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Penerapan Metode Weighted Product dalam Sistem Pendukung Keputusan Program Penerimaan Bantuan Beras Iqbal Ramadhani Mukhlis; Thomas Aquino Berno Doduk; Tri Puspa Rinjeni; Virdha Rahma Aulia; Rafika Rahmawati; Tri Luhur Indayanti Sugata; Prasasti Karunia Farista Ananto; Nambi Sembilu
Jurnal Ilmu Komputer dan Desain Komunikasi Visual Vol 9 No 2 (2024): Jurnal Ilmu Komputer dan Desain Komunikasi Visual
Publisher : Fakultas Ilmu Komputer Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/jikdiskomvis.v9i2.1120

This study aims to develop an effective Decision Support System (DSS) in the process of the rice aid program. The Weighted Product (WP) method is used as the basis for decision-making to determine the receipt of rice aid. This DSS is designed to assist program organizers in selecting rice aid recipients more efficiently and objectively. The Weighted Product method is used to calculate the weight value of each criterion given by the rice aid recipient. This study's results can positively contribute to increasing efficiency and transparency in decision-making for the rice aid program. With this Weighted Product-based DSS, it is hoped that the selection process for rice aid recipients can be carried out more objectively and measurably so that the program's benefits can be more evenly distributed and targeted.

IMPLEMENTATION OF FIREBASE IN THE DEVELOPMENT OF ANDROID-BASED QUEUE RESERVATION AND TREATMENT RECORD APPLICATIONS Audy Fitri Ariani; Agung Brastama Putra; Tri Luhur Indayanti Sugata
Jurnal Sistem Informasi Vol. 12 No. 1 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i1.9880

The development of an Android-based reservation and medical record management app is key to improving customer experience and operational efficiency in the beauty salon industry. This study explores the use of Firebase, offering features like Authentication, Firestore, Cloud Messaging, and Cloud Functions, to create a reliable mobile solution. Firebase enables real-time data management, secure authentication, and efficient notifications, enhancing both salon operations and customer experience. Developed with the Waterfall model and MVVM architecture, the app showed positive results in reservation and medical record management. Users can easily book appointments and access treatment history, with fast data transfer powered by Firebase. With response times of 120 ms for reads and 140 ms for writes, Firebase ensures seamless performance. The app reduced booking time by 79.91% compared to manual methods. Further development is recommended to include staff management and real-time analytics for optimized service and better customer insights.

Penerapan Metode Weighted Product dalam Sistem Pendukung Keputusan Program Penerimaan Bantuan Beras Iqbal Ramadhani Mukhlis; Thomas Aquino Berno Doduk; Tri Puspa Rinjeni; Virdha Rahma Aulia; Rafika Rahmawati; Tri Luhur Indayanti Sugata; Prasasti Karunia Farista Ananto; Nambi Sembilu
Jurnal Ilmu Komputer dan Desain Komunikasi Visual Vol 9 No 2 (2024): Jurnal Ilmu Komputer dan Desain Komunikasi Visual
Publisher : Fakultas Ilmu Komputer Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55732/jikdiskomvis.v9i2.1120

This study aims to develop an effective Decision Support System (DSS) in the process of the rice aid program. The Weighted Product (WP) method is used as the basis for decision-making to determine the receipt of rice aid. This DSS is designed to assist program organizers in selecting rice aid recipients more efficiently and objectively. The Weighted Product method is used to calculate the weight value of each criterion given by the rice aid recipient. This study's results can positively contribute to increasing efficiency and transparency in decision-making for the rice aid program. With this Weighted Product-based DSS, it is hoped that the selection process for rice aid recipients can be carried out more objectively and measurably so that the program's benefits can be more evenly distributed and targeted.

Implementasi Arsitektur CNN DenseNet-121 untuk Identifikasi Autoimun Kulit dengan Augmentasi Data Annisa Lusyani Zahra; Amalia Anjani Arifiyanti; Tri Luhur Indayanti Sugata
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 5 No. 2 (2025): Juli: Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v5i2.1026

Autoimmune skin diseases are conditions in which the immune system mistakenly attacks healthy skin tissue, causing inflammation, tissue damage, and changes in skin color. The similarity of symptoms among various autoimmune skin diseases, such as psoriasis, lichen planus, vitiligo, hidradenitis suppurativa, and dermatomyositis, presents a challenge for accurate and timely diagnosis. This study was conducted to support the diagnostic process by utilizing deep learning technology, specifically the Convolutional Neural Network (CNN) method with the DenseNet121 architecture. Data augmentation techniques were also applied in this study to increase dataset variation, allowing for a performance comparison between the original dataset and the augmented dataset. The results show that the CNN model with the DenseNet121 architecture, configured with a batch size of 32 and 60 epochs on the augmented dataset, achieved a high accuracy rate of 92.43%. The model was then implemented into a web-based application and integrated using the Flask framework.

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