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All Journal Dinamik Semantik Techno.Com: Jurnal Teknologi Informasi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Journal of Information System Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Techne : Jurnal Ilmiah Elektroteknika Jurnal Sistem Cerdas EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Computer Science and Technology (JACOST) Journal La Multiapp Community: Jurnal Pengabdian Pada Masyarakat
Ardytha Luthfiarta
Teknik Informatika S1, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Physics Social Sciences Other

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Pendampingan bagi Siswa SMP Negeri 7 Semarang dalam Penggunaan Software Aplikasi Hidup Bersih dan Sehat Astuti, Yani Parti; Luthfiarta, Ardytha; Hidayat, Erwin Yudi; Nugraha, Adhitya; Subhiyakto, Egia Rosi; Octaviani, Dhita Aulia
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 1 (2025): JANUARI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i1.2698

Abstract

Sekolah adalah tempat menuntut ilmu dan juga tempat sosialisasi dan interaksi antar sesamA. Selain itu sekolah juga harus beradaptasi dengan lingkungan sekitar. Seperti halnya di Sekolah Menengah Pertama (SMP) Negeri 7 Semarang yang berada di Tengah kota yang dikenal oleh banyak orang khususnya warga Semarang. Di sekolah tersebut terdapat banyak fasilitas yang sesuai dengan standart di setiap sekolah. Salah satunya adalah adanya kantin sekolah yang berada dalam lingkungan sekolah. Namun demikian banyak juga yang berjualan di luar lingkungan sekolah yang setiap hari baik sebelum jam dimulai dan jam sekolah berakhir, jajanan di luar sekolah itu banyak dikunjungi siswa. Dengan kondisi seperti itu, maka perlu diwaspadai tentang Kesehatan siswa yang guru tidak mungkin mengawasi secara terus menerus. Untuk itu perlu adanya penyuluhan dan pengarahan bagi siswa agar tidak jajan sembarangan. Jajanan yang harus dibeli harus memperhatikan dari sisi gizi yang dikandungnya. Sekarang banyak jajanan yang super pedas, mengandung pengawet dan masih banyak lagi jajanan yang hanya mengejar murah dan rasa menendang. Dalam pengarahan ini, selain menghimbau untuk memperhatikan nilai gizinya, juga diperlihatkan akibat dari jajanan yang kurang sehat. Hal ini akan ditunjukkan dengan software aplikasi digital yang memberikan pengetahuan tentang akibat dari usus yang tidak sehat. Dengan begitu, siswa akan memperhatikan jajanan setiap hari. Selain jajanan, yang perlu diperhatikan lagi adalah tentang lingkungan sekitar yaitu bagaimana siswa membuang sampah, cuci tangan sebelum makan dan lain sebagainya. Karena selain Kesehatan usus, banyak juga penyakit yang disebabkan oleh kurang bersihnya lingkungan sekitar. Sehingga dengan adanya penyuluhan ini, siswa akan terdorong melakukan pola hidup bersih dan sehat yang merupakan slogan dari pemerintah khususnya pada bidang Kesehatan
Optimizing Sentiment Analysis of Working Hours Impact on Generation Z’s Mental Health Using Backpropagation Farsya, Nabila Zibriza; Luthfiarta, Ardytha; Maharani, Zahra Nabila; Ganiswari, Syuhra Putri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7827

Abstract

The topic of working hours' impact, Generation Z, and mental health are discussions that are often found on social media such as X (used to be Twitter). The sentiment analysis addressing these topics is needed to find out people’s opinions regarding these topics. It could also be helpful as a consideration for the decision-making process for related topics research. Therefore, this research aims to improve the accuracy of the model generated by the previous sentiment analysis research regarding the working hours’ impact on Gen Z’s mental health. The contribution of this research is by building a robust Backpropagation Neural Network model and utilizing SMOTETomek to achieve higher accuracy. This research compared two oversampling techniques for data balancing: SMOTE and SMOTETomek. The result shows that this research has successfully outperformed the baseline research with the best accuracy of 91% using SVM by generating the best accuracy of 93.01% with SMOTETomek. For comparison, SMOTETomek has outperformed SMOTE by generating the best accuracy of 93.01%, while the best accuracy generated with SMOTE is 92.26%. It indicates that in the case of Indonesian text sentiment analysis of this research, SMOTETomek has a better effect compared to SMOTE.
AN ENHANCED MULTI-LAYERED IMAGE ENCRYPTION SCHEME USING 2D HYPERCHAOTIC CROSS-SYSTEM AND LOGISTIC MAP WITH ROUTE TRANSPOSITION Fauzyah, Zahrah Asri Nur; Nugraha, Adhitya; Luthfiarta, Ardytha; Farandi, Muhammad Naufal Erza
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4007

