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Titania Dwiandini
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Jl. Brig Jend. Hasan Basri, Pangeran, Kec. Banjarmasin Utara, Kota Banjarmasin, Kalimantan Selatan 70124
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INDONESIA
POSITIF
Published by Politeknik Negeri Banjarmasin
ISSN : 26203227     EISSN : 24609552     DOI : https://doi.org/10.31961/positif.v9i2.1995
Core Subject : Science,
Computer Science & IT
Since Volume 4, No. 2, 2018, the journal has been ACCREDITATED with grade "SINTA 4" by the Ministry of Research and Technology/National Research and Innovation Agency of Republic Indonesia (Kemenristek BRIN RI) of The Republic of Indonesia effective until 2023 .
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 283 Documents
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EVALUASI DAN PERBAIKAN DESAIN UI/UX DENGAN METODE USER CENTERED DESIGN PADA WEBSITE SMK NEGERI 1 BINANGUN Rahayu, Ratna Budi Sri; Prasetyo, Novian Adi; Wijayanto, Aditya
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 1 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i1.1972

Abstract

The SMKN 1 Binangun website is a website-based software system that is used to convey the latest information or news from the school to students. This website began to be used in 2020, but in its use there were several problems experienced by users. These obstacles include an interface that is not good in terms of design, page layout and website content, apart from that in terms of website appearance which is less attractive and less attractive to users and lack of updates. Incomplete information can be added with information on expertise programs and infrastructure, there is no search menu, many menus are still empty and not functioning, the alumni data update flow on the alumni menu is still confusing and can be accessed by non-alumni and website visitor traffic is still low. Based on these problems, it is necessary to evaluate and improve the UI/UX design to produce a website that fits user needs. The results of this study are improvements to the user interface of the SMKN 1 Binangun website from the user side (front-end). The results of usability testing using UEQ obtained a comparisson to benchmark rating between above average to good, indicating that the website design improvement was better than the previous design, this was reinforced by hypothesis analysis which stated that the H0 hypothesis was rejected and H1 was accepted according to the UEQ average value.
PERBANDINGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) DAN NAÏVE BAYES DALAM KLASIFIKASI PENYAKIT DIABETES Desiani, Anita; Dewi, Novi Rustiana; Arhami, Muhammad; Sitorus, Dina Suzzete; Rahmadita, Suristhia
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 1 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i1.2092

Abstract

High levels of sugar in the blood can cause diabetes. The longer people are unable to control glucose in their blood, the more complications it can cause, other diseases and even death. Early detection of diabetes is needed, one way is by carrying out data mining classification. Data mining classification in this research uses two algorithms, namely SVM (Support Vector Machine) and Naïve Bayes. This research compares the two algorithms using two methods, namely training split and k-fold cross validation which aims to get the best classification results in detecting diabetes. The best classification results are determined by calculating the average value of precision, recall and accuracy. Based on this research, the SVM algorithm with split percentage training produces average values for precision, recall and accuracy, namely 77%, 71.5%, 77.27%, while the SVM algorithm with k-fold cross validation produces average values for precision, recall , and accuracy is 77%, 72.5%, 71%. The Naïve Bayes algorithm with the split percentage training method produces average values for precision, recall and accuracy, namely 75.5%, 74.5%, 79%, while the Naïve Bayes algorithm with k-fold cross validation produces average values for precision, recall, and accuracy of 75.5%, 74.5%, 75%. The best classification result in detecting diabetes is the Naïve Bayes algorithm, the split percentage method, which provides the best accuracy, precision and recall values above 74%.
Menilai Efektivitas Scrum dalam Manajemen Proyek Agile untuk Peningkatan Layanan Perusahaan Damayanti, Murni
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2162

Abstract

Currently, various frameworks are used to implement Information Technology Governance (ITG). Due to the dynamic nature of ITG that is constantly evolving, there is an increasing demand for more efficient preparation, planning, and process development. In this context, having a supportive framework is a key priority. Therefore, the author intends to investigate how the integration of the ITIL framework into the Continual Service Improvement approach can enhance ITG. These efforts will be empowered by the implementation of a more adaptive and simplified operational approach in the form of Agile Project Management with the Scrum methodology. The goal is to accelerate the progress of ITG and make it more responsive and efficient in maximizing service quality across various organizations.
PENERAPAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DALAM ANALISIS SENTIMEN PENGARUH BRAND IMAGE DAN LABEL HARGA: STUDI ANALISIS: PRODUK SKINCARE SKINTIFIC Lathifah, Ekarini; Wicaksono, Aditya Dwi Putro; Wijaya, Andreas Rony
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2259

