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All Journal ARABIYAT Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Studi Agama dan Masyarakat Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Madaniyah: Terciptanya Insan Akademis Berkualitas Dan Berakhlak Mulia JIKO (Jurnal Informatika dan Komputer) qolamuna : Jurnal studi islam Jurnal SOLMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JURNAL ILMIAH INFORMATIKA Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT Jambura Journal of Food Technology Jurnal Tekno Kompak Jurnal Edukasi (Ekonomi, Pendidikan dan Akuntansi) JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Biogenerasi JISA (Jurnal Informatika dan Sains) BERNAS: Jurnal Pengabdian Kepada Masyarakat Al-Fusha : Arabic Language Education Journal Jurnal Pendidikan dan Teknologi Indonesia Mosharafa: Jurnal Pendidikan Matematika Tanwir Arabiyyah: Arabic as Foreign Language Journal Jurnal Dinamika Informatika (JDI) Jurnal EBONI Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Artificial Intelligence and Engineering Applications (JAIEA) PENA ABDIMAS : Jurnal Pengabdian Masyarakat Makara Journal of Technology Jurnal Sistem Informasi dan Teknologi (SINTEK) Indonesian Journal of Fundamental Sciences Journal of Tourism Education Prosiding Seminar Nasional Manajemen dan Ekonomi JURSIMA Iqtida: Journal of Da'wah and Communication Huma: Jurnal Sosiologi Jurnal Biologi Babasal Al-Zayn: Jurnal Ilmu Sosial & Hukum Jurnal Sistem Informasi dan Manajemen Maddana: Jurnal Pengabdian Kepada Masyarakat Sirajuddin : Jurnal Penelitian dan Kajian Pendidikan Islam Prosiding Seminar Nasional Unimus Jurnal Kemitraan Masyarakat Informasi interaktif : jurnal informatika dan teknologi informasi Jurnal Riset Multidisiplin Edukasi Regulate: Jurnal Ilmu Pendidikan, Hukum dan Bisnis Jurnal Cendekia Ilmiah PESHUM Jurnal Geosaintek Sintek Kuwera Sirajuddin: Jurnal Penelitian dan Kajian Pendidikan Islam Bianglala Informatika
Ahmad Faqih
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Analisis Kinerja Algoritma Machine Learning untuk Klasifikasi Prestasi Mahasiswa pada Mata Kuliah Bahasa Inggris Riri Narasati; Dadang Sudrajat; Ahmad Faqih; Indra Wiguna Marthanu; Agus Bahtiar
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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

Abstract

This study analyzes the performance of several machine learning algorithms in classifying student achievement in English language courses. The research focuses on comparing the performance of K-Nearest Neighbors (KNN), Naïve Bayes, Random Forest, and Support Vector Machine (SVM) using the K-Fold Cross Validation approach to evaluate accuracy, F1-score, and fairness. The dataset, consisting of students’ final grades, was processed through data pre-processing and feature scaling. Results show that the KNN model with K=5 achieved the highest accuracy of 100%, followed by Naïve Bayes with 95.59%. Statistical tests indicated a significant performance difference between Random Forest and SVM, while fairness evaluation revealed that Random Forest provided the most balanced error distribution. These findings confirm that KNN and Random Forest algorithms are highly effective for academic performance classification based on numerical data. The study highlights the potential of machine learning to enhance adaptive, objective, and equitable educational evaluation systems.
1D-CNN-Based Childhood Stunting Prediction through Socio-Economic Data Integration and Community Participation Bahtiar, Agus; Mulyawan, Mulyawan; Faqih, Ahmad; Lidina, Lidina; Fitria, Ananda Rizki
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2490

