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All Journal Jurnal JSIKA Format : Jurnal Imiah Teknik Informatika Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jurnal Pengabdian Masyarakat (Jupemas)
Muhammad Bagir
Islamic College for Advanced Studies (ICAS) Jakarta
Computer Science & IT Decision Sciences, Operations Research & Management Health Professions Immunology & microbiology Medicine & Pharmacology Nursing Public Health Other

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Rancang Bangun Sistem Informasi Akademik Di Akademi Keperawatan Adi Husada Surabaya bagir, Muhammad; Supriyanto, Antok; Arrosyidi, Achmad
Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA) Vol 7, No 3 (2018)
Publisher : Jurnal Sistem Informasi dan Komputerisasi Akuntansi (JSIKA)

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Abstract

Adi Husada Nursing Academy is an educational institution in the field of nursing that conducts Diploma lecture 3. Adi Husada Academy Surabaya was established in 1983 and located in Kapasari street Surabaya. During this time, academic difficulties in the recapitulation of attendance of students and lecturers as well as the academic value of the students. This is because the recapitulation is done one by one from the report of 183 lectures. While the recapitulation of academic value of students should be done by selecting one by one with the name of the students with the subject followed. From the existing problems of administrative applications required courses that can assist in the process of recapitulation of attendance of students and lecturers as well as the academic value of students. Recapitulation of student attendance is used to know the status of students in the examination. Based on the results of trials that have been done, the application successfully assist in the process of recapitulation. This journal discusses the outline of the academic application design lecture at Adi Husada Nursing Academy Surabaya.
Sistem Pendukung Keputusan Pemilihan Platform Investasi P2P Lending Menggunakan Metode Complex Proportional Assessment (COPRAS) Bagir, Muhammad; Riyanto, Umbar; Nuraini, Rini; Kustiawan, Dedi
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3246

Abstract

Through technological developments, many fintech P2P lending have emerged which are competing to offer convenience in transactions and offer fast processes. To determine a P2P lending platform as a place to invest, one must know in advance about the company profile or the application and programs offered as a whole. This of course will take a long time to select a P2P lending platform. If you choose an inappropriate P2P lending platform, it will result in losses. The purpose of this research is to build a Decision Support System (DSS) for choosing a P2P lending platform by implementing the Complex Proportional Assessment (COPRAS) approach in order to get the right decision and not take a long time. The COPRAS approach has the ability to produce the best alternative which is limited to alternative analysis through alternative assumptions by providing utility judgment so that the attributes of each alternative are arranged based on intervals. Based on the results of the case studies conducted, the highest utility score was Danamas Lender with a score of 100, then followed by Alami Funding Sharia with a score of 99.2338, Accelerant with a score of 89.8827 and Amartha Microfinance with a score of 83.4988. In addition, based on the results of black box testing, it shows that the software can run as it should.
Pelayanan Pengaduan Masyarakat Peduli Lingkungan Pada Dinas Lingkungan Hidup Kota Palangka Raya Sigai, Juniardo Silcher Runting; David, Tommy Ekadino; Bagir, Muhammad; Julianto, Eko; Handayani, Risma Utami; 'ani, Sam; Ichsan, Mochammad; Qamaruzzaman, Muhammad Haris
Jurnal Pengabdian Masyarakat (Jupemas) Vol. 5 No. 2 (2024)
Publisher : Universitas Bakti Tunas Husada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36465/jupemas.v5i2.1414

Abstract

Palangka Raya City, as the center of government and economic growth in Central Kalimantan, faces serious challenges in waste management. The increasing amount of waste generated by community and industrial activities demands attention and concrete action to maintain cleanliness and environmental sustainability. This community service activity aims to raise public awareness about the importance of proper waste management and to provide facilities for reporting and handling waste. The activities include socialization and counseling about the types of waste, the negative impacts of waste on health and the environment, as well as effective reporting procedures. By providing easily accessible reporting facilities, such as hotlines and mobile applications, it is hoped that the community can play an active role in reporting waste issues they encounter. The expected outcomes of this activity are increased public awareness, an increase in the number of waste reports, and more effective waste management, which in turn will contribute to a cleaner and healthier environment in Palangka Raya City. This community service activity is implemented as part of the Field Work Practice (PKL) of the Integrated School of Management Informatics & Computer (STMIK). This activity is expected to create a culture of shared responsibility in environmental management and support the sustainability efforts initiated by the local government.
Sistem Pendukung Keputusan Menggunakan Metode WASPAS Untuk Pemilihan Software Developer Bagir, Muhammad; Sanwasih, Mochamad; Arisantoso, Arisantoso; Rahmadian, Jefri
FORMAT Vol 14, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i1.003

