Garuda - Garba Rujukan Digital

PEMANFAATAN WORDPRESS SEBAGAI MEDIA INFORMASI DI DESA PEMUDA KNPI Utomo, Hendrik Setyo; Supriyanto, Arif; Rahmanto, Oky; Yuliyanti, Wan
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 7 No. 2 (2022): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v7i2.133

Salah satu bagian terpenting dalam penyediaan informasi dan pelayanan terkait suatu organisasi atau lembaga adalah dengan memanfaatkan teknologi informasi. Website merupakan media yang paling sering digunakan dalam penerapan teknologi informasi. Memanfaatkan website suatu organisasi dapat menyebarkan informasi sehingga informasi tersebut dapat dilihat oleh user lain yang ingin melihatnya. Hal ini disadari juga oleh pemerintah desa pemuda Komite Nasional Pemuda Indonesia (KNPI). Melalui pemerintah desa KNPI mengusulkan ke Politeknik Negeri Tanah Laut untuk dilakukan pendampingan tentang pemanfaatan dan pengelolaan website perangkat desa dan para pemuda di Desa KNPI. Tujuan kegiatan pengabdian yaitu memberikan pendampingan dan pelatihan kepada perangkat desa. Pemanfaatan wordpress sebagai media informasi dipilih karena platform wordpress gratis dan open source, selain itu juga menawarkan beberapa kemudahan dalam pengelolaan informasi suatu organisasi. Hasil kuisioner yang telah di sebar yaitu 65% (Puas) untuk aspek keandalan, 72% (Puas) untuk aspek daya tanggap, aspek kepastian sebanyak 100% (Puas) dan aspek empati sebanyak 100% (Puas).

WORKSHOP PEMBUATAN MATERI PEMBELAJARAN DENGAN CANVA UNTUK PENGAJAR SMP WALADUN SHOLEH Rahmanto, Oky; Utomo, Hendrik Setyo; Yuliyanti , Wan; Supriyanto, Arif; Anggraeni, Dewi Indra
Jurnal Pengabdian Kepada Masyarakat (MEDITEG) Vol. 9 No. 1 (2024): Jurnal Pengabdian Kepada Masyarakat (MEDITEG)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat (P3M) Politeknik Negeri Tanah Laut (Politala)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/mediteg.v9i1.271

Teknologi pembelajaran telah mengubah cara penyajian materi pembelajaran dengan menyediakan berbagai alat dan media digital yang inovatif. Artikel ini membahas pelaksanaan workshop pembuatan materi pembelajaran dengan menggunakan aplikasi Canva, yang diadakan sebagai bagian dari kegiatan Pengabdian kepada Masyarakat (PKM) di SMPS Waladun Sholeh. Workshop ini bertujuan untuk meningkatkan kemampuan guru dalam menggunakan teknologi untuk menyajikan materi pembelajaran yang lebih menarik dan efektif. Metode yang digunakan mencakup ceramah, diskusi, dan demonstrasi. Hasil kegiatan menunjukkan bahwa mayoritas peserta memberikan penilaian positif terhadap kesesuaian pengabdian dengan kebutuhan mereka, komunikasi dengan mitra, serta manfaat yang diperoleh. Namun, terdapat beberapa area yang masih memerlukan perhatian, seperti komunikasi dan penyesuaian waktu. Penelitian ini menegaskan pentingnya teknologi dalam pendidikan dan peran sentral guru dalam memanfaatkan alat digital untuk meningkatkan kualitas pembelajaran.

Machine learning to Detect Palm Oil Diseases Based on Leaf Extraction Features and Principal Component Analysis (PCA) Arrahimi, Ahmad Rusadi; Julianto, Veri; Rahmanto, Oky
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 11, No 1 (2024)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v11i1.659

Palm oil tree is one of the economically important crops that is the backbone of the Indonesian economy. However, palm oil production is often hampered by various diseases. The disease is difficult to detect in the early stages because infected trees often show no symptoms. Therefore, it is necessary to carry out identification and classification to determine whether this palm coconut plant is sick or infected with disease. In this study the disease was identified in palm coconut by identifying it through leaves by modifying the extraction process features using PCA and comparing it with no PCA for sick and healthy types. Subsequently, the classification will be done using SVM (Support Vector Machine) with various treatments such as variation of the features used and the amount of data to be processed in carrying out experiments or tests. The results obtained show that if the feature used for classifying a number of 4 or more then the accuracy value remains at 97%.

Implementation of Web Based Leave Information System at PT Arutmin Indonesia Tambang Kintap Maulana, Dhiya Ulhaq; Supriyanto, Arif; Utomo, Hendrik Setyo; Rahmanto, Oky
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3754

Leave is one of the rights that must be given to employees by a company. The leave application process at PT Arutmin Indonesia Tambang Kintap is still done manually, starting from the leave application to the results of the leave decision. The process of checking employee leave balances, leave applications, approvals and leave reports still relies on previous leave files. This kind of management process is often complained about because it is felt to be less effective and efficient when searching, changing, deleting data and data redundancy often occurs. Therefore, the aim of this research is to build and implement an employee leave information system which is expected to be able to help the process of managing leave in the Company. This information system was designed using ERD, DFD using the waterfall system development model. This system was built based on a website using the My database. SQL Based on the results of system functionality testing, this leave information system can function well without any problems.

