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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Eksplora Informatika IJEBD (International Journal Of Entrepreneurship And Business Development) JURIKOM (Jurnal Riset Komputer) Jurnal Teknologi Informasi dan Multimedia Jurnal Praksis dan Dedikasi Sosial Indonesian Journal of Electrical Engineering and Computer Science Jurnal Manajemen dan Teknologi Informasi Jurnal Ilmiah Teknologi dan Komputer (JITTER) Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Ni Made Ika Marini Mandenni
Program Studi Teknologi Informasi, Fakultas Teknik, Universitas Udayana
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Mechanical Engineering Social Sciences Other

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Analisis dan Manajemen Risiko Keamanan Aset Teknologi Informasi Menggunakan Metode OCTAVE dan FMEA Berbasis ISO 27001:2022: Studi Kasus : Perusahaan XYZ Ajeng Wahyuningtyas; Ni Made Ika Marini Mandenni; Muhammad Alam Pasirulloh
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 2 (2025): Mei : Neptunus : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i2.796

Abstract

The advancement of information technology has driven companies to adopt technology-based systems to enhance operational efficiency while also increasing the complexity of information security risks. This study aims to analyse risk factors associated with information security assets, identify potential threats, assess risks, and provide mitigation recommendations. The OCTAVE method was applied to identify threats, vulnerabilities, and critical information technology assets, while FMEA was used to determine risk mitigation priorities based on the Risk Priority Number (RPN). The mitigation recommendations were developed in accordance with ISO 27001:2022 standards. Data collection was conducted through interviews with XYZ company representatives, identifying 34 information security asset risks, including 6 hardware failure potentials, 6 software failure potentials, 14 data failure potentials, 4 human resource failure potentials, and 4 network failure potentials. The risk categorisation results revealed 5 high-level risks, 6 moderate-level risks, 20 low-level risks, and 3 very low-level risks. The mitigation recommendations include three ISO/IEC 27001:2022 clauses: Human Resource Controls, Physical Controls, and Information Technology Controls.
Analisis Sentimen Publik Terkait Kekerasan Seksual di Indonesia dengan Algoritma Naïve Bayes dan SVM Nalista, Ni Made Naila; Mandenni, Ni Made Ika Marini; Suarjaya, I Made Agus Dwi
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8556

Abstract

Semakin meningkatnya kasus kekerasan seksual yang terjadi di Indonesia, dan media sosial merupakan ruang bagi masyarakat Indonesia untuk mengekspresikan pendapat. The increasing number of sexual violence cases in Indonesia, along with the role of social media as a space for the public to express their opinions, forms the basis for this research. The study aims to classify various types of public sentiment expressed on X (formerly Twitter) and Instagram comments by applying two algorithms for comparison: Naïve Bayes and SVM. Several processes carried out, including data collection from social media, data preprocessing, manual labeling, and the implementation of both algorithms on the processed dataset. The data sources utilized are posts written in Indonesian on X (Twitter) and Instagram, focusing on issues of sexual violence in Indonesia. The sentiment analysis results were grouped into three main categories: positive, negative, and neutral. The outcomes show that SVM achieved an accuracy of 82.17% using an 80:20 data split without applying GridSearch for optimization. The SVM results outperformed those of Naïve Bayes, which achieved an accuracy of 78.92%. This investigation leads to the conclusion that SVM is more optimal in analyzing public sentiment related to sexual violence in Indonesia compared to Naïve Bayes. The sentiment analysis results from social media regarding sexual violence in Indonesia show that the majority of sentiments are neutral, with the dataset being dominated by informative content, case reports without emotional expression, and off-topic comments
AUDIT TATA KELOLA TEKNOLOGI INFORMASI DI RSUD X MENGGUNAKAN FRAMEWORK COBIT 2019 I Komang Satria Wibawa; Anak Agung Ngurah Hary Susila; Ni Made Ika Marini Mandenni
Jurnal Manajemen dan Teknologi Informasi Vol. 15 No. 2 (2025): Jurnal Manajemen dan Teknologi Informasi
Publisher : Fakultas Teknik dan Informatika Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59819/jmti.v15i2.5425

