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All Journal Jurnal Informasi dan Teknologi Community Development Journal: Jurnal Pengabdian Masyarakat Indonesia Berdaya International Journal Software Engineering and Computer Science (IJSECS) Jurnal Minfo Polgan (JMP) Jurnal Pustaka Dianmas Journal Innovations Computer Science
Octiva, Cut Susan
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Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Comparison Analysis of Service Performance Using Kruskal Wallis-Friedman Test to Minimize Waiting Time in Toll Gate System Sri Wahyuningsih, Suluh; Herli Sumerli A, Chevy; Fajri, T. Irfan; Octiva, Cut Susan; Adhicandra, Iwan
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i4.437

Abstract

The purpose of this study is to compare how well conventional, automatic, and OBU toll gates perform in terms of service. The author of this study employed two data collection techniques: primary data was gathered through interviews and field observations, and secondary data was obtained through a review of the literature. You choose which features and parameters are subject to change while the simulation is running. The system will be used to simulate how each algorithm performs in accordance with ideas and scenarios that have already been decided. Following the recording of the simulation findings, the verification step will be completed. On the basis of the outcomes of earlier data processing and analysis, the following conclusions are possible: In creating a toll gate model, two automatic toll booths spaced 60 meters apart from the toll gate were used as simulations to approximate the real thing. utilizing the Kruskal-Wallis-Friedman test computations to compare the performance of the toll gate service with six scenarios. The OBU-OBU scenario has the system's shortest waiting time, according to the computation findings. Conversely, the server utilities that are in use are traditional and traditional.
Application of Holt-Winter Exponential Smoothing Method to Design a Drug Inventory Prediction Application in Private Health Units Octiva, Cut Susan; Israkwaty; Nuryanto, Uli Wildan; Eldo, Handry; Tahir, Abdul
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i1.464

Abstract

This research aims to see how to design a drug supply prediction application using the Holt-Winter Exponential Smoothing method. The collection methods used in the research are as follows: observation, interviews. The prototyping system development method includes several important stages in designing research applications. The first stage is communication. After that, the Quick Plan stage. Construction of prototype stages. The final stage, deployment delivery and feedback, is the phase of system use by users. In addition, the team also conducts regular system maintenance to ensure optimal performance. These stages together form an iterative process for developing research applications using the prototyping method. Based on the research results, it was found that the test results for the drugs amoxicillin, cefixime, paracetamol, and CTM showed that the MAPE value was less than 10% for these four drugs, which means that the predictive value has quite high accuracy. So it can be concluded that the Holt Winter Exponential Smoothing algorithm can be well implemented to predict drug supplies.
Implementation of Rapid Application Development Method for Designing a Decision Support System to Reduce a Congestion Through Reversal Layout Engineering Octiva, Cut Susan; Ridwan, Achmad; Ramadhan, M. Irfan; Wahyu Budiarto, Balla
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i1.487

Abstract

This research aims to produce a decision support system to reduce traffic jams through U-turn layout engineering. We carried out data collection by recording traffic at the research site and conducting interviews through questionnaires submitted to the sources. System development stage, where this stage is divided into three major stages according to the method used, namely the RAD method. The three major stages are requirements planning, workshop design, and implementation. Based on the research results, it was found that the modeling of traffic passed by a U-turn can be identified through calculation graphs of volume, speed, density, capacity, degree of saturation, and geometric delay. Traffic flow engineering is implemented by modeling eight open U-turns, which are then eliminated or closed one by one in order to increase vehicle speed and reduce delays on that road section. We also carried out contraflow modeling for comparison. However, the results obtained were no better than U-turn elimination. The largest average number of motorbikes at the end of the week was only 300 motorbikes on Saturday. Meanwhile, the largest average of motorbikes on weekdays was 400 motorbikes on Thursday. The design combines two WFA methods and the fuzzy logic method to present several alternative decisions in the form of final values and bar graphs. These alternatives can be used as material for expert consideration in decision-making. A graph can serve as a benchmark when eliminating U-turns and testing contraflow on the road. Eliminating U-turns and testing contraflow on the road can provide an alternative decision solution using the largest graph.
The Application of Cobit 5.0 Framework to Measure Capability of Information and Technology Governance and Management Processes Fajri, T. Irfan; Nuryanto, Uli Wildan; Najmi, Muazziss; Suryadi, Dikky; Octiva, Cut Susan
Jurnal Informasi dan Teknologi 2024, Vol. 6, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v6i1.515

