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All Journal Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah KOMPUTASI JOIV : International Journal on Informatics Visualization JRSI (Jurnal Rekayasa Sistem dan Industri) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Jurnal Informatika Teknologi dan Sains (Jinteks) eProceedings of Engineering Journal of Community Service and Society Empowerment
Deden Witarsyah
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences

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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 Ulasan Aplikasi Maxim Untuk Peningkatan Layanan Menggunakan Algoritma Naïve Bayes Afdillah, Dwivi; Fa’rifah, Riska Yanu; Witarsyah , Deden
eProceedings of Engineering Vol. 11 No. 4 (2024): Agustus 2024
Publisher : eProceedings of Engineering

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Abstract

Abstrak — Transportasi online kian menarik perhatian danminat masyarakat untuk dijadikan salah satu kebutuhan yangdapat memudahkan aktivitas sehari-hari. Maxim merupakansalah satu transportasi online yang menepati urutan ketiga jasatransportasi online yang paling sering digunakan. Denganadanya hasil pemeringkatan jasa transportasi online tersebutmaka pihak Maxim dapat meningkatkan pelayananberdasarkan dari ulasan pengguna aplikasi Maxim melaluimetode analisis sentimen yang bertujuan untuk mengolahsejumlah besar data secara selektif dan efisien denganmengelompokkan ke dalam dua ulasan yaitu positif dan negatifdengan menggunakan algoritma Naïve Bayes. Tahap untukmelakukan analisis sentimen dibagi menjadi beberapa bagiandiantaranya yaitu pengumpulan data, preprocessing, modelling,dan evaluasi. Pada penelitian ini, menggunakan tiga skenariorasio pembanding training testing yaitu 60:40, 70:30, dan 80:20dengan menggunakan model Multinomial Naïve Bayesmenunjukkan bahwa rasio 70:30 menghasilkan model terbaikdengan nilai akurasi sebesar 87,22% yang dilakukan melaluiconfusion matrix dengan nilai recall sebesar 98,49%, nilaiprecision sebesar 86,62%, dan f1 score menghasilkan nilaisebesar 92,17%. Berdasarkan dari hasil visualisasi sentimendidapatkan hasil ulasan pengguna aplikasi Maxim cenderungmengarah ke sentimen positif dengan jumlah ulasan positifsebanyak 76% dan sentimen negatif sebanyak 24%. Sehingga,hasil kategori sentimen tersebut dapat dijadikan bahan evaluasikepada pihak developer sebagai bentuk peningkatan layananaplikasi Maxim. Kata kunci— Analisis Sentimen, Transportasi Online, Naïve Bayes
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
Omni-Channel Service Analysis of Purchase Intention Sugiat, Maria; Saabira, Nadia; Witarsyah, Deden
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.2442

Abstract

The COVID-19 pandemic has caused a decline in various aspects of the economy, including the fashion sector. Many fashion retailers have closed, so sales have fallen. However, many retailers can also adapt and change using new communication channels. This change presents new challenges for fashion companies and retailers to integrate channels into omnichannel services. This study aims to analyze the factors influencing customer behavior in omnichannel services through their intention to accept and use new technology in shopping. This study adopts the UTAUT2 model by adding two new variables: personal innovation and perceived security. This model was tested on 353 samples from Uniqlo customers residing in Indonesia. This research method uses a Quantitative PLS-SEM approach. This study tested the outer model, inner model, and hypothesis t-test with a bootstrap procedure using SmartPLS software. The results showed that the performance expectation factor did not affect the omnichannel purchase intention variable because the t-statistic value is less than 1.65. Meanwhile, other factors such as effort expectation, social influences, habits, hedonic motivation, perceived security, and personal innovativeness affect omnichannel purchase intentions because the t-statistic value is more than 1.65. The most positive and significant factor is personal innovativeness. Based on the results of this study, it is revealed that digitalization creates challenges for companies in maintaining digital businesses. Through various omnichannel service channels, this research can identify the factors influencing consumers' purchase intention
Predicting and Explaining Customer Response to Upselling in Telecommunications: A Malaysian Case Study Abdullah, Railey Shahril; Shastera Nulizairos, Nur Shaheera; Mohd Ariffin, Nor Hapiza; Witarsyah, Deden; Maskat, Ruhaila
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.2823

Abstract

This research explores the predictive capabilities of XGBoost (XGB) and Random Forest (RF) models for customer upsell responses, emphasizing the use of Explainable Artificial Intelligence (XAI) techniques to gain insights. Initially trained without hyperparameter tuning, both models were later optimized using 5-fold cross-validation. While RF consistently achieved high accuracy (0.99), XGB exhibited lower accuracy (0.85) yet demonstrated superior precision and recall. Post-tuning, XGB maintained its competitive edge despite a slight decrease in ROC-AUC scores (0.76 and 0.75 versus RF's 0.67 and 0.72), indicating proficiency in classifying positive cases. XAI techniques complemented XGB’s prediction, revealing significant predictors such as inactive duration in days, race (Chinese), total communication count, age, and active period in days. Lesser predictive value was attributed to factors such as race (Indian), gender (female), and region (northern). While the feature importance plot provided a broad overview, it did not detail specific attribute relationships to predictions. To address this, a summary violin plot was employed to illustrate how feature importance varies with actual values, enhancing the understanding of each feature's impact. Results indicated that longer inactivity periods negatively influenced predictions, while non-Chinese ethnicity, higher communication frequency, and younger age were associated with positive outcomes. Dependence plots further elucidated these relationships, highlighting how older non-Chinese customers and those with shorter inactive periods and frequent communication were more likely to accept offers. Local explanations using Shapley's force plot and LIME offered deeper insights into specific instances. Overall, the study underscores the complementary use of XAI techniques to understand a model’s predictions.
Cluster Analysis of Japanese Whiskey Product Review Using K-Means Clustering Witarsyah, Deden; Akbar, Moh Adli; Praditha, Villy Satria; Sugiat, Maria
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2601

