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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JURTEKSI Community Engagement and Emergence Journal (CEEJ) Jurnal Teknik Informatika (JUTIF) JINAV: Journal of Information and Visualization
Oktaviana, Luzi Dwi
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Library & Information Science Mathematics

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Data Mining Using Support Vector Machine Model for Baturraden Tourism Visitor Satisfaction Prediction Damayanti, Suci; Oktaviana, Luzi Dwi; Bratakusuma, Trias
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7346

Abstract

The tourism industry is a significant economic sector and a driver of local and national economic growth. Tourism not only contributes economically, but also plays an important role in introducing and preserving the cultural and natural wealth of an area. One of them is Baturraden tourism, a tourist destination located in Indonesia is experiencing a rapid increase in the number of tourist visits. Baturraden is a tourist destination located in the highlands at the foot of Mount Slamet, Indonesia, precisely in Banyumas Regency, Baturraden District. Tourists who visit every year are increasing but tour managers have not realized whether the tourists are satisfied or not so research is needed to measure the level of satisfaction of tourists so that the Baturraden tourism is better. To measure the level of satisfaction, an algorithm is needed, in this study the algorithm used is a support vector machine (SVM) to collect data that will be used as a dataset by taking reviews on google maps manually then the data is grouped into groups of satisfied and dissatisfied tourists, as many as 100 data are taken and processed. So that the final result obtained an accuracy value of 86.00%, and for reviews tend to be positive or satisfied tourists visiting the baturaden tourist area.
Adaptasi Teknologi Sebagai Penguatan Program PIK Remaja Bagi Kader Pembantu Pembina Keluarga Berencana Desa Ketenger (PPKBD) Suliswaningsih, Suliswaningsih; Oktaviana, Luzi Dwi; Khafid, Anas Nur; Furqoni, Wiqor
Community Engagement and Emergence Journal (CEEJ) Vol. 5 No. 3 (2024): Community Engagement & Emergence Journal (CEEJ)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ceej.v5i3.6496

Abstract

Desa Ketenger merupakan salah satu desa di Kecamatan Baturraden yang mendapat predikat Kampung KB, memiliki Kader Pembantu Pembina Keluarga Berencana Desa (PPKBD). Salah satu program kerja PPKBD Ketenger yaitu peningkatan SDM PIK Remaja. Salah satu tujuan PIK Remaja adalah Keterampilan Hidup (Life Skill), dimanan remaja dipersiapkan untuk dapat memiliki keterampilan sebelum mereka terjun ke kehidupan perkawinan/bermasyarakat. Selain itu, program tersebut sangat bermanfaat bagi remaja karena remaja adalah usia produktif dan usia perkembangan/pencarian jati diri. Sehingga perlu diarahkan dengan benar. Usia remaja merupakan usia sekolah, masih adanya indikasi siswa yang memiliki self control belajar yang lemah, padahal mereka berada pada era revolusi industri 4,0 yang mengharuskan seseorang memiliki self control belajar yang baik. Jika ini tidak dilakukan tindakan preventif maka akan mengganggu proses belajar siswa di sekolah. Tujuan pengabdian ini adalah memberikan pelatihan adaptasi teknologi berupa membuat desain grafis menggunakan Adobe Illustrator. Kegiatan pengabdian akan direkam dan diunggah ke platform Youtube, sehingga dapat diakses secara online.
Application of Data Mining in FP Growth Algorithm to Determine Customer Purchasing Patterns of Geprek Chicken Yulianti, Puji; Oktaviana, Luzi Dwi; Rakhmawati, Desty
JINAV: Journal of Information and Visualization Vol. 5 No. 1 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav2793

Abstract

The FP-Growth data mining algorithm used in the study to determine customer shopping patterns at Ayam Geprek Purwokerto shop. Focusing on identifying repeat purchase events, this research aims to improve the marketing strategy and operational efficiency of Ayam Geprek Purwokerto shop. With an in-depth understanding of customer preferences and shopping habits, this research provides valuable insights for business owners in customizing menu offerings and layouts that can significantly increase sales. The results of this purchase analysis provide an in-depth understanding of consumer preferences and help determine the right course of action to improve Ayam Geprek Purwokerto's business. This study shows that using the FP-Growth algorithm to analyze customer buying patterns can significantly improve the efficiency and effectiveness of Ayam Geprek Purwokerto. By understanding common buying patterns, business owners can increase inventory design more effective promotion strategies, and improve customer satisfaction. The research shows that this can be a useful guide for business owners to create more targeted and effective marketing strategies to increase business. Thus, this research significantly increases the understanding of consumer shopping habits in the food industry, especially in the Ayam Geprek Purokerto shop.The results of this study are expected to be the basis for developing smarter and more effective marketing strategies to improve the competitiveness of food companies. In addition, this research encourages further use of data mining in optimizing inventory management and marketing strategies for the food industry.
QUALITY OF SERVICE ANALYSIS OF WICO NETWORK GRAPARI TELKOM PURWOKERTO USING TIPHON STANDARD Hidayat, Rizky Bagas Nur; Oktaviana, Luzi Dwi; Kuncoro, Adam Prayogo
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2362

