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All Journal Humanika JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence JAMAIKA: Jurnal Abdi Masyarakat KOMMAS: Jurnal Pengabdian Kepada Masyarakat Journal of Research and Publication Innovation LOGIC : Jurnal Ilmu Komputer dan Pendidikan Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia OKTAL : Jurnal Ilmu Komputer dan Sains JRIIN :Jurnal Riset Informatika dan Inovasi Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) APPA : Jurnal Pengabdian Kepada Masyarakat AI dan SPK : Jurnal Artificial Intelligent dan Sistem Penunjang Keputusan
Maulana Fansyuri
Universitas Pamulang
Aerospace Engineering Arts Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Social Sciences Transportation Other

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Pengenalan Dasar Pemrograman untuk Siswa SMP YPUI Parung Al Islami, Hidayatullah; Yulianti K, Susanna Dwi; Fansyuri, Maulana
KOMMAS: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2024): KOMMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : KOMMAS: Jurnal Pengabdian Kepada Masyarakat

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Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperkenalkan dasar-dasar pemrograman kepada siswa SMP YPUI Parung sebagai upaya meningkatkan literasi teknologi dan pemahaman logika berpikir di kalangan pelajar. Metode yang digunakan meliputi pendekatan interaktif berbasis proyek melalui dua tahap, yaitu pengenalan pemrograman visual menggunakan Scratch dan pemrograman teks menggunakan Python. Kegiatan ini dilaksanakan selama dua hari dengan proses koordinasi bersama pihak sekolah, penyusunan modul, dan persiapan fasilitas pendukung. Evaluasi pemahaman dilakukan melalui pre-test dan post-test, serta observasi langsung selama kegiatan. Umpan balik positif dari siswa mengindikasikan bahwa pendekatan ini efektif dan menyenangkan, meskipun terdapat hambatan awal dalam memahami sintaks Python. Secara keseluruhan, program ini berhasil mencapai tujuan yang ditetapkan, yaitu memperkenalkan dasar-dasar pemrograman dan mendorong minat siswa untuk terus mempelajari teknologi di masa depan. Keberhasilan kegiatan ini diharapkan menjadi langkah awal untuk program lanjutan dengan materi yang lebih mendalam dan fasilitas pendukung yang lebih memadai.
WORKSHOP PENGGUNAAN TEKNOLOGI ARTIFICIAL INTELLIGENCE (AI) DALAM DUNIA PENDIDIKAN BAGI SISWA SMP YPUI PARUNG yulianti kusuma, susanna dwi; Al Islami, Hidayatullah; Fansyuri, Maulana
KOMMAS: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 2 (2025): KOMMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : KOMMAS: Jurnal Pengabdian Kepada Masyarakat

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Abstract

Kegiatan ini bertujuan untuk memperkenalkan dan meningkatkan pemahaman siswa SMP terhadap teknologi Artificial Intelligence (AI) sebagai bagian dari literasi teknologi dalam dunia pendidikan. Kegiatan ini dilaksanakan melalui workshop yang difokuskan pada pemahaman dasar AI dan aplikasinya dalam pembelajaran. Metode yang digunakan dalam kegiatan ini meliputi pendekatan interaktif dengan demonstrasi aplikasi AI, praktik langsung, serta diskusi kelompok untuk mendorong keterlibatan siswa. Evaluasi dilakukan melalui kuesioner dan observasi terhadap tingkat pemahaman siswa. Hasil kegiatan menunjukkan bahwa mayoritas siswa dapat memahami konsep dasar AI dan menunjukkan antusiasme yang tinggi terhadap penerapan teknologi ini dalam pembelajaran. Kuesioner evaluasi mengungkapkan bahwa 90 persen siswa merasa lebih percaya diri dalam menggunakan teknologi berbasis AI setelah mengikuti workshop. Meskipun demikian, keterbatasan perangkat dan akses internet di beberapa bagian sekolah menjadi kendala yang perlu diperbaiki. Kesimpulan dari kegiatan ini adalah workshop AI berhasil meningkatkan literasi teknologi siswa SMP YPUI Parung dan membangkitkan minat mereka terhadap teknologi. Oleh karena itu, disarankan untuk terus mengadakan workshop lanjutan dan meningkatkan fasilitas teknologi di sekolah guna mendukung pembelajaran berbasis teknologi yang lebih efektif.
Analisa Data Mining Untuk Prediksi Penjualan Produk Menggunakan Algoritma FP-Growth Berbasis Web Studi Kasus Online Shop Muslim Galeri Kanisisus Heatubun, Petrus; Fansyuri, Maulana
BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia Vol. 1 No. 6 (2024): BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia
Publisher : CV. Shofanah Media Berkah

