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Pelatihan Dasar Fotografi untuk Mendukung Digitalisasi Produk Kopi Bubuk di UMKM Linusco Kabupaten Pasuruan Ernawati; Ainiyah, Roisatul; Palupi, Hapsari Titi; Syarwani, Muhammad; Hasyim, Mochamad; Huda, Miftahul; Ridha, Faishal Ananta; Ahwan, Zainul; Hakim, Lukman; Sulhan, Muhammad; Swasono, Muh Aniar Hari
DEDIKASI SAINTEK Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2024): Desember 2024
Publisher : Al-Hijrah Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58545/djpm.v3i3.439

Abstract

Platform digital menjadi salah satu media utama dalam memperluas jangkauan pemasaran produk, terutama bagi Usaha Mikro, Kecil, dan Menengah (UMKM). Kualitas foto produk memiliki peran yang sangat penting untuk meningkatkan daya tarik visual dan memperluas jangkauan pemasaran produk. Tujuan dari kegiatan ini adalah untuk meningkatkan kapasitas UMKM Linusco dalam memanfaatkan fotografi produk sebagai strategi pemasaran digital. Metode pelaksanaan meliputi tiga tahapan utama: perencanaan, pelaksanaan, dan evaluasi. Tahap perencanaan mencakup identifikasi kebutuhan, penyusunan materi, dan penyediaan alat pendukung, sedangkan tahap pelaksanaan difokuskan kegiatan pelatihan. Hasil pelatihan menunjukkan peningkatan signifikan dalam pemahaman konsep fotografi produk, kemampuan pengambilan foto, dan penguasaan aplikasi pengeditan, sebagaimana ditunjukkan melalui evaluasi hasil praktik peserta. Peserta berhasil menghasilkan foto produk yang lebih menarik dan profesional, siap digunakan untuk promosi digital. Pendekatan kegiatan pelatihan mampu meningkatkan pengetahuan dan keterampilan peserta.
Karakteristik Budaya Organisasi: Sebuah Studi Kualitatif terhadap Pengusaha Batik Muslim Laweyan Surakarta Lukman Hakim; Irwan Abdullah; Nurus Sa'adah
Benefit: Jurnal Manajemen dan Bisnis Volume 6 No 2 Desember 2021
Publisher : Program Studi Manajemen Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/benefit.v6i2.14019

Abstract

This study aims to identify (1) the cultural characteristics of the Muslim batik entrepreneurs in the Batik Industry in Surakarta. (2) the values that underlie the cultural organization of Muslim batik entrepreneurs in the Laweyan Batik Industry, Surakarta. The research locations were Mahkota Batik, Putra Laweyan Batik, Gres Tenan Batik, Puspa Kencana Batik and Merak Manis Batik. This type of research uses descriptive-qualitative methods. The results of the study conclude the cultural characteristics of Muslim batik entrepreneurs organizations, as follows: (1) culture of struggle (al Mujahadah), (2) culture of togetherness (al Ijtimaiyyah), (3) culture of mutual help (at Tawauniyyah), (4) culture of humanity (al Insanniyyah), (5) professional culture (al Ihtirofiyyah), (6) creative and innovative culture (al kholaq wal mubtakar), (7) thoroughness culture (as shihah), and (8) skill culture (al khibrah).
PELATIHAN DIGITAL MARKETING DALAM MENINGKATKAN MINAT WIRAUSAHA SISWA MA MIFTAHUL ULUM PUNTIR Muhammad Imron Rosadi; Miftahul Huda; Lukman Hakim; Bagus Hari Sugiharto
JURNAL PENGABDIAN AL-IKHLAS UNIVERSITAS ISLAM KALIMANTAN MUHAMMAD ARSYAD AL BANJARY Vol 9, No 2 (2023): AL-IKHLAS JURNAL PENGABDIAN
Publisher : Universitas Islam kalimantan MAB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jpaiuniska.v9i2.11976

