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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Inovasi Global
Krismentari, Ni Kadek Bumi
STMIK STIKOM Indonesia, Denpasar
Astronomy Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences

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Penerapan Apriori Hybrid Pada Transaksi Penjualan Barang I Made Dwi Putra Asana; Ni Luh Wiwik Sri Rahayu Ginantra; Wayan Gede Suka Parwita; Ni Kadek Bumi Krismentari; Ni Putu Suci Meinarni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 4 (2021): Oktober 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i4.3350

Abstract

Ayu Nadi Swalayan is a retail company that produces a lot of every day sales transaction data, and it is stored for years without knowing the benefits and the placement of the goods is still random. From these problems, an effort is needed to process the data so the data is useful in the future. One of the process is using data mining techniques with apriori hybrid algorithm to find association rules for an items combination. Data product sale in a certain period is used to find the association rules. The results of this study are the development of applications that are used to determine consumer spending habits. So that the company can develop a strategy to promote the product sale and close placement for items that are often purchased together. The application testing found the effect of minimum support, minimum confidence on the number of rules, and lift ratio testing. The smaller the minimum support and minimum confidence, the more rules are generated and vice versa. The lift ratio value is directly proportional to the minimum confidence value and inversely proportional to the minimum support value. The higher the minimum confidence value, the higher the lift ratio value and vice versa. The more items in the transaction cause the minimum support threshold to be lowered in order to generate rules for the data analysis process with the hybrid apriori algorithm
Optimalisasi Manajemen Konten Digital Berbasis Wordpress untuk Branding UMKM Herdiana, I Kayan; Bumi Krismentari, Ni Kadek; Hendika Permana, I Putu; Kusuma Wijaya, Bagus; Ayu Nirwana, Ni Kadek
Jurnal Inovasi Global Vol. 3 No. 7 (2025): Jurnal Inovasi Global
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jig.v3i7.369

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peran vital dalamperekonomian Indonesia, namun masih banyak yang menghadapi kendala dalammembangun citra merek secara digital. Salah satu tantangan utama adalah keterbatasanpemahaman dalam pengelolaan konten digital yang konsisten dan terarah. Penelitian inibertujuan untuk mengoptimalkan manajemen konten digital berbasis WordPress gunameningkatkan branding UMKM, dengan studi kasus pada Keris Art Shop. Metode yangdigunakan adalah penelitian terapan dengan pendekatan kualitatif-deskriptif yangdilaksanakan dalam empat tahapan utama, yaitu: identifikasi dan analisis kebutuhankonten, perancangan sistem manajemen konten berbasis WordPress, implementasi danpelatihan pengelolaan, serta evaluasi terhadap efektivitas branding digital. Hasilpenelitian menunjukkan bahwa penggunaan WordPress sebagai platform pengelolaankonten memberikan dampak signifikan terhadap peningkatan visibilitas usaha secaradaring. Setelah implementasi sistem, trafik situs meningkat sebesar ±220% dalam waktutiga bulan, diikuti oleh meningkatnya interaksi pengguna dan persepsi positif terhadapmerek. Pelaku UMKM juga menunjukkan peningkatan kompetensi dalam pengelolaankonten digital secara mandiri. Luaran yang dihasilkan mencakup website aktif, panduanpengelolaan konten, pelatihan teknis, dan artikel ilmiah. Temuan ini menunjukkanbahwa strategi digital berbasis WordPress dapat menjadi model efektif dan replikatifuntuk meningkatkan branding UMKM di era transformasi digital.
Forecasting Hotel Demand with Time Series Prediction Model Using Random Forest Regression Pramita, Dewa Ayu Kadek; Saraswati, Ni Wayan Sumartini; Sandana, I Putu Dedy; Dewi, Dewa Ayu Putu Rasmika; Krismentari, Ni Kadek Bumi
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 1 (2026): Article Research January 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i1.15655

Abstract

The tourism sector, as one of the main contributors to national foreign exchange, relies heavily on the growth of the hospitality industry. Improvements in this sector are expected to enhance service quality and strengthen the overall image of tourism. However, the hospitality industry is highly dynamic, with fluctuating room demand influenced by both internal and external factors, creating challenges for accurate demand forecasting. This study develops a hotel demand prediction model using internal variables (occupancy rate, reservations, cancellations, and lead time) and external variables (events and visitor numbers). The Random Forest Regression method was employed, with predictive performance evaluated through a proxy demand index. The dataset was obtained from Adiwana Unagi Suites, Ubud, Bali, covering historical time series data from November 2021 to July 2025 with a total of 18.674 transactions. Evaluation metrics included Mean Absolute Error, Mean Square Error, Root Mean Square Error, and R-squared, applied to each hotel room type. The results demonstrate strong predictive performance, with R-squared values of 99.83% for test data, 99.95% for training data, and 88.24% for three-month prediction data, accompanied by low error values across all metrics. The lower performance in the three-month forecast may be due to the proxy demand index not fully representing actual demand. Overall, the findings highlight the potential of machine learning approaches, particularly Random Forest Regression, to support decision-making in hotel management. The model can serve as a reference for room pricing, allocation, and operational strategies, enabling stakeholders to adapt effectively to fluctuating market demand.
Co-Authors Asana, I Made Dwi Putra Ayu Nirwana, Ni Kadek Dewi, Dewa Ayu Putu Rasmika Herdiana, I Kayan I Putu Dedy Sandana I Putu Hendika Permana Kusuma Wijaya, Bagus Ni Luh Wiwik Sri Rahayu Ginantra Ni Putu Suci Meinarni Pramita, Dewa Ayu Kadek Saraswati, Ni Wayan Sumartini Wayan Gede Suka Parwita