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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Teknoinfo JIKA (Jurnal Informatika) Bulletin of Computer Science Research Insearch: Information System Research Journal Journal of Computing and Informatics Research
Heriyani, Nofitri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences Other

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RANCANG BANGUN SISTEM INFORMASI PEMBELAJARAN ANATOMI TUBUH MANUSIA BERBASIS ANDROID (STUDI KASUS: SDN CIHUNI 1) Heriyani, Nofitri
Jurnal Informatika Vol 3, No 1 (2019): JIKA (Jurnal Informatika)
Publisher : Universitas Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.927 KB) | DOI: 10.31000/jika.v3i1.2036

Abstract

Learning is a communication process between learners, teachers and teaching materials. Communication will not work without the aid of medium or message media. The message to be communicated is the content of the learning that is in the curriculum curricula poured by faculty or facilitator or other sources into communication symbols. Submission of learning messages from teachers to students today, still using teaching aids like books. This makes the students less interested and bored when absorbing the lesson thus giving the effect of lazy learning. Applications are made a medium of learning for elementary school students with references from books containing human anatomy material including the structure of the human body, skeletons and skin, muscular system, nervous system, endocrine system, respiratory, system cardio-vascular system, lymphatic system, digestive system, excretion system and reproduction system and contains anatomy learning information of the human body in detail in terms of material and images. The results of the study found that still using the use of books and media sculpture in the process of teaching and learning activities at the school. To support this application also included exercise questions, in order to find out how far the ability of students to deepen the material obtained from this application. This application development method uses Rapid Aplication Develpoment which consists of three phases namely planning, design workshop, and implementation with UML process design (Unified Modeling Language) and developed using the Eclipse IDE for data collection with literature and questioner studies, based on the results of research, applications that have been made is needed and greatly facilitates the children to learn the anatomy of the human body
PENGEMBANGAN SISTEM PAKAR MENGGUNAKAN MESIN INFERENSI DEMPSTER-SHAFER THEORY UNTUK DIAGNOSA GANGGUAN SOMATOFORM Tonggiroh, Mursalim; Heriyani, Nofitri; Handayani, Nurdiana; Nugroho, Nurhasan
Jurnal Teknoinfo Vol 18, No 2 (2024): Juli 2024
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i2.4062

Abstract

Gangguan somatoform merupakan gangguan mental dengan kondisi di mana individu mengalami gejala fisik yang menyebabkan distress signifikan atau gangguan dalam fungsi sehari-hari, namun tidak dapat dijelaskan oleh kondisi medis, penggunaan substansi, atau kondisi mental lainnya. Namun, karena kompleksitas gejala dan kesulitan dalam mendeteksi gangguan somatoform secara klinis seringkali menyebabkan keterlambatan diagnosis dan penanganan yang tidak tepat, yang dapat memperburuk kondisi pasien. Kurangnya pengetahuan tentang gangguan somatoform dan keterbatasan akses terhadap layanan kesehatan mental yang berkualitas dapat menyulitkan individu untuk mendapatkan bantuan yang dibutuhkan. Tujuannya penelitian ini dilakukan untuk membangun sistem pakar yang digunakan dalam diagnosis gangguan somatoform secara mudah dan akurat melalui penerapan metode Dempster-Shafer Theory sebagai mesin inferensinya. Pendekatan ini memiliki keunggulan dalam mengelola ketidakpastian dan informasi yang tidak lengkap, memungkinkan sistem pakar untuk membuat inferensi diagnostik berdasarkan kumpulan gejala yang diobservasi, bahkan ketika informasi tersebut tidak lengkap atau ambigu. Algoritma Dempster-Shafer Theory memanfaatkan konsep massa kepercayaan untuk menggambarkan tingkat keyakinan atau ketidakpastian tentang suatu hipotesis atau peristiwa. Sistem pakar yang dikembangkan dapat mendiagnosa berdasarkan gejalanya dan memperlihatkan hasil diagnosa, serta tindakan yang dapat dilakukan. Berdasarkan hasil pengujian dengan menggunakan sampel uji yang dipilih secara acak, didapatkan tingkat akurasi diagnosa yaitu 86,67%. Hasil tersebut mengindikasikan bahwa Dempster-Shafer Theory dapat diimplementasikan dengan baik untuk mendiagnosa gangguan somatoform.
SISTEM LAPORAN STOCK OPNAME MERCHANDISER BERBASIS WEB Handayani, Nurdiana; Septarini, Ri Sabti; Heriyani, Nofitri; Hakim, Luqmanul
Jurnal Informatika Vol 7, No 4 (2023): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v7i4.9639

