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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Prosiding SNATIF Proceeding SENDI_U Jurnal Ilmiah KOMPUTASI RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Surya Medika Jurnal Kedokteran dan Kesehatan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal DISPROTEK Jurnal Nasional Komputasi dan Teknologi Informasi Jurnal Kreativitas PKM Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Jurnal Teknologi Informasi dan Pendidikan Building of Informatics, Technology and Science Journal of Information Systems and Informatics bit-Tech Abdi Masyarakat International Journal of Marine Engineering Innovation and Research Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Indonesia Berdaya Journal of Information Technology Ampera Jurnal Promotif Preventif Jurnal Sistem Informasi Indonesian Journal of Technology, Informatics and Science (IJTIS) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Journal of Software Engineering Ampera Jurnal UNITEK Jurnal Dialektika Informatika (Detika) Global Abdimas: Jurnal Pengabdian Masyarakat Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat International Journal of Management Science and Information Technology (IJMSIT) Muria Jurnal Layanan Masyarakat PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Buletin Abdi Masyarakat (BAM) Jurnal Kalibrasi Abdi Cendekia: Jurnal Pengabdian Masyarakat Florona : Jurnal Ilmiah Kesehatan Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Innovative: Journal Of Social Science Research Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) Jurnal Sistem Informasi Galuh Jurnal Sistem Informasi dan Manajemen GEMBIRA (Pengabdian Kepada Masyarakat) Jurnal Ilmu Komputer dan Sistem Informasi Journal Artificial: Informatika dan Sistem Informasi Jurnal Penelitian Multidisiplin Bangsa Jurnal Bisantara Informatika Joong-Ki Galuh International Journal of Community Service and Development Health Safety Environment Journal ABDINE :Jurnal Pengabdian Masyarakat
Noor Latifah
Universitas Muria Kudus
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Pengelolaan Bank Sampah Muria Berseri berbasis Digital Desa Gondangmanis Kabupaten Kudus Laily Fithri, Diana; Setiawan, Rhoedy; Cahyo wibowo, Budi; Nugraha, Fajar; Latifah, Noor
ABDINE: Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2024): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Riau Pesisir

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v4i1.825

Abstract

Sampah merupakan persoalan yang sering timbul di lingkungan masyarakat. Jumlah sampah cenderung terus mengalami peningkatan seiring dengan pertambahan jumlah penduduk serta bertambahnya konsumsi masyarakat. Persoalan sampah jika tidak dikelola dengan baik akan menimbulkan berbagai masalah, terutama masalah kesehatan dan lingkungan sehingga memerlukan pengelolaan dengan terpadu dan baik. Hal ini tentunya juga dialami oleh warga masyarakat di kawasan desa Gondangmanis kabupaten Kudus.Untuk  melakukan pengelolaan sampah warga di desa Gondangmanis didirikan Bank Sampah Muria Berseri. Pada proses penerimaan sampah yang saat ini dilakukan pendataan dengan pencatatan secara tertulis dicatat dalam sebuah buku besar kemudian disalin kembali kebuku tabungan sampah milik nasabah bank sampah. Pada proses realisasi perhitungan tabungan bank sampah juga dilaksanakan penghitungan secara manual dengan mendata satu persatu tabungan sampah milik nasabah yang telah masuk ke bank sampah. Hal tersebut tentunya mengakibatkan pekerjaan menjadi kurang efektif dan efisien dalam pengelolaan bank sampah.Berdasarkan latar belakang tersebut Tim Pengabdian akan membantu pengelola bank sampah dalam melakukan pengelolaan bank sampah secara digital melalui pengembangan aplikasi sistem pengelolaan bank sampah berbasis digital. Metode yang dipakai dalam pelaksanaan program pengabdian ini adalah melakukan pendampingan dan penerapan sistem pengelolaan manajemen bank sampah untuk mengatasi permasalahan keterbatasan bidang pengelolaan bank sampah Muria Berseri
Multi-Platform Sentiment Analysis of Diabetes Mellitus on X and TikTok Using K-Nearest Neighbor, Chi-Square Selection, and Oversampling Asti Devi Mutiara Khoirun Nisa; Noor Latifah; R. Rhoedy Setiawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8061

