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Paradise, Paradise
Institut Teknologi Telkom Purwokerto
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Pemberdayaan UMKM Melalui Pemasaran Digital Arifa, Amalia Beladinna; Wibowo, Fahrudin Mukti; Alika, Shintia Dwi; Burhanuddin, Auliya; Adhitama, Rifki; Paradise, Paradise
Jurnal Pengabdian Bisnis dan Akuntansi Vol 3 No 2 (2024): Jurnal Pengabdian Bisnis dan Akuntansi Soedirman
Publisher : Jurusan Akuntansi Fakultas Ekonomi dan Bisnis Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32424/1.jpba.2024.3.02.14599

Abstract

In the digital era, the use of information technology has become a key factor in business development, especially for Micro, Small, and Medium Enterprises (MSMEs). This community service program focuses on providing training and mentoring in digital marketing for MSMEs in Brani Village, Cilacap Regency. The program aims to enhance participants’ understanding and skills in utilizing social media platforms, particularly Instagram, to promote local products such as cassava chips, salted eggs, and peyek. The training covers basic digital marketing concepts, content creation strategies, and methods to increase audience engagement. Despite facing challenges like limited digital literacy and infrastructure, the program succeeded in improving participants’ ability to create engaging content and manage online business accounts. This initiative is expected to empower MSMEs to expand their market reach and increase competitiveness through digital transformation.
Deteksi Cyberbullying pada Pemain Sepak Bola di Platform Media Sosial “X” Menggunakan Metode Long Short-Term Memory (LSTM) Pawit Widiyantoro; Paradise Paradise; Yogo Dwi Prasetyo
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 1 (2025): Januari: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i1.382

Abstract

Social media has become a crucial part of modern life around the globe, providing users with various conveniences. However, its widespread use has also brought about new challenges, one of which is cyberbullying. This harmful issue can have serious emotional and physical effects on those targeted. Cyberbullying occurs in many areas, including sports, and soccer—a sport loved by millions—is no exception. Soccer players often face severe criticism, hate speech, and harassment on social media platforms. To tackle this problem, this study aims to create a strong model for detecting cyberbullying on the social media platform “X” using the Long Short-Term Memory (LSTM) method. By utilizing advanced machine learning techniques, the proposed model intends to identify and reduce instances of cyberbullying, helping to create a safer online space for athletes and the wider community.
Optimalisasi Sirkular Ekonomi melalui Implementasi SIMBAHNIRA dalam Manajemen Limbah Organik di Desa Tanjung Maliana Puspa Arum; Chusnul Maulidina Hidayat; Paradise Paradise
SAFARI :Jurnal Pengabdian Masyarakat Indonesia Vol. 5 No. 3 (2025): Juli : SAFARI :Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/safari.v5i3.2677

Abstract

Waste issues are the main focus and challenge in supporting sustainable development and the implementation of circular economy principles. This community service aims to optimize the implementation of a circular economy system through the use of SIMBAHNIRA (Organic Waste Management Information System) technology in managing organic waste at KSM Brayan, Tanjung Village. The methods used in this service are socialization, training, and direct assistance to KSM Brayan members. Data were collected through observation, interviews, and documentation in the SIMBAHNIRA implementation process. The results show that the implementation of SIMBAHNIRA has succeeded in increasing the efficiency of waste transaction recording, encouraging community participation in collecting organic waste.
Optimalisasi Pemasaran Digital melalui Website Terintegrasi dalam Meningkatkan Ekonomi dan Daya Saing UMKM Dejarumi Muhammad Eka Purbaya; Chusnul Maulidina Hidayat; Silvia Van Marsally; Paradise Paradise
SAFARI :Jurnal Pengabdian Masyarakat Indonesia Vol. 5 No. 3 (2025): Juli : SAFARI :Jurnal Pengabdian Masyarakat Indonesia
Publisher : BADAN PENERBIT STIEPARI PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56910/safari.v5i3.2741

Abstract

The development of digital technology provides great opportunities for Micro, Small, and Medium Enterprises (MSMEs) to expand market reach and increase competitiveness. MSME Dejarumi, as one of the local business groups, still faces various obstacles in terms of marketing and optimal use of digital technology. This community service activity aims to support the increase in the capacity of MSME Dejarumi through optimization of digital marketing based on an integrated website. The implementation method includes needs analysis, integrated website development, digital marketing training and assistance, assistance and monitoring, as well as program evaluation and improvement. The results of the activity show that the existence of an integrated website can increase product visibility, simplify the transaction process, and expand market access. In addition, MSME actors also experienced an increase in understanding and skills in managing digital marketing independently. Thus, this program has succeeded in encouraging the sustainable improvement of the economy and competitiveness of MSME Dejarumi through targeted digital transformation.
Pengembangan Aplikasi Web Pariwisata Berbasis Progressive Web App untuk Meningkatkan Pengalaman Wisatawan Shaquille Akbar Demsi; Laila Isyriyah; Paradise Paradise; Rakhmad Maulidi
Jurnal ilmiah Sistem Informasi dan Ilmu Komputer Vol. 5 No. 2 (2025): Juli : Jurnal ilmiah Sistem Informasi dan Ilmu Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juisik.v5i2.1334

