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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Jurnal Ilmiah Informatika Komputer Bulletin of Electrical Engineering and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer International Journal of Engineering and Emerging Technology Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Paradharma: Jurnal Aplikasi IPTEK KOMET Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Saraswati, Ni Wayan Sumartini
Institut Bisnis Dan Teknologi Indonesia
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Public Health Social Sciences Other

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Sentiment Analysis of the Relocation of the National Capital on Social Media X Dewi, Yesi Ratna; Saraswati, Ni Wayan Sumartini; Monny, Maria Osmunda Eawea; Sarasvananda, Ida Bagus Gede; Andika, I Gede
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14622

Abstract

The relocation of the national capital is a national strategic development project that seeks input from the public. This research analyzes public sentiment towards the relocation of the capital city using the Lexicon SVM method with data from X social media. The analysis was conducted in two languages, namely Indonesian and English, to find out how public opinion on the relocation of Indonesia's capital city at the global level. The sentiment classification results show that in Indonesian, public sentiment tends to be balanced with a model accuracy of 86.79%, where 51.3% is positive sentiment and 48.7% is negative. Meanwhile, in English, positive sentiment is more dominant with a model accuracy of 89.64%, where 83.3% is positive sentiment and 16.7% is negative sentiment. Evaluation using confusion matrix shows that this model provides good results, with high precision, recall, and F1-score values. Visualization using WordCloud and frequency analysis of unigrams, bigrams, and trigrams showed that positive sentiments mostly discussed the development aspects and government policies, while negative sentiments highlighted the social and economic impacts of the relocation. In addition, further analysis shows that public sentiment fluctuates based on important government announcements and major events related to the project. These findings demonstrate the importance of monitoring public opinion over time to understand shifts in perception. This research provides insights to the government and policymakers in understanding public opinion regarding the relocation of the nation's capital. By understanding sentiment patterns, more appropriate policies can be designed to increase public acceptance of the project and address public concerns effectively.
Optimizing Hotel Room Occupancy Prediction Using an Enhanced Linear Regression Algorithms Dewa Ayu Kadek Pramita; Ni Wayan Sumartini Saraswati; I Putu Dedy Sandana; Poria Pirozmand; I Kadek Agus Bisena
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.4254

Abstract

Predicting the correct hotel occupancy rate is important in the tourism industry because it has a major impact on the level of revenue and maintenance of a hotel’s reputation. With accurate predictions, hotel performance can be optimized regarding resources, staff, and hotel facilities. The linear regression method has been proven to perform causal predictions well. However, this method has several weaknesses, such as the function of the relationship between dependent variables and independent variables that are not linear, overfitting, or underfitting in building the prediction model. The purpose of this study was to optimize the linear regression model in predicting hotel occupancy rates. The method used in this study was a Linear Regression method optimized with Polynomial Regression and regularization techniques to reduce overfitting using Ridge Regression and Lasso Regression. The results of the model evaluation showed that linear regression, which was optimized with Polynomial Regression and Ridge Regression in the model with the historical data of the Adiwana Unagi occupancy rate, historical data of the hotel occupancy rate in Bali, and the number of tourist visits in Bali, gave the best performance, with a mean absolute error score of 1.0648, root mean square error of 2.1036, and R-squared of 0.9953. The conclusion of this research was optimization using polynomial regression, achieving the best evaluation scores, where the prediction model performance indicates that variable X7 (tourist visit numbers) strongly influences the prediction of the occupancy rate.
Evaluation Analysis of the Necessity of Stemming and Lemmatization in Text Classification Ni Wayan Sumartini Saraswati; Christina Purnama Yanti; I Dewa Made Krishna Muku; Dewa Ayu Putu Rasmika Dewi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4833

