Article Per Year (5 Year)
p-Index From 2020 - 2025
2.042
P-Index
This Author published in this journals
All Journal Format : Jurnal Imiah Teknik Informatika Jurnal Pilar Nusa Mandiri Jurnal Informatika Universitas Pamulang Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JIKA (Jurnal Informatika) Tematik : Jurnal Teknologi Informasi Komunikasi Bulletin of Computer Science Research
Septarini, Ri Sabti
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
RANCANG BANGUN APLIKASI SISTEM DIAGNOSIS KERUSAKAN PADA MOBIL DAIHATSU XENIA 1.3 M/T DENGAN METODE FORWARD CHAINING Septarini, Ri Sabti; Nugroho, Thesar
Jurnal Informatika Vol 2, No 2 (2018): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (907.014 KB) | DOI: 10.31000/.v2i2.1518

Abstract

Cars have properties like humans. The car will show certain signs before it breaks. Corrective action is taken when the symptoms occur.The problem faced is that many car Users who do not know it or may know only a little and not everyone knows about it in repairing the car.The purpose of writing this thesis report is to help detect damage to Daihatsu Xenia 1.3 M / T cars as an alternative solution for vehicle Users in shortening decision making time.Research methods conducted by the author in conducting research at PT. ArmadaAuto Tara. Fleet includes direct observation of the current diagnostic system, interviews with the head of mechanics and mechanics and literature studies that are relevant to the problems faced by the author. This study uses the Forward Chaining method.The results of this study can be seen that with the application of an expert diagnostic system this car damage can help the User get information about the damage experienced in his car without having to come to the workshop or to the expert.
Analysis and Design of Decision Support System for Employee Performance Appraisal with Simple Additive Weighting (SAW) Method Taufiq, Rohmat; Septarini, Ri Sabti; Hambali, Ahmad; Yulianti, Yulianti
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6777

Abstract

The decision support system (DSS) for employee performance appraisal is a decision support system used in the employee performance appraisal process at PT. Surya Toto Tbk. Currently, the employee performance appraisal process still done manually (paper-based) so that the reports produced were not real-time. From the existing problems, this research aimed to analyze and design a decision support system according to the existing criteria using the Simple Additive Weighting (SAW) method to be able to develop into a Web-based DSS. The method used began with communication with management, especially the perpetrators of employee performance appraisals. Furthermore, planning, the process of data collection, analysis, design, and finally making reports carried out. The conclusion of this study provided a suggestion to use the criteria that had given two more criteria. By giving weights and calculations carried out for three employees, the value obtained for employee C got the highest score (0.98) followed by employee B, and the lowest score (0.85) was employee A.
MODEL RUMAH PINTAR DENGAN MENGGUNAKAN LOGIKA FUZZY SEBAGAI PENGENDALI KEAMANAN DAN KESELAMATAN PENGHUNI RUMAH Wijayanti, Rima Rizqi; Septarini, Ri Sabti; Husain, Syepry Maulana; Abdurrasyid, Abdurrasyid
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol 9, No 2 (2020)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v9i2.23531

Abstract

Data Badan Pusat Statistik tahun 2013 menunjukan bahwa kejahatan pencurian merupakan kejahatan yang paling banyak dialami oleh rumah tangga, kecenderungan meningkat dari tahun 2012 hingga 2014, Pemadam Kebakaran Provinsi DKI Jakarta mencatat selama tahun 2019 terjadi 1355 kasus kebakaran, penyebab utama diakibatkan korsleting listrik sejumlah 557 kasus. Tujuan dari penelitian ini adalah adalah menghasilkan software, hardware dan model rumah pintar yang dapat mengendalikan peralatan rumah tangga sehingga dapat memberikan keamanan dan kenyamanan serta penghematan dari waktu dan biaya bagi penghuni rumah. Smartphone dapat memonitoring dan mengontrol keamanan Pintu Gerbang Utama menggunakan pin, menyalakan lampu, memutar musik, mengisi air dalam bak secara otomatis, menyalakan kipas angin, mengetahui suhu ruangan, dan terdapat pemberitahuan mengenai kebocoran gas, kebakaran serta pencurian. ada beberapa penelitian berkaitan tentang rumah pintar namun tidak ada yang menggabungkan kompleksitas sensor yang saat ini diteliti dengan kombinasi metode fuzzy logic didalamnya sehingga penelitian mampu memberikan kontribusi keilmuan.
Implementasi MADM TOPSIS dalam Pemilihan Karyawan Baru pada PT Arthawenasakti Gemilang Berbasis Web Septarini, Ri Sabti; Taufiq, Rohmat; Handayani, Nurdiana; Asy’arie, Zain Ibrahim
Jurnal Informatika Universitas Pamulang Vol 6, No 4 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i4.14428

