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All Journal Jurnal Momentum Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JMM (Jurnal Masyarakat Mandiri) JOISIE (Journal Of Information Systems And Informatics Engineering) Jurnal Teknologi Informasi dan Pendidikan JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Intelligent Decision Support System (IDSS) Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Applied Data Sciences Jurnal Mandiri IT Jurnal Ipteks Terapan : research of applied science and education Jurnal Teknologi Jurnal Quancom: Jurnal Quantum Komputer The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Pustaka Robot Sister
Ruri Hartika Zain
Universitas Putra Indonesia YPTK Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Veterinary Other

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PENERAPAN TEOREMA BAYES PADA SISTEM PAKAR DIAGNOSA GASTROINTESTINAL Wahyuni, Suci; Wiyandra, Yogi; Zain, Ruri Hartika; Kurnia, Hezy; Yenila, Firna
Journal of Information System Management (JOISM) Vol. 5 No. 2 (2024): Januari
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2024v5i2.1396

Abstract

Gastrointestinal merupakan penyakit yang disebabkan oleh permaslaahan pada bagian pencernaan yang memiliki fungsi yang tidak maksimal. Hal tersebut terjadi disebabkan karena proses penyerapan makanan dan nutrisi menjadi tidak seimbang. Sistem gastrointestinal melibatkan semua organ dalam dari mulut sampai anus. Pentingnya pemahaman tentang permasalahan gastrointestinal perlu disosialisasikan untuk memberikan edukasi kepada Masyarakat mengenai kondisi tersebut. Salah satu alasan dalam melakukan penelitian ini adalah memberikan informasi berbasis pengetahuan melalui aplikasi yang disampaikan oleh pakar dalam memberikan edukasi kepada Masyarakat mengenai gastrointestinal. Penelitian ini dilakukan dengan menggunakan aplikasi berbasis online berupa sistem pakar dengan mengusung metode teorema bayes yang mampu menghubungkan tingkat keyakinan user (prior) kepada keyakinan baru (posterior) setelah adanya suatu observasi baru (evidence) berdasarkan kemungkinan tertentu. Hasil penelitian ini terhadap ujicoba salah satu rule yang diberikan memberikan nilai keyakinan 32.04% sehingga pengujian tersebut memberikan nilai sesuai dengan ketentuan yang telah ditetapkan oleh pakar.
PELATIHAN PEMANFAATAN TEKNOLOGI DIGITAL UNTUK MENINGKATKAN KEAMANAN DAN PERTUMBUHAN UMKM DI ERA TRANSFORMASI DIGITAL Zain, Ruri Hartika; Afira, Riandana; Awal, Hasri; Yani, Zulfitri
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Volume 6 No. 1 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i1.41392

Abstract

UMKM memegang peranan penting dalam perekonomian Indonesia, namun banyak pelaku usaha menghadapi kesulitan dalam beradaptasi dengan kemajuan teknologi digital. Di era transformasi digital, pemanfaatan teknologi dapat meningkatkan efisiensi operasional, memperluas pasar, dan memperkuat keamanan data serta transaksi bisnis. Oleh karena itu, pelatihan tentang pemanfaatan teknologi digital sangat dibutuhkan untuk mendukung pertumbuhan dan keberlanjutan UMKM. Pengabdian masyarakat ini bertujuan untuk memberikan pelatihan kepada pelaku UMKM mengenai penggunaan teknologi digital yang tepat, khususnya dalam aspek keamanan digital dan pemasaran online. Metode yang digunakan dalam pengabdian ini adalah pelatihan langsung yang mencakup topik penggunaan aplikasi keamanan, platform e-commerce, serta teknik pemasaran digital. Hasil dari pelatihan menunjukkan adanya peningkatan pemahaman peserta dalam menggunakan teknologi digital secara aman dan efektif, yang berpengaruh positif terhadap pertumbuhan usaha dan pengelolaan data. Pelatihan ini terbukti penting untuk membantu UMKM agar dapat bersaing di pasar digital secara lebih aman dan berkembang.
Robust Predictive Model for Heart Disease Diagnosis Using Advanced Machine Learning Techniques Sovia, Rini; Anam, M. Khairul; Wisky, Irzal Arief; Permana, Randy; Rahmi, Nadya Alinda; Zain, Ruri Hartika
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1092

