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The study on Malaysia Agricultural E-Commerce (AE): Customer Purchase Intention Kai Wah Hen; Choon Sen Seah; Deden Witarsyah; Shazlyn Milleana Shaharudin; Yin Xia Loh
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1372

Abstract

Electronic commerce (E-Commerce) became an essential trading platform after the Covid-19 pandemic. From essential products to luxury brands, consumers can find almost everything on the normal E-Commerce platforms with the exception of fresh agricultural products. Agricultural E-Commerce (AE) is introduced to overcome the market needs. Technology Acceptance Model (TAM) is studied and integrated with additional variables to determine the needs of AE in Malaysia. In this study, five variables (product quality, logistic service quality, perceived price & value, platform design quality, and platform security) were studied to determine the Malaysian consumers’ purchase intention towards the AE. Five hypotheses were developed to identify the relationship between the variables. A total of 300 AE users have contributed their perception as respondents in this study through a survey questionnaire. The collected data were processed before the data analysis via Statistical Package for The Social Science (SPSS) version 25.0. Descriptive analysis, and inferential analysis were conducted. The result shows that all five variables are significantly related to the purchase intention towards AE. The product quality has the highest significant value (0.805) towards the purchase intention on AE, followed by logistic service quality, platform security, platform design quality and perceived price and value. Implication, limitation, and recommendation were also being discussed to assist the AE stakeholders in improving their AE.
Implementasi Metode Asosiasi Untuk Analisis Penempatan Produk Retail Ruth Sesilya Ambarita; Deden Witarsyah; Faqih Hamami
eProceedings of Engineering Vol 10, No 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Counseling on Cooperative Management as a Driving Force for Economic Empowerment at the Sukamiskin Islamic Boarding School Bandung Kartawinata, Budi Rustandi; Akbar, Aldi; Hidayat, Agus Maolana; Witarsyah, Deden; Hamami, Faqih; Pratiwi, Oktaria Nurul; Ahmad, Mokhtarrudin; Zahid, Azham; Sujak, Aznul Fazrin bin Abu; Razali, Raja Razana Raja; Mangsor, Miza
Journal of Community Service and Society Empowerment Том 2 № 02 (2024): Journal of Community Service and Society Empowerment
Publisher : PT. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jcsse.v2i02.708

Abstract

This Community Service aims to provide understanding to cooperative administrators and students at the Sukamiskin Islamic Boarding School regarding the benefits and effective management strategies of cooperatives. The method used in this research is interviews and direct observation of cooperative administrators and students involved in cooperative activities. The research results show that counseling about cooperative management is very important to increase the understanding and skills of cooperative administrators and students in managing cooperatives. In this outreach, information and training is provided regarding the basic principles of cooperative management, financial planning, risk management and marketing of cooperative products. With this outreach, it is hoped that cooperative management at the Sukamiskin Islamic Boarding School can become more effective and have a positive impact on community economic empowerment. Cooperative administrators and students will become more competent in managing cooperatives, so that they can generate better income for their members. Counseling on cooperative management as a driving force for economic empowerment at the Sukamiskin Islamic Boarding School, Bandung City is very important to increase the understanding and skills of cooperative administrators and students in managing cooperatives. It is hoped that this counseling can provide significant benefits in increasing the income and welfare of cooperative members.
Ransomware attack awareness: analyzing college student awareness for effective defense Syamsuar, Dedy; Pakdeetrakulwong, Udsanee; Jacob, Deden Witarsyah; Chandra, Felixius Arelta
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1122-1130

Abstract

There are growing concerns about security as the usage of computers in academic settings continues to increase. This research aims to investigate the level of awareness among university students regarding security threats associated with ransomware. This study examines students' behaviour and preventive motivation for ransomware attacks, along with the measures taken to mitigate these security threats. The study model combines the theory of planned behaviour (TPB) and preventive motivation theory (PMT) with additional threat awareness (TA) variables. The research findings indicate a high level of awareness regarding the dangers. TA has a positive influence on other factors, as indicated by the significant t-values (perceived severity (PS)=4.479, perceived vulnerability (PV)=3.251, response efficacy (RE)=14.344, and self-efficacy (SE)=8.034). This research also demonstrates that subjective norm (SN) and affective responses (AR) have a key impact on behavioural intention (BI). Moreover, two of the preventive motivation factors, PS and PV, significantly contribute to BI, while the other two (RE and SE) did not show a significant contribution to BI.
Systematic Literature Review on Augmented Reality with Persuasive System Design: Application and Design in Education and Learning Nasirudin, Mohd Asrul; Md Fudzee, Mohd Farhan; Senan, Norhalina; Che Dalim, Che Samihah; Witarsyah, Deden; Erianda, Aldo
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2702