Evaluating Random Forest Algorithm: Detection of Palm Oil Leaf Disease Rahmanto, Oky; Julianto, Veri; Arrahimi, Ahmad Rusadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4798

This research investigates the application of machine learning techniques for detecting diseases in oil palm leaves, utilizing a dataset of 1,119 images sourced from plantations in the Tanah Laut district. The dataset comprises 488 diseased and 631 healthy leaf samples, which were carefully cropped to isolate leaf areas and labeled with the assistance of domain experts. For feature extraction, both Lab and RGB color spaces were considered, alongside Haralick texture features, resulting in a total of eleven features per pixel. To reduce dimensionality and select relevant features, Principal Component Analysis (PCA) and Random Forest methods were applied. Support Vector Machine (SVM) was subsequently employed for the classification of leaf health status, and model performance was evaluated using accuracy, precision, recall, and F1 score metrics, all derived from a confusion matrix. The study finds that PCA and Random Forest significantly enhance model performance, improving the ability to distinguish between healthy and diseased leaves. These findings provide valuable insights for the development of automated disease detection systems in oil palm plantations, with potential applications in precision agriculture. Additionally, the results suggest pathways for further research into plant disease diagnostics, highlighting the role of advanced machine learning techniques in enhancing crop management and supporting sustainable agricultural practices.

Evaluating Random Forest Algorithm: Detection of Palm Oil Leaf Disease Rahmanto, Oky; Julianto, Veri; Arrahimi, Ahmad Rusadi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4798

This research investigates the application of machine learning techniques for detecting diseases in oil palm leaves, utilizing a dataset of 1,119 images sourced from plantations in the Tanah Laut district. The dataset comprises 488 diseased and 631 healthy leaf samples, which were carefully cropped to isolate leaf areas and labeled with the assistance of domain experts. For feature extraction, both Lab and RGB color spaces were considered, alongside Haralick texture features, resulting in a total of eleven features per pixel. To reduce dimensionality and select relevant features, Principal Component Analysis (PCA) and Random Forest methods were applied. Support Vector Machine (SVM) was subsequently employed for the classification of leaf health status, and model performance was evaluated using accuracy, precision, recall, and F1 score metrics, all derived from a confusion matrix. The study finds that PCA and Random Forest significantly enhance model performance, improving the ability to distinguish between healthy and diseased leaves. These findings provide valuable insights for the development of automated disease detection systems in oil palm plantations, with potential applications in precision agriculture. Additionally, the results suggest pathways for further research into plant disease diagnostics, highlighting the role of advanced machine learning techniques in enhancing crop management and supporting sustainable agricultural practices.

Design and Implementation Plagiarism Checker Application with DetectGPT using Scheduler Algorithm Supriyanto, Arif; Utomo, Hendrik Setyo; Rahmanto, Oky
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3275

The increasing use of Generative AI in the field of writing in the academic world creates problems in the field of plagiarism. this problem has prompted an urgent need for plagiarism detection tools. However, not all universities are able to implement a system that is able to detect sentences or paragraphs resulting from generative AI. Recent research seeks to overcome this obstacle using AI itself, specifically through the DetectGPT model. However, the implementation of this technology has limitations, such as requiring large computing resources and quite a long examination time. Using a GPU can speed up the process, but not all users can implement it. Solutions to minimize processing time include using more than one worker, however, scheduling is essential to maximize plagiarism detection efficiency. This research proposes the implementation of the above system with the help of the scheduler. The results obtained in this system prototype are an average waiting time for checking of 457,778 seconds to complete 10 tasks with the help of 3 workers running at the same time.

Implementation of Web Based Leave Information System at PT Arutmin Indonesia Tambang Kintap Maulana, Dhiya Ulhaq; Supriyanto, Arif; Utomo, Hendrik Setyo; Rahmanto, Oky
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.3754

Leave is one of the rights that must be given to employees by a company. The leave application process at PT Arutmin Indonesia Tambang Kintap is still done manually, starting from the leave application to the results of the leave decision. The process of checking employee leave balances, leave applications, approvals and leave reports still relies on previous leave files. This kind of management process is often complained about because it is felt to be less effective and efficient when searching, changing, deleting data and data redundancy often occurs. Therefore, the aim of this research is to build and implement an employee leave information system which is expected to be able to help the process of managing leave in the Company. This information system was designed using ERD, DFD using the waterfall system development model. This system was built based on a website using the My database. SQL Based on the results of system functionality testing, this leave information system can function well without any problems.

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