Abstract

Program pengabdian ini dilaksanakan untuk meningkatkan minat siswa dalam berwirausaha, mengembangkan keahlian dalam membangun bisnis dan memanfaatkan pemasaran digital melalui media sosial. Kegiatan ini ditujukan kepada 30 siswa kelas 12 MA Miftahul Ulum Puntir Purwosari Pasuruan. Terdapat beberapa tahapan dalam pelaksanaan pengabdian ini, antara lain persiapan, pelaksanaan, pendampingan dan pelatihan, evaluasi, dan pelaporan. Pada tahap persiapan dilakukan pertemuan dengan kepala sekolah terkait identifikasi masalah dan tujuan kegiatan, serta waktu pelaksanaan. Pada tahap pelaksanaan dilakukan seminar wirausaha membangun mindset wirausaha sejak usia dini serta diskusi dengan peserta. Pada tahap pelatihan dilakukan pendampingan pelatihan pembuatan ide bisnis menggunakan Google Trends, Google My Business dan Facebook Page untuk pemasaran digital, serta teknik foto produk dan teknik pembuatan video produk. Pada tahap akhir kegiatan ini dilakukan evaluasi kegiatan berupa testimoni, penugasan dan penilaian. Hasil dari pengabdian ini terbukti mampu meningkatkan pemahaman siswa terkait pelatihan digital marketing dengan nilai rata-rata 87%.
PREDIKSI STATUS ANEMIA DENGAN PENDEKATAN PEMBELAJARAN MESIN ALGORITMA SUPPORT VECTOR MACHINE (SVM) DAN SELEKSI FITUR FIREFLY ALGORITHM Tiara Meylinda S; Hakim, Lukman
Jurnal INSTEK (Informatika Sains dan Teknologi) Vol 10 No 1 (2025): APRIL
Publisher : Department of Informatics Engineering, Faculty of Science and Technology, Universitas Islam Negeri Alauddin, Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/instek.v10i1.53170

Abstract

Anemia merupakan kelainan tubuh yang ditandai dengan rendahnya kadar hemoglobin (Hb) dalam sel darah, dan dapat menjadi masalah kesehatan yang serius terlebih pada remaja perempuan jika tidak segera diobati dengan baik. Penelitian ini dilakukan untuk memprediksi status anemia berdasarkan data pasien menggunakan algoritma SVM dengan pemilihan fitur Firefly Algorithm untuk meningkatkan akurasi. Pengujian dilakukan dengan menggunakan empat kernel algoritma SVM yaitu kernel Linear, Polynomial, RBF dan Sigmoid. Hasil penelitian menunjukkan bahwa penggabungan FA dan SVM dapat meningkatkan akurasi pada tiga kernel SVM yaitu kernel linear dari akurasi awal 98.95% menjadi 99.65%, kernel polynomial akurasi awal 94.74% menjadi 98.60%, pada kernel RBF akurasi awal 93.68% menjadi 98.25%, namun pada kernel sigmoid akurasi mengalami penurunan dari akurasi awal 47.02% menjadi 12.98%. Kesimpulannya, penerapan FA untuk memilih fitur-fitur penting pada SVM efektif dan berdampak pada peningkatan akurasi untuk tiga kernel SVM dan penurunan akurasi pada satu kernel hal tersebut terjadi karena underfitting. Seleksi fitur menjadi efektif jika menghasilkan kombinasi fitur yang tepat dan dapat menjadi tidak efektif jika menghasilkan kombinasi fitur yang tidak tepat.
Comparison of Transfer Learning Model Performance for Breast Cancer Type Classification in Mammogram Images Cahya Bagus Sanjaya; Muhammad Imron Rosadi; Moch. Lutfi; Lukman Hakim
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6177

