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All Journal Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Keteknikan dan Sains (JUTEKS) CARADDE: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal Peqguruang: Conference Series Jurnal Sisfotek Global JURNAL SIPISSANGNGI: Jurnal Pengabdian Kepada Masyarakat
Akhmad Qashlim
universitas al asyariah mandar
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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Image Processing Technology in Book Metadata Extraction System Using Optical Character Recognition (OCR) Andi Emil Multazam; Akhmad Qashlim; Muhammad Sarjan
JURNAL SISFOTEK GLOBAL Vol 13, No 1 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i1.865

Abstract

Extracting book metadata by retyping the identity of the book, such as the author's name, book title, publisher, and several other identities, is a routine that is carried out repeatedly at the Polewali Mandar district library, this activity takes much of time, using several staff and it turns out that this activity has much potential for input errors. Errors in extracting book metadata will result in errors in the book repository system database, resulting in difficulty finding and using books or book data information. This problem can be solved by creating a book metadata extraction system using image processing technology and OCR. This study aims to design a scanner technology to extract book metadata. Accuracy is carried out in 2 stages, the first validation of image extraction results using the ROC method and the second validation by directly matching the result of extracting the book's metadata with the actual book. The results of this study indicate that the system has worked with an accuracy of 98.78% with an average detection time of 1.49 seconds and has succeeded in presenting the extraction results on the website page. Thus the metadata extraction system with the OCR method can be applied to libraries to input book data.
SISTEM MONITORING KECEPATAN DAN ARAH ANGIN BERBASIS INTERNET OF THINGS (IOT) SEBAGAI PERINGATAN DINI BENCANA ALAM Ariastuti Rahman; Akhmad Qashlim; Rosmawati Tamin; Muhammad Farid Syam
JURNAL ILMU KOMPUTER Vol 10 No 1 (2024): Edisi April
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v10i1.310

Abstract

A tornado is a form of extreme weather caused by differences in air pressure and temperature in the atmosphere. This phenomenon can cause loss of life and psychological disorders. To overcome this serious impact, a system that is able to monitor the condition of the surrounding environment in real-time and provide early warning is needed. This research aims to design an Internet of Things (IoT) system for real-time monitoring of wind speed and direction as well as environmental conditions that is effective for providing early warning of natural disasters. Testing and calibration methods were carried out by comparing IoT devices with standard tools. Additional tests were conducted on the anemometer to evaluate the consistency of wind speed at certain heights and at locations adjacent to the coast and some distance from the coast. The results of this IoT device design demonstrate its ability to detect temperature, humidity, air pressure, wind speed, and wind direction, and send real-time data to the monitoring system. This research confirms that the web-based monitoring system is effective in monitoring environmental conditions and sending early warnings when the system detects tornado characteristics.
CLUSTERING NILAI ENGLISH SUNSET MAHASISWA MANGGUNAKAN METODE K-MEANS PADA LEMBAGA BAHASA DAN PENGEMBANGAN KARAKTER (LBPK) UNASMAN Salmawati salmawati; Rendi Rendi; Akhmad Qashlim
JURNAL ILMU KOMPUTER Vol 10 No 1 (2024): Edisi April
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v10i1.312

Abstract

The UNASMAN Language and Character Development Institute (LBPK) is used by all UNASMAN students to improve their English skills so they can continue their studies abroad and as alumni can later compete in the world of work with other alumni both nationally and internationally. This research aims to group student scores in the English Sunset program at the Unasman Language and Character Development Institute (LBPK) using the K-Means method. The K-Means method was chosen because of its effective ability to group data based on similarity of attributes, making it possible to identify groups of students with similar value characteristics. Student score data is collected, processed and analyzed using the K-Means algorithm to determine the optimal number of clusters. The research results show that students can be grouped into three main clusters: students with high scores, medium scores, and low scores. This information provides valuable insight for LBPK in designing more targeted teaching strategies and providing additional support for student groups in need. Feasibility analysis from a technological and operational perspective shows that this system can be implemented with adequate infrastructure and sufficient training support for staff and lecturers. This research confirms that the K-Means method can be used effectively to improve the qualitys of learning at LBPK Unasman.
Co-Authors Abdul Asis Aco Dahrul Alwi Qadri Andi Emil Multazam Andriani Andriani Andriani Andriani Ariastuti Rahman Basri Basri Jumain Jumain Mamat Mamat Mawardi Marwan Muhajir Muhajir Muhammad Assidiq Muhammad Farid Syam Muhammad Sarjan Muslimin Muslimin Padli Padli Piansar Piansar Rendi Rendi Rosmawati Tamin Rosmawati Tamin Salmawati Salmawati St. Khadija Syarli Ul Khairat