Abstract

In the rapidly evolving digital era, image encryption has become a crucial technique to protect visual data from the threat of information leakage. However, the main challenge in image encryption is improving security against cryptanalysis attacks, such as brute-force and differential attacks, which can compromise the integrity of the encrypted image. Additionally, the creation of efficient and fast encryption schemes that do not degrade image quality remains a significant challenge. This research proposes a multi-layer image encryption scheme that integrates the Logistic Map algorithm, Cross 2D Hyperchaotic (C2HM) system, and Route Transposition techniques. The method aims to enhance the security of digital image encryption by combining chaotic and hyperchaotic systems. The Logistic Map is used to generate a sequence of random values with high chaotic properties, while C2HM contributes to increasing complexity and variability. The Route Transposition technique is applied to scramble pixel positions, further strengthening the encryption’s randomness. The encryption key is derived from a combination of the image hash and user key, which are then used to calculate the initial seed in the chaotic algorithm. Experiments were conducted using standard images with a resolution of 512×512 pixels. The security analysis includes evaluations of NPCR, UACI, histogram analysis, and information entropy. The experimental results show that NPCR consistently exceeds 99.5%, while UACI ranges between 33.23% and 33.56%, indicating high sensitivity to minor changes. Histogram analysis demonstrates an even intensity distribution, and the information entropy value of 7.999 reflects an exceptionally high level of randomness. Robustness tests also indicate that this method can maintain image integrity even when subjected to damage or data loss.
A TOPIC-BASED APPROACH FOR RECOMMENDING UNDERGRADUATE THESIS SUPERVISOR USING LDA WITH COSINE SIMILARITY Nisa, Laila Rahmatin; Luthfiarta, Ardytha; Nugraha, Adhitya; Hasan, Md. Mahadi; Wulandari, Kang, Andini; Huda, Alam Muhammad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4061

Abstract

The thesis is one of the critical factors in determining student graduation. While working on the thesis, students will be guided by a lecturer who has the role and responsibility to ensure that students can prepare the thesis well so that the thesis is ready to be tested and is of good quality. Therefore, selecting a supervisor with the same expertise as the thesis topic is essential in determining students' success in completing their thesis. So far, the selection of thesis supervisors at Dian Nuswantoro University still needs to be done manually by students, so the lack of information about the supervisor can hinder students in determining the supervisor. This study aims to model the topic of lecturer research publications taken from the ResearchGate and Google Scholar platforms so that it is easier for students to choose a thesis supervisor whose research topic is relevant to the student's thesis using the Latent Dirichlet Allocation method. The LDA method will mark each word in the topic in a semi-random distribution. It will calculate the probability of the topic in the dataset and the likelihood of the word against the topic for each iteration. The results of LDA modeling present six main topics of lecturer research with the highest coherence score of 0.764, and then the resulting topics and thesis titles will be compared using cosine similarity. Students can use The highest cosine value as a reference when determining the right thesis topic. Thus, the supervisor selection process will be more focused and in accordance with the student's research interests.
Classification of Key and Time Signature in Western Musical Notation by using CRNN Algorithm with Bounding Box Soeroso, Dennis Adiwinata Irwan; Winarno, Sri; Luthfiarta, Ardytha; Aryanti, Firda Ayu Dwi
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6510