Abstract

Globally, breast cancer is the type of cancer that most women suffer from. Early detection of breast cancer is very important because there is a big chance of cure. Mammography screening makes it possible to detect breast cancer early. The study of computer-assisted breast cancer diagnosis is gaining increasing attention. Breast cancer comes in two forms: benign cancer and malignant cancer. advances in deep learning (DL) technology and its use to overcome obstacles in medical imaging, and classification using a number of transfer learning models to identify the type of breast cancer (malignant, benign, or normal). This work conducted a thorough comparison analysis of eight prevalent pre-trained CNN algorithms (VGG16, ResNet50, AlexNet, MobileNetV2, ShuffleNet, EfficientNet-b0, EfficientNet-b1, and EfficientNet-b2) for breast cancer classification. In this study, we permonData is divided into training, testing, and validation. Using the publicly accessible mini-DDSM dataset, we assess the proposed architecture. were used to measure the classification accuracy (Acc). For genBased on test results, the best accuracy was obtained using EfficientNetb2 with an accuracy value of 94% for training data and 98% for test data on mammogram images.
SEGMENTASI CITRA WAYANG DENGAN METODE OTSU Misbach Munir; M. Ikmal Farih; Lukman Hakim
CYBER-TECHN Vol. 11 No. 01 (2017): CYBER-Techn
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM)

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

Abstract

Wayang merupakan warisan budaya nusantara sekaligus warisan budaya dunia. UNESCO yang menetapkan wayang sebagai world herritage pada 7 Nopember 2003. Namun, pengakuan tersebut belum direspon oleh negara dalam mengembangkan dan melestarikan wayang sebagai budaya tradisi. Alhasil, wayang semakin ditinggalkan generasi muda yang lebih gandrung dengan budaya massa. Dibutuhkan pelestarian Wayang Kulit dengan mengembangkan media yang menarik dan mendidik, salah satu proses penting dalam mengembangkan media adalah segmentasi. Segmentasi adalah adalah salah satu teknik pengolahan citra digital yang mendasari berbagai aplikasi nyata, seperti pengenalan pola, penginderaan jarak-jauh melalui satelit atau pesawat udara, dan machine vision. Segmentasi memiliki beberapa metode salah satunya metode otsu. Metode Otsu merupakan salah satu metode segmentasi dengan menggunakan nilai ambang secara otomatis, yakni mengubah citra digital warna abu-abu menjadi hitam putih berdasarkan perbandingan nilai ambang dengan nilai warna piksel citra digital. Penelitian ini segmentasi dengan metode otsu pada 10 citra wayang kulit dengan ISO berbeda, mampu melakukan segmentasi citra wayang kulit dengan baik, yaitu dengan akurasi rata-rata 94,43%.
Implementation of Integrated Smart System Platform in Improving the Quality of Public Services through Smart Village In Pucangsari Village, Pasuruan Regency: Penerapan Integrated Smart System Platform Dalam Meningkatkan Kualitas Pelayanan Publik Melalui Smart Village Di Desa Pucangsari Kabupaten Pasuruan Hakim, Lukman; Rosadi, Muhammad Imron; Prianto, Agus
Jurnal Soeropati Vol 6 No 1: November 2023
Publisher : LPPM Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/js.v6i1.4499

Abstract

The purpose of this service is to increase the knowledge and skills of the Pucangsari village government in the concept and implementation of a smart village based on an integrated smart system platform through village administration governance, reporting, and utilization of public service applications. The method used in the integrated smart system platform development program in village government services includes three stages; the first stage of preparation by conducting surveys and interviews related to the potential and problems faced by prospective program partners; the second stage of making and developing Integrated smart system Platform Applications; and the third stage of capacity building in the form of workshops, training and socialization. The results of this community service are increased knowledge related to smart villages, the ability to use integrated smart system platform applications and improved public services which include correspondence, billing and payment of land and building taxes, as well as the existence of a community aspiration space as an improvement in the Pucangsari village government performance system.
Assistance of Tourism Cyber Public Relations in Increasing Publicity of Virtual Accessibility through Integrated Tourism Smart Platform (ITSP) in Wonokitri Tourism Village Pasuruan Hakim, Lukman; Ahwan, Zainul; Rosadi, Muhammad Imron; Sanjaya, Cahya Bagus
Jurnal Soeropati Vol 7 No 1: November 2024
Publisher : LPPM Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/js.v7i1.5531