Abstract

Sistem laporan stock opname sangat penting karena membantu perusahaan dalam memantau, mengelola dan mengoptimalkan stock opname yaitu tentang aktivitas transaksi keluar masuknya barang perusahaan. Laporan stock opname merchandiser pada PT Arina Multikarya belum dilakukan secara terkomputerisasi yaitu mengirimkan hasil foto dokumentasi dan di berikan deskripsi barang apa saja yang stok nya menipis ataupun kosong lalu dikirimkan melalui group whatsapp yang mengakibatkan dalam proses pengolahan data laporan stock opname sering terjadinya kekeliruan dan kesalahan pemasukan data serta mengalami kesulitan dalam pencarian data laporan stock opname yang sudah lampau jika dibutuhkan dikemudian hari.  Menggunakan metode User Requirement Specification (URS) untuk mengumpulkan data kebutuhan sistem yang akan dirancang secara spesifik dengan fokus kepada kebutuhan pengguna. Pemodelan sistem digambarkan menggunakan unified Modeling language (UML) dan metode pengembangan sistem yang digunakan adalah Extreme Programming, metode ekspansi perangkat lunak yang pengembangan system dalam waktu singkat dengan mendahulukan adanya interaksi cepat dari pengembangan terhadap perbedaan yang terjadi dalam bentuk apapun. Dengan merancang sistem berbasis web diharapkan dapat membantu dan memudahkan proses sistem laporan stock opname merchandiser yaitu dalam proses pengolahan data dan menyimpan data yang akhirnya menghasilkan data yang akurat yang dapat digunakan untuk keperluan perusahaan.
Decision Support System Using a Combination of COPRAS and Rank Reciprocal Approaches to Select Accounting Software Erkamim, Moh.; Handayani, Nurdiana; Heriyani, Nofitri; Soares, Teotino Gomes
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 1 (2024): Januari 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i1.7111

Abstract

Accounting software plays an important role in carrying out accounting processes that are fast, efficient, accurate and in accordance with applicable standards. With the emergence of various accounting software that offers a variety of features, users, both individuals and companies, often experience difficulty in determining the software that best suits their needs. The aim of this research is to develop a decision support system that makes it easier to choose accounting software through the application of the COPRAS approach and the Rank Reciprocal weighting technique. The Rank Reciprocal approach is used to rank or weight the criteria given by the decision-maker. The COPRAS (Complex Proportional Assessment) approach focuses on cognitive aspects so that it can accommodate the preferences and subjective assessments of decision-makers. Based on the case study that has been carried out, the highest to lowest utility value results are obtained, namely Zahir Online (A2), which obtained a score of 100. Since the decision support system's output yields a result that is identical to that of computations made by hand, it is deemed legitimate. Apart from that, the usability test obtained an average score of 91%, which proves that the system is in accordance with its usability and what is needed by its users.
Sistem Pendukung Keputusan Menggunakan Pendekatan Additive Ratio Assessment pada Penentuan Lokasi Usaha untuk UMKM Heriyani, Nofitri; Yanuardi, Yanuardi; Handayani, Nurdiana; Mulyadi, Mulyadi
Insearch: Information System Research Journal Vol 4, No 02 (2024): Insearch (Information System Research) Journal
Publisher : Fakultas Sains dan Teknologi UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/isrj.v4i02.9495