Abstract

Recruiting new employees is the process of selecting potential employees to attract talented employees who will join the company later. Improve your company's productivity by hiring new employees who meet your company's standards. In addition to the development of information and communication technology, it is considered necessary to use a decision support system for recruiting new employees to facilitate the management process in the selection of new employees. One of the decision support system methods that can be used in the potential employee selection process is the Order Preference Method (TOPSIS), which resembles an ideal solution. In this study, we developed system applications using PIECES system analysis techniques, system development techniques using waterfall models using Unified Modeling Language (UML) models, application development using Sublime, and devices using black boxes. Describes the test. The end result of hiring an employee using a decision support system provides managers with hiring recommendations and is already available as a web-based hiring system.
Sistem Pengendalian Persediaan Menggunakan Metode Moving Average dan Pengembangan Sistem Extreme Programming Alamsyah, Dedy; Damuri , Amat; Nuraini, Rini; Septarini, Ri Sabti; Yudaningsih, Nunik
TEMATIK Vol 9 No 1 (2022): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2022
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v9i1.898

Abstract

Inventory of goods is one of several important factors in a company, whether engaged in trading or manufacturing. It is important for inventory to be controlled and supervised in the recording and calculation of inventory, this is because inventory can affect financial reporting. If the amount of inventory is too large (overstock), on the other hand, if the inventory is a little, it will have an impact on the lack of inventory (stockout). The purpose of this research is to develop an inventory control system using the moving average method and the development of an Extreme Programming (XP) system. The moving average method in inventory prediction is more effective because this method compares current and previous data. To develop the system, the Extreme Programming (XP) system development method is used. This method has advantages including: fast process, time and cost efficiency, low risk, flexibility and easy to implement. From the test results using black box testing by testing the functionality, the system shows the system has met expectations with a value reaching 100%. Meanwhile, for testing with the DeLone and McLean models which measure the success of information systems, the score reaches 81.37%.
RANCANG BANGUN SISTEM INFORMASI E-DOCUMENT KEPENDUDUKAN PADA DESA PASIR JAYA Septarini, Ri Sabti; Sugiyani, Yani; Aksani, Muhammad Luthfi; Nuramalia, Eva
Jurnal Informatika Vol 7, No 1 (2023): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v7i1.7187

Abstract

Kantor Desa Pasir Jaya merupakan salah satu instansi pemerintah yang masih menggunakan sistem manual dalam proses pengarsipan datanya, terutama dalam data kependudukan. Oleh karena itu, diperlukan sistem yang lebih terkomputerisasi untuk membantu petugas dalam pengarsipan. Dalam penelitian ini, penulis menggunakan metode URS dalam analisisnya, metode scrum dalam pengembangan sistem dan metode black box dalam pengujiannya. Sistem informasi e-Document pada Desa Pasir Jaya yang dihasilkan dengan menggunakan metode Scrum secara nyata dapat memenuhi kebutuhan pengguna sesuai dengan product backlog yang dapat dilihat dari fiturnya.
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.
IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM Erkamim, Moh.; Septarini, Ri Sabti; Tonggiroh, Mursalim; Nurhayati, Siti
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.5307

Abstract

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.
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.
Sistem Pendukung Keputusan Pemilihan Perumahan Menggunakan Kombinasi Metode ROC dan ARAS Septiana, Ristasari Dwi; Herdiansah, Arief; Septarini, Ri Sabti; Irfan, Muhammad
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.005

Abstract

Selecting a suitable house is a multifaceted process that involves several considerations, including cost, location, available facilities, security, and access to transportation. Because decisions are often made subjectively, there is a risk of inefficiency, which highlights the need for a structured decision-making approach. This study presents the development of a web-based decision support application that combines the Rank Order Centroid (ROC) method for assigning criterion weights based on their priority order, and the Additive Ratio Assessment (ARAS) method for evaluating and ranking housing alternatives based on relative utility scores. The system was implemented using PHP and MySQL, incorporating modules for managing criteria, alternatives, inputting evaluations, and generating automated calculations and visual outputs. A case study with five housing options and five main evaluation criteria was conducted. The research employed a structured methodology involving problem identification, criteria selection, weight calculation using ROC, alternative evaluation using ARAS, system development, and black-box testing for validation. The findings revealed that Taman Permata achieved the highest utility score of 0.8616, placing it as the top-ranked alternative. Functional testing through a black-box approach verified that all components operated as intended. Overall, the system offers a transparent and effective tool to support users in identifying the most appropriate housing option according to their individual needs and priorities.
Co-Authors Abdurrasyid Abdurrasyid, Abdurrasyid Abdus Salam, Abdus Ahmad Hambali, Ahmad Aksani, Muhammad Luthfi Alamsyah, Dedy Asy’arie, Zain Ibrahim Azhari, Lukman Damuri , Amat Handayani, Nurdiana Handayani, Nurdiana Herdiansah, Arief Heriyani, Nofitri Husain, Syepry Maulana Luqmanul Hakim Moh. Erkamim Muhammad Irfan Nugroho, Thesar Nuramalia, Eva Pamungkas, Ilham Surya Putra Rini Nuraini, Rini Ristasari Dwi Septiana Rohmat Taufiq Rusdianto, Hengki Siti Nurhayati Tonggiroh, Mursalim Wijayanti, Rima Rizqi Yani Sugiyani, Yani Yudaningsih, Nunik Yulianti