Abstract

The hinterland area of Mount Bromo possesses exotic natural and cultural potential that can be developed into a leading tourist destination. However, the management and promotion of this potential face challenges, particularly in terms of tourism communication skills and the utilization of technology. The activity is to enhance the capacity of local tourism actors by mastering communication skills based on Tourism Cyber Public Relations and improving their ability to utilize technology to support more innovative and sustainable tourism services. Additionally, this program aims to facilitate the development of an integrated digital identity for the tourist village. The assistance program was carried out through five stages: socialization, training, technology implementation, mentoring, and sustainability evaluation. The approach employed was the Community Organizer and Community Development methods, with the main subject being the Raga Wulan Tourism Awareness Group in Wonokitri Village. The results of the activities showed a 25% increase in the knowledge of tourism actors based on pre-test and post-test results conducted during the program. Furthermore, this initiative successfully enhanced the tourism actors' skills in tourism communication, particularly in the field of Tourism Cyber Public Relations. It also resulted in the creation of branding and the development of social media and the official website of Edelweiss Wonokitri Tourism Village, as well as the realization of the Integrated Tourism Smart Platform.
Water Quality Classification Using SVM with PSO-Based Parameter Optimization Seviya, Trisna; Hakim, Lukman
Information Technology Education Journal Vol. 4, No. 3, August (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i3.9746

Abstract

This study investigates the use of Support Vector Machine (SVM) enhanced with Particle Swarm Optimization (PSO) for water quality classification. Conventional SVM models often underperform when parameters are selected manually, resulting in reduced predictive accuracy. To overcome this limitation, PSO was applied to automatically optimize the SVM kernel parameters, enabling more reliable and robust classification. The research employed a quantitative experimental framework consisting of data preprocessing, model training, optimization, and performance evaluation. The dataset included physical and chemical attributes of water quality, which were normalized and prepared before classification. Evaluation was based on standard metrics such as accuracy, precision, recall, and F1-score. The results show that the PSO-optimized SVM consistently outperformed the baseline SVM model, producing more accurate and stable classifications. This confirms the potential of metaheuristic optimization in strengthening machine learning approaches for environmental data analysis. The main contribution of this study lies in applying a PSO–SVM framework to water quality classification, a domain where such integration has been rarely explored despite its importance for sustainable resource management. The findings provide both theoretical implications for advancing metaheuristic applications in environmental informatics and practical benefits for improving decision support in water quality monitoring and management.
A LIME-Enhanced SVM Framework for Driver Drowsiness Detection in Nighttime Driving Scenarios Rahayu, Silvia Indah; Hakim, Lukman
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13868

Abstract

Nighttime traffic accidents caused by driver fatigue remain a critical issue as most visual-based detection systems find it challenging to interpret facial cues under poor lighting conditions. Key obstacles include decreased accuracy in dark settings, difficulties in detecting eye and mouth features, and the impractical nature of real-time approaches that rely on physiological sensors. This study introduces a vision-based drowsiness detection framework that integrates the Adaptive Low-light Image Enhancement (LIME) method with a Support Vector Machine (SVM) classifier employing an RBF kernel. The dataset comprises 11.566 images of eyes and mouths, which are analyzed to extract features like Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), and blink frequency. Evaluation results show that the SVM model with the RBF kernel attained 90.94% accuracy, 91.22% precision, and 91.82% recall. This system is effective in detecting drowsiness under low-light conditions and has the potential to be implemented as an early warning feature in vehicles.   Keywords: Drowsiness Detection, SVM, EAR, MAR, Adaptive LIME