Abstract

The main problem of providing internet services for provider companies, especially WiCo GraPARI Telkom Purwokerto in responding to the needs and challenges of technological digitalization. This research aims to analyze the Quality of Service (QoS) of WiCo GraPARI Telkom Purwokerto network using TIPHON standard. The TIPHON standard is a series of standards developed by ETSI (European Telecommunications Standards Institute) in order to support the interoperability of Internet Protocol (IP) based telecommunications services. Testing of throughput, delay, packet loss, and jitter parameters was carried out using the Wireshark application. Testing quality of service parameters is done through four scenarios in quiet and crowded internet network conditions for the process of downloading and uploading videos from Google Drive. The results show that the overall network performance falls into the "Very Good" category with an index of 4 for throughput, delay, and packet loss, and the "Good" category with an index of 3 for jitter. The highest throughput was recorded at 23.687564 bps, the lowest delay was 0.386 ms, with no packet loss in all scenarios, and the lowest jitter was 0.386 ms. Thus, it can be concluded that the WiCo GraPARI Telkom Purwokerto internet network has met the expected TIPHON quality standards. Suggestions for future research to be able to include the expansion of studies in various other WiCo GraPARI locations to get a more comprehensive picture as well as the use of other testing methods and tools for more varied and in-depth results.
SENTIMENT ANALYSIS OF PEGIPEGI.COM ON GOOGLE PLAYSTORE WITH NAÏVE BAYES ALGORITHM Hardian, Riski; Oktaviana, Luzi Dwi; Hamdi, Aulia
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 3 (2024): Juni 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.v10i3.3201

Abstract

Abstract: Today, many users use online platforms rather than offline platforms for ticket bookings, involving a wide range of services such as flights, hotels, trains, buses, and entertainment. PegiPegi.com, as one of the fastest growing online travel agencies in Indonesia, demonstrates success by understanding the value of technology and maintaining strong partnerships. Users of this platform often provide reviews, viewing user reviews can be done manually but this will have a less effective impact, so it needs to be done automatically with sentiment analysis. This research the Naïve Bayes method in sentiment analysis of PegiPegi.com reviews, with a focus on understanding customer satisfaction and service improvement. By combining these approaches, this research contributes to a deeper understanding of user responses to OTA services and presents the evaluation results of the Multinomial Naive Bayes classification model with an accuracy rate of 89.5%. The high precision in the Negative class demonstrates the model's ability to identify negative reviews. However, there are challenges in classifying the Neutral class, indicating the potential for further improvement. Nevertheless, the F1 score of 0.522 reflects a good balance between overall precision, recall so it can be concluded the naïve bayes algorithm is successful for performing sentiment analysis. Keywords: Sentiment analysis; naïve bayes algorithm; pegipegi.com; playstore  Abstract: Saat ini banyak pengguna platform online dibandingkan offline untuk pemesanan tiket, yang melibatkan berbagai layanan seperti penerbangan, hotel, kereta api, bus, dan hiburan. PegiPegi.com, sebagai salah satu agen perjalanan online yang berkembang pesat di Indonesia, menunjukkan keberhasilan dengan memahami nilai teknologi dan mempertahankan kemitraan yang kuat. Pengguna platform ini sering memberikan ulasan, melihat ulasan pengguna bisa saja dilakukan secara manual tetapi hal ini akan memberikan dampak yang kurang efektif, sehingga perlu dilakukan secara otomatis dengan analisis sentiment. Penelitian ini bertujuan untuk menerapkan metode klasifikasi Naïve Bayes dalam analisis sentimen ulasan PegiPegi.com, dengan fokus pada pemahaman kepuasan pelanggan dan peningkatan layanan. Dengan menggabungkan pendekatan ini, penelitian ini berkontribusi pada pemahaman yang lebih dalam tentang tanggapan pengguna terhadap layanan OTA dan menyajikan hasil evaluasi model klasifikasi Multinomial Naive Bayes dengan tingkat akurasi 89,5%. Presisi tinggi di kelas Negatif menunjukkan kemampuan model untuk mengidentifikasi ulasan negatif. Namun, ada tantangan dalam mengklasifikasikan kelas Netral, menunjukkan potensi untuk perbaikan lebih lanjut. Namun demikian, skor F1 0,522 mencerminkan keseimbangan yang baik antara presisi keseluruhan dan daya ingat sehingga dapat disimpulkan algoritma naïve bayes berhasil untuk melakukan analisis sentimen. Keywords: Analisis sentimen; naïve bayes; pegipegi.com; playstore
Co-Authors Adam Prayogo Kuncoro Aulia Hamdi DAMAYANTI, SUCI Furqoni, Wiqor Hardian, Riski Hidayat, Rizky Bagas Nur Khafid, Anas Nur Rakhmawati, Desty Suliswaningsih, Suliswaningsih Trias Bratakusuma Yulianti, Puji