Abstract

Stunting remains a significant global public health challenge, affecting approximately 148 million children under the age of five. This condition leads to long-term cognitive and physical deficits, particularly in low- and middle-income countries. Many existing prediction models fail to capture the complex interdependencies between nutritional, socio-economic, and environmental factors. To address this gap, our study introduces a 1D-Convolutional Neural Network (1D-CNN) model designed to predict childhood stunting using structured datasets collected from community health centers (Puskesmas) and validated by the Cirebon City Health Department (Dinas Kesehatan Kota Cirebon), Indonesia. The dataset includes anonymized records of children under five years old, comprising anthropometric measurements, socio-economic profiles, nutritional intake, and environmental indicators, gathered through household surveys and routine public health reporting. The proposed 1D-CNN architecture is optimized for structured data by integrating convolutional and pooling layers, dropout regularization, and dense classification layers. To enhance interpretability, we employ explainable AI (XAI) methods—SHAP and LIME—to reveal the relative influence of each feature in the model’s decision-making process. Additionally, the study applies a participatory validation approach through focus group discussions (FGDs) with community health workers, ensuring contextual relevance and ethical integrity. Experimental results demonstrate the superior performance of the proposed model, achieving 93.12% accuracy, with a precision of 97% and a recall of 89%, resulting in an F1-score of 93% across both stunted and non-stunted classes. These findings outperform traditional machine learning approaches and highlight the potential of AI-driven predictive frameworks for early stunting detection and policy-oriented health interventions. This research contributes to the advancement of data-driven public health strategies by integrating predictive analytics, community participation, and transparent AI methodologies
Evaluasi Pengaruh Kualitas Data Terhadap Performa Model Machine Learning Menggunakan Pendekatan Data-Centric AI Bisma Mahendra; Martanto; Denni Pratama; Ahmad Faqih; Rudi Kurniawan
Jurnal Sistem Informasi dan Teknologi Vol 6 No 1 (2026): Jurnal Sistem Informasi dan Teknologi (SINTEK)
Publisher : LPPM STMIK KUWERA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56995/sintek.v6i1.211

Abstract

Penelitian ini mengevaluasi pengaruh kualitas data terhadap performa model machine learning menggunakan pendekatan Data-Centric Artificial Intelligence (DCAI). Eksperimen dilakukan pada Titanic Dataset dengan membandingkan Random Forest dan Support Vector Machine (SVM) dalam tiga skenario penanganan missing values, yaitu Drop Missing, Mean Imputation, dan No Imputation. Kinerja model dievaluasi menggunakan metrik Accuracy, F1 Score, dan Area Under Curve (AUC). Hasil menunjukkan bahwa intervensi kualitas data memberikan dampak signifikan terhadap performa model. Random Forest mencapai performa terbaik pada skenario Drop Missing dengan Accuracy 0.813, F1-Score 0.758, dan AUC 0.859, sedangkan SVM memperoleh Accuracy tertinggi sebesar 0.822 pada skenario Mean Imputation. Uji statistik Paired t-Test menunjukkan tidak terdapat perbedaan performa yang signifikan secara statistik antara kedua model (p-value > 0.05). Temuan ini menegaskan bahwa peningkatan kualitas data lebih berpengaruh terhadap kinerja model dibandingkan pemilihan algoritma, sehingga mendukung paradigma Data-Centric AI.
Evaluasi Pengaruh Kualitas Data Terhadap Performa Model Machine Learning Menggunakan Pendekatan Data-Centric AI Bisma Mahendra; Martanto; Denni Pratama; Ahmad Faqih; Rudi Kurniawan
Jurnal Sistem Informasi dan Teknologi Vol 6 No 1 (2026): Jurnal Sistem Informasi dan Teknologi (SINTEK)
Publisher : LPPM STMIK KUWERA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56995/sintek.v6i1.211

Abstract

Penelitian ini mengevaluasi pengaruh kualitas data terhadap performa model machine learning menggunakan pendekatan Data-Centric Artificial Intelligence (DCAI). Eksperimen dilakukan pada Titanic Dataset dengan membandingkan Random Forest dan Support Vector Machine (SVM) dalam tiga skenario penanganan missing values, yaitu Drop Missing, Mean Imputation, dan No Imputation. Kinerja model dievaluasi menggunakan metrik Accuracy, F1 Score, dan Area Under Curve (AUC). Hasil menunjukkan bahwa intervensi kualitas data memberikan dampak signifikan terhadap performa model. Random Forest mencapai performa terbaik pada skenario Drop Missing dengan Accuracy 0.813, F1-Score 0.758, dan AUC 0.859, sedangkan SVM memperoleh Accuracy tertinggi sebesar 0.822 pada skenario Mean Imputation. Uji statistik Paired t-Test menunjukkan tidak terdapat perbedaan performa yang signifikan secara statistik antara kedua model (p-value > 0.05). Temuan ini menegaskan bahwa peningkatan kualitas data lebih berpengaruh terhadap kinerja model dibandingkan pemilihan algoritma, sehingga mendukung paradigma Data-Centric AI.
Algoritma K-Means Untuk Klasterisasi Kampung Di Desa Bojong BerdasarkanTingkat Pendidikan Yuliantin, Yovi; Faqih, Ahmad; Kaslani
Bianglala Informatika Vol. 13 No. 1 (2025): Maret 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/bianglala.v13i1.12008