Abstract

The development of information technology has brought significant changes to the tourism industry, yet challenges remain in developing comprehensive and accessible tourism web applications. This research aims to develop a multi-platform tourism web application that addresses the fragmentation of information services and trip planning, as well as accessibility limitations in destinations with limited connectivity. The research methodology includes system design using an agile approach with Scrum methodology, implementation of key features such as trip planning and article writing, and comprehensive testing through functional and acceptance testing. Implementation of Progressive Web Apps (PWA) and Trusted Web Activities (TWA) technologies is integrated to enhance accessibility and user experience. Test results show a success rate of nearly 100% in various usage scenarios, including offline conditions. The main conclusion demonstrates that the developed application successfully creates a digital ecosystem supporting holistic travel experiences, transforming how travelers plan, experience, and share their journeys. This research paves the way for innovation in leveraging web technology to improve accessibility of tourist destinations, support local economies, and promote sustainable tourism, with significant potential to transform the landscape of the digital tourism industry.
Performance Evaluation of Naïve Bayes and SVM in Sentiment Analysis of Illegal Parking Attendants Saputra, Sandra; Paradise, Paradise; Nugraha, Novanda Alim Setya
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.30714

Abstract

The increase in the number of vehicles in Indonesia has led to high demand for parking spaces, which has triggered the emergence of illegal parking attendants. This phenomenon has elicited various public responses, particularly on social media platform X. This study analyzes public sentiment toward the presence of illegal parking attendants by comparing the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms. The data used consists of 1,484 Indonesian-language tweets collected via crawling techniques. The pre-processing stage included data cleaning, case folding, word normalization, tokenization, stopword removal, and stemming. The data was then labeled with positive or negative sentiment using the InSet (Indonesia Sentiment Lexicon) approach and manually validated, before being divided into training and testing datasets. Feature extraction was performed using the TF-IDF method before being applied to the classification model. The evaluation results show that the SVM algorithm with a linear kernel approach produces the highest accuracy of 82%, outperforming Naïve Bayes: Gaussian 56%, Multinomial 74%, and Bernoulli 77%. These results are expected to contribute to the formulation of more organized and transparent parking policies, as well as demonstrate the importance of sentiment analysis as a tool to support data-driven decision making.
Analysis of the Effectiveness of Loyalty Membership Programs in Increasing Customer Retention Using Net Promoter Score (NPS) with Information System Support Cahya, Virdies Nur C; Setyanto, Refius; Paradise, Paradise
Eduvest - Journal of Universal Studies Vol. 5 No. 9 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i9.52060

Abstract

This study analyzes the effectiveness of membership loyalty programs in increasing customer retention using Net Promoter Score (NPS) with the support of information systems. Loyalty programs are one of the effective strategies in maintaining long-term relationships with customers. However, its success relies heavily on the right measurement of customer satisfaction, one of which is through NPS. NPS provides clear insights into customer loyalty levels by distinguishing between "promoters" and "detractors". Information systems play an important role in supporting the collection and analysis of customer data in real-time, enabling companies to create more personalized and relevant offers. Through the Systematic Literature Review (SLR) approach, this study reviewed various literature related to the implementation of loyalty programs, NPS measurement, and the role of information systems in improving customer retention. The results show that a combination of relevant loyalty programs, effective NPS measurement, and supportive information systems can create a better customer experience, increase satisfaction, and strengthen customer loyalty. This research also provides recommendations for companies in optimizing the use of information technology and periodic evaluation of loyalty programs to achieve maximum results in customer retention.
System of stunting information centre development using waterfall method Paradise, Paradise; Amrustian, Muhammad Afrizal
Jurnal Mandiri IT Vol. 12 No. 3 (2024): January: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i3.263

Abstract

Stunting is a condition in which the development and growth of children are stunted due to malnutrition. In Indonesia, 21.6% of the approximately 300 million stunting cases still exist. In an endeavour to combat stunting, the Indonesian government is holding posyandu at the lowest levels of government. Despite these efforts, a significant number of parents do not receive information about stunting. Therefore, this study will develop a web-based information application about stunting. The application is developed using the cascade methodology. The conclusion of this analysis was that the waterfall methodology is still applicable for small development teams. The application can then provide information on child development and malnutrition at any time.
DETECTION OF CHILDREN'S NUTRITIONAL STATUS USING MACHINE LEARNING WITH LOGISTIC REGRESSION ALGORITHM Yuliana, Yuliana; Paradise, Paradise; Qulub, Mudawil
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.2973