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Abstract

Online Shop Muslim Galeri is one of the sellers of contemporary products in the field of clothing and goods, in sales in the era of globalization 4.0, Muslim Galeri is certainly in the business of selling using technology or manually by offering directly to potential consumers. Random sales provide a very unpredictable picture in predicting product sales, it is certainly very difficult to know the progress or decline of sales of what products are sold to the Muslim Gallery. The problem that exists in Muslim galleries is the need to predict product sales to consumers. With this, Data Mining will be applied in this study as a solution to predict the sales of Muslim Gallery products.The method used in the data processing process is using the FP-Growth algorithm. Data processing using this algorithm is expected to provide an easy solution in predicting product sales at the Muslim Gallery Online Shop.
Perancangan Sistem Informasi Penjualan Kopi Robusta di Café 86 Berbasis Web (Studi Kasus: Café 86) Muhamad Faisal; Maulana Fansyuri
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 10 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Cafe 86 is a coffee shop engaged in the beverage sector that sells a wide variety of drink menus by offering a varied menu, with good taste and quality of drinks and can meet customer tastes thereby increasing customer loyalty. Cafe 86 itself is located in the Tangerang city area, precisely on Jl. Bintang Sudimara Pinang Rt.03/04. The problem that is currently happening at Cafe 86 is that menu sales are done manually, cashiers are still doing the manual method by recording customer orders, so errors often occur in recording customer orders and resulting in data related to ordering data that is still very prone to being wrong or missing and requires long time. This resulted in less efficient employee work and slightly hampered customer service. The several research methods used include the following: Literature Study Literature study is the first step that researchers take in this study, Needs Analysis In conducting a sales system analysis, data is needed, as well as supporting tools for conducting a sales system analysis, Based on reports made by the author as explained in the previous chapter, the author draws the conclusion that, The resulting website-based application for ordering café 86 menus can make it easier to order drinks and food. because they have used a computerized system. With this web-based café 86 menu ordering application, employee performance becomes efficient because they no longer use the manual method.
Komparasi Algoritma Support Vector Machine Dan CART Untuk Klasifikasi Kualitas Udara Dki Jakarta Rizki Prayogi Widartama; Maulana Fansyuri
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 11 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Air quality or air quality is a measure of air condition at a certain time and place that is measured and/or tested based on certain parameters. Exposure to high levels of air pollution can cause various harms to health, which can increase the risk of respiratory infections, heart disease and lung cancer. Jakarta is ranked 12th as a regional capital for 2021 with an annual average concentration of PM2.5 – the highest on average. As for the Southeast Asia region, Jakarta is ranked 6th as the most populous regional polluted city. Uniform and precise air quality classification can be an important role for planning and introduction of relevant policies and regulations for air pollution management by decision makers, in carrying out the classification can use technical data mining. The Support Vector Machine (SVM) and Classification and Regression Tree (CART) algorithms are part of the classification method. In this study, an analysis and comparison was carried out to determine the performance of the two methods in classifying air quality in Jakarta in 2021. And the resulting SVM classification has an accuracy value of 95.05% and an error classification value of 4.95%, and the results of the CART classification are with an accuracy value of 99.67% and a misclassification value of 0.33%. It can be interpreted that the CART algorithm is better than SVM in classification classification to determine air quality in DKI Jakarta.
Sistem Pendukung Keputusan Berbasis Web untuk Pemilihan Lokasi Strategis Coffee Shop di Kota Yogyakarta dengan SMART Siswirawan, Andhika Prasetyo; Fansyuri, Maulana
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 6 No. 4 (2025): November
Publisher : Teknik Informatika Universitas Pamulang

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Abstract

The coffee shop industry in Yogyakarta has grown rapidly along with the increasing coffee consumption and the city’s strong tourism appeal. Selecting a strategic location is a key success factor for coffee shop businesses; however, this process is complex as it involves multiple criteria such as population density, crowd level, accessibility, rental price, and competition. This study aims to develop a web-based Decision Support System (DSS) using the Simple Multi-Attribute Rating Technique (SMART) method to assist entrepreneurs in determining the optimal coffee shop location. The research applied a quantitative approach through several stages: literature review, criteria identification, data collection, system design with UML, implementation using PHP-MySQL, and testing through Black Box and White Box. The results show that the developed system can provide objective, measurable, and user-friendly location recommendations. System testing confirmed that all functions work as designed, while user feedback indicated a high level of satisfaction. In conclusion, the web-based DSS application using the SMART method is effective for selecting strategic coffee shop locations in Yogyakarta. This system provides a practical solution for entrepreneurs to enhance decision-making quality, reduce subjectivity, and support business success in an increasingly competitive market.
Analisis Kinerja Algoritma Naive Bayes dalam Memprediksi Kelulusan Mahasiswa Menggunakan Python Fansyuri, Maulana; Yunita, Devi
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 3 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i3.1491

