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All Journal Jurnal Simetris Scientific Journal of Informatics Creative Information Technology Journal Jurnal Technopreneur (JTech) CSRID (Computer Science Research and Its Development Journal) Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Intelligent Decision Support System (IDSS) Jurnal Abdi Masyarakat Indonesia Jurnal Mandiri IT Brilliance: Research of Artificial Intelligence Jurnal Minfo Polgan (JMP) Indonesian Journal of Informatics and Research PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer jurnal penelitian multidisiplin Jurnal Manajemen Informatika dan Bisnis Digital Jurnal Indonesia Sosial Teknologi Journal of Artificial Intelligence and Digital Business Jurnal Publikasi Teknik Informatika (JUPTI) Jurnal Masyarakat Madani Indonesia Innovative: Journal Of Social Science Research JURSIMA SOROT: Jurnal Pengabdian Kepada Masyarakat SmartComp Jurnal Sistem Informasi dan Manajemen Jurnal Akademik Pengabdian Masyarakat Svarga Pena: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika dan Desain Komunikasi Visual
Aang Alim Murtopo
STMIK YMI TEGAL
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Other

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Penerapan Metode Fuzzy Tsukamoto untuk Prediksi Jumlah Produksi PT Wings Padaharja Firmansyah, Muchamad Aries; Murtopo, Aang Alim; Fadilah, Nurul
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2173

Abstract

Penerapan sistem prediksi produksi berbasis kecerdasan buatan menjadi solusi penting dalam menjawab tantangan ketidakpastian pada sektor manufaktur, khususnya di lingkungan usaha mikro seperti PT Wings Padaharja. Penelitian ini bertujuan untuk membangun model prediksi jumlah produksi harian dengan memanfaatkan metode Fuzzy Tsukamoto guna meningkatkan efisiensi pengambilan keputusan operasional. Penelitian ini menggunakan pendekatan kuantitatif terapan dengan metode eksperimen, di mana data historis produksi tahun 2024 yang mencakup empat variabel utama—penjualan, permintaan, persediaan, dan retur—dianalisis melalui tahapan fuzzyfikasi, penetapan aturan IF–THEN, inferensi fuzzy, dan defuzzifikasi menggunakan metode rata-rata tertimbang. Hasil penelitian menunjukkan bahwa model prediksi yang dikembangkan mampu menghasilkan estimasi produksi dengan tingkat kesalahan yang masih dalam batas wajar, ditunjukkan oleh nilai MAE sebesar 65,21, MSE sebesar 15.698,8, dan RMSE sebesar 92,02. Temuan ini menunjukkan bahwa metode Fuzzy Tsukamoto efektif dalam menangani ketidakpastian dan kompleksitas data produksi, serta dapat diimplementasikan sebagai sistem pendukung keputusan bagi pelaku industri skala kecil hingga menengah; selanjutnya, pengembangan model lanjutan dapat diarahkan pada integrasi variabel eksternal dan penggunaan algoritma yang lebih kompleks seperti ANFIS untuk peningkatan akurasi prediktif
Penerapan Metode Naive Bayes untuk Deteksi Keaslian Daging Sapi berdasarkan Citra Daging Sapi Moonap, Dinar Auranisa; Murtopo, Aang Alim; Utami, Erni Unggul Sedya
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2254

Abstract

Penelitian ini bertujuan untuk mengembangkan model deteksi keaslian daging sapi berbasis citra digital menggunakan algoritma Naïve Bayes dengan integrasi fitur warna dan tekstur. Dataset terdiri dari 600 citra daging sapi yang terbagi seimbang antara kelas 0 (grade standar) dan kelas 1 (grade premium), dengan 50 dimensi fitur hasil ekstraksi menggunakan ruang warna RGB dan HSV untuk fitur warna, serta Gray Level Co-occurrence Matrix (GLCM) untuk fitur tekstur. Data dibagi dengan proporsi 80% untuk pelatihan dan 20% untuk pengujian. Hasil evaluasi dari sepuluh kali pengujian menunjukkan akurasi rata-rata 81,83% ± 4,01%, precision 78,26% ± 4,07%, recall 88,50% ± 5,80%, dan F1-score 82,94% ± 3,78%. Confusion matrix mengungkap bahwa model memiliki sensitivitas tinggi dalam mengidentifikasi daging asli (88,5%) dan specificity moderat dalam mendeteksi daging palsu (75,2%). Temuan ini membuktikan bahwa metode Naïve Bayes dengan kombinasi fitur warna dan tekstur efektif digunakan untuk deteksi keaslian daging sapi, sehingga berpotensi diimplementasikan pada sistem pendukung pengawasan mutu di pasar tradisional maupun industri pangan.
Klasifikasi Status Stunting Balita Tegal Menggunakan Teknik Smote Pada Metode Naives Bayes Gaussain Januarto, Sigit; Murtopo, Aang Alim; Arif, Zaenul
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2349

