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All Journal E-Journal Perdagangan Industri dan Moneter Jurnal Online Mahasiswa (JOM) Bidang Kedokteran Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Management Analysis Journal al-Afkar, Journal For Islamic Studies MALIA Jurnal Pro Hukum : Jurnal Penelitian Bidang Hukum Universitas Gresik Journal of Global Business and Management Review Jurnal Studi Agama Al-Iqtishod : Jurnal Ekonomi Syariah Transekonomika : Akuntansi, Bisnis dan Keuangan An-Nur : Jurnal Studi Islam Abdi Widya: Jurnal Pengabdian Masyarakat Mutanaqishah: Journal of Islamic Banking Jurnal Inovasi Pendidikan dan Teknologi Informasi (JIPTI) jabdimasunipem IPSIKOM Jurnal Pendidikan dan ekonomi (JUPEK)
Muhammad Arif Kurniawan
Institut Ilmu Al Qur'an An Nur Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

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PESANTRENPRENEUR SEBAGAI GERAKAN PEMBANGUNAN EKONOMI MASYARAKAT LOKAL Kurniawan, Muhammad Arif; Pramadeka, Katra
Jurnal Pendidikan dan Ekonomi (JUPEK) Vol 6 No 1 (2024): Jurnal Pendidikan dan Ekonomi (JUPEK)
Publisher : Program Studi Pendidikan Ekonomi Institut Sain dan Kependidikan (ISDIK) Kie Raha Maluku Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14176881

Abstract

Pesantrenpreneur has great potential to not only strengthen the role of pesantren as an educational institution, but also as a motor for local economic development. This research aims to reveal in detail how pesantrenpreneur movement at the Islamic Boarding School (pesantren) of Lintang Songo is used as a development of pesantren economy and to find out what strategies of Pesantren Lintang Songo has in driving the existence of its pesantrenpreneurs. This research is a qualitative study with a case study approach. Data collection using observation, structured interviews and documentation, while the data analysis technique used is the Miles and Huberman model analysis. The research results indicate that Pesantren Lintang Songo has carried out various stages of pesantrenpreneurship well, including: 1) Pesantren internship stage, 2) Pesantren launch stage, 3) Pesantren take-off stage and 4) Pesantren maturity stage. Not only that, this pesantren also has four strategies to drive its existence in the wider community, including: 1) collaborating with the local community to manage agriculture and plantations, 2) recruiting assistants from students for various pesantren productions, 3) collaborating with the local government in providing assistance to improve the skills of students in pesantren entrepreneurship and 4) renting community land to be used as productive land. The impact of pesantrenpreneurs at Pesantren Lintang Songo is greatly felt by the students and the community, especially in the development of the local community economy.
ANALISIS SENTIMEN RESPON PENGGUNA CHAT GPT MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Safitri, Angelina; Firmansyah, Ilhan; Yani, Fitri; Kurniawan, Muhammad Arif; Nuryamin, Yamin
Jurnal Inovasi Pendidikan dan Teknologi Informasi (JIPTI) Vol. 6 No. 2 (2025): Jurnal Inovasi Pendidikan dan Teknologi Informasi (JIPTI)
Publisher : Information Technology Education Department

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/jipti.v6i2.3810

Abstract

This study aims to analyze user sentiment toward ChatGPT based on comments collected from the YouTube platform using the Support Vector Machine (SVM) algorithm. SVM belongs to the supervised learning algorithm group. The data were collected through web scraping using the YouTube Data API v3, resulting in 999 valid comments. The initial process included data cleaning using regular expressions to remove irrelevant characters, duplicates, and noise. Sentiment correction was then performed using a bilingual lexicon-based function (Indonesian and English) to improve classification accuracy based on language context. The initial sentiment distribution analysis showed 53.85% positive, 33.53% negative, and 12.61% neutral sentiments. To address class imbalance, a balancing process was conducted before model training. The preprocessing stage involved feature normalization and feature selection before splitting the dataset into 70% training and 30% testing data. The SVM model was trained and evaluated using performance metrics such as accuracy, precision, recall, F1-score, and AUC. The evaluation results showed an AUC of 0.90, accuracy of 81.6%, precision of 89.2%, recall of 51.6%, and F1-score of 65.4%. Based on these results, the SVM algorithm proved effective in classifying user sentiments toward ChatGPT with a high level of accuracy after the data balancing process.
ANALISIS SENTIMEN RESPON PENGGUNA CHAT GPT MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Safitri, Angelina; Firmansyah, Ilhan; Yani, Fitri; Kurniawan, Muhammad Arif; Nuryamin, Yamin
Jurnal Inovasi Pendidikan dan Teknologi Informasi (JIPTI) Vol. 6 No. 2 (2025): Jurnal Inovasi Pendidikan dan Teknologi Informasi (JIPTI)
Publisher : Information Technology Education Department

