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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS JAKPI Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sains dan Informatika JKIE (Journal Knowledge Industrial Engineering) Jurnal Ilmiah Ecobuss Juriti Prima (Jurnal Ilmiah Teknik Industri Prima) Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Sistem Teknik Industri Jurnal Mnemonic Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Teknik Informatika (JUTIF) Blend Sains Jurnal Teknik Scientific Journal of Informatics Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Irwan Budiman
Fakultas MIPA, Universitas Lambung Mangkurat Banjarbaru, Kalimantan Selatan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences

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Energi Analysis of Significant Energy Use in Tire Company using Pareto Diagram Kamaluddin, Kamaluddin; Budiman, Irwan; Christine Sembiring, Anita
Journal Knowledge Industrial Engineering (JKIE) Vol 9 No 2 (2022): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v9i2.3252

Abstract

Melalui Peraturan Pemerintah No. 70 tahun 2009 tentang Konservasi Energi, pemerintah telah mewajibkan bagi pengguna energi besar yaitu pengguna yang menggunakan energi sama atau lebih dari 6000 setara ton minyak per tahun wajib melaksanakan kegiatan konservasi energi atau manajemen energi. Dalam penelitian di objek penelitian yang merupakan perusahaan ban, perusahaan tersebut merupakan salah satu industri yang menggunakan energi lebih dari 6000 setara ton minyak per tahun dan merupakan salah satu industri yang secara langsung memberikan dampak bagi penyediaan energi nasional. Menyadari dampak dari ketersediaan dan kenaikan harga energi ini terutama bagi industri, maka perusahaan dituntut perlu melakukan tindakan yang tepat dan bijaksana dalam mengkonsumsi energi melalui program konservasi dan penghematan energi. Penerapan Manajemen Energi yang terlihat di perusahaan masih digabungkan dengan struktur fungsional organisasi yang ada sehingga fungsi kontrolnya menjadi lemah. Pentingnya penentuan prioritas dalam melaksanakan konservasi energi, dengan menggunakan metode diagram pareto 20/80 akan memberikan penyusunan sasaran yang lebih tepat dalam mencapai efisiensi energi. Pemilihan prioritas akan memberikan potensi yang cukup besar untuk peningkatan kinerja energi, di samping itu penentuan prioritas akan membuat organisasi lebih efektif dan efisien.
Analisis Kondisi Manajemen Dokumen dengan Metode 5S di Institusi Pendidikan Manik, Cindy Vivi Anggreni; Sembiring, Anita Christine; Budiman, Irwan
Blend Sains Jurnal Teknik Vol. 3 No. 1 (2024): Edisi Juli
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v3i1.577

Abstract

Sistem 5S adalah pendekatan sistematis untuk mengatur dan memelihara tempat kerja yang bersih dan efisien Penelitian ini bertujuan untuk mengkaji status pengelolaan dokumen dengan menggunakan sistem 5S. Pengelolaan dokumen pada institusi pendidikan memegang peranan penting dalam meningkatkan efisiensi dan produktivitas. Untuk meningkatkan kualitas pengelolaan dokumen dapat digunakan sistem 5S (Seiri, Seiton, Seiso, Seiketsu, Shitsuke). Penelitian ini menggunakan jenis penelitian deskriptif kuantitatif, dengan melibatkan studi kasus pada institusi pendidikan terpilih. Pengumpulan data menggunakan angket, observasi, dan dokumentasi. Proses ini berfokus pada manajemen dokumen yang lebih efisien, dan pemantauan kualitas dokumen yang lebih baik. Dalam penelitian ini penulis mengkaji situasi pengelolaan dokumen di institusi pendidikan dengan mengunakan metode 5S. Hasil penelitian menunjukkan bahwa penerapan sistem 5S dapat meningkatkan efisiensi organisasi dan produktivitas pengelolaan dokumen di institusi pendidikan. Kajian ini merekomendasikan agar institusi pendidikan mengadopsi sistem 5S sebagai standar sistem pengelolaan dokumen untuk menjamin pengelolaan dokumen yang efisien dan efektif, yang penting untuk menjaga kualitas layanan akademik.
Implementation of Ant Colony Optimization in Obesity Level Classification Using Random Forest Wardana, Muhammad Difha; Budiman, Irwan; Indriani, Fatma; Nugrahadi, Dodon Turianto; Saputro, Setyo Wahyu; Rozaq, Hasri Akbar Awal; Yıldız, Oktay
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4696

