: Pattern Batik Insang, Pattern Batik, Patterns Batik Dump, and Pattern Megamendung. Image feature extracted using Histogram of Oriented Gradients (HOG). SVM models with linear and RF kernels with 100 decision trees are trained and tested on this dataset. The evaluation results showed that the SVM has an accuracy of 88%, with precision and recall balanced between classes, while RF has an accuracy of 86%, with some classes showing excellent performance. SVM is superior in overall accuracy, but RF offers better interpretability and ease of setting parameters. The conclusions of this study suggest that both algorithms are able to effectively classify bacterial images, but the selection of the algority depends on the specific needs of the application. Further adjustment of parameters and additional preprocessing techniques are recommended to improve model performance. This research provides a strong foundation for further development in the classification of batic images using machine learning.
Implementasi Sistem Informasi Penggajian Karyawan Berbasis Desktop Pada PT. Virgi Motor Cikarang Eko Budiarto; Hadikristanto, Wahyu; Syach, Ridwan
Jurnal SIGMA Vol 15 No 1 (2024): Maret 2024
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v15i1.5073

Abstract

PT. Virgi Motor Cikarang adalah perusahaan yang bergerak di bidang penjualan sepeda motor honda, Segmen Ahass / Service, dan penjualan sparepart motor honda.  PT VIRGI MOTOR CIKARANG didirikan sejak tahun 2001. Dalam pengolahan data karyawan selama ini menggunakan sistem penggajian terkomputerisasi namun sederhana yaitu menggunakan software Ms. Excel, sehingga dalam pengolahan datanya mengalami hambatan terjadinya proses kesalahan seperti perhitungan gaji lembur, potongan gaji, gaji pegawai, tunjangan, gaji pokoknya dan laporan gaji harus dihitung dan mengalami proses perhitungan yang berulang – ulang dari tiap karyawannya. Metode yang digunakan penulis dalam penelitian ini menggunakan metode waterfall yang terdiri dari perencanaan, analisis, perancangan, implementasi pemeliharaan. Hasil dari penelitian ini adalah menghasilkan sistem informasi penggajian yang terkomputerisasi yang diberikan kemudahan dalam memberikan informasi data penggajian seperti informasi data karyawan, data jabatan, tunjangan & data penggajian. Pada Sistem Informasi Data Penggajian, penulis menggunakan diagram arus data, ERD, dan laporan dengan menggunakan pemograman Microsoft Visual Studio 2019 dan SQL Server untuk pengolahan data. Setelah peneliti membuat Sistem Informasi Penggajian, penulis berharap agar prosedur kerja dapat lebih mudah bagi pihak-pihak terkait di PT. Virgi Motor Cikarang.
Implementasi Sistem Informasi Pedidikan dan Latihan (SIDIKLAT) pada Instalasi Diklat RSUD dr. Chasbullah Abdulmadjid Kota Bekasi Sanudin; Hadikristanto, Wahyu; Firmansyah, Andri; Edora; Purwanto
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

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

Abstract

This training activity was conducted to enhance the capacity of the staff at the Education and Training Unit (Diklat) of RSUD dr. Chasbullah Abdulmadjid, Kota Bekasi, in operating and implementing the Education and Training Information System (SIDIKLAT). The training was designed to provide an in-depth understanding of the features and functions of SIDIKLAT that support the management of education and training at the hospital. The methods used included presentations, live demonstrations, and system simulations by the participants. During the training, participants were actively engaged in each session to ensure optimal technical and operational mastery. Evaluations showed that the training successfully improved the participants' competence in using SIDIKLAT and increased awareness of the importance of technology integration in education and training management. It is expected that after this training, the Diklat staff will effectively implement SIDIKLAT in their daily activities, thereby supporting the improvement of the quality and efficiency of education and training services at RSUD dr. Chasbullah Abdulmadjid.
Optimalisasi Pemilihan Karyawan Penerima Voucher Umroh Menggunakan Metode Analytical Hierarchy Process (AHP) Ariandi, Sheva Rizky; Suprapto, S; Andika, Sophian; Hadikristanto, Wahyu
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.823

