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All Journal Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal INSYPRO (Information System and Processing) JURNAL INSTEK (Informatika Sains dan Teknologi) JURTEKSI JTP - Jurnal Teknologi Pendidikan Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Ainet : Jurnal Informatika Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia Buletin Sistem Informasi dan Teknologi Islam Jurnal Informatika Progres Jurnal INFOTEL Pangulu Abdi: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmu Pengetahuan dan Teknologi Bagi Masyarakat
LUKMAN ANAS
UNIVERSITAS MUHAMMADIYAH MAKASSAR
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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IMPLEMENTASI HYBRID LEXICON-BASED DAN SVM UNTUK KLASIFIKASI ANALISIS SENTIMEN TERHADAP PELATIHAN BBPSDMP KOMINFO MAKASSAR Nur Alam; Muhammad Faisal; Rizki Yusliana Bakti; Muhammad Syafaat; Andi Makbul Syamsuri; Muhyiddin AM Hayat; Andi Lukman Anas
PROGRESS Vol 17 No 2 (2025): September
Publisher : P3M STMIK Profesional Makassar

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Abstract

The evaluation of government training programs is often hindered by manual analysis of unstructured qualitative feedback, making the process inefficient and subjective. This study aims to implement and evaluate a sentiment classification model using a hybrid Lexicon-Based and Support Vector Machine approach to analyze participants’ perceptions of the Vocational School Graduate Academy training organized by BBPSDMP Kominfo Makassar, as well as to compare the performance of a standard SVM model with a model optimized using Particle Swarm Optimization. This quantitative research employs 2,313 unstructured review data, which undergo text preprocessing, initial lexicon-based labeling, and TF-IDF feature extraction before being classified using an SVM with an RBF kernel. The results show that the SVM model optimized with PSO consistently outperforms the standard model across all four evaluation aspects, with the most significant accuracy improvement observed in the instructor category from 84.71% to 89.02% and in the assessor category reaching 91.46%. PSO optimization has proven effective in enhancing the model’s ability to identify negative sentiments, which represent the minority class. The hybrid approach with PSO optimization is capable of producing a more accurate and balanced classification system, with practical implications as an objective automated evaluation tool.
PENERAPAN ALGORITMA MOBILENETV2 UNTUK KLASIFIKASI HURUF HIJAIYAH BERBASIS GESTUR TANGAN Muh. Riswan; Titin Wahyuni; Chyquitha Danuputri; Emil Agusalim Habi Talib; Muhammad Faisal; Lukman Anas; Andi Agung
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

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Abstract

The digitalization of religious education offers significant opportunities to enhance Hijaiyah letter learning, particularly for the hearing-impaired community through visual gesture recognition. This study aims to develop and evaluate a real-time web-based classification system for 28 Hijaiyah hand gestures using the MobileNetV2 architecture. The research methodology involves a quantitative approach utilizing transfer learning with a balanced dataset of augmented images. The model was trained using fine-tuning techniques and deployed on a web platform using TensorFlow.js and MediaPipe for efficient on-device inference. Experimental results demonstrate that the model achieved an overall accuracy of 84% on the independent test set, with specific classes reaching near-perfect detection in real-time scenarios, although misclassification persisted among visually similar gestures. The system effectively balances computational efficiency with classification performance, minimizing latency during user interaction. In conclusion, the implementation of MobileNetV2 facilitates a responsive and accessible educational tool, proving the viability of computer vision in creating inclusive religious learning environments without requiring complex server-side infrastructure.
Peningkatan Keterampilan Kelompok Julu Atia melalui Pelatihan Pembuatan Nugget Rumput Laut Kasmiati Kasmiati; Irma Andriani; Muh. Nasrum Massi; Rahmi Rahmi; Lukman Anas; Furqan Zakiyabarsi
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 10 No 1 (2026): Volume 10 Nomor 1 Tahun 2026
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v10i1.24591