Abstract

This study presents a hybrid ensemble learning framework designed to enhance the predictive accuracy, robustness, and generalizability of heart disease classification models. The framework integrates three base classifiers: Decision Tree (DT), Gaussian Naive Bayes (GNB), and K Nearest Neighbor (KNN), which are combined using a stacking ensemble method with Logistic Regression (LR) as the meta learner. Each classifier contributes a distinct analytical perspective: DT models nonlinear relationships, GNB provides probabilistic reasoning, and KNN captures similarity-based patterns. Logistic Regression aggregates their outputs to produce a unified predictive decision. To mitigate class imbalance commonly observed in clinical datasets, the Synthetic Minority Oversampling Technique (SMOTE) is applied to generate synthetic samples of the minority class, improving the model’s ability to recognize underrepresented cases. Hyperparameter optimization is performed using the Optuna framework, which applies the algorithm to efficiently explore parameter configurations. The proposed model was evaluated on a publicly available heart disease dataset and achieved an accuracy of 99.61%, precision of 99.62%, recall of 99.59%, F1 score of 99.60%, and specificity of 99.58%, corresponding to a false positive rate of only 0.42 percent. These results demonstrate the framework’s strong ability to accurately identify heart disease cases while minimizing misclassification. The integration of SMOTE, stacking, and Optuna optimization contributes to its superior performance and robustness. Consequently, this approach shows strong potential for integration into clinical decision support systems to assist healthcare professionals in reliable and timely diagnosis.
Minimize shipping costs from multi-warehouse to multi-outlet with VAM and MODI Riandari, Fristi; Zain, Ruri Hartika
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.506

Abstract

Distribution costs are a dominant component in logistics operations, especially in multi-warehouse to multi-outlet delivery schemes involving variations in supply capacity, demand, and route costs. This study aims to minimize shipping costs by modeling the problem as a Transportation Problem (TP), generating an initial solution using Vogel's Approximation Method (VAM), and ensuring an optimal solution using the Modified Distribution Method (MODI). The case study was conducted in one planning period with input data in the form of a matrix of shipping costs per unit, supply capacity per warehouse, and demand per outlet (balanced condition). The results show that the baseline distribution cost is 4,898 (thousand IDR), while the initial VAM solution reduces the cost to 3,777 (thousand IDR). After optimality testing and improvements using MODI, the minimum cost is 3,605 (thousand IDR), with an additional improvement of 172 (thousand IDR) from the VAM solution. Compared to the baseline, the optimal solution provides savings of 1,293 (thousand IDR) or 26.40%, without violating the supply-demand constraint. These findings confirm that the VAM-MODI flow is effective as a fast, audit-friendly, and applicable end-to-end procedure for the preparation of minimum cost delivery plans in logistics companies.
PEMBERDAYAAN SISWA SMK PERHOTELAN DALAM SPEAKING BAHASA INGGRIS FRONT OFFICERS MENGGUNAKAN TEKNOLOGI APLIKASI BERBASIS PYTHON Christina, Dian; Zain, Ruri Hartika; Adha, Annisha Dyuli
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 6 (2025): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i6.35626