Abstract

The Analytical Hierarchy Process (AHP) method is applied in selecting the best employees who will receive Umrah vouchers at PT. Tempo Scan Pacific Tbk Indonesia to expedite the selection process. In this research, the AHP method was used to determine four criteria for selecting the best employees, namely Attendance, Target Achievement, Work Initiative, and Teamwork. The sample of employees tested consisted of four people with the importance weight of Attendance 2 times more important than Initiative, Teamwork 3 times more important than Job Targets and Initiative 2 times more important than Job Targets. Attendance Consistency Ratio Value 7.88%, Achievement Target 8.55%, Initiative 9.95% and Teamwork 6.03%. The test results of 4 employees A, B, C and D show that Employee D has the highest value of 0.3614, followed by Employee C with a value of 0.2733, Employee A with a value of 0.2384, and Employee B with a value of 0.1267. Based on these results, it can be concluded that Employee D is the most entitled to receive an Umrah voucher.
Pemberdayaan Masyarakat Melalui Pelatihan Kepemimpinan dan Teknologi Informasi dalam meningkatkan Produktifitas Kelompok Usaha Desa Cibatu Rezeki, Fitri; Permana , Indra; Sunaryati , Titin; Hadikristanto, Wahyu; Wulandari, Siska
JPM MOCCI : Jurnal Pengabdian Masyarakat Ekonomi, Sosial Sains dan Sosial Humaniora, Koperasi, dan Kewirausahaan Vol. 2 No. 2 (2024): September
Publisher : PT. Alahyan Publisher Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61492/jpmmocci.v2i2.184

Abstract

Desa Cibatu has significant natural resource potential but faces considerable challenges in maximizing local economic growth, particularly in leadership, management, and technology adaptation. This research focuses on interventions through leadership and information technology training to enhance local capacity. Activities include intensive training in strategic decision-making, financial management, digital marketing, business mentoring and consulting. The results show a significant improvement in leadership and business management skills and an understanding of technology use. Quantitatively, there was a 15% reduction in the unemployment rate and an average 10% increase in per capita income. These findings confirm that a comprehensive and collaborative approach to local capacity development can optimize the village's economic potential, reduce unemployment, and improve community welfare. Designed interventions must be adaptive and sustainable to provide significant long-term impacts.
Rancang Bangun Sistem Informasi Penyewaan Alat Outdoor Toko Sahabat Adventure Berbasis Web Diki Febriani; Hadikristanto, Wahyu; Pradini, Purnama Sakhrial
Jurnal Ilmiah Komputasi Vol. 22 No. 4 (2023): Jurnal Ilmiah Komputasi : Vol. 22 No 4, Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.22.4.3405

Abstract

Toko Sahabat Adventure adalah salah satu penyediaan jasa penyediaan alat mendaki gunung yang berlokasi di anjun, kecamatan Plered, kabupaten Purwakarta. Proses bisnis pada Toko Sahabat Adventure ini khususnya dalam hal pencatatan data seperti data konsumen, data alat outdoor, data penyewaan, data pengembalian serta data transaksi penyewaan alat camping masih belum terkomputerisasi. Data yang belum terkomputerisasi dan tidak terintegrasi ini menyebabkan sulitnya dalam pembuatan laporan dan pengecekan mengenai informasi yang berkaitan dengan transaksi penyewaan alat, dan juga data rentan rusak dan hilang. Penelitian ini menggunakan desain UML dalam proses perancangan dan menggunakan bahasa pemrograman PHP serta Database MySQL. Hasil penelitian ini memudahkan pelanggan untuk mendapatkan informasi dan pemesanan alat-alat outdoor tanpa harus datang secara langsung ke Toko Sahabat Adventure dan dapat memberikan informasi mengenai pelaporan transaksi persewaan alat-alat outdoor di Toko Sahabat Adventure Secara akurat.
Optimasi Decision Tree Menggunakan Particle Swarm Optimization (PSO) pada Risiko Kredit KMG Bank DKI: Optimization of Decision Tree Using Particle Swarm Optimization (PSO) for Credit Risk of KMG Bank DKI Putry, Jwasky Budy Eswa; Sasongko, Ananto Tri; Hadikristanto, Wahyu
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 4 (2024): MALCOM October 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i4.1521