Abstract

Stunting merupakan salah satu masalah kesehatan serius yang memengaruhi tumbuh kembang anak, terutama pada 1.000 Hari Pertama Kehidupan. Kota Tegal termasuk wilayah dengan prevalensi stunting yang cukup tinggi, sehingga diperlukan metode prediksi yang akurat untuk mendukung intervensi gizi tepat sasaran. Penelitian ini menggunakan metode Naive Bayes Gaussian untuk mengklasifikasikan status stunting balita berdasarkan data antropometri. Permasalahan ketidakseimbangan kelas pada dataset diatasi dengan teknik oversampling Synthetic Minority Over-sampling Technique (SMOTE) guna meningkatkan kemampuan model dalam mengenali kelas minoritas. Hasil pengujian menunjukkan bahwa model sebelum penerapan SMOTE memiliki akurasi rata-rata 91,58%. Setelah penerapan SMOTE, akurasi validasi silang meningkat menjadi rata-rata 96,28% dengan presisi 94,03%, recall 91,58%, dan F1-score 92,12%. Peningkatan ini membuktikan bahwa kombinasi Naive Bayes Gaussian dan SMOTE efektif untuk prediksi status stunting. Model yang dihasilkan berpotensi diimplementasikan sebagai sistem pendukung keputusan dalam deteksi dini dan pencegahan stunting di wilayah rawan
Implementasi Algoritma K-Means untuk Pengelompokan Risiko Drop out Mahasiswa Fatah, Muhammad Raikhan Al; Murtopo, Aang Alim; Utami, Erni Unggul Sedya
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2374

Abstract

Fenomena mahasiswa putus studi (drop out) menjadi tantangan serius bagi perguruan tinggi karena berdampak pada citra institusi, efektivitas pembelajaran, dan efisiensi sumber daya. Penelitian ini bertujuan mengelompokkan risiko drop out mahasiswa penerima Kartu Indonesia Pintar (KIP) semester 6 di STMIK YMI Tegal untuk mendukung deteksi dini dan intervensi akademik yang lebih tepat sasaran. Metode penelitian menggunakan algoritma K-Means Clustering dengan data Indeks Prestasi Kumulatif (IPK) dan kehadiran mahasiswa, melalui tahapan pra-pemrosesan data, penentuan jumlah klaster optimal menggunakan metode Elbow, implementasi K-Means, serta evaluasi hasil menggunakan silhouette score. Hasil penelitian menunjukkan terbentuknya tiga klaster risiko yaitu rendah, sedang, dan tinggi, dengan nilai silhouette score 0,4101 yang mengindikasikan kualitas pemisahan klaster cukup baik; mahasiswa dengan IPK dan kehadiran tinggi tergolong berisiko rendah, sedangkan mahasiswa dengan IPK dan kehadiran rendah tergolong berisiko tinggi. Implikasi penelitian ini adalah model yang dihasilkan dapat digunakan sebagai alat bantu pihak kampus dalam mengidentifikasi mahasiswa berisiko sejak dini, merumuskan kebijakan pendampingan akademik yang lebih efektif, serta menjadi dasar pengembangan sistem pemantauan akademik berbasis data mining yang dapat diperluas dengan algoritma lain dan variabel tambahan untuk meningkatkan akurasi dan generalisasi model
Digital Marketing Efforts to Improve Products of Micro Small and Medium Enterprises (UMKM) in Tegal Santoso, Nugroho Adhi; Nugroho, Bangkit Indarmawan; Murtopo, Aang Alim; Surorejo, Sarif; Gunawan, Gunawan
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3646

