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ANALISIS FAKTOR PADA MEDIA SOSIAL DALAM PEMENUHAN KEBUTUHAN INFORMASI MENGGUNAKAN PENDEKATAN PRISMA Surbakti, Gideon Natanael Putra; Hartati, Besse; Susaningsih, Catur
Journal of Information System Management (JOISM) Vol. 7 No. 1 (2025): Juni
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2025v7i1.2021

Abstract

Media sosial menjadi sarana utama di kalangan masyarakat dalam mencari informasi. Efektivitas media sosial dalam memenuhi kebutuhan informasi bergantung pada beberapa faktor diantaranya kredibilitas, terpaan media, kemanfaatan, jenis konten, dan selektivitas informasi. Tujuan penelitian untuk menentukan metode dan pendekatan yang tepat dalam menganalisis faktor-faktor tersebut sehingga dapat digunakan sebagai dasar pengoptimalan pemanfaatan media sosial. Penelitian ini menggunakan metode SLR (Systematic Literature Review) dengan pendekatan  PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) yang menyaring 6446 artikel dari berbagai sumber dan menghasilkan 35 artikel yang paling relevan untuk dijadikan bahan acuan untuk melakukan penelitian dalam menganalisis pemenuhan kebutuhan informasi pada media sosial. Dari kajian ini didapatkan bahwa kredibilitas adalah faktor yang paling sering dibahas dalam literatur. Metode analisis yang paling umum digunakan adalah uji regresi linear sederhana, dan media sosial yang paling sering dijadikan sebagai objek penelitian adalah Instagram. Hasil penelitian ini dapat digunakan sebagai referensi dalam penelitian mengenai pengoptimalan pemenuhan kebutuhan informasi pada media sosial.
SINERGI POLITEKNIK IMIGRASI DAN KANTOR IMIGRASI DALAM PENGEMBANGAN KOMPETENSI PRAKTIS TARUNA MELALUI PROGRAM LATJAPURA DI KANTOR IMIGRASI KELAS I TPI MALANG Susaningsih, Catur; Hartati, Besse; Rosmaya, Mila; Prabadhi, Isidorus Anung
Jurnal Abdimas Imigrasi Vol 6 No 1 (2025): JURNAL ABDIMAS IMIGRASI
Publisher : Polteknik Imigrasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52617/jaim.v6i1.747

Abstract

Kegiatan pengabdian masyarakat ini menerapkan pendekatan Participatory Action Research (PAR) untuk meningkatkan pemahaman masyarakat tentang sistem Autogate di Kantor Imigrasi Jakarta Barat. Program kolaboratif antara akademisi, petugas imigrasi, dan masyarakat ini dirancang melalui tiga tahap utama: (1) identifikasi kebutuhan berbasis partisipasi, (2) pengembangan materi penyuluhan interaktif, dan (3) implementasi dengan pendekatan learning by doing. Metode evaluasi menggunakan kombinasi kuesioner pre-test/post-test (N=85), observasi partisipan, dan diskusi kelompok terfokus menunjukkan peningkatan signifikan dalam pemahaman teknis (47%), persepsi manfaat (52%), dan kemudahan penggunaan (43%). Temuan ini memperkuat teori Technology Acceptance Model dengan menegaskan pentingnya experiential learning dalam adopsi teknologi. Program ini juga menghasilkan modul pelatihan standar yang telah diadopsi oleh Kantor Imigrasi sebagai bagian dari kurikulum pelatihan petugas. Implikasi praktisnya mencakup rekomendasi untuk desain antarmuka yang lebih inklusif dan model kolaborasi institusi pendidikan-instansi pemerintah yang lebih terstruktur.
IMPLEMENTASI CHATBOT DALAM BERBAGAI BIDANG Daffa Hawari, Faiz; Hartati, Besse; Wilonotomo, Wilonotomo
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13745

Abstract

Transformasi digital mendorong pemanfaatan teknologi kecerdasan buatan (AI), salah satunya adalah chatbot yang digunakan dalam berbagai bidang seperti layanan informasi, bisnis, pendidikan, dan kesehatan. Penelitian ini bertujuan untuk menganalisis implementasi chatbot serta pendekatan penelitian yang digunakan. Metode PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) digunakan dalam studi literatur ini, dengan menyaring 41 artikel dari 141.719 artikel yang ditemukan melalui berbagai sumber akademik. Hasil penelitian menunjukkan bahwa chatbot paling banyak diterapkan dalam layanan informasi, diikuti oleh bisnis, pendidikan, dan kesehatan. Dari sisi metodologi, pendekatan kualitatif mendominasi dengan 17 studi, diikuti oleh kuantitatif (7 studi), rekayasa perangkat lunak (7 studi), mix method (3 studi), R&D (3 studi), eksperimen (2 studi), SLR (1 studi), dan studi kasus (1 studi). Tren penggunaan chatbot mengalami peningkatan signifikan, terutama pada tahun 2023. Kesimpulan dari penelitian ini menegaskan bahwa chatbot berperan penting dalam meningkatkan efisiensi layanan dan pengalaman pengguna, meskipun masih menghadapi tantangan dalam pemrosesan bahasa alami (NLP) dan pemahaman konteks. Pengembangan lebih lanjut diperlukan untuk meningkatkan akurasi, interaktivitas, serta integrasi chatbot dengan teknologi AI lainnya guna mendukung transformasi digital yang lebih optimal di berbagai sektor.
SERANGAN DEAUTHENTICATION ATTACK PADA WIRELESS ACCESS POINT: SYSTEMATIC LITERATUR REVIEW Saddam Ariyanto, Muhammad; Boy Hertantyo, Galuh; Hartati, Besse
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.13808

