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All Journal JUSIM (Jurnal Sistem Informasi Musirawas) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) BEES: Bulletin of Electrical and Electronics Engineering
Hidayat, Asep Toyib
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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MEMBERSHIPPLICATION BERBASIS ANDROID DENGAN PENERAPAN KOTLIN PROGRAMMING LANGUAGE DI WIJAYA FITNESS CENTER (WFC) Hidayat, Asep Toyib; Rio, Rio; Santosa, I Gede Olka
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 8 No 1 (2023): JUSIM (Jurnal Sistem Informasi Musirawas) JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v8i1.1952

Abstract

Perkembangan teknologi informasi dan e-commerce saat ini menjadi fokus penting dalam dunia bisnis. Dengan memanfaatkan teknologi tersebut, pelaku bisnis dapat meningkatkan omset dan memberikan layanan informasi kepada konsumen. Dalam penelitian ini akan dibuat sebuah sistem berbasis android untuk Wijaya Fitness Center (WFC) yang berlokasi di Megang, Lubuk Linggau Utara II, Kota Lubuklinggau, Sumatera Selatan. WFC menyediakan tiga paket olahraga dan memiliki pengunjung lebih dari 50 orang setiap harinya. Namun saat ini, sistem manajemen data masih bersifat manual dan mengalami kendala dalam hal keamanan dan akses informasi. Dengan adanya sistem berbasis android, diharapkan dapat mempermudah proses pendaftaran anggota, pelaporan harian, dan memastikan keamanan data.
Rancang Bangun Sistem Monitoring Ruang Hidroponik Berbasis Mikrokontroler Nodemcu Dengan Penjadwalan Pemberian Nutrisi Otomatis Anggoro, Dimas Bayu; Armanto, Armanto; Hidayat, Asep Toyib; Karman, Joni
BEES: Bulletin of Electrical and Electronics Engineering Vol 5 No 1 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v5i1.5518

Abstract

Indonesia has vast agricultural and plantation lands, yet the efficiency and productivity of this sector still need improvement. One solution is the application of Internet of Things (IoT) technology in hydroponic systems, allowing for automatic and real-time control and monitoring of plant conditions. This research aims to develop a hydroponic room monitoring system based on the NodeMCU microcontroller with automated nutrient scheduling. The methods used in this study include the design and implementation of an IoT system using NodeMCU, humidity sensors, temperature sensors, and nutrient pumps, as well as the development of a smartphone application for monitoring and control. The research results show that the developed system can accurately monitor hydroponic environmental conditions and automatically provide nutrients according to the scheduled time. The use of this technology is expected to facilitate farmers in monitoring and maintaining hydroponic plants, improving water and nutrient use efficiency, and optimizing crop yields. In conclusion, the application of IoT in hydroponic systems positively impacts agricultural productivity, especially in areas with limited land, and offers a practical solution for urban communities interested in modern agriculture.
Klasfikasi Tingkat Kematangan Roasting Biji Kopi Berbasis Deep Learning dengan Arsitektur MobileNet Firmansyah, Tegar; Kurniawan, Rudi; Hidayat, Asep Toyib
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6811

Abstract

Coffee is one of the most widely consumed beverage ingredients in Indonesia and has high economic value to improve the community's economy and as a source of foreign exchange. The roasting process is an important stage in coffee processing because it affects the aroma and flavor of coffee. What is often encountered is that visually determining the level of coffee roasting is often inaccurate and prone to human error. To overcome this problem, this study uses a deep learning approach with a transfer learning method based on MobileNet architecture to classify the level of coffee roasting maturity based on digital images. MobileNet was chosen due to its lightweight and fast architecture, suitable for implementation on mobile devices. This research aims to compare the performance of the model in detecting coffee roasting level automatically, efficiently, and objectively. With this approach, it is expected that coffee enthusiasts and producers can easily recognize the type of coffee roasting, support product quality consistency, and reduce dependence on experts in the roasting process. This study analyzed the performance of the classification model with the results showing excellent performance. The model achieved a total accuracy of 99.50%, with consistently high precision, recall, and f1-score values across all classes, including several classes with perfect scores (1,000). Evaluation using ROC curves and AUC also demonstrated the model's ability to distinguish between the two classes.
Co-Authors Anggoro, Dimas Bayu Armanto, Armanto Firmansyah, Tegar Karman, Joni Rio, Rio Rudi Kurniawan Santosa, I Gede Olka