Abstract

An IT governance audit at X Hospital was conducted due to various issues affecting service quality and system performance. Critical points included an overloaded database that resulted in suboptimal website information updates, inadequate server specifications to run the website when users were active, poorly managed network cables that made the server vulnerable to disruptions, and an under-protected IT unit in website management. The study aimed to identify critical points, elicit IT process capabilities, and provide improvement recommendations based on the COBIT 2019 Framework. The methods used included interviews, observations, business goal mapping and alignment, and a capability level questionnaire. The audit results identified five main domains, namely APO12, BAI10, DSS02, DSS03, and DSS04, all at capability level 2. Recommendations included IT risk integration, asset management, accelerated incident handling, improved service and satisfaction, and rapid adaptation to increase capabilities to levels 3, 4, and 5.
Analisis Sentimen Publik Terkait Kekerasan Seksual di Indonesia dengan Algoritma Naïve Bayes dan SVM Nalista, Ni Made Naila; Mandenni, Ni Made Ika Marini; Suarjaya, I Made Agus Dwi
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8556

Abstract

Semakin meningkatnya kasus kekerasan seksual yang terjadi di Indonesia, dan media sosial merupakan ruang bagi masyarakat Indonesia untuk mengekspresikan pendapat. The increasing number of sexual violence cases in Indonesia, along with the role of social media as a space for the public to express their opinions, forms the basis for this research. The study aims to classify various types of public sentiment expressed on X (formerly Twitter) and Instagram comments by applying two algorithms for comparison: Naïve Bayes and SVM. Several processes carried out, including data collection from social media, data preprocessing, manual labeling, and the implementation of both algorithms on the processed dataset. The data sources utilized are posts written in Indonesian on X (Twitter) and Instagram, focusing on issues of sexual violence in Indonesia. The sentiment analysis results were grouped into three main categories: positive, negative, and neutral. The outcomes show that SVM achieved an accuracy of 82.17% using an 80:20 data split without applying GridSearch for optimization. The SVM results outperformed those of Naïve Bayes, which achieved an accuracy of 78.92%. This investigation leads to the conclusion that SVM is more optimal in analyzing public sentiment related to sexual violence in Indonesia compared to Naïve Bayes. The sentiment analysis results from social media regarding sexual violence in Indonesia show that the majority of sentiments are neutral, with the dataset being dominated by informative content, case reports without emotional expression, and off-topic comments
Co-Authors A.A. Istri Alit Dwi Purnamaningrat Ajeng Wahyuningtyas Anak Agung Ketut Agung Cahyawan Wiranatha Anak Agung Kompiang Oka Sudana Anak Agung Ngurah Hary Susila Anak Agung Putu Mahendra Putra Assegaf, Achmad Jefri Ayu Widyastuti Purnamasari Ayu Wirdiani Clarissa Anindita Damayanthi, Ni Luh Putu Ari Yunia Dana, I Putu Ngurah Krisna Dwi Putra Githa Dwi Rusjayanthi, Dwi Erna Yulianti Fatmawati Fatmawati Gede Yudha Prema Pangestu Gideon Setya Budiwitjaksono Gilang Ramadhan, Rizki Aditiya Gusti Agung Ayu Putri Hafidz Amarul M I Dewa Gede Wahya Dhiyatmika I Gede Susrama Mas Diyasa I Gede Susrama Masdiyasa I Gusti Made Ngurah Ardi Yasa I Kadek Erik Priyanto I Kadek Owen Nirvana Kaskora I Ketut Adi Purnawan I ketut Gede Darma Putra I Komang Agus Ady Aryanto I Komang Satria Wibawa I Made Agus Dwi Suarjaya I Made Dharmawan Setiadi I Made Oka Mahendra Putra I Made Sukarsa I Nyoman Piarsa I Putu Agus Eka Pratama Ida Ayu Wahyu Kumara Putri Ida Bagus Gede Jayeng Gotama Ilham Ade Widya Sampurno Irianto Yohanes Sampe James Kawilarang Mohammad Rafka Mahendra A Muhammad Alam Pasirulloh Nalista, Ni Made Naila Narayana, I Putu Kevin Ari Ni Putu Intan Waindika Dharma NYOMAN DITA PAHANG PUTRA, NYOMAN Pande Made Satrya Dinata Panji Wiratama Santoso Parayana, I Putu Mega Putra Prasta, I Gede Andi Primanggara Gamaswara Putra Githa, Dwi Putra, I Putu Bayu Aditya Putu Anantha Prasetya Yogantara Putu Arismawan Jaya Kusuma Putu Arya Hening Tryasthana Putu Eka Suryadana Putu Riyaldi Putra Narendra Putu Wira Buana Rangga Laksana A Redana, Made Gede Gumiar Putra Santoso, Panji Wiratama Sasmita, Gusti Made Arya Setiawan, Ariyono setiawan, kadek dede Vira Deva, Made Marshall Widiana Putra Winarta Wiratama, I Putu Bayu Adhya Yusliza Binti Mohd Yasin