Abstract

Obesity is a pressing global health issue characterized by excessive body fat accumulation and associated risks of chronic diseases. This study investigates the integration of Ant Colony Optimization (ACO) for feature selection in obesity-level classification using Random Forests. Results demonstrate that feature selection significantly improves classification accuracy, rising from 94.49% to 96.17% when using ten features selected by ACO. Despite limitations, such as challenges in tuning parameters like alpha (α), beta (β), and evaporation rate in ACO techniques, the study provides valuable insights into developing a more efficient obesity classification system. The proposed approach outperforms other algorithms, including KNN (78.98%), CNN (82.00%), Decision Tree (94.00%), and MLP (95.06%), emphasizing the importance of feature selection methods like ACO in enhancing model performance. This research addresses a critical gap in intelligent healthcare systems by providing the first comprehensive study of ACO-based feature selection specifically for obesity classification, contributing significantly to medical informatics and computer science. The findings have immediate practical implications for developing automated diagnostic tools that can assist healthcare professionals in early obesity detection and intervention, potentially reducing healthcare costs through improved diagnostic efficiency and supporting digital health transformation in clinical settings. Furthermore, the study highlights the broader applicability of ACO in various classification tasks, suggesting that similar techniques could be used to address other complex health issues, ultimately improving diagnostic accuracy and patient outcomes.
Accurate Skin Tone Classification for Foundation Shade Matching using GLCM Features-K-Nearest Neighbor Algorithm Syahputra, Muhammad Reza; Mazdadi, Muhammad Itqan; Budiman, Irwan; Farmadi, Andi; Saputro, Setyo Wahyu; Rozaq, Hasri Akbar Awal; Sutaji, Deni
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4723

Abstract

Foundation shade matching remains a significant challenge in the beauty industry, particularly in Indonesia where consumers exhibit three distinct skin tone categories: ivory white, amber yellow, and tan. Manual foundation selection often results in mismatched shades, leading to customer dissatisfaction. This study presents a novel automated skin tone classification system combining Gray Level Co-Occurrence Matrix (GLCM) feature extraction with the K-Nearest Neighbor (KNN) algorithm. The GLCM method extracts four key texture features (contrast, homogeneity, energy, and entropy) from facial images, while KNN performs classification. A comprehensive dataset of 963 facial images was used, with 770 training and 193 test samples collected under controlled lighting conditions. After testing K values from 1 to 15, the optimal K=1 achieved 75.65% accuracy. Compared to baseline color histogram methods (60% accuracy), our GLCM-KNN approach demonstrates 15.65% improvement in classification performance. This research contributes to computer vision applications in beauty technology, enabling the development of mobile applications for virtual foundation try-on and personalized product recommendations. The findings have significant implications for the cosmetics industry, particularly for automated cosmetic shade matching systems and enhanced customer experience in online beauty retail. Further research is recommended to explore deep learning approaches and expand dataset diversity to improve accuracy.
PEMETAAN KONDISI INTERNAL DAN EKSTERNAL UMKM TRANSPORTASI DENGAN MENGGUNAKAN ANALISIS SWOT DI SUMATERA UTARA AROTAMA, ARDIAN HIRAMAN; BUDIMAN, IRWAN
JAKPI - Jurnal Akuntansi, Keuangan & Perpajakan Indonesia Vol. 8 No. 2 (2020): Jurnal Akuntansi, Keuangan & Perpajakan Indonesia (JAKPI)
Publisher : Universitas Negeri Medan (UNIMED)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/jakpi.v8i2.20737

Abstract

Abstrak: Penelitian ini memfokuskan pada perusahaan jasa yang sedang mengalami penurunan jumlah penumpang pada wilayah Medan, Bandara Kualanamu Internasional, Siantar, Parapat, Sibolga, dan daerah Singkil. UMKM  juga mengalami permasalahan  yang diakibatkan beberapa factor yaitu: kekurangan armada, cara memasarkan kepada konsumen kurang, dan keterlambatan penjemputan konsumen. Penelitian ini bertujuan untuk mengetahui posisi perusahaan dalam Matriks IFAS dan EFAS serta program kerja prioritas. Metode yang dipakai dalam penelitian ini adalah analisis  SWOT adalah metode perencanaan strategis yang digunakan untuk mengevaluasi kekuatan (strengths), kelemahan (weaknesses), peluang (opportunities), dan acaman (threats) dalam suatu proyek atau spekulasi bisnis. Hasil analisis SWOT menunjukkan bahwa perhitungan Matriks IFAS dan EFAS diperoleh hasil IFAS lebih tinggi daripada EFAS dan skor tertinggi terdapat pada Strengths sebesar 2,0667.Kata kunci : Strategi, SWOT Analysis, Balanced Scorecard, QSPM    
Evaluation of User Experience in the Banjarbaru Disdukcapil Public Service Application Using User Experience Questionnaire and System Usability Scale Martalisa, Asri; Wahyu Saputro, Setyo; Turianto Nugrahadi, Dodon; Abadi, Friska; Budiman, Irwan
Scientific Journal of Informatics Vol. 11 No. 4: November 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.13780