Abstract

Augmented Reality (AR) is an innovative technology that has gained significant scholarly attention. It uses computer-generated sensory inputs like visuals, sounds, and touch to enhance how we perceive the real world, providing a transformative impact on human sensory experiences. Motivated by the possibilities of augmented reality (AR) in the realm of the educational learning environment, this research aims to document the evolving landscape of augmented reality (AR) applications in education and training, with a specific emphasis on the incorporation of persuasive system design (PSD) elements. The study also explores the diverse technologies and methodologies for developing these applications. A systematic literature review was conducted, analyzing 44 articles following the protocol for PRISMA assessments. Four research questions were formulated to investigate trends in AR applications. Between 2016 and 2023, publications on AR applications doubled, with a significant focus on the educational field. Marker-based AR methods dominated (68.49%), while markerless methods constituted 31.51%. Unity and Vuforia were the most used platforms, accounting for 77.27% of applications. Most research papers assessed application effectiveness subjectively through custom-made questionnaires. University students were identified as the primary target users of AR applications. Only a few applications integrated persuasive elements, even for adult users. This highlights the need for further studies to fully grasp the possibilities of combining persuasive system design with augmented reality applications in education
Analisis Sentimen dan Pemodelan Topik terhadap Aplikasi Pembelajaran Online pada Platform Google Play Kamil, Andhika Ihsan; Pratiwi, Oktariani Nurul; Witarsyah, Deden
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6023

Abstract

Kita hidup di era teknologi di mana setiap aspek kehidupan terhubung dengan teknologi. Maraknya aplikasi belajar daring di Indonesia, seperti Ruangguru, menandai perkembangan di bidang pendidikan. Aplikasi Ruangguru fokus pada jasa pendidikan dan telah melayani lebih dari 22 juta pengguna. Untuk mempertahankan kepuasan pelanggan, diperlukan analisis sentimen dan pemodelan topik terhadap ulasan pengguna. Penelitian ini menggunakan 31.070 dataset ulasan pengguna di Google Play, dilanjutkan dengan pelabelan dan preprocessing sebelum data akan digunakan. Analisis sentimen memakai algoritma Support Vector Machine menunjukkan hasil yang baik dengan akurasi 88,89%, presisi 87,11%, recall 91,22%, dan F1-score 89,11%. Teknik k-10 fold cross validation menghasilkan akurasi rata-rata 89,06%. Kemudian model digunakan pada 10.000 ulasan baru, dengan hasil mayoritas ulasan memiliki sentimen positif. Pemodelan topik dengan Latent Dirichlet Allocation mengidentifikasi 5 topik utama pada sentimen positif dengan nilai koherensi 0,4779, berfokus pada pengalaman positif dan kegunaan aplikasi dalam membantu belajar. Pada sentimen negatif, ditemukan 4 topik utama dengan nilai koherensi 0,4899, yang banyak mengungkapkan keluhan tentang materi pembelajaran yang kurang lengkap.
Causal Inference in Observational Studies: Assessing the Impact of Lifestyle Factors on Diabetes Risk Witarsyah, Deden; Almohab, Hadi; A A Abushammala, Haneen
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.1295

