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All Journal Jurnal Sains dan Informatika ILKOM Jurnal Ilmiah Building of Informatics, Technology and Science Journal of Intelligent Software Systems Jurnal Teknologi Informasi
Wiwi Widayani, Wiwi
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Computer Science & IT Engineering Mathematics

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PERBANDINGAN ALGORITMA K-MEANS DAN SFCM PADA PENGELOMPOKKAN RUMAH TANGGA MISKIN Widayani, Wiwi; Harliana, Harliana
Jurnal Sains dan Informatika Vol 6 No 1 (2020): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.07 KB) | DOI: 10.34128/jsi.v6i1.200

Abstract

Secara definisi rumah tangga miskin dan penduduk miskin memiliki sudut pandang yang berbeda, dimana definisi rumah tangga miskin akan lebih ditekankan kepada individu yang akan dijadikan survey dalam menentukan penduduk miskin sedangkan penduduk miskin lebih kepada kumpulan dari beberapa rumah tangga miskin. Penelitian ini dilakukan untuk membandingkan antara algoritma K-Means dan Fuzzy Substractive Clustering (SFCM) dalam mengelompokkan rumah tangga miskin. Kedua algoritma ini akan dibandingkan berdasarkan simpangan baku dan validitas hasil pengelompokkan yang dihasilkan. Berdasarkan 6 pengujian yang telah dilakukan, maka didapatkan hasil bahwa dari sisi waktu algoritma K-Means mampu mengelompokkan lebih cepat bila dibandingkan dengan algoritma SFCM, namun dari sisi simpangan baku kelompok, simpangan baku antar kelompok, maupun akurasi maka algoritma SFCM memiliki performa yang lebih baik bila dibandingkan dengan algoritma K-Means
Implementasi Metode Forward Chaining dan Certainty Factor Pada Sistem Pakar Diagnosis Penyakit Sinusitis Nurerwan, Mizani Achmad; Wulandari, Irma Rofni; Astuti, Yuli; Widayani, Wiwi
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2630

Abstract

Sinusitis is similar to symptoms of minor illnesses such as runny nose, cough, and headache. Mild symptoms cause people to ignore these symptoms often. Besides, limited costs and doctor's practice hours make consultations difficult. Signs of infection that are not treated quickly can cause complications, and the infection can spread to the eye sockets or the brain. One of the ways to diagnose sinusitis early is to use an expert system so that in this study implemented the Certainty Factor and forward chaning methods to create a system that can diagnose sinusitis according to the symptoms felt and provide information about the disease and how to treat sinusitis symptoms early. Forward chaining is used as an inference method, and the certainty factor is used to calculate the level of probability of disease based on the expert's belief value and the symptoms of sinusitis selected by the user. The data used is disease data consisting of four types of sinusitis and fifteen symptoms. Based on the results of black box testing, the system that has been built functions well as expected. Expert systems in diagnosing have an accuracy of 70%.
IMPLEMENTASI DESIGN THINKING UNTUK PERANCANGAN UI/UX APLIKASI ONE COLLECTING AGENT (OCA) Pujastuti, Eli; Nurmasani, Atik; Widayani, Wiwi; Farida, Lilis Dwi; Widjiati, Nur; Kusumaningrum, Andi Sutra
JuTI "Jurnal Teknologi Informasi" Vol 3, No 1 (2024): Agustus 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/juti.v3i1.1405

Abstract

Aplikasi One Collecting Agent (OCA) adalah sebuah aplikasi yang dibangun untuk mempermudah pengumpulan data pengelolaan Pajak Penghasilan (PPh) kegiatan Perguruan Tinggi untuk PPh 21, PPh 23, dan PPh 4 Ayat 2 khususnya di Universitas ABC. Dimana, pengelolaan PPh tersebut masih dilakukan dengan bantuan google spreadsheet yang menimbulkan adanya permasalahan seperti, tampilan lembar kerja di dalam spreadsheet berbentuk tabel menyamping membuat pengguna mengalami kesulitan dalam pengisian data yang mengakibatkan ketidakefektifan pengoperasian dan kinerja pengguna. Oleh karena itu, diperlukan adanya sebuah perancangan UI/UX dan frontend berbasis website untuk memberikan tampilan lembar kerja yang lebih nyaman dan optimal. Tujuan dari penelitian ini adalah melakukan perancangan UI/UX dan frontend aplikasi One Collecting Agent (OCA) dengan menerapkan metode Design Thinking agar dapat memenuhi tampilan desain antar muka yang dibutuhkan dan diinginkan pengguna.  Metode Design Thinking adalah metode yang berpusat pada manusia untuk memecahkan masalah yang muncul dari pengguna. Metode ini memiliki 5 tahap, yaitu empathize, define, ideate, prototype, dan test. Tahap empathize merupakan tahap mencari permasalahan dan kebutuhan pengguna. Tahap define dan ideate merupakan tahap menentukan masalah dan merancang ide solusi.  Tahap prototype adalah tahap mengimplementasikan ide solusi ke dalam tampilan desain. Tahap test dilakukan dengan pengujian prototype kepada 30 responden menggunakan metode System Usability Scale (SUS) yang diperoleh hasil 75 dengan kategori Excellent, Acceptable, dan grade scale C.  Hasil penelitian ini adalah perancangan UI/UX dan frontend aplikasi One Collecting Agent (OCA) menggunakan metode Design Thinking yang dapat memenuhi tampilan desain antar muka yang dibutuhkan dan diinginkan pengguna.
Performance Assessment of Branch Office Assistant (KCP) Leaders Using the Simple Additive Weighting Method Wibowo, Dwi; Astuti, Femi Dwi; Astuti, Yuli; Widayani, Wiwi; Fauzi, Arma
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1502