Abstract

Stemming and lemmatization are text preprocessing methods that aim to convert words into their root and to the canonical or dictionary form. Some previous studies state that using stemming and lemmatization worsens the performance of text classification models. However, some other studies report the positive impact of using stemming and lemmatization in supporting the performance of text classification models. This study aims to analyze the impact of stemming and lemmatization in text classification work using the support vector machine method, in this case, devoted to English text datasets and Indonesian text datasets, and analyze when this method should be used. The analysis of the experimental results shows that the use of stemming will generally degrade the performance of the text classification model, especially on large and unbalanced datasets. The research process consisted of several stages: text preprocessing using stemming and lemmatization, feature extraction with Term Frequency-Inverse Document Frequency (TF-IDF), classification using SVM, and model evaluation with 4 experiment scenarios. Stemming performed the best computation time, completing in 4 hours, 51 minutes, and 41.3 seconds on the largest dataset. While lemmatization positively impacts classification performance on small datasets, achieving 91.075% accuracy results in the worst computation time, especially for large datasets, which take 5 hours, 10 minutes, and 25.2 seconds. The Experimental results also show that stemming from the Indonesian balanced dataset yields a better text classification model performance, reaching 82.080% accuracy.
ANALISIS KOMPARASI LINEAR REGRESSION DAN POLYNOMIAL REGRESSION UNTUK PREDIKSI HARGA SAHAM Ni Wayan Sumartini Saraswati; I Wayan Dharma Suryawan; I Made Andi Kertha Yasa
Jurnal Ilmiah Informatika Komputer Vol 30, No 1 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i1.14070

Abstract

Investasi memegang peranan penting dalam melawan inflasi dan mendorong pertumbuhan ekonomi. Di antara berbagai instrumen investasi, saham menawarkan potensi keuntungan yang tinggi, tetapi memerlukan analisis yang cermat untuk meminimalkan risiko dan memaksimalkan keuntungan. Penelitian ini berfokus pada prediksi harga penutupan yang disesuaikan (Adj Close) dari saham PT Mitra Energi Persada Tbk (KOPI.JK), sebuah perusahaan energi yang terdaftar di Bursa Efek Indonesia (BEI), menggunakan teknik regresi machine learning, karena data historis yang mengalami fluktuasi signifikan. Dengan membandingkan Linear Regression dan Polynomial Regression yang dilengkapi dengan pengoptimalan regularisasi Ridge dan Least Absolute Shrinkage and Selection Operator (LASSO). Penelitian ini bertujuan untuk mengidentifikasi model yang paling efektif dalam memprediksi harga saham. Hasil analisis menunjukkan bahwa fitur Low dan High memiliki korelasi yang paling kuat dengan harga Adj Close, sementara Volume memiliki korelasi terendah. Polynomial Regression dengan degree=3 dan pengoptimalan regularisasi Ridge memberikan performa terbaik. Hasil evaluasi mencapai Mean Square Error (MSE) 122.9618, Root Mean Squared Error (RMSE) 11.0888, dan R-squared (R²) 0.9883. Pada pengoptimalan model menggunakan LASSO cenderung mengurangi relevansi fitur sehingga memberikan performa yang lebih buruk
REVITALISASI IDENTITAS PRODUK MELALUI DESAIN KEMASAN MAKANAN DI KAJA KANGIN WARUNG Putu Ananda Sitarasmi; Saraswati, Ni Wayan Sumartini; I Dewa Made Krishna Muku; I Wayan Dharma Suryawan; Dewa Ayu Kadek Pramita; I Kadek Agus Bisena; Ketut Jaya Atmaja
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2025): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

