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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) INFORMAL: Informatics Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Mantik UTAMAX : Journal of Ultimate Research and Trends in Education Indonesian Journal of Data and Science JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) 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
Aniek Suryanti Kusuma, Aniek Suryanti
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 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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Implementation of Web-Based Counseling System at SMK Negeri 1 Sukawati Welda, Welda; Kusuma, Aniek Suryanti; Junantara, Argi
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 3 (2025): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.204

Abstract

State Vocational High School (SMK) Negeri 1 Sukawati, located in Gianyar Regency and renowned for its excellence in the field of visual arts, had a total of 533 students in the 2023/2024 academic year. As part of its efforts to enhance the quality of education, the school has implemented a Guidance and Counseling (BK) program aimed at helping students develop self-awareness, improve self-confidence, and behave in accordance with school regulations. One of the key components of this program is the student violation recording system. Currently, the process of recording violations is carried out manually using BK logbooks and Microsoft Excel, which is time-consuming and requires a high level of accuracy. This becomes a significant challenge considering the large number of students and the variety of infractions that need to be documented. This study aims to design and implement a web-based guidance and counseling information system to facilitate a more efficient and accurate method of recording student violations. By utilizing a web-based system, the recording process can be automated, data retrieval becomes easier, and student or parental summons can be generated automatically once certain violation thresholds are reached. The focus of this research is the development of a system that enables guidance counselors to report student violations more easily, contributing to improved student discipline. The implementation of this system is expected to enhance the efficiency of violation data management and support the school’s efforts in fostering better student discipline.
Pengenalan Coding Untuk Siswa SD Pelangi Jimbaran Dewi, Ni Wayan Jeri Kusuma; Antara, I Gede Made Yudi; Kusuma, Aniek Suryanti
Parta: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/parta.v6i1.6782

Abstract

Keterampilan pemrograman atau coding pada jenjang pendidikan dasar di Indonesia masih belum memperoleh perhatian yang memadai dan belum terintegrasi dalam kurikulum formal, berbeda dengan negara maju yang telah menerapkan pendekatan Computational Thinking sejak dini. Merespons tantangan tersebut, kegiatan Pengabdian kepada Masyarakat (PKM) ini dilaksanakan di SD Pelangi Jimbaran dengan tujuan meningkatkan literasi digital siswa melalui pelatihan bertema “Pengenalan Dampak Teknologi Informasi, Internet, dan Coding” menggunakan pendekatan berbasis aljabar dan bahasa pemrograman Python. Pelatihan diberikan kepada siswa kelas IV hingga VI dengan metode kombinatif berupa ceramah, demonstrasi, dan praktik langsung yang dirancang secara bertahap dan kontekstual. Hasil evaluasi menunjukkan peningkatan signifikan pada rata-rata pemahaman siswa, yaitu dari 43,6 menjadi 75,1 untuk materi TI, dari 45,4 menjadi 77,6 untuk pemanfaatan internet, serta dari 41,7 menjadi 76,4 untuk kemampuan dasar coding. Selain peningkatan kognitif, kegiatan ini juga mendorong kepercayaan diri, rasa ingin tahu, dan partisipasi aktif siswa dalam proses pembelajaran. Temuan ini memperkuat bukti bahwa pendekatan edukatif yang interaktif dan berbasis praktik efektif dalam membentuk pola pikir logis, kritis, dan sistematis sejak usia sekolah dasar. Oleh karena itu, kegiatan ini berkontribusi dalam menyiapkan generasi muda yang adaptif terhadap perkembangan teknologi digital dan mampu menggunakan teknologi secara bijak dan produktif.
Deep Learning for Automatic Assessment and Feedback in LMS-Based Education Kusuma, Aniek Suryanti; Ekayana, Anak Agung Gde; Dwi Utami Putra, Desak Made
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 3 (2025): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.109333

Abstract

Learning Management Systems (LMS) play a critical role in modern education by organizing content, facilitating communication, and supporting student assessment. However, most current LMS platforms depend on manual grading and generalized feedback, which can be inefficient and lack personalization. This research enhances LMS capabilities by integrating deep learning techniques—specifically Natural Language Processing (NLP)—to automate assessment and deliver personalized feedback. The system analyzes student input, such as written assignments and discussion forum posts, to evaluate performance and generate real-time, adaptive feedback. A modular framework was developed using a Bidirectional LSTM-based architecture trained on sequence data with regression objectives. The model was evaluated using the Mean Squared Error (MSE) metric. The results show that the model performs reasonably well, with predictions closely aligned to actual values in most cases, although its performance decreases slightly at the distribution extremes. Visualization via scatter plots further confirms the model's ability to capture context and structure in textual input. These findings demonstrate the model's feasibility in educational environments and its potential to reduce instructor workload while improving the quality of feedback. Future work will consider integrating attention mechanisms and multilingual capabilities for broader applicability.
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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (730.697 KB) | DOI: 10.33173/jsikti.29

Abstract

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
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 Manik Dirgayusari Batubulan, Kadek Suarjuna Bevi Libraeni, Luh Gede Desak 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 Ginantra , Ni Luh Wiwik Sri Rahayu 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 Made Candiasa I Made Sutajaya I Nyoman Agus Suarya Putra I Nyoman Jayanegara I Putu Yudiarta I Wayan Adi Saputra, I Wayan Adi I WAYAN SUDIARSA Ika Amellia Rizanty Indra Pratistha Junantara, Argi Komang Sri Aryati Kompiang Martina Dinata Putri Kusuma Dewi, Ni Wayan Jeri Mr Welda Muchsini - Ni Kadek Nita Noviani Pande Ni Ketut Utami Nilawati Ni Made Mila Rosa Desmayani* Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Ni Putu Manik Ardiyanti Ni Putu Mitha Laraswati Ni Wayan Indah Juliandewi 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 Swari, Ni Putu Eka W, Welda Wardani, Ni Wayan Welda Willdahlia, Ayu Gede Willdahlia, Ayu Gede