Abstract

Desa Bojong menghadapi tantangan dalam memetakan tingkat pendidikan penduduknyasecara terstruktur. Meskipun data tersedia, kurangnya pengorganisasian menyebabkan kesenjanganakses pendidikan, terutama di wilayah-wilayah tertentu. Penelitian ini bertujuan untukmengelompokkan tingkat pendidikan warga Desa Bojong menggunakan algoritma K-Means, sehinggadapat memberikan wawasan yang lebih mendalam tentang kondisi pendidikan masyarakat. Data yangdigunakan mencakup 6.027 penduduk dari 10 kampung, dengan atribut seperti usia, pendidikanterakhir, pekerjaan, dan status pernikahan. Proses analisis mengikuti tahapan Knowledge Discovery inDatabase (KDD) dan dilakukan menggunakan perangkat lunak RapidMiner. Hasil penelitianmenunjukkan bahwa jumlah klaster yang ideal adalah 7, dengan nilai terbaik 0,467 untuk DaviesBouldin Index (DBI). Setiap klaster menunjukkan tingkat pendidikan tertentu. Cluster 6 memiliki tingkatpendidikan yang sangat tinggi, dengan banyak penduduk yang sampai perguruan tinggi. Sementaraitu, Cluster 0 terdiri dari orang-orang yang hanya tamat SD atau bahkan tidak sekolah. Studi inimenunjukkan distribusi pendidikan di Desa Bojong. Hasil ini dapat membantu pemerintah desamembuat program pendidikan yang lebih baik. Kampung dengan tingkat pendidikan rendah dapatberkonsentrasi pada program yang meningkatkan akses pendidikan dasar, seperti literasi dan subsidipendidikan, sedangkan kampung dengan tingkat pendidikan tinggi dapat berkonsentrasi padapengembangan program pendidikan lanjutan atau pelatihan vokasional. Metode ini diharapkan dapatmembantu Desa Bojong mengatasi kesenjangan pendidikan dan meningkatkan kualitas hidupwarganya dengan menyediakan program yang tepat sasaran. Selain itu, penelitian ini membantuimplementasi algoritma K-Means dalam pengelompokan data pendidikan di daerah pedesaan.
Comparison of Graph-Based Filtering and Non-Local Means Techniques in Diabetic Retinopathy Classification Gita Antar Wulan; Irawan, Bambang; Faqih, Ahmad; Putra, Aris Pratama; Nurhakim, Bani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1869

Abstract

Classification of diabetic retinopathy (DR) based on retinal images is important for early detection, but is often hampered by poor image quality such as noise, uneven lighting, and low contrast. This study analyzes the effect of applying three image filtering techniques, namely Graph Laplacian Filtering (GLF), Graph Convolutional Network (GCN), and Non-Local Means (NLM), on improving the performance of Diabetic Retinopathy classification. The three methods were compared with a baseline model without filtering using VGG16 and evaluated through accuracy, AUC, loss, and image quality metrics such as PSNR, SSIM, MSE, and RMSE.The results showed that graphical and spatial filtering did not always improve classification performance, as VGG16 Fine-Tuning without filtering achieved the highest accuracy of 97.84%. Combinations with NLM, GCN, and Graph Laplacian resulted in lower accuracy due to the smoothing effect that removed important microfeatures on the retina. However, NLM remained effective in reducing noise without disturbing edge structures. These findings confirm that improving image visual quality does not always correlate with CNN accuracy, so preprocessing must focus on preserving diagnostic features.  
Revitalisasi Apotek Hidup Masyarakat Desa Sumberagung Kecamatan Weleri Kabupaten Kendal Satria Kamalil Hidayat; Risma Septiana Putri; Nor Faizatun Nikmah; Nur Hikmatul Azizah; Cika Cahya Kafita Purnama; Siti Ifroh Alwildah; Ahmad Faqih
Jurnal Kemitraan Masyarakat Vol. 1 No. 3 (2024): September: Jurnal Kemitraan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/jkm.v1i3.413