Abstract

Diabetes mellitus is a chronic health condition that is widely discussed by the public on social media, generating a large volume of opinions that are difficult to interpret manually. This study analyzes public sentiment toward Diabetes mellitus using data collected from X (Twitter) and TikTok. Text data were preprocessed (cleaning, slang normalization, stopword removal, and stemming) and duplicate entries were removed. Sentiment labels were generated automatically through a rule-based lexicon across four categories (positive, negative, neutral, and irrelevant/discarded), and the reliability of this automatic labeling was verified through manual validation of a stratified sample of 200 data points, measured using Cohen's Kappa. Positive and negative data were then weighted using TF-IDF, reduced using Chi-Square feature selection, balanced using SMOTE, and classified using K-Nearest Neighbor (KNN). Model performance was evaluated using accuracy, precision, recall, and F1-score, and compared across four scenarios: baseline KNN, KNN with Chi-Square, KNN with SMOTE, and the combined KNN+Chi-Square+SMOTE model. The manual validation of 198 valid samples produced an agreement accuracy of 59.60% and a Cohen's Kappa of 0.459 (moderate agreement), indicating that the main source of disagreement lies at the boundary between the neutral and sentiment-bearing classes, while direct positive-negative misclassification was rare (4.5%). The combined model achieved an accuracy of 82.86%, with a macro-averaged precision of 82.95%, recall of 83.56%, and F1-score of 82.79%. Interestingly, Chi-Square feature selection alone yielded the highest accuracy among the four scenarios (85.10%), suggesting that feature selection contributed more to performance gains than class balancing in this dataset. These findings suggest that combining feature selection and oversampling techniques improves the reliability of multi-platform sentiment classification for health-related topics and can inform more effective public health communication strategies regarding diabetes.
Decision Support System for Selecting the Best Smartphone Using the Multi Attribute Utility Theory (MAUT) Method at Sinar Mas Selluler Kudus Arina Fawaida; Noor Latifah; Yudie Irawan
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8145

Abstract

The increasing variety of smartphone products with different specifications and prices makes the selection process more difficult for customers and often results in subjective recommendations from sales personnel. This study aims to develop a web-based Decision Support System (DSS) for smartphone selection at Sinar Mas Selluler Kudus using the Multi Attribute Utility Theory (MAUT) method. The system evaluates smartphone alternatives based on five criteria: Random Access Memory (RAM), Internal Storage, Screen Size, Battery Capacity, and Price. The research employed the System Development Life Cycle (SDLC) approach, including planning, analysis, design, implementation, and testing. The MAUT method was applied through criteria weighting, utility normalization, preference value calculation, and ranking to generate objective recommendations. The developed system was functionally validated using Black Box Testing to ensure that all system features operated according to the specified functional requirements. The developed system successfully automated the evaluation process, reduced subjective decision-making, and improved the efficiency of smartphone selection. The calculation results showed that Huawei (A3) achieved the highest preference value of 0.7215, indicating that it is the most suitable smartphone alternative according to the predefined criteria and weights. The implementation results demonstrate that the proposed system can assist sales personnel in providing objective recommendations while helping customers compare smartphone alternatives more efficiently based on their preferences and budget constraints. Therefore, the proposed system provides accurate, transparent, and consistent recommendations to support customers and sales personnel in making better purchasing decisions.
Comparative Performance of Apriori, FP-Growth, and ECLAT for Menu Bundling Astriana Putri Kumala Dewi; Noor Latifah; Supriyono Supriyono
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13696