Abstract

Since 2008, the Japanese whiskey business has grown steadily. Overall, the whiskey market (at factory price) is expected to reach $2.95 billion in 2019, accounting for 8.6 percent of the entire alcoholic beverage industry. The rise in popularity of Japanese whiskey is associated with the country's growing international reputation. Founded 1985 as an independent bottler, Master of Malt was the first company to service clients who ordered single malt whiskey through the mail-order system. Master of Malt's omnichannel approach encompasses all channels available to the company. Known as their 'omnichannel,' this refers to the organization's capability to provide speed and precision from any place at any time. As their brand has grown over the years, they have used various marketing strategies, including a website redesign and rebuild that involved the creation of all relevant content and designing and constructing landing pages for their website. Following a clustering technique, we discovered that the data is being divided into four distinct groups and that these clusters may serve as a recommender system based on the occurrence of terms in each of the categories. Our summarizing component combined phrases related to the exact subtopics and provided users with a concise summary and sentimental information about the group of phrases.
Implementasi Metode Asosiasi Untuk Analisis Penempatan Produk Retail Ambarita, Ruth Sesilya; Witarsyah, Deden; Hamami, Faqih
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Analisis dan Penerapan Enterprise Architecture pada Bagian Service Menggunakan Togaf ADM di PT. Subur Ban Mandiri Bangun, Agita Oktavian; Witarsyah, Deden; Fauzi, Rokhman
eProceedings of Engineering Vol. 10 No. 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Bengkel adalah sebuah tempat yang menyediakan ruang dan peralatan untuk memperbaiki benda/kendaraan. Bengkel juga bergerak di bidang penyedia layanan service dan penjualan spare part. Ketersediaan spare part menjadi salah satu hal yang penting karena berdampak pada waktu tunggu layanan (metode fast moving). Oleh karena itu, perusahaan harus menyediakan produk sesuai kebutuhan pelanggan dengan memperhatikan jumlah penjualan dan waktu pengadaan produk tersebut. Kesalahan dalam mengelola data historis pelanggan dan safety stock dapat menurunkan kualitas service perusahaan tersebut. Demi meningkatkan kualitas layanan dan juga kinerja perusahaan dalam berbagai aspek, PT.Subur Ban mandiri harus selalu siap dalam melakukan peningkatan kinerja dan pengembangan strategi bisnis perusahaan. Untuk melakukan peningkatan tersebut maka diperlukan perbaikan dari fungsi sistem informasi kedalam rancangan Enterprise Architecture. Perancangan dan penerapan Enterprise Architecture yang digunakan untuk sistem informasi PT.Subur Ban Mandiri adalah framework TOGAF ADM, karena fleksibel dan juga menyediakan método untuk membangun, mengelola dan dapat memenuhi kebutuhan dalam pengembangan perusahaan mulai dari peningkatan kualitas service, stock, data historis pelanggan strategi bisnis dan teknologi yang membuat keputusan bagi stakeholder.Kata Kunci-enterprise architecture, TOGAF ADM, service, sparepart
Co-Authors A A Abushammala, Haneen Abdullah, Railey Shahril Abel Junando Adila Chusnul Fatiyah Adityas Widjajarto Adventus Angga Kurniawan Afdillah, Dwivi Agus Maolana Hidayat Ahmad Musnansyah Ahmad, Mokhtarrudin Akbar, Moh Adli Aldi Akbar Aldi Mustafri Aldo Erianda, Aldo Almohab, Hadi Ambarita, Ruth Sesilya Andri Gautama Suryabrata Andri Gautama Suryabrata, Andri Gautama Asim Shahzad Bangun, Agita Oktavian Bin Salamat, Mohamad Aizi Budi Rustandi Kartawinata Chandra, Felixius Arelta Che Dalim, Che Samihah Dedy Syamsuar Dermawan, M Farhan Hussaini Fa'rifah, Riska Yanu Fabiyola Nindya Susilo Fakhrurroja, Hanif Faqih Hamami Fauzi, Rokhman Fiqih Muhammad Haekal Rosyadi Gosal, Yose Thimothy Hairulnizam Mahdin Hairulnizam Mahdin Hairulnizam Mahdin Hamami, Fakqih Haniyah , Salma Ika Putri Puspitasari Ikhsan Yudha Pradana Iqbal Yulizar Mukti Kamil, Andhika Ihsan Lukman Abdurrahman Mangsor, Miza Marheni Eka Saputri Maria Imdad Maskat, Ruhaila MD Fudzee, Mohd Farhan Melinsye Herliani Ahab Mohamad Aizi Bin Salamat Mohamad Aizi Bin Salamat, Mohamad Aizi Mohd Ariffin, Nor Hapiza 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 Praditha, Villy Satria Pratiwi, Oktaria Nurul Puspitasari, Aprilia Mega Putra, Hidayatul Aji Adika Putri Kurniawati 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 Saabira, Nadia Seah, Choon Sen Senan, Norhalina Seno Adi Putra Shaharudin, Shazlyn Milleana Shastera Nulizairos, Nur Shaheera Shazlyn Milleana Shaharudin Shazlyn Milleana Shaharudin Soni Fajar Surya Gumilang Sugiat, Maria Sujak, Aznul Fazrin bin Abu Suryabrata, Andri Gautama Sutoyo , Edi Tatang Mulyana Wah Hen, Kai Wicaksono, Hanif Catrio Xia Loh, Yin Yuda, Chairiandi Putra Zahid, Azham Zirawani Baharum Zirawani Baharum