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

Abstract

Dalam sektor kuliner, terutama pada usaha mikro dan kecil seperti warung tradisional di Bali, aspek desain kemasan sering kali masih kurang diperhatikan. Padahal, di tengah kompetisi pasar yang kian ketat dan dominasi produk modern, kemasan yang dirancang secara menarik dan bermakna dapat menjadi keunggulan tersendiri yang membedakan produk lokal dari pesaingnya. Kaja Kangin Warung adalah sebuah usaha kuliner di Desa Singakerta, Ubud yang berdiri semenjak bulan Agustus tahun 2022. Saat ini, kemasan yang digunakan masih bersifat sederhana dan belum menggambarkan keunikan identitas lokal yang dapat meningkatkan nilai jual dan daya saing. Revitalisasi desain kemasan dilakukan pada kemasan rice bowl yang berupa desain pada paper bowl. Proses desain didasarkan pada proses analisis segmentasi, targeting dan positioning market dengan memperhatikan usaha pesaing di sekitarnya. Proses tahapan desain kemasan dilakukan dengan tahapan membuat concept board, dilanjutkan dengan tahapan sketsa awal, hingga pada proses desain akhir yang mencakup desain pada identitas brand, tipografi, tata letak, visual, dan warna hingga dihasilkan desain kemasan yang diharapkan mampu memberikan identitas produk dan meningkatkan daya saing usaha.
Indonesian Public Sentiment Toward Electric Vehicles: Analysis of Social Media Data Saraswati, Ni Wayan Sumartini; Suryawan, I Wayan Dharma; Muku, I Dewa Made Krishna; Bisena, I Kadek Agus; Pramita, Dewa Ayu Kadek
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.15179

Abstract

The development of electric vehicles (EVs) in Indonesia has progressed significantly, supported by government subsidies for Battery-Based Electric Motor Vehicles. These subsidies have sparked mixed public reactions that some support them due to environmental benefits and pollution reduction, while others oppose them for various reasons. Social media platform X serves as a valuable source for gauging public opinion, though analyzing such data manually can be complex. To address this, sentiment analysis, particularly using the Support Vector Machine (SVM) method, offers an efficient solution. This study analyzes 23,031 Indonesian-language tweets from social media platform X, collected between October 2023 and July 2024, using SVM for sentiment classification. The best-performing model, with parameter C = 0.5 and without stemming, achieved an accuracy of 84.98%. The findings suggest that Indonesians generally view electric vehicles positively, with more favorable sentiments than negative ones. This study offers implications across methodological, industrial, and policy domains. Word cloud analysis further supports this, highlighting public support in areas such as pricing, infrastructure, and environmental impact. However, the study also identifies key concerns, including issues around subsidies, taxes, vehicle durability, battery types, and import regulations. Overall, the research provides meaningful insights into the diverse perspectives of Indonesian citizens regarding EVs, helping to inform future policy and development strategies.
Indonesian Public Sentiment Toward Electric Vehicles: Analysis of Social Media Data Saraswati, Ni Wayan Sumartini; Suryawan, I Wayan Dharma; Muku, I Dewa Made Krishna; Bisena, I Kadek Agus; Pramita, Dewa Ayu Kadek
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.15179

Abstract

The development of electric vehicles (EVs) in Indonesia has progressed significantly, supported by government subsidies for Battery-Based Electric Motor Vehicles. These subsidies have sparked mixed public reactions that some support them due to environmental benefits and pollution reduction, while others oppose them for various reasons. Social media platform X serves as a valuable source for gauging public opinion, though analyzing such data manually can be complex. To address this, sentiment analysis, particularly using the Support Vector Machine (SVM) method, offers an efficient solution. This study analyzes 23,031 Indonesian-language tweets from social media platform X, collected between October 2023 and July 2024, using SVM for sentiment classification. The best-performing model, with parameter C = 0.5 and without stemming, achieved an accuracy of 84.98%. The findings suggest that Indonesians generally view electric vehicles positively, with more favorable sentiments than negative ones. This study offers implications across methodological, industrial, and policy domains. Word cloud analysis further supports this, highlighting public support in areas such as pricing, infrastructure, and environmental impact. However, the study also identifies key concerns, including issues around subsidies, taxes, vehicle durability, battery types, and import regulations. Overall, the research provides meaningful insights into the diverse perspectives of Indonesian citizens regarding EVs, helping to inform future policy and development strategies.
PKM DESCRIPTIVE ANALYSIS PADA ELY’S CAFE ADIWANA UNAGI SUITE Saraswati, Ni Wayan Sumartini; Muku, I Dewa Made Krishna; Suryawan, I Wayan Dharma; Martarini, Ni Made Lisma; Novitasari, Dwi; Nirwana, Ni Kade Ayu; Agetania, Ni Luh Putu; Yanti, Christina Purnama; Waas, Devi Valentino; Marlinda, Ni Luh Putu Mery; Juniartini, Ni Komang Tri
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2023): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59458/jwl.v3i2.61

