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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 Jurnal Inti Talafa : Jurnal Teknik Informatika 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 JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) 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 Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB 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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Implementasi Aplikasi Manajemen Arsip Berbasis Website Pada Kantor Notaris Anita Hiramayani Menggunakan Algoritma Rapid Application Development Atthoriq, Syaifullah; Fauziah, Sifa; Hadikristanto, Wahyu
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4641

Abstract

In an increasingly connected world of information technology, the use of digital solutions to address records management challenges is becoming increasingly important, including in the context of notary offices. Anita Hiramayani Notary Office is one of the leading notary offices operating in Tambun sub-district, the main problem identified is the difficulty of finding data within a certain period of time. Where administrative staff have to spend a long time to track and find the necessary data in piles of various excel files and worksheets. To overcome this problem, Notary Anita Hiramayani's office needs to implement a website-based records management application with the application of the Rapid Application Development algorithm. The results of the research after the implementation of a website-based records management application, show that the application can overcome the problems of records management faced by the notary office can increase efficiency in making reports and the effectiveness of legal services provided by the notary office
Sistem Informasi Penjualan Hewan Qurban Berbasis Web Menggunakan Metode Rapid Aplication Development (RAD) Fadlurrohman, Muhammad Shiddiq; Hadikristanto, Wahyu; Widodo, Edy
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5584

Abstract

The Al-Muslim Foundation is an organization that carries out the process of selling sacrificial animals, but still uses traditional methods such as recording orders, payments and animal information manually using books or physical records. This has the potential to cause recording errors and data loss, which makes it very possible for errors to occur in the process. This research aims to build a web-based system to help handle this problem. The system that will be created uses the Rapid Application Development method. Testing of this system will be carried out using the black box testing method. The results of this research show that the Al-Muslim Foundation has succeeded in increasing effectiveness and efficiency in the process of selling sacrificial animals, as well as expanding sales so that they can be accessed by potential buyers anytime and anywhere.
Detect the Activity of Benign and Malignant Breast Cancer Ayu Fitriyani; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1870

Abstract

Breast cancer detection is an important stage for early cancer diagnosis. In this study, a Convolutional Neural Network (CNN) algorithm is used to detect breast cancer. The dataset used consists of MRI scan images of benign and malignant breast cancer, which are processed through breast image cropping and data augmentation. The model was trained using CNN architecture with transfer learning method of VGG-16 model. The results of the model training showed good performance with an accuracy of 62%. These findings show the potential of using CNN and transfer learning in improving early detection of breast cancer.
Valuation of Svm Kernel Performance in Organic and Non-Organic Waste Classification Dahyoung Yenuargo; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1873

Abstract

In an era of increasing concern for environmental sustainability, waste management remains an important global issue. Efficient waste classification, in particular distinguishing between organic and recyclable materials, is essential for reducing environmental impact. Traditional manual classification methods are often error-prone and inefficient. This research evaluates the performance of SVM models with RBF and Polynomial kernels for waste classification, using SqueezeNet for feature extraction. Datasets from Kaggle were preprocessed and augmented to improve model training. The experimental results show that the SVM model with RBF kernel outperforms the Polynomial kernel in classifying organic and recyclable waste, with an accuracy of 97.9% compared to 97.3% for the Polynomial kernel. This finding underscores the importance of kernel selection and parameter tuning in optimising SVM models for non-linear classification tasks. This research contributes to the development of more efficient and accurate waste classification technologies, promoting better waste management practices. Further research is recommended to explore advanced feature extraction methods and expand the scope of classification to cover a wider range of waste categories.
Industrial Safety Helmet Detection: Innovative CNN-Based Classification Approach Herdyanto, Febro; Fatchan, Muhamad; Hadikristanto, Wahyu
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1925