Abstract

Abstract: Children's nutritional issues are an important concern for parents to pay attention to growth and development, especially health and well-being. According to the results of the Ministry of Health's Indonesian Nutrition Status Survey (SSGI), there are 4 nutritional problems for children in Indonesia, namely stunting, wasting, underweight and everweight. In this research, how to predict signs of symptoms of a decline in a child's nutritional status using a machine learning algorithm, a prediction model was designed using logistic regression in Python IDE to predict whether a child is indicated by a decline in nutrition or not. Dataset from Bengkayang Community Health Center data consisting of 657 pediatric patient data. The dataset is divided into 7 features (independent variables) and 1 predictor (dependent variable). Test results show perfect performance with precision, recall, F1-score, accuracy values of 100%. Then the visualization results on the ROC (Receiver Operating Characteristic) curve to depict the TP (True Positive) value on the Y axis against the FP (false Positive) value on the become overfit. It is recommended that in preparing the training dataset, measure the training data and reduce the features, after carrying out feature selection to increase the accuracy of the model.            Keywords: child nutritional status; growth and development logistic regression; machine learning Abstract: Masalah Gizi anak menjadi perhatian penting bagi orangtua untuk memperhatikan tumbuh kembang, terutama kesehatan dan kejahteraan. Menurut hasil survei status Gizi Indonesia (SSGI) Kemenkes memperlihatkan 4 permasalahan gizi anak di Indonesia yaitu stunting, wasting, underweight, dan everweight. Dalam penelitian ini, bagaimana memprediksi tanda gejala penurunan status gizi anak menggunakan  algoritma  machine  learning dirancang model prediksi menggunakan logistic regression pada Python IDE dengan  memprediksi anak  terindikasi  penurunan gizi  atau tidak. Dataset dari data Puskesmas Bengkayang  yang terdiri 657 data pasien anak. Dataset dibagi menjadi 7 feature (variabel independen) dan 1 predictor (variabel dependen). Hasil Pengujian memperlihatkan kinerja yang sempurna dengan nilai presisi, recall,  F1-score, akurasi, sebesar 100%. Kemudian hasil Visualisasi pada kurva ROC (Receiver Operating Characteristic) untuk menggambarkan nilai TP (True Positif) di sumbu Y terhadap nilai FP (false Positif) di sumbu X juga menunjukkan nilai yang sangat tinggi dan sudah mendekati angka 1 ini pertanda bahwa model ini menjadi overfit. Sebaiknya dalam persiapan training dataset diukur dengan data training dan mengurangi feature, setelah melakukan feature Selection untuk meningkatkan akurasi model. Keywords: logistic regression; machine learning; status gizi anak; tumbuh kembang
Identification of Evaluation Results in E-Banking Services Transaction for Product Recommendation using the BIRCH and Davies Bouldin Index Method Buananta, Septian Eka Ady; Ahmad, Muhammad Aliif; Mahmood, Jamilah; Paradise, Paradise
JURNAL INFOTEL Vol 16 No 2 (2024): May 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i2.1116

Abstract

E-banking transaction services in the banking world include many products offered to customers. However, the existence of regulatory factors may limit the extent to which banks can promote e-banking services, especially in cases where promotions involve incentives or special offers. Besides, there is a need for data analysis that is used to help the process of recommending product promos from these services. Recommendations for this product promo can be known from the evaluation process of data collected from e-banking transaction services for purchases and payments. The clustering method suitable for providing significant and influential results compared to other methods is BIRCH, which is assisted by the Davies Bouldin Index method to determine the list of product groups with the lowest value. The results of this evaluation process show that data can be grouped based on which services have low levels of use. The services in question are Deposits, Credit Cards on Mobile Services, OVB, and Inter-Bank Transfers on Mobile Services. Therefore, this service can be used as a reference to increase product promotion by the bank.
Co-Authors Ahmad, Muhammad Aliif Aiza Yudha Pratama Alika, Shintia Dwi Amalia Beladinna Arifa Arif Budiman Asro Nasiri Aufa Salsabila Nahrowi Aulia Burhanuddin Auliya Burhanuddin Buananta, Septian Eka Ady Cahya, Virdies Nur C Chusnul Hidayat Chusnul Maulidina Hidayat Eva Rahma Indriyani Gladi Pawestri Utami I Anna Tul Munikhah Khusnul Fauziah Kusrini Kusrini Kusrini Kusrini Kusrini, Kusrini Laila Isyriyah Mahmood, Jamilah Maliana Puspa Arum Merlinda Wibowo Merlinda Wibowo Merlinda Wibowo Merlinda Wibowo Mudawil Qulub Muhammad Afrizal Amrustian Muhammad Eka Purbaya Muhammad Yusril Aldean Munthe, Adrian Wismar Novanda Alim Setya Nugraha Pawit Widiyantoro Qulub, Mudawil Rakhmad Maulidi Rifki Adhitama, Rifki Riqqah Fadiyah Alya Saputra, Sandra Sarah Astiti S.Kom., M.MT Setyanto, Refius Shaquille Akbar Demsi Silvia Van Marsally Teguh Rijanandi Veithzal Rivai Zainal Vera Wati Wahyu Adi Prabowo Wahyu Adi Prabowo wahyu prabowo Wibowo, Fahrudin Mukti Yogo Dwi Prasetyo Yuliana Yuliana Yuliana Yuliana Yuliana Yuliana, Yuliana