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/jipti.v6i2.3810

Abstract

This study aims to analyze user sentiment toward ChatGPT based on comments collected from the YouTube platform using the Support Vector Machine (SVM) algorithm. SVM belongs to the supervised learning algorithm group. The data were collected through web scraping using the YouTube Data API v3, resulting in 999 valid comments. The initial process included data cleaning using regular expressions to remove irrelevant characters, duplicates, and noise. Sentiment correction was then performed using a bilingual lexicon-based function (Indonesian and English) to improve classification accuracy based on language context. The initial sentiment distribution analysis showed 53.85% positive, 33.53% negative, and 12.61% neutral sentiments. To address class imbalance, a balancing process was conducted before model training. The preprocessing stage involved feature normalization and feature selection before splitting the dataset into 70% training and 30% testing data. The SVM model was trained and evaluated using performance metrics such as accuracy, precision, recall, F1-score, and AUC. The evaluation results showed an AUC of 0.90, accuracy of 81.6%, precision of 89.2%, recall of 51.6%, and F1-score of 65.4%. Based on these results, the SVM algorithm proved effective in classifying user sentiments toward ChatGPT with a high level of accuracy after the data balancing process.
PENERAPAN MODEL TRANSFORMER UNTUK DETEKSI BERITA PALSU DALAM BAHASA INDONESIA BERBASIS NATURAL LANGUAGE PROCESSING Rukmana, Andi; Kuswandi, Ferdi; Makin, Samsul; Styo Yuniarti, Angger; Kurniawan, Muhammad Arif
IPSIKOM Vol. 14 No. 2 (2026): IPSIKOM
Publisher : LPPM UNIVERSITAS INSAN PEMBANGUNAN INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/ipsikom.v14i2.474

Abstract

The rise of false information in Indonesia has turned into a pressing problem in today's digital era, primarily driven by the heavy reliance on social media as the dominant source of information. This study aims to evaluate the effectiveness of the Transformer model in detecting fake news written in Indonesian and to compare its performance with traditional methods such as LSTM and Naïve Bayes. An experimental quantitative approach was employed, utilizing a curated dataset of verified real and fake news articles. The data underwent preprocessing stages, including text cleaning, tokenization, and transformation into numerical vector formats prior to model training. The results demonstrate that the Transformer model surpasses other methods, achieving an accuracy of 92.6% and outperforming both LSTM and Naïve Bayes in all principal evaluation metrics. In addition, the Transformer model efficiently detects typical linguistic patterns found in hoax content, including exaggerated expressions, conspiracy-related terms, and repetitive sentence constructions. Validation on an external dataset further confirms the model’s ability to maintain performance stability beyond the initial training data. Despite its promising results, the implementation of this model faces several challenges, including the limited availability of Indonesian-language datasets and concerns related to data ethics and privacy. This study contributes theoretically to the advancement of Transformer-based NLP and practically supports the enhancement of digital literacy and the development of contextual and adaptive hoax detection systems in Indonesia.
SOSIALISASI DAN PELATIHAN TABULAMPOT (TANAMAN BUAH DALAM POT) YANG DILAKSANAKAN DI PERUMAHAN GREEN PANONGAN RESIDENCE TANGERANG Arfan; Agistiawati, Eva; Mariyanah, Siti; Rahmawati, Yunita; Kurniawan, Muhammad Arif; Fuadi, Aris; Wahid, Abdul
Jurnal Abdimas Universitas Insan Pembangunan Indonesia Vol. 4 No. 2 (2026): Agustus-2026
Publisher : LPPM Universitas Insan Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/jabdimasunipem.v4i2.180