Abstract

The advancement of information technology has driven an increased demand for competent software developers aligned with project specifications, making the selection process a strategic challenge for organizations. However, manual selection is often subjective, time-consuming, and prone to errors. Therefore, this study aims to develop a Decision Support System (DSS) based on the Weighted Aggregated Sum Product Assessment (WASPAS) method. WASPAS was chosen for its ability to integrate the strengths of the Weighted Sum Model (WSM) and Weighted Product Model (WPM) to produce decisions based on criteria weights and alternative performance. The system is designed as a web-based application to provide ease of access and usability, featuring key functionalities such as data management for criteria, alternatives, and values, as well as calculation and result presentation using the WASPAS method. The case study results indicate that Mochammad Rizal (A3) is the best alternative with the highest score of 0.8904, followed by Yosua Surojo (A4) with a score of 0.8718. Tommy Pratama (A2) ranks third with a score of 0.7101, while Gigih Prayitno (A1) occupies the last position with a score of 0.6713. System testing using the black-box testing method ensures that all features function according to the designed specifications. This study contributes a systematic solution to simplify the software developer selection process while reducing subjective bias in decision-making.
Sistem Pakar Diagnosa Penyakit Infeksi Saluran Pernapasan Atas pada Klinik Dharma Medica Menggunakan Metode Forward Chaining Bagir, Muhammad; Farkhatin, Naely; Frastian, Nahot
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol 6, No 02 (2025): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v6i02.11777

Abstract

Infeksi Saluran Pernapasan Atas (ISPA) merupakan penyakit yang umum dan mudah menular, terutama pada anak-anak. ISPA dapat disebabkan oleh berbagai virus, bakteri, dan jamur. Gejala umum ISPA antara lain batuk, pilek, sakit tenggorokan, dan demam. Saat ini, banyak klinik medis menghadapi masalah utama dalam mendapatkan diagnosis yang tepat. Keterbatasan waktu dan sumber daya sering kali mengakibatkan penundaan dalam proses diagnosa, yang dapat memengaruhi kualitas perawatan pasien. Kompleksitas kondisi medis yang semakin meningkat juga menambah kesulitan dalam menetapkan diagnosis yang akurat. Oleh karena itu dibuatlah Sistem Pakar ini dengan tujuan untuk mengembangkan sebuah sistem pakar yang dapat membantu dalam mendiagnosis penyakit Infeksi Saluran Pernapasan Atas (ISPA) pada Klinik Dharma Medica. Sistem ini bertujuan untuk memberikan diagnosis awal yang cepat dan akurat, serta saran penanganan yang tepat berdasarkan gejala yang dialami pasien. Metode yang digunakan dalam pengembangan sistem pakar ini adalah metode Forward Chaining. Forward Chaining adalah teknik inferensi dalam kecerdasan buatan yang dimulai dari fakta-fakta awal dan menerapkan aturan-aturan untuk mencapai kesimpulan atau diagnosis. Hasil Penelitian yang dilakukan di Klinik Dharma Medica telah terbukti efektif dalam membantu proses diagnosis. Sistem ini mampu mengidentifikasi berbagai gejala yang terkait dengan infeksi saluran pernapasan atas dan memberikan hasil diagnosis yang akurat berdasarkan data yang diberikan oleh pengguna.
Klasifikasi Risiko Diabetes Mellitus Menggunakan K-Nearest Neighbors dengan Peningkatan Performa Melalui Teknik Oversampling ADASYN Bagir, Muhammad; Mayatopani, Hendra; Riyanto, Umbar; Alamsyah, Dedy
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7237

Abstract

Diabetes mellitus is a chronic metabolic disease with a continuously increasing global prevalence. Early detection of diabetes risk is crucial to reduce long-term health complications and the associated healthcare costs. However, a major challenge in applying machine learning models to medical data is the issue of class imbalance, which can lead to model bias toward the majority class. This study aims to develop a diabetes risk classification model by integrating the K-Nearest Neighbors (KNN) algorithm with the Adaptive Synthetic Sampling (ADASYN) technique to address the class imbalance problem. The dataset used was obtained from the Kaggle platform, containing 2,000 patient samples with nine predictive features. Data preprocessing was performed through missing value imputation, outlier handling using winsorizing, and feature normalization using StandardScaler. ADASYN was applied to generate adaptive synthetic samples for the minority class, and the KNN model was trained and evaluated using confusion matrix, precision, recall, F1-Score, accuracy, and ROC-AUC metrics. The results indicate that the implementation of ADASYN improved the ROC-AUC Score by 5.48% (from 91.34% to 96.82%) and the overall accuracy by 2.50% (from 81.50% to 84.00%). The F1-Score for the Diabetes class also increased by 0.40%. The integration of KNN and ADASYN has proven effective in enhancing model performance for detecting high-risk diabetes patients and improving sensitivity toward the minority class.
Co-Authors Achmad Arrosyidi Alamsyah, Dedy Antok Supriyanto Arisantoso Arisantoso David, Tommy Ekadino Eko Julianto Farkhatin, Naely Handayani, Risma Utami Ichsan, Mochammad Kustiawan, Dedi Mayatopani, Hendra Mochamad Sanwasih Muhammad Haris Qamaruzzaman Nahot Frastian Rahmadian, Jefri Rini Nuraini, Rini Riyanto, Umbar Sam'ani Sam'ani Sigai, Juniardo Silcher Runting