Abstract

This study presents the development and evaluation of a CNN-based model for detecting safety helmets in industrial settings. Utilizing a dataset from GitHub, which includes images of individuals wearing safety helmets in various industrial environments, the model was trained using the YOLOv8 architecture over 100 epochs. The comprehensive training process involved data augmentation techniques to enhance generalization capabilities. The evaluation results demonstrated high precision (0.92) and recall (0.856) for helmet detection, with an overall mAP50 of 0.766. Visual analysis through precision-confidence curves confirmed the model's high reliability in detecting helmets at higher confidence thresholds. These findings suggest that the implementation of this model in real-time monitoring systems could significantly enhance industrial safety by reducing manual inspection efforts and ensuring compliance with safety regulations
Pelatihan Peningkatan Kemampuan Guru SMP IT Insan Kamil Cikarang Dalam Melakukan Evaluasi Pembelajaran Menggunakan Computer Base Test (CBT) Miharja, Muhammad Najamuddin Dwi; Edora, Edora; hadikristanto, Wahyu; Andika, Sophian; Herol, Herol
Welfare : Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2023): Welfare : June 2023
Publisher : Fakultas Ekonomi dan Bisnis Islam, IAIN Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/welfare.v1i2.506

Abstract

This community service program aims to improve the ability of IT Insan Kamil Cikarang Middle School teachers in conducting learning evaluations using the Computer-Based Test (CBT). Teachers will be given training and an introduction to CBT and given practice to create questions and enter them into the CBT platform. The training method used is a competency-based training approach using demonstration methods and hands-on practice in learning. The results of this training indicate an increase in teacher competency in designing, developing, and implementing information technology-based learning evaluations. It is hoped that this program can increase effectiveness and efficiency in learning evaluation, as well as increase student motivation in learning. Challenges that need to be overcome include the lack of understanding and use of technology by teachers and students, and the need for the right approach in implementing CBT. This program is expected to provide greater benefits for teachers and students.
Improving Employee Retention Through Prediction and Risk Management Using Machine Learning Pratama, Galang Rintang Widya; Fatchan, Muhamad; Hadikristanto, Wahyu
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 Alfarizi, Muhammad Farhan; Fatchan, Muhamad; Hadikristanto, Wahyu
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.
IMPEMENTASI CONTENT MODERATION DALAM SOCIAL MEDIA INSTAGRAM UNTUK DETEKSI CYBERBULLYING DENGAN MACHINE LEARNING BERBASIS CLOUD. Hadikristanto, Wahyu
Indonesian Journal of Business Intelligence (IJUBI) Vol 5 No 2 (2022): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v5i2.2804

Abstract

Media sosial adalah platform di internet yang memungkinkan pengguna untuk berkomunikasi, berbagi informasi, dan terhubung dengan orang lain. Instagram adalah salah satu media sosial yang paling banyak digunakan di seluruh dunia. Cyberbullying adalah tindakan menyiksa, mengancam, atau menyiksa seseorang secara online. Machine learning adalah teknologi yang memungkinkan komputer untuk mempelajari danmengembangkan kemampuan tanpa diberi instruksi secara eksplisit. Machine learning dapat digunakan dalam berbagai bidang, termasuk content moderation untuk mencegah cyberbullying. Secara keseluruhan, penelitian tentang content moderation dengan machine learning berbasis cloud cukup efisien, mengingat nilai akurasi yang diperoleh sebesar 85%.
Grouping of Village Status in West Java Province Using the Manhattan, Euclidean and Chebyshev Methods on the K-Mean Algorithm Pranoto, Gatot Tri; Hadikristanto, Wahyu; Religia, Yoga
JISA(Jurnal Informatika dan Sains) Vol 5, No 1 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i1.1097

