Article Per Year (5 Year)
p-Index From 2021 - 2026
3.469
P-Index
This Author published in this journals
All Journal JURNAL SISTEM INFORMASI BISNIS JOIV : International Journal on Informatics Visualization Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Information Systems and Informatics Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi Akuntansi SPEED - Sentra Penelitian Engineering dan Edukasi Jurnal Media Computer Science Paradigma Indonesian Journal Computer Science (ijcs) Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan
Galih Setiawan Nurohim
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 26 Documents
Search

 1   2   3 
Knowledge-Based Intelligent System for Diagnosing Three-Wheeled Motorcycle Engine Faults Ary Setyadi, Heribertus; Supriyanta, Supriyanta; Nurohim, Galih Setiawan; Widodo, Pudji; Sutanto, Yusuf
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2487

Abstract

Three-wheeled motor engine damage is one of the most serious problems with all motorcycles. When problems appear, it becomes difficult for users to repair and diagnose faults because knowledge about machine breakdown symptoms is minimal. Most motorcycle repair shops don’t have mechanics who understand tricycle motorbike engines, so they are less accurate in diagnosing damage symptoms, only based on estimates. Three-wheeled motorbikes have several differences in structure and spare parts compared to motorcycles because tricycle motorbikes have an axle like a car. For this problem, an information system is needed with a method that combines an expert's experience, expertise, and knowledge to develop expert system applications based on several cases that have been experienced and are known as case-based reasoning. This research aims to produce a web-based expert system to diagnose and solve tricycle motorbike engine damage problems. The case-based reasoning method with the K-Nearest Neighbor algorithm is used to assist in analyzing engine damage and give solutions to the issues in three-wheeled motorbike engines. Using two methods is appropriate because of the answers found and the similarities calculated by the cosine similarity method, which experts then review to get the proper solution. From testing using 20 samples of diagnostic data, an accuracy percentage of 85% was obtained. The calculation result for precision is 85%, and recall is 85%.
Implementation MFEP Method in Developing Recommendation System for Program Keluarga Harapan (PKH) Recipients Nugroho, Wawan; Nurohim, Galih Setiawan; Setyadi, Heribertus Ary Setyadi; Perbawa, Doddy Satrya
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 2 (2024): September 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i2.4978

Abstract

Poverty occurs because of the imbalance between unlimited human needs and limited resources. This results in a lack of income to meet basic living needs. The Indoonesian government's efforts to alleviate poverty include providing assistance to the poor or underprivileged with assistance called Social Assistance, one of which is the Program Keluarga Harapan (PKH). Problems often occur in determining who is entitled to receive PKH assistance. The conventional selection process is considered inefficient because it requires a long process and the influence of the committee's subjectivity in the assessment, the criteria used in the survey are not in accordance with government regulations and the limited quota of total PKH recipients, so there are still people who do not receive PKH even though they meet the criteria. This research uses the Multi Factor Evaluation Process (MFEP) method. System testing uses the black box method and Boundary Value Analysis techniques which focus on finding system errors. To test the system's accuracy by comparing the MFEP process from the system results and facts based on PKH recipients in 2022 and producing an accuracy value of 91%.
Analisis Pola Belanja dengan Metode Apriori: Studi Kasus pada Data Transaksi Penjualan Alat Kesehatan di Joyo Alkes Nurohim, Galih Setiawan; Fauzi, Ahmad; Al Amin, Budi; Perbawa, Doddy Satrya
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 1 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i1.3196

Abstract

Penelitian ini bertujuan untuk menganalisis pola belanja dengan metode algoritma Apriori pada data transaksi penjualan toko alat kesehatan. Langkah-langkah analisis meliputi penghapusan kolom tidak penting, konversi data ke format transaksional, dan penggunaan algoritma Apriori untuk menghasilkan aturan asosiasi. Hasil analisis mengidentifikasi pola belanja yang memberikan wawasan berharga bagi toko dalam merencanakan strategi pemasaran dan penataan produk. Joyo Alkes, sebagai contoh toko alat kesehatan di Sukoharjo, memiliki banyak transaksi penjualan harian yang jika tidak diolah, data hanya menjadi sampah. Dengan teknologi data mining, data transaksi bisa diubah menjadi informasi berharga untuk peningkatan penjualan dan promosi produk. Algoritma Apriori digunakan untuk menganalisis data penjualan Joyo Alkes, memungkinkan pengembangan penjualan dan pemasaran produk yang lebih efektif. Pada penelitian ini, menggunakan nilai minimal support (penunjang) sebesar 5% dan nilai minimal confidence (kepastian) sebesar 60%. Hasil penelitian yang didapatkan bahwa pembeli produk 021m3 akan membeli produk onehealthcanul dan 026m3part2 secara bersamaan. dan pembeli produk reg akan membeli produk t021m3.
Optimization of Prediction for Cancellation of Hotel Room Reservation Using Decision Tree with Feature Selection and Resampling Rahmawati, Eka; Nurohim, Galih Setiawan
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp211-215