Abstract

There are various kinds of products that are included in cosmetic products, namely personal care, make up, fragrance including perfume, hair care, and skincare. Skincare has become one of the primary needs for women in Indonesia today, because skincare can maintain healthy skin. Skincare is a beauty product that is used by users to clean dirt on the face. In deciding to choose skincare products, of course, consumers are influenced by various factors such as skincare quality, brand image, price, and others. In addition, reviews of skincare products are also important as an effort by cosmetic companies to attract consumers' buying interest. One method in deep learning to analyze is the Convolutional Neural Network (CNN). Sentiment analysis is carried out as an effort to evaluate and determine consumer satisfaction with skincare products as well as materials for service improvement. This study uses the CNN method which in this model has several stages such as data scraping, data preprocessing which consists of data cleansing & case folding, stemming, tokenizing, filtering (stopword removal), labeling process, modeling, and model evaluation. In this study, the data used is scraping data on the Tokopedia website about skincare skintific products. The data will be processed with the CNN model to obtain an accuracy value resulting from the performance of the model.
RANCANG BANGUN GAME STOCK STREET SAGA BERDASARKAN ANALISIS TEKNIKAL Tristiyanto; Yuliyanto, Kurniawan Dwi; Syarif, Admi; Wulansari, Ossy Endah Dwi
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research focuses on the development of the "Stock Street Saga" game, which effectively integrates technical analysis concepts using indicators such as volume, momentum, trend, and oscillator. The game is designed to provide a simulation that allows players, especially beginners, to practice and understand technical analysis without financial risk. The research utilized the Game Development Life Cycle (GDLC) method, ensuring a systematic approach from initiation to production and testing. User Acceptance Testing (UAT) results from 40 respondents, consisting of novice traders and game developers, showed that the game effectively facilitates learning technical analysis. With an average UAT score of 75.57%, it indicates that the game meets the criteria of being a good educational tool, successfully implementing technical analysis concepts and offering an effective learning experience
PENERAPAN MODEL GREEN SUPPLY CHAIN MANAGEMENT UNTUK PENGEMBANGAN INDUSTRI BATIK TULIS MADURA DENGAN GSCOR DAN ANP Ismiyati; Darmawan, Aang Kisnu; Bakir
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2482

Abstract

Research on the implementation of Green Supply Chain Management (GSCM) in every business unit is very important considering the urgent environmental issues. This research focuses on the assessment of the GSCM process and performance measurement to determine the performance value of GSCM in the Madura Batik Writing Industry. The methods used are the greenSCOR method and the analytical network process (ANP) method. The Green SCOR method is used to identify and measure environmental and sustainability performance in the supply chain including The 5 core processes are planning, procurement, production, delivery and return. Meanwhile, the ANP method is used to determine the weight of importance of each core process. The results of the research on measuring the performance of the supply chain of the written batik industry using the GreenSCOR model showed a value of 65.5225, showing that the written batik industry in Pamekasan Regency is included in the category of "Avarange" related to the measurement of supply chain management performance reflecting the overall performance companies in the batik tulis industry. The weighting results of the Analytic Network Process (ANP) method show that the criteria "Make" (0.34) and "Plan" (0.31) are the most important in performance assessment, followed by "Source" and "Deliver" with weights of 0.16, and 0.10 respectively while "Return" has the lowest weight (0.06). The implication of this research is the importance of strengthening planning and efficiency in the production process. This research can produce valuable publications in academic journals related to supply chain management, sustainability, and creative industries. The results of these studies can serve as a reference for practitioners, researchers, and policymakers in their efforts to implement sustainable practices in the batik writing industry and other industries.
Analisis Sentimen Masyarakat Terhadap Kesehatan Mental Pada Media Sosial Twitter Dengan Menggunakan Machine Learning Aulia, Hudatul; Zulfadhilah, Muhammad; Prastya, Septyan Eka; Pebriadi, Muhammad Syahid
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2545

