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All Journal Jurnal Akuntansi dan Pembangunan (JAKTABANGUN) E-Mabis: Jurnal Ekonomi Manajemen dan Bisnis Jurnal Informatika Ekonomi Bisnis International Journal of Educational Review, Law And Social Sciences (IJERLAS) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) J-MIND (Jurnal Manajemen Indonesia) International Review of Practical Innovation, Technology and Green Energy (IRPITAGE) Eduvest - Journal of Universal Studies AGILITY: Jurnal Lentera Manajemen Sumberdaya Manusia Jurnal Intelek Dan Cendikiawan Nusantara Jurnal Solusi Masyarakat Dikara SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Jurnal Pengabdian Kepada Masyarakat Indonesia Journal of Accounting Research, Utility Finance and Digital Assets (JARUDA)
YANITA YANITA
Faculty Of Economic And Business Universitas Malikussaleh
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Public Health Social Sciences Other

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KEAMANAN SIBER DI ERA DIGITAL: TINJAUAN PENERAPAN DATA MINING UNTUK DETEKSI ANCAMAN PADA PELAKU USAHA KECIL Faizah Amirah Harahap; Taufiq Taufiq; Yanita Yanita
SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Vol. 3 No. 3 (2026): SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, Nopember
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/suliwa.v3i3.355

Abstract

The rapid digital transformation of Indonesian MSMEs has increased exposure to cyber threats such as phishing, malware, ransomware, and DDoS. This study aims to review the application of data mining and machine learning for cyber threat detection, especially in the context of small businesses. A systematic literature review (SLR) with the PRISMA approach was used. Articles were collected from Google Scholar and Semantic Scholar (2018–2026), screened using inclusion and exclusion criteria, and analyzed descriptively. From 19 collected articles, 11 were reviewed: seven on data mining/machine learning for cyber threat detection and four on MSME cybersecurity. The results show that Random Forest, C4.5/J48, SVM/SMO, Naive Bayes, and K-Means are commonly used. Feature selection (Information Gain, PCA) and class balancing (SMOTE) improve accuracy and training efficiency, with reported accuracy generally above 90%. However, most studies use public datasets such as KDD Cup’99, AWID, CICIDS2017, and CIC-MalMem-2022, not data from MSME environments. Key challenges include class imbalance, false positives, limited resources, data quality, scalability, and low digital literacy. Non-technical factors—management commitment, governance, training, and cost—are also critical. Data mining has potential for MSME threat detection, but implementation requires lightweight, context-specific models and organizational readiness.
IMPLEMENTASI K-ANONYMITY UNTUK MENGURANGI RISIKO IDENTIFIKASI PADA DATASET DATA PRIBADI Fathimah Az Zahra; Taufiq Taufiq; Yanita Yanita
SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Vol. 3 No. 3 (2026): SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, Nopember
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/suliwa.v3i3.366

Abstract

Sharing personal data for research and analysis creates a risk of identifying individuals, because removing direct identifiers alone is not enough. This study implements k-anonymity on 16,007 records of the UCI Adult dataset using five quasi-identifiers (age, sex, race, marital status, native country), with income as the sensitive attribute. The method is full-domain generalization with record suppression (5% limit), evaluating all 180 combinations of generalization levels for k = 2, 3, 5, and 10 in Python. The results show that unique records fell from 1,352 (8.45%) to zero for all values of k, maximum re-identification risk fell to 1/k, and average risk fell from 0.1442 to 0.0341 (k = 2) and down to 0.0045 (k = 10). This protection came with a rise in total information loss from 0.0922 to 0.2471, with 4.2% to 4.7% of records suppressed and age fully hidden at k = 10. In this configuration, k = 5 was a balanced choice between privacy and utility. However, 1.51% to 12.65% of records still sit in classes that are homogeneous in income, leaving them vulnerable to homogeneity attacks, so k-anonymity should be complemented with l-diversity or t-closeness.
ANALISIS KARAKTERISTIK URL PHISHING DAN LEGITIMATE SEBAGAI INDIKATOR ANCAMAN KEAMANAN SIBER MENGGUNAKAN DATASET PUBLIK Nasywa Azzahra; Taufiq Taufiq; Yanita Yanita
SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi Vol. 3 No. 3 (2026): SULIWA: Jurnal Multidisiplin Teknik, Sains, Pendidikan dan Teknologi, Nopember
Publisher : LEMBAGA KAJIAN PEMBANGUNAN PERTANIAN DAN LINGKUNGAN (LKPPL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/suliwa.v3i3.370

