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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Telematika : Jurnal Informatika dan Teknologi Informasi INFORMAL: Informatics Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal EDUTECH Undiksha Jurnal Mantik UTAMAX : Journal of Ultimate Research and Trends in Education Indonesian Journal of Data and Science Jurnal Scientia JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) PROFICIO: Jurnal Pengabdian Masyarakat Cendikia : Media Jurnal Ilmiah Pendidikan JURNAL ILMIAH GLOBAL EDUCATION JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Parta: Jurnal Pengabdian Kepada Masyarakat Jurnal Puan Indonesia Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Jurnal Penjaminan Mutu Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka KOMET Jurnal ilmiah teknologi informasi Asia Educare: Journal Educational and Multimedia

Aniek Suryanti Kusuma

Institut Bisnis Dan Teknologi Indonesia

Author-ID : 630431

Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Sentiment Analysis of Roblox Game Reviews Using Support Vector Machine Method Dewi, Ni Kadek Feby Puspita; Sudipa, I Gede Iwan; Sunarya, I Wayan; Kusuma Dewi, Ni Wayan Jeri; Kusuma, Aniek Suryanti
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15272

The development of digital technology has driven changes in entertainment consumption patterns, especially among the younger generation. Roblox has become one of the most popular online gaming platforms, with a wide range of user opinions recorded on Google Play Store. This study aims to classify the sentiment of Roblox user reviews (positive, negative, neutral) and evaluate the performance of the Support Vector Machine (SVM) algorithm with TF-IDF weighting and automatic labeling using Lexicon InSet. Data was obtained by crawling 10,000 reviews during the period of April 2–May 23, 2025, and after the preprocessing stage, 8,950 data remained for analysis. The classification results show that the sentiment distribution consists of 41.3% positive (3,703 reviews), 41.8% neutral (3,739 reviews), and 16.8% negative (1,507 reviews). Model evaluation using a confusion matrix produced high performance with 87.03% accuracy, 87.29% precision, 87.03% recall, and an F1-score of 86.67%. WordCloud visualization shows that positive reviews emphasize creativity and interactive features, while negative reviews are dominated by technical complaints such as lag and errors. These findings prove that the combination of SVM, TF-IDF, and Lexicon InSet is effective in sentiment analysis and provides valuable input for developers to improve application quality and user protection. Further research is recommended to adopt a hybrid approach based on deep learning and aspect-based sentiment analysis to generate more insights.

PKM: IMPLEMENTASI SISTEM INFORMASI BANK SAMPAH BANJARANGKAN ASRI Desmayani, Ni Made Mila Rosa; Bevi Libraeni, Luh Gede; Kusuma, Aniek Suryanti
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.v4i2.73

Sistem Informasi Bank Sampah Banjarangkan Asri, berbasis Website dirancang untuk mengatasi permasalahan pada sistem pencatatan transaksi Bank Sampah. Pencatatan transaksi setoran sampah dan penarikan saldo yang masih manual pada buku tabungan menyebabkan potensi kerusakan, kehilangan, dan kesalahan pencatatan pada buku tabungan nasabah. Selain itu, dalam proses pencatatan transaksi, kader juga sering kali lupa mencatat harga sampah, memerlukan waktu yang cukup lama untuk mencari informasi pada tabel daftar harga dasar Bank Sampah. Oleh karena itu diperlukan sistem informasi bank sampah untuk dapat meningkatkan efisiensi, dan efektivitas. Dalam penelitian ini, penulis menggunakan teknik pengembangan waterfall. Tahapan yang pertama yaitu menganalisis kebutuhan, tahap kedua mendesain sistem, tahap ketiga menuliskan kode program, tahap keempat melakukan pengujian sistem, dan tahap yang terakhir yaitu penerapan dan pemeliharaan sistem. Sistem informasi ini dibuat dengan berbasis website dengan menggunakan bahasa pemrograman PHP dan MYSQL serta menggunakan Framework Laravel. Implementasi sistem dapat beroperasi dengan baik, pengujian sistem dilakukan dengan menggunakan metode pengujian Blackbox dengan menguji sejumlah 33 fungsionalitas pada website Bank Sampah Banjarangkan Asri didapatkan hasil 100% valid. Dimana dapat disimpulkan bahwa semua pengujian fungsionalitas dengan menggunakan Black Box testing semuanya berhasil. Kata Kunci : Sistem Informasi, Bank Sampah Banjarangkan Asri, metode waterfall.

