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All Journal International conference on Information Technology and Business (ICITB) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Rahmalia Syahputri
Department of Electrical & Computer Engineering, Curtin University, Australia. Faculty of Computer Science, IBI Darmajaya, Indonesia
Computer Science & IT Economics, Econometrics & Finance Engineering

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M-LEARNING APPLICATION FOR COMPUTER NETWORKING SUBJECTS Syahputri, Rahmalia; Nurfiana, Nurfiana; Fernando, Ilham
Prosiding International conference on Information Technology and Business (ICITB) 2016: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 2
Publisher : Prosiding International conference on Information Technology and Business (ICITB)

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Abstract

Nowadays, mobile application, called mobile learning, is widely used among academic staff to help them in the process of teaching and learning at university. This research proposed the use of mobile learning in computer network subjects, particularly computer network and security, to facilitate the ease of access to the source of material and evaluation. Based on the questionnaire that distributed to the students, 75% respondents found this application is easy to use, attractive, and helping them to understand the content of subjects.  KEY WORDS: Mobile learning, teaching media, networking subjects
S-GIS: DIGITAZING SKIN DISEASE SPREAD IN LAMPUNG PROVINCE INDONESIA Syahputri, Rahmalia; Hasibuan, Muhammad Said
Prosiding International conference on Information Technology and Business (ICITB) 2015: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 1
Publisher : Prosiding International conference on Information Technology and Business (ICITB)

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Abstract

Skin disease is a common disease whether in urban orrural area. Various types are listed in this category. Someof them are easily transmitted and turn into epidemic. Tohelp the health department or other parties to map thespread of the diseases as well as to broadcast theinformation easily to the citizen, thus it is important todevelop a system that able to provide data based ongograpfical. Furthermore, the data should be easily to beaccesed.To enable related parties to be able to collect,store, and analyze the spread of skin disease particularlyin Lampung Province Indonesia, a geographicalinformation system has been developed. In addition, thissystem acts as a monitoring tool for Government orAgencies that responsible for the health issues inLampung and Indonesia.KEY WORDS: geographic information system, skindiseases spread, Lampung Province.
IMPORTATION OF PUMPING EQUIPMENT IN PIPING CO., LTD ABC - ANALYSIS OF PATTERNS AND SOME RECOMMENDATION SOLUTIONS Hoang, Vo Le; Syahputri, Rahmalia
Prosiding International conference on Information Technology and Business (ICITB) 2018: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 4
Publisher : Prosiding International conference on Information Technology and Business (ICITB)

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Abstract

Import-export activities have meaningfully and significantly influenced and tributed to every economy. However, the effect and the influent scale of these activities, especially importation, still have not been popularly declared. The objectives of this study are analysing and evaluating the importation of pumps based on the study of common issues in import activities of the company ABC located in Ho Chi Minh city that run a piping business. Besides, this paper overview, through the data obtained, to see the fluctuation of the index in the import activities of the company. Accordingly, strengths, weaknesses, opportunities, and threats of the company ABC are pointed out by the SWOT matrix analysis method. From this, several solutions and recommendations are proposed for optimizing advantages and benefits of import activities of the company ABC in particular and the whole economy of Vietnam in general.Keywords: importation; piping company; solutions and recommendations; SWOT matrix.
Android-based Detection of Melon Leaf Diseases Using Convolutional Neural Network and TensorFlow Syahputri, Rahmalia; Winarto; Trisnawati, Sherli; Taufik
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.14542

Abstract

Melon productivity in Indonesia has experienced a significant decline due to leaf diseases, while manual detection performed by farmers remains subjective, time-consuming, and highly dependent on individual experience. To address this issue, this study aims to develop a mobile-based melon leaf disease detection system utilizing a Convolutional Neural Network (CNN) architecture integrated into the Tani Cerdas Android application via the TensorFlow framework. The dataset consists of 250 images of melon leaves categorized into five classes: healthy, aphids, fusarium wilt, leaf caterpillars, and unknown. Data were collected from two different melon farms employing distinct cultivation methods and processed through the machine learning life cycle, including data cleaning, manual labeling using one-hot encoding, splitting into 80% training and 20% validation sets, model training, and performance evaluation. The CNN model was trained for 11 epochs using ReLU and Softmax activation functions and a dropout rate of 0.2 to reduce the risk of overfitting. Training results achieved an accuracy of 91.5% with a loss value of 0.313, while model validation reached 71.9% accuracy. The ROC-AUC evaluation indicated excellent classification performance in most classes (AUC 0.99–1.00), although performance in the fusarium wilt class remained lower (AUC 0.87). Deployment of the model into the Tani Cerdas application achieved an average field accuracy of 86.33%. This study demonstrates the effectiveness of CNN and TensorFlow integration in supporting rapid and independent detection of melon leaf diseases via mobile devices, offering potential for the development of similar systems for other horticultural commodities.
Co-Authors Fernando, Ilham Hoang, Vo Le M Said Hasibuan Mochammad Imron Awalludin Taufik Trisnawati, Sherli WINARTO