Abstract

Seaweed is a leading commodity in the fisheries sector that has not been optimally utilized, particularly by community groups, to increase its added value. The problem faced by these groups is a lack of knowledge and skills in processing and selling seaweed-based products. This activity aims to improve the knowledge and skills of "Julu Atia" partners in the production and marketing of seaweed nuggets. The method used was to directly involve 20 members in training and mentoring activities. The training included counseling and practical training on nugget production and marketing, while the mentoring aimed to evaluate the group's ability to independently produce and market the product. Initial knowledge and skills of partners were determined through pre- and post-tests. The results showed that partner knowledge was relatively low, with an average of 34.5%, increasing by 55% to 89.5% after participating in the community service activity. Through nugget production, the added value increased by IDR 222,000 per kg of seaweed. Thus, this activity effectively increased the empowerment level of "Julu Atia" and can be replicated in other groups to improve the welfare of coastal communities.
PENERAPAN ALGORITMA HIDDEN MARKOV MODEL PADA PREDIKSI EKSPOR KOMODITI BIJI KOPI Wiwin Fuad Sanjaya; Fahrim Irhamna Rachman; Emil Agusalim Habi Talib; Muhammad Faisal; Lukman Anas; Muhammad Syafaat S. Kuba; Indriyanti Azis
PROGRESS Vol 18 No 2 (2026): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i2.466

Abstract

Fluktuasi volume dan nilai ekspor komoditas biji kopi Indonesia dipengaruhi oleh faktor dinamis yang tidak dapat diamati secara langsung, seperti pergeseran kondisi pasar internasional dan dinamika iklim. Penelitian ini bertujuan untuk menerapkan algoritma Hidden Markov Model (HMM) dalam memodelkan tren tersembunyi (hidden states) serta memprediksi tren ekspor biji kopi. Dataset yang digunakan merupakan data historis bulanan ekspor biji kopi periode 2020–2024. Estimasi parameter dilakukan menggunakan algoritma Baum-Welch, sedangkan performa model dievaluasi menggunakan metrik Mean Absolute Error (MAE) dan Root Mean Square Error (RMSE) serta dibandingkan dengan metode Seasonal Naïve (S-Naïve). Hasil penelitian menunjukkan bahwa HMM mampu mengidentifikasi tiga state utama (Naik, Stabil, dan Turun) dengan nilai MAE sebesar 20,81 dan RMSE sebesar 28,45. Performa HMM melampaui metode S-Naïve yang memiliki MAE sebesar 35,12. Dengan demikian, pendekatan HMM terbukti adaptif dalam menangkap volatilitas dan transisi kondisi pasar pada komoditas biji kopi.
Co-Authors Abd Halik Lateko Abdul Rakhim Nanda Adi Malik Muhammad Mutsuhito Agung, Andi Ahmad Risal Alfiani, Ananda Andi Agung ANDI AGUNG DWI ARYA BULU Andi Makbul Syamsuri ANDI MAWADDA TAIBA MAWADDA TAIBA Andi Muhammad Akbar Andi Yusri andi Yusri Arvianda Asep Indra Syahyadi Aswad, Muh. Akhwan Adam Bakti, Rizki Yusliana Basir, Basri Chatarina Umbul Wahyuni Chyquitha Danuputri Danuputri, Chyquitha Dayang Aisyah Dian Pramana Putra, Dian Pramana Emil Agus Salim Habi Talib Emil Agusalim H. T Fachrim Irhamna Rachman Fahmi Ramadhan S Fahrim I. Rahman Fahrim Irhamna Rachman Firman Firman Furqan Zakiyabarsi Herdiansyah Herdiansyah Indriyanti Azis Irma Andriani Kasmiati Kasmiati Kazman Riyadi Lukman M a h a r i d a Muh. Akhwan Adam Aswad Muh. Nasrum Massi Muh. Riswan Muhammad Asygar Faeruddin Muhammad Faisal Muhammad Syafaat S. Kuba Muhsin, Arief Muhsin, Muh Arief Muhyiddin A.M Hayat Mujadilah, Siti Muniardi Muniardi Muniardi, Muniardi Nadir Nadir Namora, Namora Nandy Rizaldy Najib Nur Alam Nur Alam Nur Annisa Syarifuddin Nur Fadillah Sari Rahman Rahman Rahman, Erik RAHMANIA Rahmania Rahmaniah, Rahmaniah Rahmi Rahmi Reski Amalia Salam Rezki Nurdin Ridwang Ridwang Ridwang Ridwang Ridwang, Ridwang Riswan, Muh. Saleh, Syafiuddin Sarina Setiawan, Tommy Reynaldy Syadiah Nor Wan Shamsuddin SYAFAR, A. MUHAMMAD Syafiuddin Saleh Syahril Akbar SYAHYADI, ASEP INDRA TANTRI INDRABULAN Titin Wahyuni Wahyuddin Wiwin Fuad Sanjaya