Abstract

Prediksi kelulusan mahasiswa menjadi kebutuhan penting dalam lingkungan perguruan tinggi untuk mendukung peningkatan kualitas akademik, efektivitas pembimbingan, dan strategi pencegahan ketidaklulusan. Penelitian ini bertujuan untuk menganalisis kinerja algoritma Naive Bayes dalam memprediksi kelulusan mahasiswa berbasis data akademik dan non-akademik dengan memanfaatkan bahasa pemrograman Python. Algoritma Naive Bayes dipilih karena memiliki karakteristik komputasi sederhana, efisien, serta mampu menangani data berukuran besar dengan performa klasifikasi yang kompetitif. Penelitian dilakukan menggunakan dataset mahasiswa yang mencakup variabel seperti indeks prestasi, jumlah SKS, tingkat kehadiran, dan status kelulusan. Proses pengolahan data terdiri atas pembersihan data, penyandian data kategorikal, pembagian dataset menjadi data latih dan data uji, serta pelatihan model Naive Bayes. Evaluasi model dilakukan menggunakan Confusion Matrix, Accuracy, Precision, Recall, dan F1-Score untuk memberikan gambaran performa klasifikasi secara komprehensif. Hasil penelitian menunjukkan bahwa algoritma Naive Bayes mampu melakukan prediksi kelulusan mahasiswa dengan akurasi tinggi, yaitu 85%, serta nilai Precision, Recall, dan F1-Score yang konsisten, sehingga menegaskan keandalan model dalam mengidentifikasi mahasiswa yang lulus maupun tidak lulus. Temuan ini memperkuat potensi algoritma Naive Bayes sebagai sistem pendukung keputusan di perguruan tinggi untuk memetakan risiko ketidaklulusan sejak dini.. Kata kunci:
Co-Authors Abdul Syukur Adinda Fatmah Afra Anggita Salsabila Agus Pangondian Silalahi Ahmad Farhan, Ahmad Ahmad Kahfi Djaelani Ajeng Trias M, Rizkyanti Akbar Prayudi, Lalu Alfatah, Alif Amalia Monitha Januari, Rossa Andika Arya Pratama Arifin, Teguh Ariyadi Anatasia, Alfi Arjuno Wibowo, Rayhan Aulia Rahman, Verrel Aulia Ramadhan, Salsabila Azzahra, Amalia Bagus Firmansyah Budiman Nadapdap, Panri Deanova, Ryanda Deko Triyadi DENI SETIAWAN Devi Yunita Devi Yunita Devi Yunita Dian Nurul Iman Diky Hernadi Dimas Aribi Dimas Setiawan Dwi Santoso, Rendi Dwitama Saputra, Farhan Dzikri Fauzi Ramdhani Eduard Elmansius Zebua Ekrinifda, Ardilla Eprilianto, Winky Erika Alfira Lia Fachri Ramdhani, Tyas Fatimah Az-zarro Fauzan Hazami, Ahmad Fazril Ramadhan Fready Anggara Gideon Triman Harefa Hanif, Abdul Helen Chandra Dewi Hernadi, Diky Hibatullah Ferniko, Tegar hidayatullah Al Islami Ikhlas Syahidan Zai, Muhammad Ikhwanul Maghsauma Jordi Ricaldo Kanisisus Heatubun, Petrus Kartika Putri, Dila Khoirun nisya Khoirunnisya Khoirunnisya Khoirunnisya Khoirunnisya, Khoirunnisya Kidunga, Lyra Laela S, Mutiara Lusiyanti Lu’ay Shafa Apta Hermawan Ma'mum, Sukron Marsiano, Joseph Marvella, Shera Meriansyah, Yuda Mikael Immanuel Christianto Moh Fiqhi Nur Hidayatulloh Mohamad Ryan Herdiyana Mohamad Ryan Syekhan Ramadan Muhamad Faisal Muhammad Akhdan Irfan Muhammad Azzam Pridana Muhammad Fiqih Muhammad Ikhwan Muhammad Rifaldi, Aldi Muhammad Rizki Rahmatullah Murni Nabila, Dhaifina Naia Natasya, Ris Nani Suningrat Nasywa Sakha Ningrum Nata Pratama, Fadhil Nice, Kristina NUR HASANAH Nur Naimah, Fatika Nurhasanah Nurhasanah Nurhasanah Nurhasanah Nurkholis Ajie Kurniawan, Muhammad Nursarah Sahirah Pramudya Wirananda, Muhammad Pratama, Arijal Pratama, Reza Putra Mulya, Ageng Rafly Thabroni, Mochammad Rianto, Risky Ricky Tri Setiawan Putra Riki Baehaki Rivan Saputra, Rivan Rizki Murtadho Rizki Prayogi Widartama Robby Azzukruf Routya Faizan, Alfreza Sagita Octaviani, Kezia Saputra, Saldy sesilawati Shahrudin Shelvi Eka T Sheny Aprilia Ningsih Sherlvi Eka Tassia Silviana, Fijriani Siswirawan, Andhika Prasetyo Susanna Dwi Yulianti Kusuma Tassia, Shelvi Eka Teguh Riyanto Tipalahi, Ramdan Tri Mustakim, Raka Ulfa Valentino Rattu, Samuel Wafiqah Nur Azizah Wahyu Nur Pambuko Wulandari Ega M, Nadya Yaqumi, Zesi Yehezkiel Yulianti K, Susanna Dwi