Abstract

The global prevalence of type 2 diabetes has escalated in recent decades, prompting an urgent need for effective prevention strategies. Physical activity has emerged as a significant modifiable risk factor for mitigating diabetes risk, yet the precise causal relationship remains a subject of debate, particularly in observational studies. This research leverages advanced causal inference methods to rigorously estimate the effect of physical activity on the risk of developing type 2 diabetes. By employing Propensity Score Matching (PSM), we address confounding biases inherent in observational data, ensuring more reliable estimates of treatment effects. Additionally, we integrate machine learning techniques, including causal forests, to explore heterogeneous treatment effects (HTEs) across different population subgroups. Our findings highlight that the benefits of physical activity in reducing diabetes risk are not uniform but are more pronounced among individuals with higher body mass index (BMI), further underlining the necessity of tailored interventions. The application of advanced causal inference models allows us to account for confounders such as diet, socioeconomic status, and pre-existing health conditions, offering a more comprehensive understanding of the relationship between physical activity and diabetes prevention. This study contributes to the growing literature by demonstrating that physical activity significantly reduces diabetes risk, with particular benefits for high-risk subgroups. Our findings provide evidence for public health policies that emphasize physical activity as a cornerstone of diabetes prevention, promoting individualized approaches to intervention.
Analisis Sentimen Opini Publik Terhadap Fenomena Childfree Menggunakan Algoritma Naïve Bayes Pada Media Sosial Twitter Haniyah , Salma; Witarsyah, Deden; Sutoyo , Edi
eProceedings of Engineering Vol. 11 No. 4 (2024): Agustus 2024
Publisher : eProceedings of Engineering

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Abstract

Abstrak - perkembangan media sosial, terutama twitter, sebagai sarana komunikasi dan penyaluran pendapat semakinpesat. Gerakan childfree, yakni keputusan individu untuktidak memiliki anak, telah menjadi topik yang ramaidibicarakan di media sosial. Hal ini mencerminkan perubahanpandangan masyarakat terhadap kehidupan keluarga danmemiliki dampak signifikan pada dinamika sosial dankebijakan publik. Penelitian ini bertujuan untuk menganalisissentimen pengguna twitter terhadap gerakan childfreemenggunakan algoritma naïve bayes. Penelitian ini akanmengidentifikasi dan memahami pandangan masyarakatmengenai childfree berdasarkan cuitan-cuitan di twitter.Penelitian ini menggunakan metode analisis sentimen denganmemanfaatkan media sosial twitter. Data diambil melaluiproses crawling pada periode 19 desember 2022 hingga 16januari 2023. Data yang diperoleh diolah menggunakan teknikterm frequency-inverse document frequency (tf-idf) untukmenghasilkan 974 data yang siap untuk dianalisis. Algoritmanaïve bayes digunakan untuk klasifikasi sentimen, denganvariasi data training dan data testing pada simulasi 60:40,70:30, 80:20, dan 90:10. Mayoritas sentimen yang munculadalah positif (mendukung childfree) dengan persentasetertinggi pada simulasi 4 (90:10) mencapai 90,72%. Sentimenpositif ini mencerminkan dukungan terhadap kebebasanindividu, pertimbangan finansial, kesejahteraan mental, sertapengakuan terhadap peran keluarga dalam keputusanchildfree. Hasil penelitian ini dapat memberikan pemahamanlebih lanjut tentang faktor-faktor yang mempengaruhikeputusan childfree, serta dampaknya dalam berbagaikonteks, termasuk hubungan individu, kebijakan publik, dandinamika sosial. Kata kunci— analisis sentimen, childfree, rapidminer, naïve bayes, text processing.
Analisis Sentimen Pada Komentar Youtube Untuk Mengetahui Pandangan Masyarakat Kepada Calon Presiden Indonesia 2024 Menggunakan Algoritma Support Vector Machine Mufriz, Muhammad Fadwa; Witarsyah, Deden; Fa'rifah , Riska Yanu
eProceedings of Engineering Vol. 11 No. 4 (2024): Agustus 2024
Publisher : eProceedings of Engineering