Abstract

Transaction data at Selaras Coffee and Space had not been systematically utilized to evaluate menu combinations or determine which association rule mining algorithm best suited the data characteristics. This study compares Apriori, FP-Growth, and ECLAT for generating menu-bundling recommendations. Sales records from 1–31 December 2025 were preprocessed by removing 950 operational transaction-item pairs, resulting in 6,213 transactions and 76 unique menus. The algorithms were evaluated on the same binary matrix using a minimum support of 0.01, a minimum confidence of 0.20, and a lift ratio greater than 1. The evaluation included parameter sensitivity, 30 repeated measurements of execution time and peak Python memory allocation, scalability using 25–100% of the transactions, and rule quality based on support, confidence, lift, leverage, conviction, and cosine similarity. All algorithms produced identical outputs of 68 frequent itemsets and five eligible rules. On the full dataset, ECLAT recorded the lowest mean execution time at 0.037701 s, followed by Apriori at 0.040419 s and FP-Growth at 0.069637 s. FP-Growth used the lowest mean peak memory at 1.026966 MB, while ECLAT showed the lowest runtime growth as the dataset size increased. The strongest rule was Mie Laksa → Air Mineral 330 Ml, with a lift of 2.755987. These findings show that no algorithm dominated every criterion: ECLAT offered the best full-data runtime and scalability, FP-Growth was the most memory-efficient, and the extracted rules provided measurable candidates for menu-bundling strategies.
Decision Support System for Determining Signature Menus Using the Integration of BMW, MOORA, and Copeland Scores Meta Ardi Setiawan; Anteng Widodo; Noor Latifah
Building of Informatics, Technology and Science (BITS) Vol 8 No 2 (2026): September 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i2.10936