Abstract

Jaringan Wi-Fi rentan terhadap serangan siber seperti Deauthentication Attack, yang dapat memutus koneksi pengguna secara paksa dan membuka celah bagi serangan lanjutan. Penelitian ini menggunakan metode Systematic Literature Review (SLR) dengan pendekatan PRISMA untuk mengkaji metode, jenis pengujian, dan tools yang digunakan dalam evaluasi keamanan Wireless Access Point (WAP). Hasil menunjukkan bahwa Deauthentication Attack adalah serangan paling umum, dengan tools seperti Aircrack-ng dan Fluxion paling sering digunakan. Fokus utama pengujian lebih kepada pencegahan dan perlindungan jaringan dari ancaman siber
ANALISIS KEPUASAN PEMOHON TERHADAP INOVASI BERBASIS APLIKASI : SYSTEMATIC LITERATURE REVIEW Akbar, Maulana; Hartati, Besse; Ari Nursanto, Gunawan
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.14037

Abstract

Di era digital, inovasi berbasis aplikasi semakin banyak diterapkan dalam layanan publik untuk meningkatkan efektivitas, efisiensi, dan transparansi. Permasalahan utama yang menjadi fokus penelitian ini adalah sejauh mana kepuasan pemohon dapat ditingkatkan melalui layanan berbasis aplikasi, serta tantangan apa saja yang dihadapi dalam penerapannya. Tujuan dari penelitian ini adalah untuk mengidentifikasi dan menganalisis faktor-faktor utama yang mempengaruhi kepuasan pemohon terhadap layanan berbasis aplikasi, serta memberikan rekomendasi berbasis literatur untuk peningkatan kualitas layanan tersebut. Metode penelitian menggunakan pendekatan Systematic Literature Review (SLR) dengan protokol PRISMA. Data dikumpulkan dari berbagai basis data akademik seperti CrossRef, Semantic Scholar, Google Scholar, dan IEEE-Xplore, dengan total 33 artikel terpilih yang dianalisis dari rentang tahun 2020 hingga 2024.Hasil menunjukkan bahwa 70% studi menggunakan pendekatan kualitatif dan 76% layanan yang diteliti berbasis aplikasi. Faktor utama yang berpengaruh terhadap kepuasan pemohon meliputi kecepatan layanan, kemudahan akses, keandalan sistem, dan kualitas respons petugas. Rekomendasi strategis mencakup penerapan teknologi lanjutan seperti AI dan chatbot, serta pelatihan SDM dan perbaikan infrastruktur digital.
Digitalization, organizational change, and human resource management at the Immigration Polytechnic Akbar, Rasona Sunara; Abdurahman, Ayi; Nursanto, Gunawan Ari; Hartati, Besse
Annals of Human Resource Management Research Vol. 5 No. 3 (2025): September
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/ahrmr.v5i3.2838

Abstract

Purpose: This study aims to examine how digitalization influences and is influenced by organizational structures and human resource management in the Indonesian education industry. Research Methodology: This study employs a qualitative approach using semi-structured interviews and focused group discussions to explore how digital technology is implemented in human resource management within the Indonesian education sector. Participants include education leaders, HR officials, policymakers, and edutech developers, selected through purposive and snowball sampling methods to ensure relevant and in-depth insights. Data were collected through individual interviews and thematic workshops, allowing researchers to capture both personal experiences and group dynamics related to digital transformation challenges and strategies. Results: The results show that the success of digital transformation in HR management in Indonesia's education sector depends on the balance between human, technological and organizational aspects. Key challenges include a lack of training, uneven infrastructure, and an organizational culture that is not adaptive to change. Therefore, a holistic strategy is needed that includes digital competency development, visionary leadership, and policies that support technological innovation and transparency. Conclusions: Digital transformation in HRM within Indonesia's education sector is hindered by gaps in human skills, technology access, and rigid organizational structures. Weak digital leadership and ethical concerns around AI further slow progress. A holistic approach developing digital competencies, promoting innovation, and ensuring transparent AI is essential for effective and sustainable transformation. Limitations: The study’s qualitative scope limits generalizability. It also reflects a specific time frame and may include selection bias from purposive sampling. Contribution: This study offers insights into aligning HR and digital strategies using the HTO framework and promotes ethical, inclusive digital transformation in education.
The LEGAL IMPLICATION of US-CHINA TRADE WAR ON INDONESIA’S POLICY RELATING TO PALM OIL INDUSTRY Widayat, Wisnu; Hartati, Besse; Adillah, Muhammad Arief
Indonesian Law Journal Vol. 17 No. 2 (2024): Indonesian Law Journal Volume 17 No 2, 2024
Publisher : Badan Pembinaan Hukum Nasional Kementerian Hukum Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33331/ilj.v17i2.149