Abstract

Digital marketing is promotional activities and market search through the media digitally online by utilizing various means such as social networks. The aim of this research is to increase knowledge and skills about digital marketing, especially social media, for Small and Medium Enterprises (SME) business people to increase their sales and profits. Digital marketing is the use of social media networks to carry out promotional activities and map digital markets. By using computers or other electronic equipment, digital marketing ideas can bring together geographically diverse parties. The aim of this research is to identify the most effective digital marketing tactics for the growth of MSMEs in Tegal City and Tegal Regency. The method used in this research is descriptive qualitative. With Data collection through observation, interviews, and secondary sources, such as books, journals, and articles, were used to collect information for this research. The results of this research show that the productivity growth of MSMEs in Tegal City and Tegal Regency has not been positive. Even when a website for an online business has been created, not everyone has implemented a digital marketing plan. It can be seen that digital marketing strategies have not received much attention from MSMEs in Tegal City and Tegal Regency. So it is hoped that MSMEs in Tegal City and Tegal Regency can adapt to changing times, namely selling online using digital marketing strategies.
Application of the nearest neigbour interpolation method and naives bayes classifier for the identification of bespectacled faces Murtopo, Aang Alim; Januarto, Sigit; Anandianskha, Sawaviyya; Gunawan, Gunawan
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 2 (2024): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i2.242

Abstract

Facial recognition technology has rapidly advanced, but identifying individuals wearing glasses remains challenging due to altered or obscured facial features. This study addresses this issue by combining the Nearest Neighbor Interpolation Method and Naive Bayes Classification for bespectacled face identification. The method applies interpolation to enhance facial image quality, preserving critical features before classification by Naive Bayes into spectacle and non-spectacle classes. Using the Kaggle MeGlass dataset for training and testing, the approach achieved a training accuracy of 78%, a testing accuracy of 76%, and a cross-validation value of 0.70. These results indicate a significant improvement in recognizing bespectacled faces, contributing to enhanced accuracy in facial recognition systems. Despite these advancements, further improvements are possible, such as integrating more advanced models and expanding the dataset, which could lead to even greater accuracy and reliability in practical applications. This research provides a novel solution to a persistent challenge in facial recognition technology
Optimasi Search Engine Optimization (SEO) On Page Untuk Meningkatkan Peringkat Website Hondasukabumi.com Di Google Alim Murtopo, Aang; Nursidik, Maulia; Syefudin, Syefudin; Gunawan, Gunawan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.10715

Abstract

Artikel penelitian ini berjudul "Optimasi Search Engine Optimization (SEO) On Page Untuk Meningkatkan Peringkat Website Hondasukabumi.com Di Google", bertujuan untuk mengidentifikasi dan menerapkan strategi optimasi SEO On Page yang efektif dalam meningkatkan peringkat website bisnis lokal di mesin pencari Google. Menggunakan metode studi literatur dan observasi, penelitian ini fokus pada analisis kata kunci tertentu dari tahun 2020 hingga 2024 dan optimasi elemen-elemen SEO On Page seperti title tag, meta deskripsi, dan struktur heading. Hasil penelitian menunjukkan bahwa penerapan strategi SEO On Page yang ditargetkan berdasarkan analisis kata kunci dan optimasi konten relevan berhasil meningkatkan visibilitas dan peringkat website Hondasukabumi.com di hasil pencarian Google. Implikasi dari penelitian ini menekankan pentingnya SEO On Page dalam strategi pemasaran digital untuk bisnis lokal, memberikan wawasan penting bagi pemilik bisnis dan praktisi SEO dalam meningkatkan performa website di era digital.
Application of the haversine formula method to determine the closest distance to a minimarket Muttaqin, Anik; Murtopo, Aang Alim; Syefudin, Syefudin; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.293