Abstract

The Ministry of Villages, Development of Disadvantaged Areas and Transmigration (Ministry of Village PDTT) is a ministry within the Indonesian Government in charge of rural and rural development, empowerment of rural communities, accelerated development of disadvantaged areas, and transmigration. Village Potential Data for 2014 (Podes 2014) in West Java Province is data issued by the Central Statistics Agency in collaboration with the Ministry of Village PDTT which is in unsupervised data format, consists of 5319 village data. The Podes 2014 data in West Java Province were made based on the level of village development (village specific) in Indonesia, by making the village as the unit of analysis. Base on the Regulation of the Minister of Villages, Disadvantaged Areas and Transmigration of the Republic of Indonesia number 2 of 2016 concerning the village development index, the Village is classified into 5 village status, namely Very Disadvantaged Village, Disadvantaged Village, Developing Village, Advanced Village and Independent Village based on the ability to manage and increase the potential of social, economic and ecological resources. Village status is in fact inseparable from village development that is under government funding support. However, village development funds have not been distributed effectively and accurately according to the conditions and potential of the village due to the lack of clear information about the status of the village. Therefore, the information regarding the villages priority in term of which villages needs more funding and attention from the government is still lacking. Data mining is a method that can be used to group objects in a data into classes that have the same criteria (clustering). One of the algorithms that can be used for the clustering process is the k-means algorithm. Data grouping using k-means is done by calculating the closest distance from data to a centroid point. In this study, different types of distance calculation in the K-means algorithm are compared. Those types are Manhattan, Euclidean and Chebyshev. Validation tests have been carried out using the execution time and Davies Bouldin index. From this test, the data Village Potential 2014 in West Java province have grouped all the 5 status of the village with the obtained number of villages for each cluster is a cluster village Extremely Backward many as 694 villages, cluster Villages 567 villages, cluster village Evolving as much as 1440 villages, the cluster with Desa Maju1557 villages and the cluster Independent Village for 1061 villages. For distance calculation, Chebyshev has the most efficient accumulation time of 1 second compared to Euclidean 1.6 seconds and Manhattan 2.4 seconds. Meanwhile, the Euclidean method has the value, Davies Index most optimal which is 0.886 compared to the Manhattan method 0.926 and Chebyshev 0.990.
Co-Authors ., Sapardi A. Reza Baehaqa Jamroni Jamroni Abdul Halim Anshor Abdul Hasyim Abimanyu, Aldo Anggito Achmad Firmansyah Putra Adrianna Syariefur Rakhmat Adriansyah, Putri Nabila Adinda Agung Nugroho Ahmad Gunawan Ahmad Zy Ahmad, Asyari Alfarizi, Muhammad Farhan Ali Nurdiansyah Ananto Tri Sasongko Andika, Sophian Andri Firmansyah Anggara, Bastian Anisa Anisa Anisa Rahmawati Anshor , Abdul Halim Ansor, Abdul Halim Ariandi, Sheva Rizky Arvita Emarilis Intani Aswan S Sunge Atma, Dodit Ardi Atthoriq, Syaifullah Ayu Fitriyani Badruzzaman, Aceng Dahyoung Yenuargo Dichi Setiawan Diki Febriani Dodit Ardiatma Doni, Muhamad Edi Junianto Edi Widodo Edora Edora Edora Edora, Edora Edy Widodo Eko Budiarto Eko Budiarto Ermanto Fadlurrohman, Muhammad Shiddiq Fajar Arief Rachman fatchan, fatchan Fatchan, Muhammad Fauzi Ahmad Muda Fitri Rezeki Gatot Tri Pranoto Hanif, Sa’ad Khairudin Herdyanto, Febro Herol, Herol Holwati Ikmal Riyan Firmansyah Imam Nasai2 Indradewa, Rhian Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Karsito, Karsito Keswanto Kurniadi, Nanang Tedi Laki, Abraham Leo Contantinus Meze Listanto, Firgiawan Maulida Ramadhan Mico Giovanni Dermawan Miharja, Muhammad Najamuddin Dwi Muhamad Fatchan Muhammad Fatchan Muhammad Makmun Effendi 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 Prasetyo Pratama, Galang Rintang Widya Prayoga, Dimas Purdianto Purdianto Purwanto Purwanto Purwanto Putri N.A, Anindya Rahmawati, Shinta Melliana Rahmawati Rasmiati Nur Aeni Retno Purwani Setyaningrum Riska Puspa Anggraeni Putri Risky Bambang Sutrisna Rizky Igel Herisaputra romanuddin, ahmad Rosyati Adelia S Suprapto Sandi Salvan N N Sanudin Sanudin Sanudin Satria Permana, Muhammad Safri Setiawan, Dani Yuda Dwi Siska Wulandari, Siska Suderajat, Agung Sufajar, Sufajar Sufajar, Suprapto Suhardian Suhardian Suherman Suherman Suherman Sunaryati , Titin Sunita Dasman Sya syah Apriliyani Syach, Ridwan 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