Time Series Analysis of Tourist Arrivals to Bali Using Data Kusuma, Aniek Suryanti; Batubulan, Kadek Suarjuna
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 4 (2025): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.216

This research performs a time series analysis on the number of tourist arrivals to Bali, using historical data to identify patterns, trends, and potential forecasting models. The tourism sector is crucial to Bali's economy, and understanding visitor trends can assist in planning and resource allocation. Data from 2010 to 2023 is analyzed, focusing on monthly arrival statistics sourced from government tourism departments. Several time series methods are employed, including seasonal decomposition, autocorrelation, and ARIMA (AutoRegressive Integrated Moving Average) modeling. The analysis reveals distinct seasonal patterns, with peaks during holiday periods and off-peak lulls. A significant impact of global events, such as the COVID-19 pandemic, is observed, causing sharp declines in tourist arrivals. By fitting ARIMA models, we forecast future trends in tourist numbers, providing insights into the potential recovery trajectory of Bali's tourism industry post-pandemic. The research concludes with recommendations for stakeholders, including government agencies and businesses, on how to prepare for future fluctuations in tourist arrivals and capitalize on seasonal trends. Understanding these patterns is essential for fostering sustainable growth and minimizing economic disruptions within the tourism sector.

PELATIHAN PEMANFAATAN GOOGLE FORM BAGI TENAGA PENDIDIK DI SMP NEGERI 2 BANGLI Dirgayusari, Ayu Manik; Kusuma, Aniek Suryanti; Putra, Desak Made Dwi Utami; Welda, Welda; Supartha, I Kadek Dwi Gandika
Jurnal Pengabdian Masyarakat Sabangka Vol 1 No 04 (2022): Jurnal Pengabdian Masyarakat Sabangka
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/sabangka.v1i04.262

Sebagai salah satu SMP negeri di Kabupaten Bangli, SMPN 2 Bangli ingin menyiapkan tenaga pendidiknya agar siap untuk pembelajaran secara daring akibat pandemi saat ini. Tenaga pendidik di SMPN 2 Bangli tidak semuanya mampu menggunakan dan mengoperasikan Google Form karena faktor usia dan karena belum terbiasa. Selain itu Google Form merupakan salah satu aplikasi yang disarankan oleh dinas terkait untuk digunakan dalam proses belajar mengajar pada pembelajaran daring saat ini. Dengan Google Form diharapkan setiap guru dapat memberikan tugas, kuisioner, ulangan harian atau pun ujian secara daring. Melalui kegiatan pengabdian masyarakat STIKI Peduli ini, SMPN 2 Bangli bekerja sama dengan STMIK STIKOM INDONESIA (STIKI) untuk melakukan pelatihan pemanfaatan Google Form untuk para tenaga pendidik. Metode pengabdian yang dilakukan adalah pemberian pelatihan dengan menggunakan metode Presentasi, metode Praktek Langsung, Tanya Jawab (Diskusi), dan pemberian Pretest dan Posttest kepada peserta pelatihan sebelum dan sesudah pelatihan dilakukan. Pelatihan ini dilaksanakan di sekolah dengan penerapan protokol kesehatan yang ketat. Kegiatan ini dilakukan selama 2 hari agar jumlah peserta dalam ruangan tidak terlalu banyak. Harapannya semua tenaga pendidik di SMPN 2 Bangli dapat ikut berpartisipasi dan mendapatkan pemahaman tentang Google Form.

Data Analysis of Bitcoin Price Trends Using KNN Prediction Models Kusuma, Aniek Suryanti
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 4 (2023): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.247

This study investigates Bitcoin price trends and evaluates the effectiveness of the K-Nearest Neighbors (KNN) algorithm for predicting price movements in the cryptocurrency market. Leveraging a decade of historical Bitcoin price data, trading volume, and market capitalization, the research assesses the accuracy and reliability of KNN in capturing the complex and volatile nature of Bitcoin price dynamics. The methodology includes data preprocessing, exploratory analysis, and predictive modeling with hyperparameter optimization. The findings reveal that while KNN achieves moderate accuracy (53%), it performs better in identifying price decreases (Class 0) with a recall of 66% compared to price increases (Class 1) with a recall of 40%. The study also highlights key challenges, including Bitcoin's high volatility and multicollinearity among features like Moving Averages. To improve prediction accuracy, the research recommends feature expansion, advanced modeling techniques (e.g., LSTM networks), and the integration of external factors such as market sentiment and macroeconomic indicators. These results contribute to the growing body of knowledge in cryptocurrency forecasting, providing insights for investors, traders, and researchers to navigate the complex cryptocurrency landscape.