Abstract

Di tengah persaingan yang makin ketat, Business Intelligence (BI) menjadi solusi dalam tantangan bisnis perusahaan yang lebih solutif. BI dalam prosesnya memanfaatkan data historis yang selalu bertumbuh semakin banyak. Dengan BI perusahaan dapat memiliki strategi yang lebih kuat dan pengambilan keputusan yang lebih matang. Penelitian ini membangun BI pada Adiwana Unagi Suites yang menghasilkan visualisasi data untuk mengambil keputusan yang tepat. Adapun tool yang digunakan adalah Tableau, software BI dan visualisasi data yang cepat, powerful, dan efektif digunakan. Dari penelitian ini, dihasilkan tujuh visualisasi data berdasarkan pertanyaan yang telah dikemukakan terlebih dahulu untuk membantu strategi bisnis. Adapun hasilnya berupa visualisasi data dengan berbagai bentuk grafik, seperti butterfly bar chart, vertical bar chat, line chart, tabel pivoting, serta box plot.
PENDAMPINGAN DAN PELATIHAN SISTEM INFORMASI BANK SAMPAH DI TPS 3R BAWANA LESTARI DESA PANGKUNGKARUNG Kartini, Ketut Sepdyana; Saraswati, Ni Wayan Sumartini; Sandhiyasa, I Made Subrata; Putra, I Nyoman Tri Anindia; Pramest, Ni Luh Gede Sintia
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2023): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59458/jwl.v3i2.62

Abstract

Bank Sampah merupakan suatu lembaga yang digunakan untuk mengelola kegiatan pengumpulan, pemilahan dan pengolahan sampah dari masyarakat setempat dengan tujuan mendaur ulang dan dijual atau diolah menjadi produk yang memiliki nilai ekonomi. Penulisan ini dilakukan di Bank Sampah Bawana Lestari Desa Pangkungkarung, Kecamatan Kerambitan, Kabupaten Tabanan. Pengolahan data di Bank Sampah masih dilakukan secara manual dengan menggunakan buku. Oleh karena itu, penulis membuat sebuah sistem informasi berbasis web yang dapat membantu proses pencatatan di Bank Sampah. Pengembangan sistem menggunakan metode waterfall Sedangkan pengumpulan data penulis menggunakan metode wawancara, observasi, kepustakaan, dokumen dan arsip. Pengujian sistem menggunakan black box testing dan user experience quisioner (UEQ). Hasil dari penulisan ini adalah sebuah sistem berbasis web yang dapat membantu petugas dalam melakukan pencatatan dan nasabah dapat melakukan pengecekan saldo dan penjualan sampah secara mandiri.
PKM MENGEMBANGKAN REVENUE MANAGEMENT SYSTEM UNTUK KAJA KANGIN WARUNG Saraswati, Ni Wayan Sumartini; Suryawan, I Wayan Dharma; Bisena, I Kadek Agus; Pramita, Dewa Ayu Kadek; Muku, I Dewa Made Krishna; Hartono, Eddy; Sandana, I Putu Dedy; Sari, Ni Luh Pangestu Widya
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2024): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat)
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59458/jwl.v4i2.91