Abstract

The hotel industry is highly competitive and faces challenges, such as fluctuating demand, intense competition, and shifting consumer preferences. One critical issue that hotels frequently encounter is the cancellation of room reservations, which disrupts operational planning and resource management and leads to significant financial losses. Accurately predicting the likelihood of reservation cancellation is essential to mitigate these negative impacts and optimize revenue management strategies. This study focuses on the development of a predictive model for hotel room reservation cancellations using a decision-tree algorithm. The Decision Tree was selected for its ability to manage complex relationships between variables and ease of interpretation, making it accessible to hotel managers without technical expertise. To enhance the performance of the model, a forward selection technique was employed to identify the most relevant features, ensuring a balance between the model complexity and predictive accuracy. Additionally, resampling techniques were applied to address class imbalance in the dataset, which is common in cancellation cases where non-cancelled reservations outnumber cancelled reservations. This study explores the prediction of hotel room reservation cancellations using a decision tree algorithm enhanced by feature selection and resampling. The model achieved an accuracy improvement to 90%, with precision and recall each increasing by 5,5% after applying these techniques. These findings suggest practical applications for improving cancellation predictions and optimizing revenue management strategies for hotels. The study provides insights into how data-driven approaches can enhance decision-making processes within the competitive hospitality industry.
Effectiveness And Efficiency Of LLM Models Vs Traditional Machine Learning In Sentiment Analysis Of Indonesian Language Product Reviews Nurohim, Galih Setiawan; Amin, Budi Al; Setyadi, Heribertus Ary
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8681

Abstract

This research aims to conduct a comparative analysis of the performance and efficiency of several machine learning models in the task of sentiment analysis on Indonesian language customer reviews. In the digital business era, a quick and accurate understanding of customer opinions is a strategic asset for making decisions, from product development to marketing strategy. Four models were evaluated: two Transformer-based models (agufsamudra/indo-sentiment-analysis and ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa), Naive Bayes, and K-Nearest Neighbors (KNN) on a dataset of 5,400 product reviews. The evaluation metrics used are Accuracy, Precision, Recall, and F1-Score. The results show that the Naive Bayes model and the Transformer model 'agufsamudra/indo-sentiment-analysis' achieve the highest performance with an F1-Score and accuracy of around 95%, significantly outperforming other Transformer models (90%) and KNN (47%). The crucial finding of this research is that the performance of the classical Naive Bayes model is equivalent to the state-of-the-art Transformer model. From an accounting and business perspective, this implies that solutions with much higher computational efficiency (Naive Bayes) can provide a more optimal Return on Investment (ROI) for large-scale implementation of customer sentiment monitoring systems.
Memanfaatkan AI untuk Storytelling: Panduan Praktis untuk Content Creator pada Yayasan Kelurahan Banjarsari Galih Setiawan Nurohim; Budi Al Amin; Diah Pradiatiningtyas
Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial Vol. 2 No. 2 (2025): Mei : Masyarakat Berkarya : Jurnal Pengabdian dan Perubahan Sosial
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karya.v2i2.1393

Abstract

In this fast-paced time, the relationship between content creators and audiences can be built using storytelling and quality content as an attraction. Along with the emergence and development of technology, AI or Artificial Intelligence now facilitates the creative process for content creators. AI can assist from drafting, visuals, to editing. This article aims to directly explain how AI can help improve efficiency, generate ideas, and expand ways of telling a story. However, when integrating AI into the creative process, there are limitations that must not lose the personal touch and creative flair that make a story feel meaningful and remain authentic. Content creators are able to use human insight and the sophistication of AI to produce stronger, more innovative, and relevant storytelling amidst increasingly fierce digital competition.
Pengenalan Artificial Intelligence Pada Pondok Pesantren Yatim Al Ikhsan Surakarta Budi Al Amin; Candra Agustina; Wawan Haryanto; Galih Setiawan Nurohim
Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Vol. 1 No. 2 (2024): April: Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bersama.v1i2.158

Abstract

Introduction and use of artificial intelligence (AI) technology is increasingly widespread in various aspects of human life. In the context of community service, AI has great potential to improve the quality of life of people through a variety of innovative applications. This article discusses how AI can be used in community service, including practical applications in the field of education. Student Data Management: Al Ihsan Foundation can use AI to manage orphan student data such as personal data, academic data, and health data. AI-supported data management systems can integrate this information better, thus enabling more personalized and customized services. Learning and Development: AI can be used to develop online learning platforms that are tailored to individual student learning needs. AI systems analyze student learning preferences and progress and recommend the most effective learning materials and methods. By leveraging AI, younger generations can create exciting, high-quality content without having to have specialized expertise in graphic design or video editing. For example, technologies such as Canva Magic Studio leverage artificial intelligence to make it easier to make exciting designs.The training aims to provide a better understanding to the younger generation of the basic concepts of AI and its applications in everyday life, including in the creation of creative digital content. Hopefully, with a better understanding of AI, the younger generation will be able to develop their creative potential and use it for a variety of positive purposes in their lives.
Penerapan Sistem Informasi E-Posyandu dalam Pengawasan Pertumbuhan Gizi Anak di Posyandu Kelurahan Mojosongo Surakarta Ahmad Fauzi; Budi Al Amin; Doddy Satrya Perbawa; Galih Setiawan Nurohim
Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat Vol. 1 No. 4 (2024): Oktober: Kesejahteraan Bersama : Jurnal Pengabdian dan Keberlanjutan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/bersama.v1i4.690