Time Series Prediction of Doge Coin Prices Using LSTM Networks Kusuma, Aniek Suryanti; Wardani, Ni Wayan
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 5 No 3 (2023): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.255

This research explores the application of Long Short-Term Memory (LSTM) networks for predicting Dogecoin prices, addressing the challenges of cryptocurrency market volatility and non-linearity. A historical dataset spanning November 2017 to the present, including features such as opening and closing prices, daily highs and lows, and trading volume, was used for model development. Data preprocessing involved handling missing values, normalization, and structuring the data into a supervised learning format. The LSTM model was designed with optimized hyperparameters, trained using the Adam optimizer, and evaluated against metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Benchmarking with traditional models like ARIMA and SVR demonstrated the LSTM model's superior performance in capturing temporal dependencies and adapting to high volatility. Despite its robust performance, the study highlights limitations, including the exclusion of external factors like market sentiment and a dataset limited to specific timeframes. Future research could integrate broader datasets and advanced features to enhance model precision. This work contributes to the field of cryptocurrency forecasting, offering insights for traders, investors, and researchers navigating volatile markets.

Sistem Informasi Akademik Serta Penentuan Kelas Unggulan Dengan Algoritama K-Means di SMP Negeri 3 Ubud Kusuma, Aniek Suryanti; Aryati, Komang Sri
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 1 No 3 (2019): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

SMP Negeri 3 Ubud is educational establishments located at Silungan Lotunduh Ubud. SMP Negeri 3 Ubud has excellent class, to define the student entry into superior class using a manual system that is using Microsoft Excel. This system is inefficient because it requires a lot of time when creating. In addition to the data processing of academic, especially a student's scores are still manually so difficult when creating repot. Based on the problems it created an Academic Information System as well as the determination of class excellent using clustering method with K-Means algorithm. with the academic information system and determination superior class computerized then administrative staff easier and faster in processing student data, teacher data and employee data. The method used to determine which class superior that is Clustering K-Means algorithm. With the K-Means algorithm will process the value system and grouping students according to the value closest to the cluster center point. With this system superior class determination more quickly and efficiently

Sistem Pendukung Keputusan Pemilihan Saham BUMN dengan Model AHP Kusuma, Aniek Suryanti; Aryawan, I Made Gitra
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 1 No 4 (2019): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Investing or investing money in the hope of generating long-term profits and in the near future, can be done by investing in stocks. Stock investment in the Indonesia Stock Exchange which is one of the investments with high profit levels. The profit of stock investment is greatly influenced by the selection of the right stocks in a portfolio. However, if one chooses shares in a portfolio, there may be a loss. To avoid these losses investors usually buy liquid BUMN shares on the stock market. The problem that reappears is that not all SOE shares produce significant and sometimes stagnant profits. Analyzing the uncertainty of a stock, investors can involve the stock selection process by using a decision support system. Stock selection with SPK can produce a stock portfolio with a higher level of profit compared to the results of individual decision making. Implementation of the SPK stock selection uses two economic approaches, namely fundamental analysis and technical analysis. Fundamental analysis uses financial ratio data which has a significant influence on a company's stock development. This study uses the AHP method to accommodate the results of individual stock decision making. AHP method is used to rank the best alternative from a number of alternatives. This research produces individual stock ranking which can be used as a stock selection recommendation for investors.

Optimasi Pendistribusian Kelas Pada Dosen di STMIK STIKOM Indonesia Menggunakan Algoritma Genetika Kusuma, Aniek Suryanti; Aryati, Komang Sri
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 2 No 1 (2019): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

The stage of class scheduling starts from scheduling courses in classes, then distributing the class to lecturers. The process of distributing classes to lecturers becomes an obstacle for the STMIK STIKOM Indonesia academic body because the academic body must adjust the existing class with the lecturer who is interested in it as well as the lecturer chosen to support a class so that it does not have classes that have a time conflict. One method for solving these problems is by using genetic algorithms that work by generating a number of random solutions and then processing the collection of solutions in a genetic process. There are eight genetic algorithm procedures, which are random chromosome generation procedures, chromosome repair to validate chromosomes from their limits, fitness function to calculate the feasibility of a solution, crossover, mutation, child repair and elitism. The output of this research is in the form of an analysis and determination of the system requirements that must exist. In addition, it produces a trial report on the effect of genetic parameters to determine the effect of changes in the value of genetic parameters on the fitness value and the time used to carry out the distribution process.

