Article Per Year (5 Year)
p-Index From 2021 - 2026
0.751
P-Index
This Author published in this journals
All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Sistem Komputer dan Informatika (JSON)
Muhammad Irfan Sarif
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Model EPAM-2025 Untuk Analisis Keselarasan Opini Publik dan Kebijakan Literasi Digital Wiyono, Tri; Muhammad Irfan Sarif; Andika Dwi Aryo H; Ahmad Syaukani; Muhammad Zikri Ramadhan
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9367

Abstract

Transformasi digital yang berlangsung cepat menuntut peningkatan literasi digital yang lebih komprehensif. Namun, berbagai indikator nasional menunjukkan penurunan pada aspek etika digital, keamanan siber, dan kemampuan berpikir kritis. Penelitian ini bertujuan menganalisis kesenjangan antara opini publik dan kebijakan literasi digital nasional melalui pendekatan komputasional berbasis Natural Language Processing (NLP). Untuk tujuan tersebut, dikembangkan model hibrida orisinal EPAM-2025 (Entity–Policy Alignment Model) sebagai kerangka pengukuran keselarasan kebijakan. Dataset penelitian terdiri atas 2.165 tweet berbahasa Indonesia yang diperoleh secara etis melalui API platform X (Twitter). Prosedur analisis mencakup pembersihan data, tokenisasi, ekstraksi entitas menggunakan Named Entity Recognition (NER), analisis sentimen, serta pengukuran kesamaan semantik berbasis TF-IDF cosine similarity. Skor keselarasan dihitung menggunakan formula Sa = αSm + βSs(norm). Hasil penelitian menunjukkan dominasi opini netral (92,24%) serta tingkat kesamaan semantik yang sangat rendah (<0,1), menandakan bahwa terminologi kebijakan digital seperti digital safety dan digital ethics belum terinternalisasi dalam wacana publik. Model EPAM-2025 juga menunjukkan performa evaluatif yang stabil dengan klasifikasi tepat pada dua kategori aktif (“Tidak Selaras” dan “Perlu Analisis Lanjut”). Penelitian ini memberikan kontribusi metodologis melalui pengembangan pendekatan kuantitatif yang objektif untuk mengukur keselarasan opini publik terhadap kebijakan, serta membuka peluang pemanfaatan analitik opini publik dalam mendukung perumusan kebijakan nasional berbasis bukti.
Optimalisasi Digital Workplace Berbasis Sistem Informasi Terhadap Kinerja PegawaiPada Sistem Work From Home Ahmad Syaukani; Muhammad Irfan Sarif
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 2 (2026): April 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i2.6170

Abstract

This study aims to analyze the effect of a digital workplace based on information systems on employees’ administrative and documentation performance in supporting bureaucratic digital transformation. The research employs a qualitative approach through literature review and case studies. Three cases are examined, namely road damage management in North Maluku, the implementation of the SI MANTAP Sumut application with the Maker–Checker–Signer mechanism, and the use of SIMPEG e-Kinerja in Bogor City. The results indicate that a digital workplace based on information systems has a significant impact on improving employee performance, particularly in terms of administrative efficiency, data accuracy, documentation quality, as well as transparency and accountability. The North Maluku case shows improved reporting speed and responsiveness. SI MANTAP Sumut enhances data validity through internal control mechanisms, while SIMPEG e-Kinerja in Bogor City supports more objective, data-driven performance evaluation. However, challenges remain, including limited technological infrastructure, varying levels of digital competence among employees, and suboptimal system utilization. Therefore, strengthening system integration, improving human resource capacity, and developing more adaptive and integrated systems are necessary.
ANALISIS KOMPARATIF ALGORITMA K-MEANS DAN K-MEDOIDS DALAM CLUSTERING RASIO DISTRIBUSI ALOKON TERHADAP PUS  DI PROVINSI SUMATERA UTARA TAHUN 2025 Panggabean Siahaan; Muhammad Irfan Sarif; Siti Qomariyah; Satria Sinurat; Norita Tampubolon
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 2 (2026): April 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i2.6173

Abstract

Unequal distribution of contraceptive supplies (Alokon) relative to the target population remains a persistent challenge in family planning programs, particularly in regions with high demographic heterogeneity. Evaluation based on absolute distribution values generates proportional bias, as larger-population areas automatically receive higher volumes without accounting for the proportional needs of the Reproductive Age Couples (PUS) population. This study proposes a ratio-based approach — dividing total Alokon distributed by the number of  PUS — as the primary clustering variable to enable proportional comparison and reduce population-scale bias across 33 districts and cities in North Sumatra Province. Two algorithms, K-Means and K-Medoids based on Partitioning Around Medoids (PAM), were comparatively evaluated using Silhouette Score as the evaluation metric. The optimal number of clusters (K = 3) was determined through a combination of the Elbow Method — which identified a 75.12% WCSS reduction from K = 2 to K = 3 — and Silhouette Score validation. Results show that both algorithms produced identical cluster compositions: 16 districts in the low-distribution group (48.5%; = 0.1687), 13 districts in the moderate group (39.4%; = 0.3117), and 4 districts in the high group (12.1%; = 0.6077), with equal average Silhouette Scores of = 0.6998 (reasonable structure). Densely populated areas such as Medan City and Deli Serdang — despite receiving the highest absolute distribution volumes — were classified in the low group when measured proportionally, demonstrating the superiority of the ratio-based approach. To the best of the authors' knowledge, this study is the first to apply comparative clustering on Alokon distribution using a proportional ratio framework in North Sumatra Province, providing empirical evidence on algorithm performance in normalized health service distribution data. 
ANALISIS SENTIMEN MASYARAKAT TERHADAP KEBIJAKAN PEMBERANTASAN JUDI ONLINE DI INDONESIA MENGGUNAKAN NATURAL LANGUAGE PROCESSING PADA MEDIA SOSIAL Irwansyah Putera Sitorus; Muhammad Irfan Sarif; Nurlina Sari Harahap
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 2 (2026): April 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i2.6175

Abstract

The rapid growth of online gambling in Indonesia has become a serious social problem, prompting the government to implement various eradication policies. This study aims to analyze public sentiment toward Indonesia's online gambling eradication policy using Natural Language Processing (NLP) techniques on social media data collected from YouTube. A total of 237 comments were gathered and processed through preprocessing stages including cleaning, normalization, stopword removal, and stemming using the Sastrawi library. Sentiment labeling was performed using a weighted lexicon-based approach with 600+ sentiment words. Classification was conducted using three models—Random Forest, Linear SVM, and Logistic Regression—with SMOTE applied for class balancing and 5-fold cross-validation for robustness evaluation. The best model, Linear SVM, achieved an accuracy of 97.92% and a CV score of 97.56%. Results showed that 57.4% of public sentiment was neutral, 28.3% positive, and 14.3% negative, indicating that the majority of the public responds to this issue informationally. This study demonstrates that NLP-based sentiment analysis is an effective tool for evaluating public perception of digital policy in Indonesia.
Co-Authors Ahmad Syaukani Andika Dwi Aryo H Irwansyah Putera Sitorus Muhammad Zikri Ramadhan Norita Tampubolon Nurlina Sari Harahap Panggabean Siahaan Satria Sinurat Siti Qomariyah Wiyono, Tri