Abstract

Phishing URLs can imitate legitimate services and expose users to credential theft. This study compared lexical and structural characteristics of phishing and legitimate URLs using the public PhiUSIIL dataset, which documents 100,945 phishing and 134,850 legitimate URLs. URL strings were parsed offline without visiting their destinations. Eight features were examined: URL length, hostname length, digit proportion, hyphen count, hostname dot count, IP-based hosts, HTTPS scheme, and query presence. After removing 425 duplicate records, 235,370 URLs were analyzed using medians, interquartile ranges, proportions, Mann–Whitney tests, rank-biserial effect sizes, and Holm correction. Phishing URLs showed larger digit proportion (r = 0.45), URL length (r = 0.44), hyphen count (r = 0.30), and host length (r = 0.25), whereas hostname dot count differed negligibly (r = −0.03). HTTPS appeared in 48.6% of phishing URLs versus 100% of legitimate URLs; IP-based hosts and query strings occurred only among phishing URLs. Because all legitimate URLs were HTTPS homepage addresses without paths or queries, these contrasts partly reflect how the classes were built. The features are candidate warning indicators, not deterministic rules.
COMPETENCE, WORK DISCIPLINE, AND EMPLOYEE PERFORMANCE: THE MEDIATING ROLE OF WORK MOTIVATION IN A PALM OIL PLANTATION Alya Rehana; Yanita; Husaini; Marbawi; Nur Faliza; Naufal Bachri
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 6 No. 6 (2026): December - ON PROGRESS
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.23881877

Abstract

This study examines the effects of competence and work discipline on employee performance and tests work motivation as a mediating mechanism at the Garden Unit of PT Perkebunan Nusantara IV Regional VI Cot Girek, North Aceh. A quantitative cross-sectional survey was conducted with 200 employees selected from a population of 539 using purposive sampling. Data were collected through a five-point Likert questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4. The measurement model satisfied convergent validity, discriminant validity, and internal consistency requirements. Competence had positive effects on work motivation (β = 0.467, p < 0.001) and employee performance (β = 0.286, p < 0.001). Work discipline also positively affected work motivation (β = 0.223, p = 0.001) and performance (β = 0.220, p < 0.001). Work motivation was the strongest direct predictor of performance (β = 0.480, p < 0.001). Indirect effects through work motivation were significant for competence (β = 0.224) and work discipline (β = 0.107), indicating partial mediation. The findings show that employee performance in plantation operations improves when ability and disciplined work practices are supported by stronger work motivation.
Co-Authors A Hadi Arifin A Hadi Arifin A Hadi Arifin A. Hadi Arifin Aiyub Aiyub Alviana Alviana Alya Rahmi Alya Rehana Atika Sulistia Aulia Yunita Khairani Azhar Azhar Azhar Bakhtiar Bakhtiar Cut Daramutia Wau Cut Millisa Darmawati Dwi Wulan Br Pardede Eka Sudarmawan, I Wayan EM Yusuf Iis Eva Afrida Fadhila Khairani Husna Faizah Amirah Harahap Fathimah Az Zahra Fauzan Jordi Fitri, Suraida Hendrik Pandiangan Husaini Ibrahim Qamarius Ike Helmaliya Putri Ikramuddin, Ikramuddin Khairawati Khairawati, Khairawati Khairil Anwar Liani Sabrina Likdanawati Maisyura Maisyura Marshanda Aulia Putri Masyithah Matriadi, Faisal Mohd, Heikal Mohd. Heikal Mohd. Heikal Nailah Salsabila Nasywa Azzahra Naufal Bachri, Naufal Nauval Putra Neza Lestari Putri Nur Faliza Nurfaliza Nurmala Pauzana Aulia Siagian Putri Ananda Harahap Putri Faradila Ratna Rico Nur Ilham Roiyani Sabila Zuina Saharuddin Saharuddin Salmiah Sandra Abadi Selvy Handayani Shintya Anggraini Siti Nabila Hakim Siti Nurhasanah Sullaida Sullaida Sullaida Sullaida Suraida Fitri Syukriah T. Hasinta Melani Taufiq Taufiq Taufiq Taufiq Teguh Setiawan Wibowo Wardana, Miko Andi Yurina Yurina Yusniar Yusniar Yusniar Zahratul Dahlia Zilla Syabrina Putri Zulmiardi Zurrahmi Wirda