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All Journal JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Journal of Informatics and Information Security ALMUSTOFA: Journal of Islamic Studies and Research Service
Intan Safira
Unknown Affiliation
Religion Humanities Computer Science & IT Environmental Science Languange, Linguistic, Communication & Media Social Sciences Other

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Penerapan Algoritma K-Means untuk Mengetahui Pola Persediaan Barang pada Toko Raja Bekasi Intan Safira; Ratna Salkiawati; Priatna, Wowon Priatna
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ykryzk32

Abstract

This study aims to determine how much the results of grouping goods affect the needs of consumers. Excess inventory will greatly fill the warehouse and be inefficient because of the expiration date on food products, beverages, etc. Currently Toko Raja still manages goods manually so it is not time efficient. To solve this problem, a technique is needed, namely data mining. The data mining technique that will be used in this research is the K-Means Clustering method. K-Means is one of the most popular algorithms because it is easy and simple to implement. However, the results of the clustering of K-Means are very dependent on theselection of the initial cluster center point. Calculation of accuracy in this study using the test results of the K-Means clustering method using the Davies-Bouldin Index (DBI) is 1.856 where the DBI value close to zero cluster is good enough. From the resulting accuracy, it can be concluded that the K-Means Clustering method can support the system well.
INTERKONEKSI AGAMA DAN SAINS: MEMAHAMI MAKNA BUAH DELIMA DALAM AL-QUR'AN, HADIS, DAN PENELITIAN KESEHATAN KONTEMPORER Vita Susmita; Intan Safira; Riski Maulana; Laila Sari Masyhur
Almustofa Journal of Islamic Studies and Research Vol 2 No 01 (2025): almustofa
Publisher : BAMALA Institute

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

Abstract

Buah delima (Punica granatum) memiliki kedudukan penting dalam tradisi Islam dan mendapatkan perhatian signifikan dalam kajian ilmiah modern. Meskipun demikian, kajian interdisipliner yang mengintegrasikan perspektif teologis dari Al-Qur’an dan hadis dengan temuan ilmiah di bidang kesehatan masih relatif terbatas. Penelitian ini menggunakan metode tinjauan pustaka tematik untuk mengkaji posisi dan manfaat delima berdasarkan sumber-sumber primer keislaman dan literatur ilmiah kontemporer. Dalam Al-Qur’an, delima disebutkan pada Surah Al-An‘am (6):99 dan Ar-Rahman (55):68 sebagai salah satu tanda kebesaran Allah, sementara hadis menganjurkan konsumsi delima dengan alasan nilai spiritual dan potensi terapeutiknya. Penelitian ilmiah menunjukkan bahwa delima mengandung berbagai senyawa bioaktif yang memiliki sifat antioksidan dan antiinflamasi, serta berperan dalam menurunkan risiko penyakit degeneratif seperti penyakit kardiovaskular dan kanker. Hasil kajian ini menegaskan bahwa buah delima tidak hanya memiliki nilai religius dan simbolik yang tinggi, tetapi juga manfaat empiris yang signifikan dalam konteks kesehatan. Oleh karena itu, delima relevan untuk dimasukkan dalam praktik kesehatan holistik yang berlandaskan nilai-nilai Islam. Penelitian lanjutan sangat diperlukan untuk mengeksplorasi potensi aplikatif buah delima secara klinis dan farmakologis dalam pengobatan modern.
Perancangan Alat Deteksi Alergi Berbasis Sensor Dengan Kecerdasan Buatan Giulia Salzano Badia; Intan Safira; Liala Syarifah Wahdani; Discha Zahra Amanina; Aris Febriyanto; Aripin
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 6 No. 11 (2025)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol6iss11pp4303-4312

Abstract

This research aims to develop a non-invasive allergy detection tool using artificial intelligence technology, specifically the Convolutional Neural Network (CNN) method. This tool is designed to detect allergic reactions caused by food through sensors applied to human skin. The research methodology includes literature study, data collection, design creation, system design, tool creation, and testing stages. This tool uses a camera to detect allergic reactions on the skin, which are then analyzed using an image processing algorithm with the CNN method integrated in a minicomputer. Data processing on skin reaction samples to allergic substances is divided into four classes, including atopic, angioedema, normal skin, and urticaria. The CNN algorithm used consists of several layers, including convolutional layers, pooling, and fully connected layers. The data collection process is carried out with 2 data, namely primary data and secondary data. Primary data collection is done by taking images of normal and allergic patient skin. Secondary data is obtained from Kaggle. The results of the study show that this tool prototype is able to detect changes in the skin surface due to allergic reactions, such as redness or swelling, quickly and accurately. Testing of this device yielded an accuracy rate of 92%, indicating its high accuracy in detecting allergic reactions
Co-Authors Aripin Aris Febriyanto Discha Zahra Amanina Giulia Salzano Badia Laila Sari Masyhur Liala Syarifah Wahdani Priatna, Wowon Priatna Ratna Salkiawati Riski Maulana Vita Susmita