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All Journal SINTECH (Science and Information Technology) Journal Innovation in Research of Informatics (INNOVATICS) Jurnal Informatika: Jurnal Pengembangan IT
Roshinta, Trisna Ari
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Software Testing in the Indonesian Industry: Survey of Methods, Tools, and Documentation Maspupah, Asri; Rahmani, Ani; Min, Joe Lian; Roshinta, Trisna Ari
Innovation in Research of Informatics (Innovatics) Vol 6, No 2 (2024): September 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i2.12636

Abstract

Software testing plays a crucial role in the software development by ensuring that software is accurate and of high quality. Many software companies neglect software testing, which can lead to unprofitable business outcomes. For example, ineffective software testing may fail to identify all defects, resulting in increased development costs. A key factor determining the success of software testing is the strategy for implementing the testing process, the selection of testing tools, and the documentation of testing activities. This article examines the current state of software testing processes in the Indonesian software industry. The research objective is to analyze the software testing implementation strategy within the software development context, focusing on three main areas: software testing methodology, software testing tools, and software testing documentation. The research employs a survey method, collecting data from several respondents, Indonesian software companies, via an online questionnaire. The research findings indicate that testing is still predominantly manual. However, some software companies have begun to adopt a combination of manual and automated testing. Most companies utilize software testing documentation for reporting purposes during the execution of tests. Nevertheless, documenting test cases as a guide for testing execution is not prioritized as highly as bug reporting. Conversely, many Indonesian software companies have adopted testing tools and conducted performance testing to ensure software quality. Consequently, the software testing process in the Indonesian software industry tends to adhere to formal methods in accordance with the ISO/IEC/IEEE 29119 software testing standards
Self-Isolation Monitoring of COVID-19 Patients Using Fuzzy Inference System-Tsukamoto Roshinta, Trisna Ari; Masbahah, Masbahah
SINTECH (Science and Information Technology) Journal Vol. 5 No. 2 (2022): SINTECH Journal Edition Oktober 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v5i2.1114

Abstract

In self-isolation of Covid-19 patients, it is very important to carry out regular condition checks. Currently, the examination of severity of patien’s condition can be carried out by the patient himself online with the tools as measurement provided by public health center, and the data can be monitored by medic team. Several applications for monitoring the daily condition of Covid-19 patients have been developed but the parameters used in the monitoring application are not standardized and the accuracy of the application is unknown. This study aims to develop a Covid-19 patient monitoring application using more complete and accurate parameters. The input parameters used are body temperature, O2 saturation, pulse rate, and respiratory rate. The output is the level of the Covid-19 patient's condition which is divided into mild, moderate, and severe, as well as information on the actions that must be taken. This research uses the Fuzzy Inference System-Tsukamoto method. The test results between the system output and expert testing related to the condition of Covid-19 patients show that this self-checking application for monitoring has an accuracy of 95%.
Analisis Spam Komentar Instagram menggunakan Support Vector Machine dengan Variasi Hyperparameter Haqimi, Nur Azizul; Roshinta, Trisna Ari
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

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Abstract

Instagram (IG) is a web and mobile-based social media application where users can share photos or videos with the available features. These features include captions, tagging, adding locations where photos or videos were taken, editing and filtering photos or videos before they are uploaded from the smartphone application and certain tags so that the photos can be seen by many people. Instagram as social media is not only a medium for communication but also for developing brands and selling products. Spam that often appears in spam comments is a barrier to getting appropriate information. When identifying spam and non-spam comments, a challenging problem is that the number of spam comments is less than non-spam comments, thus causing an imbalanced dataset problem. Imbalanced data sets can affect the performance of classification algorithms. Support Vector Machine (SVM) to classify comments between two classes (spam or nonspam) which is the maximum distance between the hyperplane and the closest item from both classes. Analysis of related research that has been carried out with feature variations states that the addition of 90 different features to the data used to increase classification accuracy on imbalanced data.  Other related research discusses Complementary Naïve Bayes which can be used to balance dataset classes. This research describes the selection of Support Vector Machine hyperparameters, especially for unbalanced data where the level of similarity is almost the same, so hyperparameter experiments are needed for the best accuracy
Co-Authors Asri Maspupah Haqimi, Nur Azizul Masbahah Masbahah, Masbahah Min, Joe Lian Rahmani, Ani