Abstract

This study examines the measurement of Information Technology governance and management capability levels using Cobit 5.0. Researchers collected data through questionnaires and interviews. Data processing from questionnaires and interviews can reveal the company's current level. In the EDM domain, the company scored very high in the process that addresses information technology risk optimization. Regular evaluation of business processes is crucial to create alignment and deal with possible risks. To move up to level two, companies must identify and understand the impact of the risks that arise. Companies should enhance their information technology services and security within the domain, perform audits, and report current and future risks. In this domain, companies must identify service capacity, predict future needs, and be ready to face sudden changes. In the DSS domain, companies need to have information system analysis experts conduct training for their staff, identify availability and service problems, and test the ability of their systems to move up to level two.
The Application of Artificial Intelligence for Anomaly Detection in Big Data Systems for Decision-Making Octiva, Cut Susan; Suryadi, Dikky; Judijanto, Loso; Laia, Mitranikasih; Irwan, Dedy
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3358

Abstract

The development of big data technology has generated huge volumes of diverse data, creating challenges in detecting anomalies that could potentially affect decision-making. This research aims to examine the application of artificial intelligence (AI) in detecting anomalies in big data systems to support faster, more accurate and effective decision-making. The approach used includes the integration of machine learning algorithms, such as classification-based detection, clustering, and deep learning, in identifying abnormal patterns in large datasets. The research method involves real-time dataset-based simulations by measuring the performance of AI models using accuracy, precision, recall, and F1-score metrics. The results show that the application of AI can significantly improve the anomaly detection capability compared to conventional methods, with an average accuracy of 92%.
Introduction to Cybersecurity for Teachers and Students in Indonesia in the Digital Era (Pengenalan Keamanan Siber bagi Guru dan Siswa di Indonesia di Era Digital) Octiva, Cut Susan; Rahayu, Novi; Laia, Mitranikasih; Suryadi, Dikky; Hakim, Muhammad Lukman
Indonesia Berdaya Vol 6, No 1 (2025)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.20251004

Abstract

This Community Service (PKM) activity aims to increase cybersecurity literacy among teachers and students as part of efforts to support digital transformation in education. The training was conducted online with an interactive approach, involving 50 participants from various schools in Indonesia. The material includes an introduction to cyber threats, mitigation strategies, and daily digital security practices. The evaluation was done through pre-test and post-test, accompanied by a participant satisfaction questionnaire. The results showed a significant improvement in participants' understanding, with an average score increase of 73%. The level of satisfaction of participants with the training reached the "excellent" category with an average score of 4.75 on a scale of 5. These findings reflect the effectiveness of the designed training methods. However, the limitations of digital infrastructure are the main challenge in implementing activities. This Activity has contributed positively to building cybersecurity awareness and literacy in the education sector. In addition to providing direct benefits to participants, this program is expected to be a model for similar training that supports the sustainable strengthening of digital literacy in Indonesia.Abstrak. Kegiatan Pengabdian Kepada Masyarakat (PKM) ini bertujuan untuk meningkatkan literasi keamanan siber di kalangan guru dan siswa sebagai bagian dari upaya mendukung transformasi digital dalam pendidikan. Pelatihan dilakukan secara daring dengan pendekatan interaktif, melibatkan 50 peserta dari berbagai sekolah di Indonesia. Materi yang diberikan meliputi pengenalan ancaman siber, strategi mitigasi, dan praktik keamanan digital sehari-hari. Evaluasi dilakukan melalui pre-test dan post-test, disertai dengan kuesioner kepuasan peserta. Hasil penelitian menunjukkan adanya peningkatan pemahaman peserta yang signifikan, dengan peningkatan skor rata-rata sebesar 73%. Tingkat kepuasan peserta terhadap pelatihan mencapai kategori “sangat baik” dengan skor rata-rata 4,75 dari skala 5. Temuan ini mencerminkan efektivitas metode pelatihan yang dirancang. Namun, keterbatasan infrastruktur digital menjadi tantangan utama dalam pelaksanaan kegiatan. Kegiatan ini telah memberikan kontribusi positif dalam membangun kesadaran dan literasi keamanan siber di sektor pendidikan. Selain memberikan manfaat langsung kepada peserta, program ini diharapkan dapat menjadi model pelatihan serupa yang mendukung penguatan literasi digital di Indonesia secara berkelanjutan.
Edukasi dan Pelatihan Penggunaan Teknologi Augmented Reality (AR) dalam Pembelajaran Interaktif di Sekolah Dasar Octiva, Cut Susan; Wahyuningsih, Suluh Sri; Suryadi, Dikky; Rahayu, Novi; Irwan, Dedy
Jurnal Pustaka Dianmas Vol 5, No 1 (2025)
Publisher : Universitas Prof. Dr. Moestopo (Beragama)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32509/dianmas.v5i1.5571