Abstract

Purpose: Dukcapil Banjarbaru is an online-based government agency application used for various public services. According to the complaint report from Disdukcapil Banjarbaru, several users have reported similar problems and difficulties. The application has received a rating of 3.3 stars from approximately 24.000 users on the Google Play Store. Therefore, researchers conducted a user experience analysis using the UEQ methods and a usability evaluation using the SUS methods. Methods: This research analyzes user experience in applications using the UEQ to identify issues faced by users and evaluate usability through the System Usability Scale. The UEQ method is chosen for its efficiency and simplicity in assessing user experience within an application. The SUS method is employed because it is an effective approach for obtaining reliable statistical data and generating clear and accurate scores. Result: The UEQ benchmark results show that the scales for Attractiveness (1.59), Efficiency (1.68), Accuracy (1.66), and Stimulation (1.54) are categorized as "Good." The scales for clarity (1.37) and novelty (0.80) are classified as "Above Average." Meanwhile, the SUS score of 65 positions the application within the "acceptable" category for the acceptability range, the "D" category on the grade scale, and the "OK" category for adjective ratings. This indicates that while the Banjarbaru Dukcapil application has good usability, it requires improvements based on the total SUS score, which reveals several critical areas with scores below the average (258.4). Novelty: In this research, solutions for improvements are provided to Disdukcapil based on each aspect to improve the quality of the application, thereby offering better services to users.
Application of Adaboost Algorithm with SMOTE and Optuna Techniques in Sleep Disorder Classification Anshory, Muhammad Naufal; Mazdadi, Muhammad Itqan; Saragih, Triando Hamonangan; Budiman, Irwan; Saputro, Setyo Wahyu
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 2 (2025): May
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i2.99

Abstract

Data imbalance is a serious challenge in developing machine learning models for sleep disorder classification. When models are trained on an uneven distribution of classes, classification performance for minority classes such as insomnia and sleep apnea is often low. As a result, the overall accuracy may seem elevated, yet the sensitivity to important cases to be weak. Therefore, this research aims to design and develop a robust sleep disorder classification model with the AdaBoost algorithm, with improved performance through the integration of two main approaches, namely data balancing technique utilizing SMOTE and hyperparameter optimization using Optuna. This research contributes by showing that the combination of the two approaches can significantly improve model performance, not only in terms of global accuracy, but also accuracy on previously overlooked minority classes. The dataset utilized is the Sleep Health and Lifestyle Dataset which consists of 374 synthesized data and is divided into three categories: insomnia, sleep apnea, and none. This method stages include data preprocessing, data division using train-test split (80:20), application of SMOTE to balance the class distribution, hyperparameter tuning using Optuna, and model training with the AdaBoost algorithm. Evaluation was performed using classification metrics: accuracy, precision, recall, and F1-score. Results showed that mix of SMOTE and Optuna yielded the best results, accuracy 90.6%, F1-score 0.83871 for insomnia, and 0.81250 for sleep apnea. This performance was consistently superior to scenarios with no SMOTE or no tuning. This confirms the importance of using combination strategies to obtain fair and accurate classification on medical data. Future research is recommended to use real datasets as well as test the capabilities of this research on other models such as XGBoost or LightGBM.
Strategi Pengembangan Pemasaran Produk Hortikultura pada PT Sumber Alam Jaya Perkasa Nantheni, Sobha; Budiman, Irwan
Ecobuss Vol 12 No 1 (2024): Jurnal Ilmiah Ecobuss, Volume 12, Nomor 1, Maret 2024
Publisher : Fakultas Ekonomi dan Bisnis Universitas Panca Marga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51747/ecobuss.v12i1.1862

Abstract

This study aims to determine the application and alternative marketing strategies for horticultural products so that the company can increase sales. The method used in this research uses desciptive analysis with a quantitative approach. The data collection technique used a questionnaire method with a sample of 22 respondents. In addition, there is additional supporting data from books and other sources related to the research. The data obtained was then analyzed using the SWOT analysis method to determine the strengths, weaknesses, opportunities, and threats of the company’s marketing strategy. The results of the study as shown in the Cartesian diagram that the company is in quadrant I which supports an aggressive growth strategy (Growth Oriented Strategy) which is a very favorable situation because it has strengths and can take advantage of existing opportunities.
Improving nutrient prediction models with polynomial and ratio features and mRMR selection Indriani, Fatma; Budiman, Irwan; Kartini, Dwi; Handayani, Lilies
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.9189