Abstract

Pada dunia perbankan prediksi risiko kredit merupakan aspek penting yang menentukan keberhasilan dalam pengelolaan kredit. Penelitian ini bertujuan untuk meningkatkan akurasi prediksi risiko kredit Kredit Multiguna (KMG) di Bank DKI dengan menggunakan metode Particle Swarm Optimization (PSO). Dalam konteks ini, PSO digunakan untuk mengoptimalkan dalam menemukan kombinasi parameter terbaik yang dapat meningkatkan performa model prediksi risiko kredit. Penelitian menunjukkan bahwa penggunaan Particle Swarm optimization (PSO) ini meningkatkan akurasi prediksi risiko kredit secara signifikan. Dengan menggunakan Particle Swarm optimization (PSO) menghasilkan akurasi prediksi mencapai 99,13%. Sebaliknya , tanpa optimasi PSO, akurasi yang diperoleh dari Decision Tree hanya sebesar 97,83 %. Hal ini membuktikan bahwa PSO mampu meningkatkan akurasi prediksi risiko kredit secara signifikan. Dengan demikian, Bank DKI dapat mengambil keputusan yang lebih tepat dalam pemberian kredit KMG, yang pada akhirnya dapat mengurangi tingkat kredit macet dan meningkatkan stabilitas finansial bank.
Implementation of The Apriori Algorithm in Managing Stock Items at Drl.Rumahan Retail Satria Permana, Muhammad Safri; Widodo, Edy; HadiKristanto, Wahyu
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4239

Abstract

Drl.Rumahan is a retail store that sells a variety of motorcycle lamp modifications. Drl.Rumahan is still struggling with determining stock levels and understanding customer purchases. Additionally, they are not utilizing transaction data as a valuable information source. Without leveraging this data, Drl.Rumahan will fall behind its business competitors and lose customers because the products they seek are unavailable. This situation will inevitably become a significant problem if it continues. This study aims to utilize sales transaction data as valuable information and identify customer purchasing patterns from the sales transaction data. The algorithm used is the Apriori algorithm to identify purchasing patterns from the transaction data set. The results of this study identified the three highest rules: if someone buys a pass beam switch, they will buy a shroud with a support value of 5.8% and a confidence value of 47.6%; if someone buys a shroud, they will buy a pass beam switch with a support value of 5.8% and a confidence value of 45.5%; and if someone buys a shroud, they will buy a relay with a support value of 5.2% and a confidence value of 40.9%. These results can inform business strategy decisions by increasing the inventory of products that form rules and serve as a guide for promotional product packages for products that have rules above the minimum support and minimum confidence.
Improving Employee Retention Through Prediction and Risk Management Using Machine Learning Galang Rintang Widya Pratama; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Applied Research and Sustainable Sciences Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijarss.v2i6.1960

Abstract

This research investigates the effectiveness of two machine learning models (Logistic Regression and Random Forest) in predicting employee turnover. This research uses IBM HR Analytics employee attrition and performance dataset and performance dataset from Kaggle and implements nested ensemble models in Google Colab. After data pre-processing steps such as feature merging, generation, engineering, cleaning, coding, and normalisation, the data is divided into training and testing sets. The models were trained and evaluated based on their accuracy. The results of averaging the three departments showed that the Random Forest model achieved the highest accuracy (97.7%) compared to Logistic Regression (94.6%). Therefore, this study shows that Logistic Regression is the most suitable model to predict employee turnover in the given dataset.
Comparison of Defective Casting Product Classification Results Using the K-Nearest Neighbors Algorithm Muhammad Farhan Alfarizi; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Applied Research and Sustainable Sciences Vol. 2 No. 6 (2024): June 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijarss.v2i6.1968