Abstract

This research seeks to employ the Convolutional Recurrent Neural Network (CRNN) algorithm to develop a method for classifying key and time signatures from sheet music images. The research design involved compiling a dataset of 285 sheet music images, which includes 15 types of key signatures and 19 types of time signatures. The methodology encompasses annotation using the bounding box technique, image preprocessing, and applying the CRNN model for classification using K-Fold Cross Validation because of the limited dataset. Then, the model is evaluated using the Multi Class Confusion Matrix and performance metrics. The primary findings of this study reveal that the developed model achieves 96% accuracy in key signature classification and 95% in time signature classification when utilizing bounding boxes. Conversely, the absence of bounding boxes substantially negatively impacted the accuracy of key signature classification, resulting in only a 58% accuracy rate. Time signature classification performed even worse, with an accuracy of just 19%. This research highlights the substantial accuracy enhancements achievable by incorporating bounding boxes. Therefore, we anticipate that this research will help singers, especially those in choirs, to understand and express music better using existing technologies while enhancing the accuracy of optical music recognition using the CRNN model.
Aspect-Based Sentiment Analysis with LDA and IndoBERT Algorithm on Mental Health App: Riliv Aryanti, Firda Ayu Dwi; Luthfiarta, Ardytha; Soeroso, Dennis Adiwinata Irwan
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.8958

Abstract

Indonesia's mental health crisis in 2024 is increasing along with the high growth of internet users. Thus, high internet usage provides an opportunity for mobile applications including Riliv, a popular mental health application in Indonesia to become the most complete solution for overthinking, anxiety, and depression. This research aims to analyze the sentiment correlation of aspects based on App Store and Play Store reviews through scraping to effectively expose Riliv’s user satisfaction knowledge to developers using topic labeling with Latent Dirichlet Allocation (LDA) and sentiment labeling using Bidirectional Encoder Representations from Transformers (BERT) indobenchmark/indobert-base-p1 model on Aspect-Based Sentiment Analysis (ABSA). This study used 3068 reviews from September 2015 to December 2024. The main results obtained were 1) Identified the sentiment that positive is highest in 2020, neutral is highest in 2020, and negative is highest in 2018. 2) Identified 4 main aspects of the Riliv application: Access Support, Counseling Services, Meditation Features, and User Interface with LDA. 3) The majority distribution was negative on User Interface, neutral on Counseling Services, and positive on Meditation Features. 4) The effectiveness of IndoBERT compared to the non-transformer baseline algorithm. 5) The most optimal results were obtained with 70% training, 10% validation, and 20% testing, resulting in 95% accuracy.
Pendampingan Aplikasi OncoDoc Untuk Mendeteksi Potensi Kanker Bagi Warga Kelurahan Tegalsari Semarang Defri Kurniawan; Ardytha Luthfiarta; Abu Salam; Catur Supriyanto; Danang Wahyu Utomo; Dhita Aulia Octaviani
Community : Jurnal Pengabdian Pada Masyarakat Vol. 4 No. 1 (2024): Maret : Jurnal Pengabdian Pada Masyarakat
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/community.v4i1.497

Abstract

Penerapan Pola Hidup Bersih dan Sehat (PHBS) diperlukan bagi warga kelurahan Tegalsari, kecamatan Candisari, Semarang khususnya bagi warga RW 002. Warga RW 002 yang didominasi oleh orang tua rentan terhadap penyakit kanker, apabila tidak menerapkan PHBS pada kehidupakan sehari-hari. Kegiatan Program Kemitraan Masyarakat (PKM) diselenggarakan dengan topik pentingnya PHBS dan pengenalan aplikasi OncoDoc untuk melakukan deteksi dini terhadap resiko penyakit kanker. Metode pelaksanaan kegiatan pengabdian meliputi Analisa Kebutuhan dan Identifikasi Masalah, Menetapkan Tujuan, Menyusun Materi Pengabdian, Pendampingan Aplikasi, dan Publikasi Kegiatan. Kegiatan PKM dilaksanakan di Balai RT 003 / RW 002 yang dihadiri oleh 18 warga yang terdiri dari pengurus RW, RT dan ibu-ibu PKK. Kegiatan PKM diawali dengan sambutan oleh Ketua Kegiatan PKM dan Ketua RW 002, dilanjutkan dengan penyampaian materi, diakhiri dengan diskusi, tanya jawab, kuis serta penyerahan plakat. Kegiatan PKM memberikan manfaat berupa pengetahuan pentingnya penerapan PHBS dan memberikan manfaat teknis berupa ketrampilan bagi warga untuk dapat melakukan deteksi dini melalui aplikasi OncoDoc.
Peningkatan Kesadaran Kanker Usus pada Siswa SMP Ibu Kartini melalui Aplikasi Mobile Dewi, Ika Novita; Utomo, Danang Wahyu; Salam, Abu; Luthfiarta, Ardytha; Octaviani, Dhita Aulia; Dzaki, Azmi Abiyyu; Haresta, Alif Agsakli
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 2 (2025): MEI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i2.2987