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan edukasi dan pelatihan kepada guru-guru Sekolah Dasar mengenai pemanfaatan teknologi Augmented Reality (AR) dalam pembelajaran interaktif. Di era digital saat ini, teknologi AR memiliki potensi besar untuk meningkatkan efektivitas dan daya tarik proses belajar-mengajar, khususnya dalam menyampaikan materi yang bersifat abstrak dan kompleks. Sasaran kegiatan adalah para pendidik di tingkat Sekolah Dasar yang belum familiar atau belum memanfaatkan AR dalam kegiatan belajar-mengajar mereka. Metode pelaksanaan kegiatan meliputi penyampaian materi melalui seminar, demonstrasi langsung penggunaan aplikasi AR, serta praktik langsung pembuatan media pembelajaran berbasis AR menggunakan perangkat mobile dan platform gratis yang mudah diakses. Kegiatan dilaksanakan di SDN 0100462, dengan partisipasi aktif dari guru kelas dan guru mata pelajaran. Hasil dari kegiatan menunjukkan bahwa para peserta mengalami peningkatan pemahaman dan keterampilan dalam mengintegrasikan AR ke dalam pembelajaran. Evaluasi melalui pre-test dan post-test serta kuesioner kepuasan peserta menunjukkan adanya peningkatan signifikan dalam pengetahuan dan minat terhadap implementasi teknologi AR di kelas. Diharapkan kegiatan ini dapat menjadi langkah awal dalam transformasi digital pembelajaran di Sekolah Dasar dan memicu inovasi berkelanjutan dalam metode pengajaran.
Implementasi Teknologi Informasi pada UMKM: Tantangan dan Peluang Octiva, Cut Susan; Haes, Putri Ekaresty; Fajri, T. Irfan; Eldo, Handry; Hakim, Muhammad Lukman
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13823

Abstract

Penelitian ini bertujuan untuk mengkaji implementasi teknologi informasi pada Usaha Mikro, Kecil, dan Menengah (UMKM), dengan fokus pada tantangan dan peluang yang dihadapi dalam proses tersebut. Teknologi informasi (TI) memainkan peran penting dalam meningkatkan efisiensi operasional, daya saing, dan kapasitas inovasi UMKM. Namun, adopsi TI di kalangan UMKM masih menghadapi berbagai hambatan, seperti keterbatasan sumber daya finansial, kurangnya pengetahuan dan keterampilan teknologi, serta resistensi terhadap perubahan. Melalui pendekatan kualitatif, penelitian ini mengumpulkan data dari wawancara mendalam dengan pemilik dan manajer UMKM di berbagai sektor industri. Hasil penelitian menunjukkan bahwa meskipun ada tantangan yang signifikan, UMKM yang berhasil mengintegrasikan TI dalam operasional mereka mengalami peningkatan produktivitas, akses pasar yang lebih luas, dan kemampuan untuk menawarkan produk dan layanan yang lebih inovatif. Selain itu, ditemukan bahwa dukungan eksternal, seperti pelatihan dan subsidi pemerintah, serta kerjasama dengan penyedia teknologi, sangat membantu dalam mengatasi hambatan implementasi TI.
Penggunaan Teknik Data Mining untuk Analisis Perilaku Pengguna pada Media Sosial Octiva, Cut Susan; Fajri, T. Irfan; Sulistiarini, Emma Budi; Suharjo, Suharjo; Nuryanto, Uli Wildan
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13936