Abstract

Abstrak: Keterampilan berbicara bahasa Ing,gris merupakan kemampuan penting bagi siswa SMK Perhotelan, terutama bagi mereka yang akan bekerja di bidang front office. Namun, pembelajaran di sekolah sering kali masih berfokus pada teori dan kurang memberikan kesempatan praktik berbicara secara aktif. Kegiatan pengabdian kepada masyarakat (PKM) ini bertujuan untuk memberdayakan siswa melalui pelatihan speaking berbasis aplikasi Python yang dirancang untuk melatih percakapan interaktif dalam konteks pelayanan hotel. Fokus dari pelatihan ini untuk meningkatkan soft skill siswa, terutama dalam hal komunikasi dan kepercayaan diri dalam berbahasa inggris. Kegiatan ini melibatkan 34 siswa jurusan Perhotelan yang mengikuti pre-test dan post-test, dengan 20 soal yang digunakan untuk mengukur peningkatan kemampuan berbicara mereka. Hasil analisis data menggunakan uji Wilcoxon menunjukkan nilai signifikansi < 0,001, yang berarti terdapat peningkatan kemampuan berbicara secara signifikan setelah pelatihan. Berdasarkan hasil posttest, kompetensi speaking siswa meningkat sebesar 17,5%. Hasil ini membuktikan bahwa penerapan teknologi berbasis Python efektif dalam meningkatkan kompetensi komunikasi siswa, serta relevan dengan kebutuhan dunia industri perhotelan.Abstract: English speaking skills are crucial for vocational high school students majoring in Hospitality, especially for those who will work in the front office. However, learning in schools often still focuses on theory and lacks opportunities for active speaking practice. This community service activity (PKM) aims to empower students through Python-based speaking training designed to practice interactive conversations in the context of hotel services. The focus of this training is to improve students' soft skills, particularly in terms of communication and confidence in speaking English. This activity involved 34 students majoring in Hospitality who took pre-tests and post-tests with 20 questions used to measure improvements in speaking skills. Data analysis using the Wilcoxon test showed a significance value of < 0.001, indicating a significant improvement in speaking skills after training. Based on the post-test results, students' speaking competency increased by 17.5%. These results prove that the application of Python-based technology is effective in improving students' communication skills and is relevant to the needs of the hospitality industry.
A mixed integer linear programming approach for last-mile e-commerce optimization through micro-fulfillment centers Riandari, Fristi; Zain, Ruri Hartika
Journal of Intelligent Decision Support System (IDSS) Vol 9 No 1 (2026): March: 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.v9i1.338

Abstract

The rapid growth of e-commerce increases the complexity of last-mile delivery due to high distribution costs, urban congestion, and increasingly tight delivery time demands. This study proposes a Mixed Integer Linear Programming (MILP) approach to optimize e-commerce last-mile distribution through the determination of Micro-Fulfillment Centers (MFCs). The model simultaneously determines (i) the locations of candidate MFCs to be opened and (ii) the allocation of demand zones to selected facilities, with the objective of minimizing the total network cost consisting of fixed facility costs and variable last-mile service costs. Service quality is enforced through a hard service level agreement (SLA) mechanism by limiting allocation to only pairs of facility zones that meet a certain travel time threshold, while operational feasibility is guaranteed through capacity constraints at each MFC. The model outputs are implementable in the form of selected MFC locations, zone allocation maps, and performance indicators for evaluation, including total cost decomposition, weighted travel time metrics, and facility capacity utilization to identify potential bottlenecks. Numerical illustrations show that the MILP formulation yields feasible location–allocation decisions with respect to SLA and capacity, while avoiding the “closest/fastest” heuristic that can potentially lead to facility overload. This framework supports decision-makers in designing efficient, responsive, and scalable last-mile networks, and can be extended to incorporate demand uncertainty, SLA penalties (soft-SLAs), multi-echelon structures, and sustainability objectives.
Co-Authors Adha, Annisha Dyuli Adhista Ricky Yatra Afira, Riandana Anam, M Khairul Awal, Hasri Christina, Dian Devita, Retno Devita, Retno Fachry Abda El Rahman Firna Yenila Fitri Insani Hendrik, Billy Ipriadi Ipriadi - Ipriadi Ipriadi, Ipriadi Irzal Arief Wisky Khadnova, Triuliamri Kurnia, Hezy Kurnia, Hezy Mahessya, Raja Ayu Mardhiah Masril Nasution, Ayu Lestiani Okfalisa Okfalisa Permana, Randy Putra, Ondra Eka Rahmi, Nadya Alinda Randy Permana Riandari, Fristi Sarjon Defit Setiawan, Adil Sovia, Rini Sri Rahmawati Suci Wahyuni Suci Wahyuni Sumijan Surmayanti, Surmayanti Wiyandra, Yogi Yani, Zulfitri Yenila, Firna Yogi Wiyandra