Abstract

Indonesia has been the largest producer and exporter of Crude Palm Oil (CPO) in the world since 2006.However, Indonesia faces complex challenges related to global CPO trade, starting from the global issue of China and the United States trade war, Including other strategic issues. The impact of the complexity of the US and China trade war is hitting Indonesia where palm oil from Indonesia is considered to be old and not environmentally friendly. This will impact market demand and disrupt the stability of national production. So an appropriate policy strategy is needed to manage this. The research objective is used as consideration for stakeholders in reviewing Indonesia's CPO policy in anticipation of the future. The research method uses a sociolegal approach. The research results show that the reasons for the decline in Indonesian CPO exports are the rejection of several European Union countries, which prevented the entry of Indonesian CPO and the influence of the China and United States trade war where soybean and sunflower oil are abundant as boycott between China and the US. Then, to fight against the European Union, Indonesia filed a lawsuit with the WTO, then certification of Palm Oil Plantations in Indonesia as part of the resistance will certainly have a positive impact on Indonesian CPO and developing biodiesel so that CPO consumption is used domestically.
FULL E-BOOK INDONESIAN LAW JOURNAL VOLUME 17 N0. 2, 2024 Muhammad, Fahrurozi; Widayat, Wisnu; Hartati, Besse; Adillah, Muhammad Arief; Sihombing, Putrida; Rangkuti, Liza Hafidzah Yusuf; Batubara, Dinda Aprilia; Syam, Farhans Mahendra; Chang, Soonpeel; Gonzales, Marcellino
Indonesian Law Journal Vol. 17 No. 2 (2024): Indonesian Law Journal Volume 17 No 2, 2024
Publisher : Badan Pembinaan Hukum Nasional Kementerian Hukum Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The 2024's second edition of Indonesian Law Journal Volume 16 has been published. The discussion topic of this edition is Legal Impact of Geopolitical Tensions on International Trade Agreements and Business and Human Rights National Strategy in relation with Business and Investment Policy. This edition presents 6 (six) articles from authors with various backgrounds. Please enjoy reading as we hope these article in our Journal are beneficial and constructive towards the development of national law.
Enhancing Public Wellbeing Through Autogate at Soekarno-Hatta International Airports Nursanto, Gunawan Ari; Prabadhi, Isidorus Anung; Hartati, Besse; Wilonotmo, Wilonotmo; Piranti, Nurul Maharani
Return : Study of Management, Economic and Bussines Vol. 3 No. 3 (2024): Return : Study of Management, Economic And Bussines
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v3i2.214

Abstract

The rapid advancement of information technology (IT), marked by innovations such as artificial intelligence (AI) is reshaping various sectors and challenging traditional frameworks, particularly towards automation. This transformation is particularly evident in public policy, as governments strive to enhance efficiency and citizen satisfaction. The adoption of information and communication technology, such as Autogate systems, emerges as a crucial strategy. In the context of immigration services, Autogate facilitates expedited immigration clearance procedures through biometric technology, enhancing security and efficiency. However, the implementation of such technologies raises concerns about public wellbeing. This research aims to assess the use and impact of Autogate technology on public wellbeing, focusing on its implementationat at Soekarno-Hatta Airport. The research methodology employed in this study involves two key approaches, interviews and observational studies. Findings reveal significant improvements in passenger experience and immigration efficiency, highlighting the potential of Autogate to enhance border management and public wellbeing. This research contributes to understanding the implications of technological advancements in immigration management and informs policymakers and stakeholders about the opportunities and challenges associated with Autogate implementation and public well being.
ALGORITMA K-MEANS DALAM IMPLEMENTASI BIDANG PEKERJAAN Akmal Khansa Al Irsyad; Priati Assiroj; Besse Hartati
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 02 (2025): Volume 10, Nomor 02 Juni 2025 publish
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i02.26772

Abstract

Rapid technological advances have affected various fields, especially in data management. The increasing volume of data generated from various sources demands efficient management and analysis methods. Data mining techniques offer a structured approach in processing, classifying, and grouping data to support decision making in various fields. This study is a systematic review of the application of data mining techniques, with a primary focus on the K-Means Clustering algorithm. This study analyzes the trend of data mining applications, especially in data classification and grouping to improve the effectiveness of decision making. Based on a systematic literature review, it was found that the K-Means Clustering algorithm is widely applied in sales analysis, market segmentation, stock optimization, and predictions in the social and health fields. In addition, other algorithms such as Decision Tree, Naïve Bayes, and K-Nearest Neighbor are also commonly used in predictive analysis and data classification. This study provides insight into the effectiveness of various data mining techniques and their future development opportunities.