Abstract

This community service (PKM) program aims to empower the residents of Green Residence Panongan, Tangerang, through the cultivation of fruit trees in pots, locally known as Tabulampot. The initiative was driven by the challenges of limited green open space and the need for improved family food security within urban housing environments. The program employed a Community-Based Development (CBD) approach and participatory andragogy methods, which included socialization, technical demonstrations, guided practice, and intensive mentoring conducted from September 2025 to February 2026. The results indicated a significant success in achieving the program's objectives. Participants' cognitive knowledge regarding urban farming increased by 68%, and 100% of the 35 participating families successfully demonstrated the technical skills required for planting. The adoption rate reached 82%, surpassing the initial target of 75%, with a plant survival rate of 89% after three months. Furthermore, the program successfully established the "Green Residence Tabulampot Community," complete with an organizational structure and a digital communication platform to ensure long-term sustainability. This initiative not only enhances environmental greening but also provides potential economic savings of approximately Rp 100,000 to Rp 300,000 per month per household and promotes a healthier lifestyle through the production of fresh, organic fruit in limited residential spaces.
STRATEGI BRANDING DAN PEMASARAN ONLINE PADA UMKM RUMAHAN RT 05/01 DESA PANONGAN, KECAMATAN PANONGAN, KABUPATEN TANGERANG, BANTEN Arfan; Agistiawati, Eva; Mariyanah, Siti; Rahmawati, Yunita; Taro, Mazdhalifah; Kurniawan, Muhammad Arif; Fuadi, Aris; Wahid, Abdul; Simorangkir, Yosua Novembrianto; Rukmana, Andi; Prabowo, Anto; Widjiyanta; Sadewo, Tatang Iman; Sasono, Ipang; Johan, Muhammad; Fajriyah, Nurul; Suseno, Bayu; Nugroho, Pratomo Djati; Kabir, Abdul; Fitri, Aminul; Purnama, Desi; Saputra, Aldo Aly; Raisayah, Zahra Atikah
Jurnal Abdimas Universitas Insan Pembangunan Indonesia Vol. 4 No. 2 (2026): Agustus-2026
Publisher : LPPM Universitas Insan Pembangunan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58217/jabdimasunipem.v4i2.183

Abstract

Micro, Small, and Medium Enterprises (UMKM) play a vital role in improving the community's economy and family well-being. However, many home-based UMKM still face challenges in product branding, digital marketing, utilizing digital platforms, and expanding market reach, including UMKM at Green Panongan Residence, RT 05/01, Panongan Village, Panongan District, most of whom still rely on conventional marketing and lack a strong brand identity. This Community Service (PKM) activity aims to improve the knowledge and skills of UMKM in implementing branding and online marketing strategies to increase business competitiveness. The methods used included observation, identifying partner needs, interactive lectures, guided practice based on artificial intelligence (AI), and ongoing mentoring on brand identity development, business social media management, and digital platform utilization. The activity was held on June 16, 2026, and was attended by 90 participants. The results showed an increased understanding of the importance of brand identity, the use of digital media for promotion, and a shift in mindset from conventional marketing to the use of digital technology. This program supports community economic empowerment and strengthens the capacity of business actors to face the challenges of the digital era.
Co-Authors Abdul Wahid Agistiawati, Eva Ahmad Fauji, Ahmad Ahmad Shofiyuddin Ichsan ARDIANSYAH ARDIANSYAH Arfan Ayuningtyas, Andini Bayu Suseno Beni setyawan Damayanti, Sekar Ayu Dewi, Anggi Pascalia Dwi Harmoyo Eko Priyojadmiko Emiliana, Eka Fajriyah, Nurul Firmansyah, Ilhan Fitri Yani Fitri, Aminul Fitriana Annisa Fuad Ahmad Riva’i Fuadi, Aris Guritno, Danur Condro Hasanah, Latifa Nur Hasna, Shofwatun Hikmah, Nuril Ida Maftukhah Isnaini, Dewi Lailatul Isyanti, Amalia Putri Jihad Lukis Panjawa Jihad Lukis Panjawa Johan, Muhammad Kabir, Abdul Khairunnas, Muhammad Kusumaningtyas, Amelia Titik Kuswandi, Ferdi Lina Lina Makin, Samsul Mariyanah, Siti Miftah Azrin Mohammad Tegar Indrayana Muhammad Ikhsanudin, Muhammad Nugroho, Pratomo Djati Nuryanti, Yulis Pamela, Queen Prabowo, Anto Pramadeka, Katra Purnama, Desi Raisayah, Zahra Atikah Rindiansyah, Dodi Rukmana, Andi Rukmana, Andy Sadewo, Tatang Iman Safitri, Angelina Saputra, Aldo Aly Sasono, Ipang Simorangkir, Yosua Novembrianto Siti Maesaroh Sri Wahyuni Asnaini, Sri Wahyuni Styo Yuniarti, Angger Sudiyono, Rachma Nadhila Sugiharti, Rr. Retno Supiana, Nana syafira aulia Taro, Mazdhalifah Ulhaq, Dhiya Widjiyanta WINANTI, WINANTI Yamin Nuryamin Yuniarti, Angger Styo Yunita Rahmawati