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Abstract

— Analisis sentimen merupakan metode penting dalam memahami pandangan dan opini masyarakat terhadap suatu peristiwa atau entitas. Dalam konteks pemilihan presiden 2024 di Indonesia, analisis sentimen menjadi krusial untuk memahami dukungan dan pendapat masyarakat. Dalam penelitian ini, peneliti menggunakan metode Support Vector Machine (SVM) untuk melakukan analisis sentimen terhadap komentar masyarakat pada platform YouTube terkait pemilihan presiden 2024. Tahapan analisis dimulai dengan preprocessing, termasuk langkah-langkah seperti tokenisasi, normalisasi, penghapusan stop words, dan lemmatisasi. Selanjutnya, data dibagi menjadi 70% untuk training dan 30% untuk testing. Peneliti melakukan grid search untuk menentukan parameter terbaik untuk model SVM, seperti kernel dan parameter C. Label yang dianalisis terdiri dari positif, negatif, dan netral, yang merepresentasikan sentimen komentar masyarakat terhadap calon presiden. Hasil penelitian menunjukkan bahwa model SVM mampu mengklasifikasikan sentimen komentar dengan akurasi yang memuaskan setelah dilakukan grid search untuk penentuan parameter terbaik. Model Anies dan Prabowo menunjukkan performa yang sangat baik dengan nilai precision, recall, dan F1-score yang tinggi untuk semua label sentimen, yaitu sekitar 94%, 92%, dan 93% untuk Anies, serta sekitar 96%, 97%, dan 96% untuk Prabowo. Sedangkan model Ganjar memiliki performa yang lebih rendah dengan precision sekitar 83%, recall sekitar 80%, dan F1-score sekitar 81%. Kata kunci— Pemilihan Presiden; Analisis Sentimen; Support Vector Machine; YouTube; Vader Lexicon, grid search
Co-Authors A A Abushammala, Haneen Abel Junando Adila Chusnul Fatiyah Adityas Widjajarto Adventus Angga Kurniawan Agita Oktavian Bangun Agus Maolana Hidayat Ahmad Musnansyah Ahmad, Mokhtarrudin Aldi Akbar Aldi Mustafri Aldo Erianda, Aldo Almohab, Hadi Andri Gautama Suryabrata Andri Gautama Suryabrata, Andri Gautama Aprilia Mega Puspitasari Asim Shahzad Bin Salamat, Mohamad Aizi Budi Rustandi Kartawinata Chairiandi Putra Yuda Chandra, Felixius Arelta Che Dalim, Che Samihah Choon Sen Seah Dedy Syamsuar Fa'rifah, Riska Yanu Fabiyola Nindya Susilo Fakhrurroja, Hanif Fakqih Hamami Faqih Hamami Fauzi, Rokhman Fiqih Muhammad Haekal Rosyadi Hairulnizam Mahdin Hairulnizam Mahdin Hairulnizam Mahdin Hanif Catrio Wicaksono Haniyah , Salma Hidayatul Aji Adika Putra Ikhsan Yudha Pradana Kai Wah Hen Kamil, Andhika Ihsan Lukman Abdurrahman M Farhan Hussaini Dermawan Mangsor, Miza Marheni Eka Saputri Maria Imdad MD Fudzee, Mohd Farhan Melinsye Herliani Ahab Mohamad Aizi Bin Salamat Mohamad Aizi Bin Salamat, Mohamad Aizi Mohd Farhan MD Fudzee Mohd Farhan MD Fudzee, Mohd Farhan Mohd Izuan Hafez Ninggal Mohd Sanusi Azmi Mokhairi Makhtar Mufriz, Muhammad Fadwa Muhammad Fadhly Arham Muhammad Mufti Kamil Muhammad Mufti Kamil, Muhammad Mufti Muhammad Ridwan Aam Muharman Lubis Nadila Lintang Hapsari Nasirudin, Mohd Asrul Nazri Mohd Nawi Nur’Aifaa Zainudin Oktariani Nurul Pratiwi Pakdeetrakulwong, Udsanee Parasetia Abu Aditya Pratiwi, Oktaria Nurul R. Wahjoe Witjaksono Rachmadita Andreswari Rayinda Pramuditya Soesanto Razali, Raja Razana Raja Rio Savero Aranov Rizky Afrian Renadri Rizky Afrian Renadri, Rizky Afrian Robby Dwi Hartanto Ruhaila Maskat Ruth Sesilya Ambarita Senan, Norhalina Seno Adi Putra Shazlyn Milleana Shaharudin Shazlyn Milleana Shaharudin Shazlyn Milleana Shaharudin Soni Fajar Surya Gumilang Sujak, Aznul Fazrin bin Abu Suryabrata, Andri Gautama Sutoyo , Edi Tatang Mulyana Yin Xia Loh Zahid, Azham Zirawani Baharum Zirawani Baharum