Sistem Informasi Pelayanan Jasa Pencucian Mobil Dan Motor Pada Max Car Wash Berbasis Web Kusuma, Aniek Suryanti; Sadiawan, I Wayan Gede
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 2 No 4 (2020): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Service is the provision of a performance or invisible action from one side to another side. One of the companies that focus on services is Max Car Wash, Max Car Wash is a company engaged in car wash and motorcycles services located at Jalan Raya Batubulan, Sukawati, Gianyar, Bali. Issues contained among the recording transactions are still on a note and ledger, the distribution of commissions to the staff is not maximum yet. In addition, the service to customers is less satisfactory seen from the behavior of some existing customers that can’t wait for his vehicle in the wash. Based on these problems, Max Car Wash needs a service system that is expected to assist in serving the process of payment transactions and recording commission staff each workmanship. In this system is also available queue booking feature, where customers can make a booking queue first. This study has been successfully built an information system service car and motor wash. This system aims to help the company by improving customer service and provide ease in obtaining the reports desired company.

Co-Authors -, Muchsini Afrilawati, Retika Anak Agung Gde Ekayana Aristamy, I Gusti Ayu Agung Mas Aryati, Komang Sri Aryawan, I Made Gitra Ayu Gede Willdahlia Ayu Gede Willdahlia Ayu Gede Willdahlia Ayu Gede Willdahlia Ayu Gede Willdahlia Ayu Gede Willdahlia Ayu Manik Dirgayusari Batubulan, Kadek Suarjuna Bevi Libraeni, Luh Gede Desak Dwi Utami Putra Desak Dwi Utami Putra Desak Made Dwi Utami Putra Desak Made Dwi Utami Putra Desak Made Dwi Utami Putra Desak Made Dwi Utami Putra Dewi, Ni Kadek Feby Puspita Dewi, Ni Wayan Jeri Kusuma Dirgayusari, Ayu Manik Eddy Hartono Gede Surya Mahendra I Dewa Made Krishna Muku I Gede Andika I Gede Iwan Sudipa I Gede Made Yudi Antara I Gede Ratnaya I Gede Sujana Eka Putra, I Gede Sujana Eka I Gusti Agung Indrawan I Kadek Budi Sandika I Kadek Dwi Gandika Supartha I Kadek Dwi Gandika Supartha I Ketut Setiawan I Komang Juliana I Komang Sudarma I Made Candiasa I Made Sutajaya I Made Tegeh I Nyoman Agus Suarya Putra I Nyoman Jayanegara I Putu Yudiarta I Wayan Adi Saputra, I Wayan Adi I WAYAN SUDIARSA I Wayan Sukra Warpala Ika Amellia Rizanty Indra Pratistha Junantara, Argi Ketut Agustini Komang Sri Aryati Kompiang Martina Dinata Putri Kusuma Dewi, Ni Wayan Jeri M.Pd S.T. S.Pd. I Gde Wawan Sudatha . Mr Welda Muchsini - Ni Kadek Nita Noviani Pande Ni Kadek Nita Noviani Pande Ni Kadek Nita Noviani Pande Ni Kadek Nita Noviani Pande Ni Kadek Nita Noviani Pande Ni Kadek Nita Noviani Pande Ni Ketut Utami Nilawati Ni Luh Wiwik Sri Rahayu Ginantra Ni Made Mila Rosa Desmayani* Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Ni Nyoman Parwati Ni Nyoman Parwati Ni Putu Eka Swari Ni Putu Manik Ardiyanti Ni Putu Mitha Laraswati Ni Wayan Indah Juliandewi Ni Wayan Jeri Kusuma Dewi Nuarta, I Ketut Pasek Pande, Ni Kadek Nita Noviani Putra, Putu Satria Udyana Putu Gede Surya Cipta Nugraha PUTU SUGIARTAWAN Sadam Mubaraq Sadiawan, I Wayan Gede Sunarya, I Wayan Sutarwiyasa, I Ketut W, Welda Wardani, Ni Wayan Wawan Sudata Welda Welda Welda W Willdahlia, Ayu Gede Willdahlia, Ayu Gede

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