Abstract

This study compares the accuracy of K-Nearest Neighbors (KNN) and Naive Bayes algorithms in detecting defects in impeller products. Using a dataset of impeller images, we applied preprocessing, feature extraction, and selection techniques. The models were assessed using metrics such as precision, accuracy, F1-score, recall. and with KNN achieving 98.11% accuracy and Naive Bayes 85.38%. The t-SNE visualization confirmed distinct clustering of defective and non-defective products. Our findings suggest that KNN is more reliable for defect detection in industrial applications. These results provide valuable insights for implementing effective machine learning models in manufacturing quality control.
Co-Authors ., Sapardi Abdul Halim Anshor Abdul Hasyim Abimanyu, Aldo Anggito Aceng Badruzzaman Achmad Firmansyah Putra Ade Muslim Agung Nugroho Ahmad Fauzi Ahmad Zy Ahmad, Asyari Ali Nurdiansyah Ananto Tri Sasongko Andika, Sophian Andri Firmansyah Anggara, Bastian Anisa Anisa Anisa Rahmawati Anshor , Abdul Halim Ariandi, Sheva Rizky Arvita Emarilis Intani Aswan S Sunge Atma, Dodit Ardi Ayu Fitriyani Badruzzaman, Aceng Dahyoung Yenuargo Dichi Setiawan Diki Febriani Dodit Ardiatma Doni, Muhamad Edi Junianto Edi Widodo Edora Edora Edora Edy Widodo Eko Budiarto Ermanto Fajar Arief Rachman Fatchan, Muhammad Fauzi Ahmad Muda Febro Herdyanto Galang Rintang Widya Pratama Gatot Tri Pranoto Gunawan, Ahmad Herol Herol Holwati Ikmal Riyan Firmansyah Imam Nasai2 Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Jamroni, A. Reza Baehaqa Jamroni Karsito Keswanto Kurniadi, Nanang Tedi Laki, Abraham Leo Contantinus Meze Listanto, Firgiawan Maulida Ramadhan Mico Giovanni Dermawan Muhamad Fatchan Muhammad Farhan Alfarizi Muhammad Fatchan Muhammad Makmun Effendi Muhammad Najamuddin Dwi Miharja Muhammad Suprayogi2 Naufal Muyassar Nawangsih, Ismasari Nita Paramita Njai Njai Nur Azizah Nurhadi Surojudin Nurul Ariffaeni Islami Oktavianto, Rainal Zulian Permana , Indra Pradini, Purnama Sakhrial Prasetyo Prayoga, Dimas Preatmi Nurastuti Purdianto Purdianto Purnama Sakhrial Pradini Purwanto Purwanto Purwanto Putri N.A, Anindya Putri Nabila Adinda Adriansyah Rahmawati, Shinta Melliana Rahmawati Rasmiati Nur Aeni Retno Purwani Setyaningrum REZEKI, FITRI Risky Bambang Sutrisna romanuddin, ahmad Rosyati Adelia S Suprapto Sandi Salvan N N Sanudin Satria Permana, Muhammad Safri Sa’ad Khairudin Hanif Setiawan, Dani Yuda Dwi Siska Wulandari, Siska Sophian Andika Suderajat, Agung Sufajar, Sufajar Sufajar, Suprapto Suhardian Suhardian Suherman Suherman Suherman Sunaryati , Titin Sunita Dasman Sya syah Apriliyani Syach, Ridwan Syariefur Rakhmat, Adrianna Taofik Safrudin Taufik Hidayat Tiani Ayu Lestari Tiara Deswara Pungkas Tri Ngudi Wiyatno Turmudi Zy, Ahmad Vidya Anis Fitri Yahya, Adiba Yahya, Adibah Yoga Religia Yusup, Diana