Abstract

Kanker usus merupakan salah satu penyakit yang dapat dicegah melalui kesadaran kesehatan yang baik dan deteksi dini. Namun, kurangnya edukasi kesehatan di kalangan remaja menjadi tantangan dalam upaya pencegahan penyakit ini. Program kemitraan masyarakat (PKM) ini bertujuan untuk memberikan edukasi dan meningkatkan pemahaman siswa SMP Ibu Kartini Semarang tentang pola hidup bersih dan sehat (PHBS), faktor risiko, serta deteksi dini kanker usus. Selain itu, program ini juga memperkenalkan aplikasi mobile Oncodoc sebagai sarana untuk deteksi dini kanker secara mandiri. Kegiatan dalam program ini mencakup sesi edukasi kesehatan, demonstrasi penggunaan aplikasi mobile Oncodoc, serta evaluasi pemahaman peserta melalui diskusi dan tanya jawab. Hasil evaluasi menunjukkan bahwa setelah mengikuti program, pemahaman siswa mengenai faktor risiko kanker usus, pentingnya pola hidup sehat, dan manfaat deteksi dini meningkat secara signifikan. Siswa juga menunjukkan ketertarikan terhadap penggunaan teknologi sebagai alat bantu dalam menjaga kesehatan. Temuan dari program ini mengindikasikan bahwa edukasi berbasis teknologi dapat menjadi metode yang efektif dalam meningkatkan kesadaran kesehatan remaja. Oleh karena itu, program serupa direkomendasikan untuk diperluas ke sekolah lain dengan tambahan sesi tindak lanjut guna memastikan pemanfaatan aplikasi secara optimal dalam mendukung edukasi kesehatan
Comparative Analysis of T5 Model Performance for Indonesian Abstractive Text Summarization Bagus Dwi Satya, Mohammad Wahyu; Luthfiarta, Ardytha; Althoff, Mohammad Noval
SISTEMASI Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4884

Abstract

The rapid growth of digital content has created significant challenges in information processing, particularly in languages like Indonesian, where automatic summarization remains complex. This study evaluates the performance of different T5 (Text-to-Text Transfer Transformer) model variants in generating abstractive summaries for Indonesian texts. The research aims to identify the most effective model variant for Indonesian language summarization by comparing T5-Base, FLAN-T5 Base, and mT5-Base models. Using the INDOSUM dataset containing 19,000 Indonesian news article-summary pairs, we implemented a 5-Fold Cross-Validation approach and applied ROUGE metrics for evaluation. Results show that T5-Base achieves the highest ROUGE-1, ROUGE-2, and ROUGE-L scores of 73.52%, 64.50%, and 69.55%, respectively, followed by FLAN-T5, while mT5-Base performs the worst. However, qualitative analysis reveals various summarization errors: T5-Base exhibits redundancy and inconsistent formatting, FLAN-T5 suffers from truncation issues, and mT5 often generates factually incorrect summaries due to misinterpretation of context. Additionally, we assessed computational performance through training time, inference speed, and resource consumption. The results indicate that mT5-Base has the shortest training time and fastest inference speed but at the cost of lower summarization accuracy. Conversely, T5-Base, while achieving the highest accuracy, requires significantly longer training time and greater computational resources. These findings highlight the trade-offs between accuracy, error tendencies, and computational efficiency, providing valuable insights for developing more effective Indonesian language summarization systems and emphasizing the importance of model selection for specific language tasks.
Leveraging BERT and T5 for Comprehensive Text Summarization on Indonesian Articles Satya, Mohammad Wahyu Bagus Dwi; Luthfiarta, Ardytha
Jurnal Sistem Cerdas Vol. 8 No. 2 (2025): August
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i2.458