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memegang peranan penting dalam perekonomian Indonesia. Akan tetapi, UMKM sering menghadapi tantangan dalam pemilihan lokasi usaha yang strategis, yang merupakan faktor kunci kesuksesan. Metode tradisional yang digunakan dalam menentukan lokasi usaha sering kali subjektif dan kurang sistematis, sehingga diperlukan pendekatan yang lebih objektif dan terstruktur. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan (SPK) dengan menerapkan pendekatan Additive Ratio Assessment (ARAS) untuk membantu pemilik UMKM memilih lokasi usaha yang optimal. Pendekatan ARAS memiliki keunggulan dalam memberikan hasil yang lebih objektif dengan mempertimbangkan berbagai kriteria secara simultan dan menilai alternatif sesuai dengan tingkat kepentingannya. Dalam penelitian ini, menghasilkan SPK yang dapat memberikan rekomendasi alternatif lokasi usaha terbaik melalui perangkingan nilai kinerja relatif. Konsistensi antara output sistem dan perhitungan manual menunjukkan validitas perhitungan yang dihasilkan oleh sistem. Hasil uji usability dengan rata-rata skor 91,25% mengindikasikan bahwa SPK yang dikembangkan berhasil mengintegrasikan fungsionalitas yang dibutuhkan dengan antarmuka yang intuitif dan mudah digunakan.
Pengembangan Sistem Pakar Diagnosis Jenis Stres Menggunakan Pendekatan Dempster-Shafer Theory Sah, Andrian; Heriyani, Nofitri; Jafar Rumandan, Rhaishudin; Lasiyono, M. Munawir
Journal of Computing and Informatics Research Vol 4 No 2 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v4i2.1941

Abstract

Stress is a psychological issue commonly experienced in society and can develop into more serious disorders if not properly addressed. However, access to professional services remains limited due to constraints such as time, cost, and unequal distribution of mental health professionals. Therefore, the objective of this study is to develop an expert system using a web-based Dempster-Shafer Theory (DST) approach capable of diagnosing stress types based on user-reported symptoms. DST enables the integration of various pieces of evidence to produce conclusions with measurable confidence levels. The system is equipped with functionality for managing symptom data, stress types, and the ability to provide diagnostic results accompanied by recommended solutions. Testing results demonstrated an accuracy level of 93.33%, placing this system in the "Good" category according to standard performance evaluation classifications. The implementation of DST has proven effective in managing data uncertainty and supporting confidence-based decision-making. This research contributes to the development of DST-based diagnostic technology that can be widely accessed via a web platform, providing a reliable alternative for early detection of stress types.
Pendekatan Hybrid K-Means SMOTE dan Logistic Regression Untuk Deteksi Dini Diabetes Mellitus Pada Imbalanced Data Salam, Abdus; Azhari, Lukman; Septarini, Ri Sabti; Heriyani, Nofitri
Bulletin of Computer Science Research Vol. 5 No. 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i3.502

Abstract

The increasing global prevalence of Diabetes Mellitus necessitates more accurate early detection efforts, particularly through machine learning-based approaches. However, one of the main challenges in medical classification lies in data imbalance, where the number of diabetic cases is significantly lower than that of non-diabetic ones. This study aims to develop a hybrid model by integrating Logistic Regression and K-Means SMOTE to enhance the sensitivity of early detection for Diabetes Mellitus, especially toward the minority class. Logistic Regression is chosen for its computational efficiency and interpretability, while K-Means SMOTE plays a role in balancing class distribution by generating synthetic samples in a structured manner based on clusters of minority class data. The dataset used consists of 2,000 records with 9 health-related features, obtained from the Kaggle platform. Evaluation results indicate that the model utilizing K-Means SMOTE achieves the best performance, with an accuracy of 82.00%, an F1-score of 72.73% for the Diabetes class, and the highest ROC-AUC score of 87.48%. Compared to models without oversampling and with standard SMOTE, this approach improves model generalization and sensitivity to positive cases. These findings have practical implications for the development of fairer and more effective machine learning-based early detection systems, particularly for implementation in healthcare facilities with limited resources.
Co-Authors Abdus Salam, Abdus Azhari, Lukman Handayani, Nurdiana Jafar Rumandan, Rhaishudin Lasiyono, M. Munawir Luqmanul Hakim Moh. Erkamim Mulyadi Mulyadi Nurhasan Nugroho Sah, Andrian Septarini, Ri Sabti Soares, Teotino Gomes Tonggiroh, Mursalim Yanuardi Yanuardi