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Anggi Zafia
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Journal of Informatics, Information System, Software Engineering and Applications (INISTA)
Published by Universitas Telkom
ISSN : -     EISSN : 26228106     DOI : https://doi.org/10.20895/inista
Core Subject : Science,
Computer Science & IT
Journal of Informatics, Information System, Software Engineering and Applications (INISTA) is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto with ISSN 2622-8106 , Indonesia. Journal of INISTA covers the field of Informatics, Information System, Software Engineering and Applications. First published will be in September 2018 for an electronic version. The aims of Journal of INISTA are to disseminate research results and to improve the productivity of scientific publications. Journal of INISTA is published twice in Mei and November. Publication will be published "Volume 2 number 2" in May 2020.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 3 Documents
 1 
Search results for , issue "Vol 8 No 1 (2025): November 2025" : 3 Documents clear
Implementation of Forward Chaining And Certainty Factor Methods for Android-Based Red Onion Diagnosis Ghozali, Imam; Athiyah, Ummi; Nur, Yohani Setiya Rafika
Journal of INISTA Vol 8 No 1 (2025): November 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v7i2.1779

Abstract

Shallots are one of the crucial horticultural commodities in Indonesia, used in various social layers. Brebes is one of the main shallot producing regions with a significant increase in production. However, farmers often experience reduced yields due to disease attacks and lack of guidance from experts. This researcher aims to develop an Android-based expert system that applies the Certainty Factor and Forward Chaining methods to identify diseases in shallot plants. This system uses rules to identify onion disease symptoms and calculates the confidence level for each possible diagnosis. The Forward Chaining method helps identify symptoms sequentially, while the Certainty Factor calculates confidence in the possibility of disease. The research results show that this method is effective in providing an accurate diagnosis of onion diseases from the 5 diseases tested by the recommended system with a percentage value of 100%. In conclusion, the expert system created for diagnosing shallot plants using the Android-based forward chaining and certainty factor method was successfully built. Then, for Functionality Testing based on black box testing carried out by experts, the results were obtained with 100% accuracy, which means the system is in accordance with its functional requirements.
Website Based Ticket Ordering Application Design Using Laravel Framework (Bedegung Waterfall Tour, Muara Enim Regency) Gunawan, Wawan; Liana, Lia Nur
Journal of INISTA Vol 8 No 1 (2025): November 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v8i1.1946

Abstract

Bedegung Waterfall is a well-known natural tourism destination located in Bedegung Village, Muara Enim Regency, offering beautiful scenery and a prominent waterfall. Despite its popularity, the ticket booking process is still conducted manually, resulting in long queues, slow transactions, service delays, and traffic congestion around the tourist area, which reduces visitor comfort and management efficiency. To address these issues, this study proposes developing a web-based ticket-booking application to streamline transactions and enhance tourism service quality. The system was designed and developed using the Extreme Programming (XP) software development method to ensure flexibility, rapid development, and effective collaboration. The application was implemented using the Laravel framework, PHP as the programming language, and MySQL as the database management system, due to its reliability in handling large volumes of data. System design was supported by Flowcharts, Use Case Diagrams, Class Diagrams, Activity Diagrams, and Entity-Relationship Diagrams (ERDs) to clearly describe system workflows and data relationships. The objective of this research is to design, implement, and evaluate a web-based ticket booking system that improves transaction efficiency, reduces queues, and enhances visitor convenience. The system supports three user roles: Super Admin, Tourist Staff, and Member, each with distinct access rights and functionalities. System testing was conducted using the Black-Box Testing method to evaluate functional suitability against user requirements. A total of 37 testing scenarios were executed across all user roles, and the results showed that all system functions operated as expected, achieving a 100% testing success rate, indicating that the developed application is effective and feasible for implementation at Bedegung Waterfall.
Multi-Layer Perceptron with Advanced Acoustic Features for Speech Emotion Recognition in Education Evaluation Tamamul Wafa, Muhammad Afiq
Journal of INISTA Vol 8 No 1 (2025): November 2025
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v8i1.2096

Abstract

Traditional methods for evaluating lecturer performance in education, such as student surveys, are often limited by their nature. This study explores the development of an objective, a framework to complement these evaluations through Speech Emotion Recognition (SER). This Research utilizes a specialized Indonesian speech emotion dataset, applying data augmentation techniques to enhance model generalization. A set of advanced acoustic features, including Mel Frequency Cepstral Coefficients (MFCCs), Chroma, and Spectral Contrast, along with their statistical variations, is used to create representations of the vocal expressions. A Multi Layer Perceptron (MLP) neural network was designed and trained on these features to classify five different emotions: happy, angry, sad, surprised, and neutral. The Research resulted in a model that demonstrated very good performance, achieving an overall classification accuracy of 94% with high precision, recall, and F1-scores across all emotions, indicating a balanced and reliable system. A critical feature analysis was also conducted, revealing the significance of the standard deviation of Chroma and MFCC features. This study shows that an MLP model paired with feature engineering can be used as a powerful and objective tool for providing deeper insights into student feedback, contributing a valuable new methodology for quality assurance in higher education.

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