Abstract

Kita berada pada era banjir data seiring dengan berkembangnya teknologi informasi dan internet. Biaya internet dan biaya media penyimpanan yang semakin murah mendorong masyarakat industri untuk menggunakan teknologi informasi dalam rangka mendukung jalannya perusahaan. Kaja Kangin Warung merupakan warung makan yang berada di daerah Ubud dimana saat ini hanya menggunakan sistem kasir dan dalam pengambilan keputusan untuk strategi bisnisnya. Untuk saat ini data yang terkumpul belum diolah secara maksimal dan belum memiliki informasi berharga untuk pengambilan keputusan yang lebih baik. Kegiatan pengabdian masyarakat ini mengembangkan descriptive analytics bagi Kaja Kangin Warung. Warung yang merupakan unit kecil ini memiliki urgensi yang lebih tinggi untuk mendapatkan penangangan berupa business intelligence system, mengingat bahwa perubahan strategi sangat penting untuk pengembangan warung. Descriptive analytics akan dikembangkan berbasis web application berdasarkan kebutuhan dari manajemen akan informasi yang digunakan untuk pengambilan keputusan. Adapun sumber datanya diperoleh dari data historis transaksi penjualan warung. Kegiatan PKM ini menghasilkan 10 halaman yang menampilkan visualisasi bisnis sehingga dapat bermanfaat dalam menjawab pertanyaan-pertanyaan bisnis Kaja Kangin Warung.
Co-Authors Alvin Limawan Susanto Andika, I Gede Atmaja, Ketut Jaya Chatarina Umbul Wahyuni Christina Purnama Yanti Christina Purnama Yanti Dewa Ayu Putu Rasmika Dewi Dewa Ayu Putu Rasmika Dewi Dewa Ayu Putu Rasmika Dewi Dewi Natalia, Sang Ayu Made Krisna Dewi, Dewa Ayu Putu Rasmika Dewi, Yesi Ratna Eddy Hartono Eddy Hartono Eddy Hartono Eddy Hartono I Dewa Made Krishna Muku I Dewa Made Krishna Muku I Dewa Made Krishna Muku I Gede Adi Sudi Anggara I Gusti Ayu Agung Diatri Indradewi I Kadek Agus Bisena I Kadek Agus Bisena I Kadek Putra Agung Darmawan I Ketut Setiawan I Made Andi Kertha Yasa I Made Sukarsa I Nyoman Tri Anindia Putra I Nyoman Yudha Chandra Dinata I Putu Dedy Sandana I Putu Dedy Sandana I Putu Krisna Suarendra Putra I Wayan Agustya Saputra I Wayan Dharma Suryawan Ida Bagus Gede Sarasvananda Juniartini, Ni Komang Tri Kadek Budi Sandika Ketut Gede Darma Putra, I Ketut Laksmi Maswari Ketut Sepdyana Kartini Krisna, Gede Gana Eka Made Sudarma MADE WAHYU ADHIPUTRA Maria Osmunda Eawea Monny Melinia Hutari Natalia, Sang Ayu Made Krisna Dewi Ni Komang Tri Juniartini Ni Luh Pangestu Widya Sari NI LUH PUTU AGETANIA . NI LUH PUTU MERY MARLINDA Ni Made Lisma Martarini Ni Wayan Mirah Senja Pertiwi Ni Wayan Wardani Nirwana, Ni Kade Ayu Pirozmand, Poria Poria Pirozmand Poria Pirozmand Poria Pirozmand Poria Pirozmand Pramana, I Gusti Kadek Candra Adi Cahya Pramest, Ni Luh Gede Sintia Pramita, Dewa Ayu Kadek Pramitha, Gede Dana Putu Ananda Sitarasmi Putu Wirayudi Aditama Sandhiyasa, I Made Subrata Sari, Ni Luh Pangestu Widya Waas, Devi Valentino Wardani, Ni Wayan Weizhi Song