Abstract

Abstract— Performance Appraisal is a process that allows organizations to know, evaluate, measure and assess the performance of their members appropriately and accurately. This activity is closely related and influences the effectiveness of the implementation of human resource activities in the company, such as promotion, compensation, training, career management development and others. This is because the performance appraisal function can provide important information to the company to improve decisions and provide feedback to employees about their actual performance.The implementation of the achievement and performance appraisal of KCP leaders at KSPPS Tunas Artha Mandiri Nganjuk Branch has so far still used manual and has not used a decision support sistem so that the data generated is not accurate and takes a long time. As a result, if used in decision making, it is not appropriate and causes problems such as non-transparent management, decreased quality and performance of KCP leaders. The author applies and implements the Additive Weighting method (SAW) to measure the achievement and performance assessment of the Sub-Branch Office leadership at KSPPS Tunas Artha Mandiri Nganjuk Branch. With the aim of this decision support sistem can provide information and recommendations as well as accurate and efficient performance appraisal data.Keywords-Decision Support Sistem, Simple Additive Weighting, Employee Appraisal
An AI-integrated IoT-based Self-Service Laundry Kiosk with Mobile Application Kusrini, Kusrini; Muhammad, Alva Hendi; Fauzi, Moch Farid; Kuswanto, Jeki; Bernadhed, Bernadhed; Widayani, Wiwi; Pramono, Eko; Muktafin, Elik Hari; Ariyanto, Yossy
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2050.382-393

Abstract

This paper proposes KILAO, an IoT-based self-service laundry kiosk connected with a mobile application that aims to improve the laundry experience by improving user convenience and operational efficiency. This study aims to streamline the washing process using autonomous payment systems, real-time monitoring, and AI-based queue management, resulting in better resource utilization and higher user satisfaction. The development technique comprises identification and requirement gathering, development of both software and hardware prototypes, and evaluation of the prototype. In the requirement-gathering phase, the design of a kiosk machine that consists of hardware and software is defined by combining regular washing machines with IoT technologies for remote control and monitoring. We also developed a mobile application to engage with the kiosk machine. The kiosk simplifies the choice of laundry bundles and accepts various payment options, including cash, cashless transactions, and card-based purchases. The evaluation procedure of the prototype was conducted by using expert evaluations. They are from academics and industry professionals who verified the system’s effectiveness and market potential. The results have shown several unique selling features for KILAO. Extensive payment options and self-service operations were highlighted from the customer’s perspective as key benefits. From the seller’s perspective, its interoperability with traditional washing machines enables a low-cost shift to intelligent, self-service operations, eliminating the need for pricey coin-operated machines. Also, the automatic monitoring system that detects cycle completion can reduce waiting times and improve energy efficiency. In summary, KILAO presents a significant advancement in laundry automation by integrating IoT and AI. Moreover, the Gradient boosting algorithm forecasts waiting times and gives real-time information on machine availability, removing the need for physical queueing. The research demonstrates that KILAO’s capability to provide self-service laundry by providing a user-friendly mobile application can enhance user experience, operational efficiency, and energy utilization.
DIGITAL ACTIVITY LOCATION CLUSTERING BASED ON TWITTER GEOSPATIAL DATA FOR SPATIOTEMPORAL BUSINESS INTELLIGENCE Laksono, Triyan Agung; Andriyani, Widyastuti; Putra, Fadhlih Girindra; Ruas da silva, Ivonia Fatima; widayani, Wiwi
Journal of Intelligent Software Systems Vol 4, No 1 (2025): Juli 2025
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v4i1.2005

Abstract

This research develops an approach for clustering digital activity locations based on Twitter geospatial data with the aim of supporting business intelligence spatiotemporal . By utilizing the Twitter Geospatial Data dataset containing more than 14 million tweets geo-tagged from the United States, this study implements and compares the DBSCAN and K- Means algorithms to identify spatial and temporal patterns of Twitter user activity. The research process begins with the data pre -processing stage using the Knowledge Discovery Database (KDD), followed by the implementation of the clustering algorithm , and ending with the integration of the results into the dashboard.business intelligence using Power BI . The results show that DBSCAN is able to detect irregular clusters that follow geographic patterns and population density, while K- Means produces a division of the region into three main clusters (West Coast, Central Region, and East Coast) with different temporal activity patterns. Integration of clustering results into a BI dashboard produces actionable business insights , such as identification of digital activity hotspots , optimal time for content delivery, geographic segmentation for marketing strategies, and temporal activity patterns for campaign scheduling. This research contributes to the development of an integrated spatiotemporal analysis pipeline to support data-driven decision making.
Co-Authors Alva Hendi Muhammad Andriyani, Widyastuti ATIK NURMASANI Bernadhed, Bernadhed Eko Pramono Eli Pujastuti, Eli Fauzi, Arma Fauzi, Moch Farid Femi Dwi Astuti Harliana Harliana Jeki Kuswanto Kusrini, Kusrini Kusumaningrum, Andi Sutra Laksono, Triyan Agung LILIS DWI FARIDA Muktafin, Elik Hari Nurerwan, Mizani Achmad Putra, Fadhlih Girindra Ruas da silva, Ivonia Fatima Wibowo, Dwi Widjiati, Nur Wulandari, Irma Rofni Yossy Ariyanto Yuli Astuti