Abstract

In a digital era that demands speed and efficiency, determining the closest distance to minimarkets is crucial for consumers and the logistics industry. This study proposes the use of the haversine method to improve the accuracy of distance calculations. Through quantitative and quasiexperimental approaches, this study describes the steps of data collection, pre-processing, and application of haversine formulas. The results demonstrate the reliability of the haversine method in estimating distances accurately, allowing users to make more informed decisions in planning trips or logistics strategies. These findings contribute to the academic literature and field practice by providing a more robust and applicable methodology for determining the closest distance. Keywords: haversine, closest distance, minimarket.
Application of fuzzy tsukamoto method in forecasting weather Murtopo, Aang Alim; Aslam, Muhammad Nur; Andriani, Wresti; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.305

Abstract

In today's information age, accurate weather prediction is essential given its far-reaching impact on various aspects of life and economic activity. This study aimed to test the effectiveness of Fuzzy Tsukamoto's method in predicting important weather variables such as temperature, humidity, and precipitation. This research method uses a combination design that includes experimental methods for model development, quantitative analysis of historical weather data, and model validation using separate data. The results showed that the Fuzzy Tsukamoto method was able to increase the accuracy of weather predictions compared to conventional methods, with a significant decrease in the value of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In conclusion, this study successfully demonstrates that Fuzzy Tsukamoto's method can be a more accurate alternative in weather prediction, making a significant contribution to the field of meteorology and its practical application in decision-making in various sectors that depend on weather prediction.
Application of genetic algorithm and backpropagation neural networks to predict Tegal City population Murtopo, Aang Alim; Nursahid, Wahyu; Fadilah, Nurul; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.308

Abstract

Use of Genetic Algorithms and Backpropagation Neural Networks for Population Prediction in Tegal City, which aims to create precise prediction models using advanced computational techniques. This research uses a quantitative approach that combines experimental methods, data analysis, and model validation to implement and test predictive models. By using genetic algorithms for parameter optimization and neural network backpropagation for training, the findings show that the model can accurately predict population numbers with minimal error and high determination coefficients. The implications of this study are significant for urban planning and public policy development due to the accuracy and effectiveness of the model in forecasting population growth based on historical data.
Co-Authors Adhi Santoso, Nugroho Aditdya, Maulana Afridar, Halim Amalani, Mukhamad Zulfa Bakhtiar Anandianskha, Sawaviyya Andriani, Wresti Angesti, Devi Cici Angesti, Devi Cici Anshori, Abu Hasan Al Arif, Zaenul Aslam, Muhammad Nur Azmi, Isni Bangkit Indarmawan Nugroho Bayu Aji Santoso Cahyo, Septian Dwi Diana Pramestiningsih Erni Unggul Sedya Utami, Erni Unggul Sedya Fadli, Muhamad Rizaldi Satrio Farkhan, Ali Fatah, Muhammad Raikhan Al Firmansyah, Muchamad Aries Gunawan Gunawan Gunawan Gunawan Gunawan Gunawan Gunawan Haryadi, Didi Isnaeni Hamidah Isni Azmi Januarto, Sigit Karsidin, Karsidin Khafidz Basri Kurniawan, Rifki Dwi M. Herly Rumambi Marstyo Ardiansyah Maulana Aditdya Miftakhudin, Muhammad Moonap, Dinar Auranisa Muttaqin, Anik Naja, Naella Nabila Putri Wahyuning Nugroho Adhi Santoso Nugroho Adhi Santoso Nursahid, Wahyu Nursidik, Maulia Nurul Fadhilah Nurul Fadilah Nurul Fadilah Nurul Fadilah, Nurul Pingky Septiana Ananda Priyatna, Bayu Qurrotu Aini, Atikah Retno Ayuning Putri Rifki Dwi Kurniawan Rini Mayasari Rito Cipta sigitta Hariyono Riyadi, Fajar Sugeng Rudi Juniyanto Santoso, Bayu Aji Santoso, Nugroho Adh Santoso, Nugroho Adhi Santoso, Nugroho Adi Sarif Surorejo Septiana Ananda, Pingky Sifa Melina Salsabila Syefudin Syefudin Syefudin Syefudin, Syefudin Triwinanto, Mohammad Amin Triwinanto Wahyu Romadhona Wresti Andriani Yustira . Zaenal Arif Zaenul Arif