Abstract

One of the main challenges in the field of Natural Language Processing (NLP) is developing systems for automatic text summarization. These systems typically fall into two categories: extractive and abstractive. Extractive techniques generate summaries by selecting important sentences or phrases directly from the original text, whereas abstractive techniques focus on rephrasing or paraphrasing the content, producing summaries that resemble human-written ones. In this research, models based on Transformer architectures, including BERT and T5, were used, which have been shown to effectively summarize texts in various languages, including Indonesian. The dataset used was INDOSUM, consisting of Indonesian news articles. The best results were achieved with the T5 model, using the abstractive approach, recorded ROUGE-1, ROUGE-2, and ROUGE-L scores of 69.36%, 61.27%, and 66.17%, respectively. On the other hand, the extractive BERT model achieved ROUGE-1, ROUGE-2, and ROUGE-L scores of 70.82%, 63.99%, and 58.40%.
Co-Authors ., Junta Zeniarza ., Junta Zeniarza Abu Salam Abu Salam Adhitya Nugraha Adhitya Nugraha Adhitya Nugraha Affandy Affandy Althoff, Mohammad Noval Aris Febriyanto Aryanti, Firda Ayu Dwi Astuti, Yani Parti Bagus Dwi Satya, Mohammad Wahyu Basiron, Halizah Cahya, Leno Dwi Catur Supriyanto Catur Supriyanto Defri Kurniawan Dhita Aulia Octaviani Dzaki, Azmi Abiyyu Edi Faisal Edi Sugiarto Egia Rosi Subhiyakto, Egia Rosi Erwin Yudi Hidayat Fahreza, Muhammad Daffa Al Fahrezi, Sahrul Fahrezi Fahrezi, Sahrul Yudha Fahri Firdausillah Fairuz Dyah Esabella Farandi, Muhammad Naufal Erza Farsya, Nabila Zibriza Fauzyah, Zahrah Asri Nur Firmansyah, Gustian Angga Ganiswari, Syuhra Putri Hafiizhudin, Lutfi Azis Haresta, Alif Agsakli Harun Al Azies Hasan Shobri Heru Lestiawan Huda, Alam Muhammad Ika Novita Dewi Imam Muttaqin, Almas Najiib Indrawan, Michael Irham Ferdiansyah Katili Ivan Zuhdiansyah Julius Immanuel Theo Krisna Junta Zeniarja Krisna, Julius Immanuel Theo L. Budi Handoko Leno Dwi Cahya Maharani, Zahra Nabila Mahardika, Pramesthi Qisthia Hanum Md. Mahadi Hasan, Md. Mahadi Michael Indrawan Muhammad Daffa Al Fahreza Muhammad Jamhari Muhammad Rafid Mumtaz, Najma Amira Muttaqin, Almas Najiib Imam Nauval Dwi Primadya Nisa, Laila Rahmatin Octaviani, Dhita Aulia Primadya, Nauval Dwi Rafid, Muhammad Ramadhan Rakhmat Sani Rismiyati Rismiyati Sahrul Yudha Fahrezi Salsabila, Pramesya Mutia Satya, Mohammad Wahyu Bagus Dwi Setiawan, Dicky Soeroso, Dennis Adiwinata Irwan Sri Winarno Sri Winarno Suprayogi Suprayogi Suryaningtyas Rahayu Syarifah, Ulima Muna Utomo, Danang Wahyu Wibowo Wicaksono Wibowo Wicaksono Wulandari, Kang Andini Wulandari, Kang, Andini Zarifa, Yasmine Zuhdiansyah, Ivan