Abstract

Indonesia is one of the countries that cultivate various plants. Plants are not only used for food or decoration, plants are also very useful as medicines and healers. Plants that can be used to treat and cure diseases are commonly called live pharmacies. live pharmacy plants are quite useful to be used as a source of business because they can be sold and certainly improve the village economy.This research method uses a practical approach directly by going to the community to conduct counseling and planting practices. The results of this study are that the community is still unfamiliar with the concept of live pharmacy, with the practice of planting and counseling about live pharmacy making the Sumber Agung Village Community who are present there become more aware of the use of vacant land to plant useful plants
Comparison of TF-IDF and Word2Vec Feature Representations for Emotion Classification of Tokopedia E-Commerce Review Using LinearSVC Azzahra, Fitriyani; Irawan, Bambang; Faqih, Ahmad; Pratama, Denni; Kurnia, Dian Ade
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.2215

Abstract

This study aims to compare the performance of TF-IDF and Word2Vec feature representations for emotion classification of Tokopedia e-commerce reviews using the LinearSVC algorithm. The dataset used is PRDECT-ID, which consists of 5,400 Indonesian-language reviews labeled with positive and negative emotions. The preprocessing stages include case folding, non-alphabet character cleaning, slang normalization, stopword removal, Sastrawi stemming, and emoji handling. Feature extraction was performed using TF-IDF and Word2Vec, after which the models were trained using LinearSVC and evaluated through 5-Fold Cross Validation and holdout testing. The experimental results show that TF-IDF achieves better performance, with an accuracy of 0.65, a macro-F1 score of 0.645, and a Cohen’s Kappa value of 0.294. Meanwhile, Word2Vec attains an accuracy of 0.58 and a macro-F1 score of 0.540. These findings indicate that TF-IDF is more effective for short and informal texts characteristic of Indonesian e-commerce reviews.
Implementation of Sharia Marketing Strategy for Madura Grocery Stores to Increase the Competitiveness of MSMEs Ahmad Faqih; Abdur Rohman
Regulate: Jurnal Ilmu Pendidikan, Hukum dan Bisnis Vol. 3 No. 1 (2026)
Publisher : Penerbit Hellow Pustaka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61166/regulate.v3i1.40