Abstract

Integrated Service Posts (Posyandu) are important facilities for monitoring children's nutritional growth and development, but there are still many posyandu that use manual methods for recording data. This results in obstacles such as inaccurate data, delays in decision making, and difficulty in accessing information. To overcome this problem, the E-Posyandu information system was implemented at the Posyandu, Mojosongo Village, Surakarta. E-Posyandu is a digital platform designed to facilitate automatic and structured recording, storage and processing of children's nutritional data. This research aims to examine the effectiveness of implementing the E-Posyandu system in improving monitoring of children's growth and nutritional status in Mojosongo Village. By using this technology, the monitoring process becomes more efficient, data is easier to access, and the potential for recording errors can be minimized. Apart from that, this system also offers reminders and notification features to parents regarding the posyandu schedule and necessary health measures.The results of the implementation show an increase in the accuracy and speed of collecting child nutrition data, as well as increased parent participation in monitoring their child's health. It is hoped that E-Posyandu can become an innovative model to be applied in other posyandu in Indonesia.
Penentuan Kelayakan dan Jenis Lembaga Keuangan dalam Pemberian Modal UMKM Menggunakan Metode AHP dan Decision Tree Setyadi, Heribertus Ary; Nurohim, Galih Setiawan; Nugroho, Wawan
Jurnal Ilmiah FIFO Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2024.v16i1.007

Abstract

Terdapat beberapa kendala dibalik kehadiran UKM dalam pengelolaan usaha tersebut, antara lain kesulitan memperoleh pinjaman dari perbankan karena kurangnya pengetahuan pegawai yang ada, kurangnya perkembangan teknologi informasi, dan beberapa syarat yang tidak dapat terpenuhi. Tujuan penelitian ini untuk mengembangkan sistem pendukung keputusan yang dapat membantu dalam menentukan kelayakan UMKM dan lembaga keuangan yang sesuai untuk melakukan pinjaman. Terdapat 25 sampel UMKM yang berada di Kota Surakarta untuk dijadikan bahan penelitian. Algoritma decision tree dan metode Analytic Hierarchy Process (AHP) digunakan dalam penelitian ini. Tahap pertama untuk penentuan kelayakan suatu UMKM yang akan diberi pinjaman menggunakan algoritma decision tree. Penentuan rekomendasi jenis lembaga keuangan yang sesuai menerapkan metode AHP. Dari hasil pengujian diperoleh tingkat akurasi penerapan algoritma decision tree sebesar 80%. Pengujian tingkat akurasi penerapan metode AHP menghasilkan nilai 76,9%. Dari kedua pengujian tersebut, dapat dikatakan bahwa sistem yang dibuat sudah baik atau akurat.
UTILIZING END USER DEVELOPMENT METHOD FOR DEVELOPING PENCAK SILAT ORGANIZATION INFORMATION SYSTEMS Setyadi, Heribertus Ary; Wahyuningsih, Hartati Dyah; Nurohim, Galih Setiawan; Sundari, Sundari
Jurnal Pilar Nusa Mandiri Vol. 21 No. 2 (2025): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v21i2.6487

Abstract

Gondang is one of the PSHT sub-branches located in Sragen Regency, Central Java, Indonesia. In managing member data from recruitment to promotion, conventional methods are still used using office applications and information dissemination is still using brochures and social media. This research aims to develop an information system that can help manage data and disseminate information at PSHT Gondang. The system developed can manage the registration of prospective member to become a member and the process of promotion. Delivery of information in the form of organizational structures, announcements, activity schedules, services for member and community, activity galleries containing photos and videos can also be accessed through the system.EUD was chosen as a method in system development because time required is quite short with a relatively small cost allocation. The system is created using Laravel framework and Firebase as a database with a responsive display so that it can be accessed using a smartphone. By using the EUD method, users can modify the appearance and existing information if there is a change in data from the organization which was not available in previous research.
Co-Authors Ahmad Fauzi Ahmad Fauzi Akbar, Muhammad Faitullah Al Amin, Budi Amin, Budi Al Budi Al Amin Candra Agustina Diah Pradiatiningtyas Doddy Satrya Perbawa eka rahmawati Fauzi Ahmad Muda Fauzi, Ahmad Heribertus Ary Setyadi Indradewa, Rhian Muhammad Faittullah Akbar Nugroho, Wawan Pudji Widodo Setyadi, Heribertus Ary Setyadi Siti Khotimah Sundari Sundari Supriyanta Supriyanta Sutanto Sutanto Sutanto Sutanto Wahyuningsih, Hartati Dyah Wati, Fanny Fatma Wawan Haryanto Yusuf Sutanto