Abstract

Due to limited space and regulations, food labels often lack information on micronutrients, i.e., vitamins and minerals. Accurately predicting missing these micronutrient data is essential yet challenging. This study explores the feasibility of using machine learning to predict these missing nutrients based on a limited reported nutrient (protein and carbs). Using the Tabel Komposisi Pangan Indonesia (TKPI) dataset, we evaluated the performance of 12 diverse classifiers to predict binary classes ("low" or "high") for 13 target micronutrients. Random forest emerged as the best performing classifier with an average accuracy of 0.7421 across all target nutrients. Additionally, we introduced feature engineering techniques by incorporating polynomial and ratio features to enhance model performance. Minimum redundancy maximum relevance (mRMR) feature selection was then applied to identify the most informative features. This approach boosted the average accuracy of the random forest classifier to 0.7591. These findings highlight the efficacy of feature engineering and selection in enhancing nutrient prediction models, demonstrating the potential to improve consumer knowledge about unknown nutrients in food.
Analisa dan Usulan Perbaikan Layanan Sertifikasi Produk dengan Metode Lean Service Kacaribu, Loista Sevnin; Tarigan, Uni Pratama; Sembiring, Anita; Budiman, Irwan
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 3 (2024): July
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i3.30454

Abstract

Product Certification Service is a service to business actors who want to get their products certified through the Indonesian National Standard Mark User Product Certificate (SPPT SNI), either compulsorily or voluntarily regulated products. Therefore, the Standardization and Industrial Services Center (BSPJI) Medan as a public service unit that has a Product Certification Agency (LSPro) is needed. The problem is the length of the LSPro BSPJI Medan service process to complete the company's SPPT SNI starting from the application until the issuance of the SPPT SNI. This causes losses for business actors both in funds and time. The purpose of this study is to provide suggestions for improvement and optimize time by maintaining value-added activities and reducing non-value-added activities. The methods used are Lean Service, Waste Analysis and for design using the FVSM Method. The results showed that there was waste that occurred in the LSPro BSPJI Medan service. From the results of the FVSM carried out, there was a reduction in service time from 92 working hours to 26 working hours.
Co-Authors Adi Mu'Ammar, Rifqi Ahdyani, Annisa Salsabila Ahmad Tajali Al Ghifari, Muhammad Akmal Al Habesyah, Noor Zalekha Andi Farmadi Andreas Panjaitan, Andreas Anita Christine Sembiring Anshory, Muhammad Naufal Antoh, Soterio AROTAMA, ARDIAN HIRAMAN Arumbasari, Atita Azizah, Azkiya Nur Azizah, Siti Roziana Chandra Wijaya david Deni Sutaji Dodon Turianto Nugrahadi Dwi Kartini, Dwi Engmir Faisal, M. Reza Fathmah, Siti Fatma Indriani Friska Abadi Halim, Kevin Yudhaprawira Halimah Halimah Hartono, James Luis Herteno, Rudy Jumadi Mabe Parenreng Kacaribu, Loista Sevnin Kamaluddin Kamaluddin Kartika, Tengku Heny Lilies Handayani Mahmud Mahmud Manik, Cindy Vivi Anggreni Martalisa, Asri Muhammad Alkaff Muhammad Itqan Mazdadi Muhammad Reza Faisal, Muhammad Reza Muliadi Muliadi MULIADI -, MULIADI Nantheni, Sobha Noor Hidayah Nurdiansyah Nurdiansyah Prastya, Septyan Eka Radityo Adi Nugroho Rhamadani, Poetri Rizky, Muhammad Hevny Rozaq, Hasri Akbar Awal Rudy Herteno Said, Muhammad Al Ichsan Nur Rizqi Santonius, celvin Saputro, Setyo Wahyu Saragi , Yosefin Saragih, Triando Hamonangan Sembiring, Anita Stefen Sembiring, Andes Stepvani, Putri Syahputra, Muhammad Reza Tajali, Ahmad Tampubolon, Jusra Tarigan, Uni Pratama Tuti Sarma Sinaga Wahyu Caesarendra Wahyu Saputro, Setyo Wardana, Muhammad Difha Wati, Vera Winda Agustina YILDIZ, Oktay Yunida, Rahmi