Abstract

This study aims to analyze the marketing strategies implemented by Madurese traditional grocery stores (Toko Klontong Madura) in order to enhance competitiveness within the Micro, Small, and Medium Enterprises (MSME) sector. Facing increasingly complex market competition, traditional retail businesses must develop marketing strategies that not only retain loyal customers but also attract new ones. This research adopts a descriptive qualitative approach, using observation, interviews, and documentation for data collection. The findings reveal that personalized customer approaches, flexible pricing, friendly service, and strategic location usage are key factors in sustaining the competitiveness of Madurese grocery stores. The study concludes that appropriate and contextual marketing strategies can strengthen MSMEs amidst the rise of modern retail outlets.
Co-Authors -, Kaslani Abdullah Baharun abdur rohman Abi Fajar Ahmad Fauzi Achmad Supandi Ade Rizki Rinaldi Ade Rizki Rinaldy Adella, Luthfiyyah Iffah Adellia Putriani Adjie Setyadj, Mochammad Adnan Adnan Agung Triyono agus bahtiar Agus Riyadi Ahlam Musaydah Ahmad Jihadi Akhmad Abu Khasan Muzakki Akhmad Subhan Al Ghozali, Muhammad Iqbal Ali, Ashehad Aswen Amelia, Mita Andi Setiawan Andriawan, Dimas Annisa Rahmi Anshari, Rahman Ardiyanto Saleh Modjo Arif Rinaldi Dikananda Arnas Arnas, Arnas Arum Sari Arya Wijaya, Arya Athhar Hafizha Luthfi ayu hardani, anita Aziz Ramadhani Azzahra, Fitriyani Badruddin Bafadal, Mentarry Bambang Irawan Bambang Siswoyo Basysyar, Fadhil Muhammad Bisma Mahendra Chatarina Umbul Wahyuni Cika Cahya Kafita Purnama Dadang Sudrajat Denni Pratama Devika Rahayu Daud Dewi Wahyuni K. Baderan Diding Herudin Diding Herudin Diding Herudin, Diding Herudin Dienwati Nuris, Nisa Dikananda, Arif Rinaldi Dikananda, Fatihanursari Dini Andriyani Dita Rizki Amalia Dita, Mesya Sabhna Adma Djamadi, Dian Anggreini Edi Tohidi Eka Permana, Sandy Enjelita, Ratu Erieska Aprilyanti Ezra Pratama, Daffa Fadhil Muhammad Basysyar Fadilah, Euis Fajri, Ibnu Fajria, Azzahra Moudy Fathurrohman, Fathurrohman Febiyanto, Anggi Fidya Arie Pratama Fitria, Ananda Rizki Fuad Pontoiyo Gagarin, Muhamad Yuri Giannetti, Niccolo Gifthera Dwilestari Gilang Ramadhan Gita Antar Wulan Gumelar, Restu Habiballoh, Hafshoh Hafshoh Habiballoh Hamdan, Faiz Dzul Fahmi Hamzah, Hasyrul Haqiyah, Aridhotul Hasim Hasim Hasim Hasim Herdiyana, Ruli Hermawan, Bagus Hermawan, Muhammad Andi Hidayat, Manarul Hikmah Maulani Himawan, Toni Ilah Holilah Ilma’nun, M. Lulu Indra Wiguna Marthanu Irfan Ali, Irfan Jamiatur Rasyidah Jannah, Afni Nur Juliandro, Daniel K. Toiyo, Frandika Kadir, Rian Kaslani Khaerul Anam Khairul Akmal, Khairul Khairussalam Khoirul Huda, Muhammad Knohl, Alexander Komalasari, Cahyaningrum Kurnia, Dian Ade Kurniasih, Desta Dwi La Alio La Alio Laili Hidayatun Nikmah Laksono, Agung Lestari, Anjar Ayuning Lestari, Wien Lidina, Lidina Lila Zulfa Kamila M. Basysyar, Fadhil Ma'rufah, Ummu Mahendra, Yusril Muhamad Izha Mahludin H. Baruwadi Maman Abdurrahman Manarul Hidayat Martanto Maulana Sidiq, Cecep Maulana, Haris Mey Yulan Moko Mia Nurmala Mifta Almaripat Miftahul Huda Mohammad Sholehuddin Mohammad Syaefudulloh Muh. Arfah Syam Muharram Muharram Muhfidz Hidayat, Aziz Muhibuddin Mukdin, Novita B Mulyana, Dani Mulyawan Mulyawan Mulyawan, Mulyawan Nalahuddin Saleh Narasati, Riri Narasati Nasruddin Nasruddin Nida Naswa Ningsih, Indah Ratna Nor Faizatun Nikmah Norma Feti Farida Novi Mardiana Nur Atika Astriani Nur Farida, Farah Nur Halimah Nur Hikmatul Azizah Nuraini, Asyifa Nurhadiansyah Nurhakim, Bani Nurjana Adi Wijaya Nurul Aini, Yuli Odi Nurdiawan Oktavia, Riska Permadani Pertiwi, Pirda Parida Permana , Sandy Eka Permana, Sandy Eka Pratama, Denni Pratama, Fidya Arie Putra, Aris Pratama Rahayu, Helda Kusuma Rahma, Aliya Anisa Ramiro Firjatullah, Federicko Ramli Utina Raudya, Talitha Rayhan, Tubagus Muhammad Riri Narasati Risma Septiana Putri Risnayanti R Juramang Ristika Handarini Riyanto Adji Rizqy, Muhammad Enricco Rohmat, Cep Lukman Rosmeri Manurung, Agnes Rudi Kurniawan Rusmayana, Sigit Saeful Anwar, Saeful Saepu Qirom, Dani Saepudin, Asep Safitri, Ikraeni Sagita, Ayu Sandy Eka Permana Sandy Eka Permana, Faqih Satria Kamalil Hidayat Selly Novita Sari Septianto, Muhamad Arif Sigit Rusmayana Siti Ifroh Alwildah SM, Farid Solihudin, Dodi Subaegi, Angga Sugihartono, Tri Suharno, Achmad Sulaeman, Muhamad Supandi, Achmad Suryani Dewi, Ike Susana, Heliyanti Syaefudulloh, Mohammad Syam, Muh Arfah Syam, Muh. Arfah Syayid Al Manar Tania June Tati Suprapti Tengku Riza Zarzani N Tissa Aunilla Tomayahu, Tian Toriquddin Umar, Achmad Jauhari Wahyu Ningrum Sulistyowati Wanada, Gada Wanda, Aliffa Wijaya, Nurjana Adi Yonny Koesmaryono Yoshua, Deden Yudhistira Arie Wijaya Yuliantin, Yovi