Abstract

Metode data mining digunakan dalam penelitian ini untuk menganalisis perilaku pengguna media sosial. Media sosial, yang menghasilkan volume data yang besar dan beragam, telah menjadi platform utama bagi individu untuk berinteraksi dan berbagi informasi. Penelitian ini berfokus pada mengekstraksi pola-pola tersembunyi dan memahami perilaku pengguna yang kompleks dengan menggunakan teknik data mining. Data dikumpulkan dari platform media sosial, diproses sebelum menggunakannya, dan digunakan algoritma pemrosesan data seperti clustering, association rule mining, dan analisis sentimen. Hasil penelitian menunjukkan bahwa metode data mining dapat mendeteksi pola perilaku pengguna yang berbeda, seperti preferensi konten, pola interaksi sosial, dan kecenderungan temporal. Mining aturan asosiasi menemukan hubungan antaraktivitas pengguna, sedangkan clustering mengelompokkan pengguna berdasarkan kesamaan perilaku. Analisis sentimen memberikan pemahaman tentang bagaimana pengguna melihat dan merasakan sesuatu. Hasil ini dapat digunakan untuk berbagai aplikasi praktis, seperti strategi pemasaran yang lebih efektif, peningkatan fitur platform, dan pengalaman pengguna yang lebih baik. Penelitian ini menunjukkan bahwa teknik data mining adalah cara yang efektif untuk menganalisis perilaku pengguna di media sosial. Dengan mengetahui lebih banyak tentang perilaku pengguna, penyedia layanan dapat mengoptimalkan strategi mereka untuk memenuhi kebutuhan dan preferensi pengguna dengan lebih baik. Penelitian lebih lanjut disarankan untuk mengeksplorasi metode data mining lainnya dan menerapkannya pada dataset yang lebih luas.
Algoritma Naïve Bayes untuk Mengidentifikasi Hoaks di Media Sosial Haq, Muhamad Ziaul; Octiva, Cut Susan; Ayuliana, Ayuliana; Nuryanto, Uli Wildan; Suryadi, Dikky
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13937

Abstract

Hoaks yang menyebar di dunia maya terus bertambah, oleh sebab itu penelitian ini akan membuat dan memeriksa fungsionalitas dari algoritma Naïve Bayes dalam mendeteksi serta mengenali hoaks pada jejaring sosial. Algoritma yang diambil adalah Naïve Bayes karena dapat memproses data teks yang large-scale dengan kompleksitas tersendiri dan pengimplementasiannya yang mudah. Dataset yang digunakan untuk penelitian ini terdiri dari postingan media sosial yang dikategorikan sebagai hoaks atau bukan hoaks. Pra-pemrosesan data mencakup tokenisasi, ekstraksi fitur, dan pembersihan teks menggunakan teknik TF-IDF (Term Frequency-Inverse Document Frequency). Selanjutnya, algoritma Naïve Bayes dilatih dan diuji menggunakan cross-validation untuk memastikan bahwa model itu akurat dan dapat digunakan di mana saja. Hasil penelitian menunjukkan bahwa algoritma Naïve Bayes dapat mengidentifikasi hoaks dengan tingkat kesalahan yang sangat rendah. Penelitian ini menunjukkan bahwa algoritma Naive Bayes efektif dalam mendeteksi konten hoaks di media sosial, seperti yang ditunjukkan oleh evaluasi model menggunakan metrik seperti ketepatan, recall, dan skor F1. Penelitian ini juga menemukan bahwa algoritma ini dapat diintegrasikan dalam sistem pemantauan media sosial untuk meningkatkan kualitas informasi yang beredar.
Co-Authors Abdul Tahir Achmad Ridwan, Achmad Ayuliana Ayuliana Churniawati, Ninik Eldo, Handry Emma Budi Sulistiarini Haq, Muhamad Ziaul Hasma, Nur Amalia Herli Sumerli A, Chevy IRWAN, DEDY Israkwaty Iwan Adhicandra Judijanto, Loso Mitranikasih Laia Muhammad Agus Muljanto Muhammad Lukman Hakim, Muhammad Lukman Mutasar Najmi, Muazziss Ningsih, Liasulistia Primulyanto, Brevmana Anugrah Putri Ekaresty Haes Rahayu, Novi Ramadhan, M. Irfan Rastiti, Liza Sri Wahyuningsih, Suluh Suharjo Suharjo Suryadi, Dikky Uli Wildan Nuryanto Wahidin Wahidin Wahyu Budiarto, Balla Wahyuningsih, Suluh Sri