Abstract

Menu optimisation is a crucial yet challenging challenge for business sustainability because the speciality coffee sector is marked by dynamic consumer tastes and a high degree of product diversity. This study tackles a basic operational issue at Inti Coffee, where a subjective, intuition-based method is currently used to identify "signature offerings"the important menu items that ought to be given priority for promotion, inventory, and resource allocation. This current process, which mainly depends on the owner, operational manager, and lead barista's intuition, is intrinsically vulnerable to individual cognitive biases, personal taste preferences, and inconsistent evaluation, which frequently results in less than ideal menu performance and lost revenue opportunities. The main goal of this research is to develop and deploy an online Decision Support System (DSS) that offers a transparent, data-driven, and organised framework for objectively ranking menu items in order to get around these restrictions. A hybrid multi-criteria decision-making (MCDM) technique is included into the suggested system to guarantee group unanimity and robustness. In order to minimise pairwise comparison inconsistencies and capture the knowledge of the three primary decision-makers, the Best-Worst Method (BWM) is first used to systematically extract the relative relevance weights of six different evaluation criteria. Second, a thorough dataset of 500 real sales transactions is used to assess and rank 51 menu alternatives using the MOORA (Multi-Objective Optimisation on the basis of Ratio Analysis) method. Both financial parameters (total items sold, HPP or cost of goods sold, and profit margin) and operational characteristics (uniqueness of taste score, preparation time, and ingredient lifetime) are included in the evaluation criteria. In order to successfully resolve any potential conflicts between decision-makers, the Copeland Score is finally used to combine the individual preference rankings into a single, collective group score. This study makes three main contributions: first, it develops a novel integrated DSS framework that integrates BWM, MOORA, and Copeland Score into a single unified workflow specifically designed for signature menu selection; second, it involves three different stakeholders (owner, operational manager, and head barista) in the group decision-making process, ensuring that the final recommendation reflects a balanced consensus rather than individual bias; and third, it creates a fully functional web-based system with statistical validation tools that empirically verify the accuracy and dependability of the recommendations using Spearman correlation, RMSE, and overlap ratio against actual customer preferences. The creation of a useful, web-based DSS that turns menu curating from an art to a science and offers a reproducible model for other food and beverage businesses is the main contribution of this research. With a MOORA score of 0.249180 and a Copeland Score of 50, the interim results show that the system is able to identify "Kopi Susu Aren" as the best-performing signature item. A poll involving 130 participants was carried out to verify the system's output against human judgement in the actual world. In addition to a low Root Mean Square Error (RMSE) of 5.5734 and an overlap ratio of 66.7%, the results show a strong positive correlation (Spearman's rho = 0.9238) between the system's ranks and participant feedback, proving the system's high accuracy and practical applicability. In order to provide scalability and usability for continuous operational choices, the DSS is implemented using a combination of PHP Native, Python, MySQL, and a testing dashboard based on Streamlit.
Co-Authors - Supriyono Achmad Fauzi Adzani Ghani Ilmannafian Agus Tiyo, Muhammad Savra Ahyudiya, Higan Nanda Ainur, Ghefira Al Maududi, Abul A'la Al-Maududi, Abul Ala Andi Agus Setyawan Andriawan, Yogi Andriawan, Yogi Andy Prasetyo Utomo Anggraeny, Wahyu Kartika Anisa Handayani Annas Fatia, Imelda Anteng Widodo Anwar Mallongi Aprilia, Tyas Ardila, Septiyani Arfiyan, Farel Dani Ari Adaninggar Arif Setiawan Arina Fawaida Arinda, Yosi Duwita Asih, Erny Asti Devi Mutiara Khoirun Nisa Astriana Putri Kumala Dewi Atik Rokhayani Azizah Zen Baiti Rahman Berliana Adya Wulandari Budi Cahyo Wibowo Dewi Masitoh Dian Aditya Diana Laily Fithri Diana Laily Fithri Diana Laily Fithri Dihartawan, Dihartawan Diyas Aditya Adi Saputra DWI RAHMAWATI Eko Darmanto Elsya Vera Indraswari Erlina Nofianti Ernyasih, Ernyasih Fadina Salwa Aulia Putri Fajar Nugraha Fajrini, Fini fatia, imelda annas Fatmala, Indah Fauzi, Sa'ad Fauzia, Ghina Zahrotul Fawwaz, Muhammad Taufiq Febrina Larasati Ferry Ferdiansyah, Ferry Ghefira Ainur Ghufriyyah, Shinta Gilang Anugerah Munggaran Gudnanto Hakim, Chaerul Wisnu Handayani, Rosmawati Herdiansyah, Dadang Herlina Sari, Nurya Hidayat, Hilmi Bayu Higan Nanda Ahyudiya Ida Ayu Putu Sri Widnyani Ika Friscila, Ika Imam Abdul Rozaq Iman, Hadad Karsa Nur Indriani Zabrina Putri Irawati, Diana Izzatul Wahyuningsih Jaksa, Suherman Januar Ariyanto Jarir Bafadlol Albayhaqi Juhazty, Meti Brendha Kharisma, Dayu Swasti Kristiana, Isha Desty Kurniasari, Nita Kurniawan, Rizky Dwi Kusumawardhana, Muhammad Anton Laily Fithri, Diana Lina Anjelina Lisa Rachmawati Lubis, Anwar Lukito, Aji Lusida, Nurmalia Madiana, Tiara Septya Mariatul Kiptiah Marlina Oktaviani Maulidiawati, Chyntia Melviani, Melviani Meta Ardi Setiawan Mochammad Imron Awalludin Mubarrizi, Nor Muhammad Muhammad Muhammad Arifin Muhammad Indra Darmawan Muhammad Maulana Abdurrohman Muhammad Rizky muhammad rizky, muhammad Muhammad Shofiyuddin Muhammad Sukron Ma'mun Munaya Fauziah Nada Kusumawardani Nadiva Naifa Najla Nafar Ja’far Ashidiqi Nafi’ Inayati Zahro Nastiti, Kunti Natashia, Dhea Nishwatul Khofifah Noor Yulita Dwi Setyaningsih Nova Briyan Haidar Novanto, Ilham Setyo Nujulla, Puspa Odang, Maulidina Salsabilla Pawestri, Hasna Pratomo Setiaji Purwanto, Ari Joko Putri Handayani Putri Kurnia Handayani Putri, Vivinda Trisnowati R Rhoedy Setiawan Rahman, Nisa Aulia Rayhana, Rayhana Restu Prayoga, Hendrika Ricko Muhammad Firdaus Rike Syahniar Rina Fiati Rina Saputri Rohama, Rohama Romadhon, Zainur Romdhona, Nur Sa'dan, Ahmad Setyawan, Andi Agus SG, Hardiman Shofiani Dwi Natalia Slamet Rahayu Slametiningsih, Slametiningsih Sofian, Ahmad Soni Adiyono Suherman, Suherman Sulistina Rini Supriyono Supriyono Supriyono Suryaalamsah, Inne Indraaryani Sutono Sutono Sutono Syafiul Muzid Tiara Septya Madiana Triana Srisantyorini Triya Adzani Maulidina Tutik Khotimah Viki Muliawati Wulandari Wahdah, Rabia Wiwit Agus Triyanto Wulandari, Berliana Adya Yudie Irawan Zakaria Mubarok, Adhi Zulfa Himmatul Ulya Zuyyina Syarifa Yahya