Abstract

Mental health affects lives globally, with around 300 million people experiencing depression in 2019, including 15.6 million in Indonesia. The Covid-19 pandemic increased cases of anxiety and depression, and by 2022, WHO reported 23 million people suffering from psychiatric disorders. In Indonesia, adolescent mental health issues are also high, with excessive social media use linked to an increase in emotional disorders. Twitter, with its real-time data, is becoming an important tool for analyzing public sentiment and understanding opinions through analytics and machine learning techniques. This study aims to determine public sentiment towards mental health in Indonesia through Twitter social media and test the effectiveness of using machine learning in sentiment analysis. The results show that the Naive Bayes and Decision Tree methods are effective in analyzing sentiment, with an accuracy of 91% and 89% respectively. The average result of cross validation shows a value of 73.21% for Naive Bayes and 67.02% for Decision Tree. In this study, positive sentiment is more dominant with a percentage value of 78.7%, while negative sentiment is only 21.3%. The findings indicate that Indonesians' awareness of the importance of mental health is increasing, and they increasingly understand the importance of maintaining mental health
ANALISIS USABILITY PADA APLIKASI INDOFARM UNTUK MENGUKUR TINGKAT KEPUASAN PELANGGAN MENGGUNAKAN CUSTOMER SATISFACTION INDEX DAN USER EXPERIENCE QUESTIONNAIRE Pramanda, Riska; Ilhamsyah; Mutiah, Nurul
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2105

Abstract

The rapid growth of digitalization has driven the expansion of E-Commerce, including the Indofarm application in Pontianak, which provides grocery delivery services. However, users have reported issues related to system performance and service quality. This study evaluates customer satisfaction using the Customer Satisfaction Index (CSI) and User Experience Questionnaire (UEQ) with 26 measurement indicators. The results show a CSI score of 52.70%, indicating a "moderately satisfied" category. Importance Performance Analysis (IPA) identifies seven attributes—speed, security, motivation, expectations, efficiency, organization, and attractiveness—as critical areas for improvement. Additionally, one attribute, "Pleasant," is rated highly but is of lower priority. The findings suggest that Indofarm should focus on enhancing key service aspects while reallocating resources from less critical attributes to improve overall customer satisfaction.
PENERAPAN ALGORITMA K-NEAREST NEIGHBOR UNTUK DETEKSI DINI STATUS GIZI PASIEN DEWASA Wijayanti, Dian; Hermawan, Arief; Avianto, Donny
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 2 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i2.2255

Abstract

Assessing the nutritional status of adult patients is essential to gain a comprehensive understanding of their condition and assist healthcare workers in planning appropriate treatment. However, manual assessment is time-consuming and labor-intensive, especially when the number of patients exceeds the number of available healthcare workers. This can hinder the timely and accurate delivery of nutritional care. The K-Nearest Neighbor (KNN) algorithm is a commonly used method for nutritional status classification, particularly in toddlers, pregnant women, or for obesity classification in adults. The use of KNN for early detection of adult nutritional status remains rarely explored. This study applies the KNN algorithm to classify the nutritional status of adult patients using data from the Alamanda 1 ward and the ICU ward at Sleman Regional General Hospital, collected from January 2 to October 18, 2023. The dataset includes patient height, weight, and nutritional status. The algorithm was implemented using RapidMiner with odd k-values less than 20, and data splits of 90:10, 70:30, and 50:50 for training and testing. Results show that the optimal k-values for the highest accuracy were k = 1 and k = 3 using the 70:30 data split, both achieving an accuracy of 96.77%. The highest sensitivity, 97.61%, was also achieved at k = 3 with the same data split. The KNN algorithm demonstrates strong potential to be developed into an early detection system for assessing the nutritional status of adult patients in hospitals, supporting faster and more accurate nutritional care services
SISTEM INFORMASI BANK SAMPAH PADA BANK SAMPAH INDUK CAHAYA KENCANA MANIS KABUPATEN BANJAR PROVINSI KALIMANTAN SELATAN Rozaq, Abdul; Krisna Ade Satria, Maximilianus; Yuniar Fahmi, Rizka; Fitri, Rahimi
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 11 No 1 (2025): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v11i1.14358

Abstract

Garbage is an environmental problem that is very complex and complicated to solve. The presence of waste banks is an alternative to reduce waste problems by converting waste into rupiah. The research was conducted with the aim of designing and developing an information system that can be applied to the Parent Waste Bank Cahaya Kencana Manis Banjar Regency, South Kalimantan Province in order to provide optimal information and can be accessed in real time by its customers. This type of research uses the Research and Development (R&D) research method and the waterfall method as a development method applied to the waste bank information system to ensure that the resulting information system meets user needs by applying communication, planning, modeling, construction, and deployment. The design results are converted into a system that runs according to business flow with the Bootstrap framework and MySQL database. As a result, the waste bank information system was successfully created and implemented at the Parent Waste Bank Cahaya Kencana Manis Banjar Regency, South Kalimantan Province. The information system also supports a responsive display when accessed using a mobile device. Blackbox testing results show that the information system can run as needed

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