Garuda - Garba Rujukan Digital

SKALA LIKERT DALAM SELEKSI KARYAWAN BARU DENGAN METODE FUZZY TSUKAMOTO BERBASIS WEB (STUDI KASUS: PT TELKOM AKSES AREA SAMARINDA) Ukkas, Muhammad Irwan; Ekawati, Hanifah; Riandi, Tendi
Sebatik Vol. 22 No. 2 (2018): DESEMBER 2018
Publisher : STMIK Widya Cipta Dharma

PT Telkom Akses adalah anak perusahaan Telkom yang bergerak pada bidang bisnis penyediaan dan pengelolaan infrakstruktur jaringan fiber di indonesia. Semakin berkembangnya Telkom Akses maka diperlukan sumber daya manusia lebih banyak. Oleh karena itu Telkom Akses melakukan rekrut karyawan baru melalui divisi HCM (Human Capital Management). Sebelum melakukan rekrut karyawan, telah dibuat skema seleksi calon karyawan agar mendapatkan sumber daya manusia sesuai dengan visi dan misi perusahaan. Untuk mempermudah proses seleksi karyawan baru di Area Kota Samarinda maka pada penelitian ini merancang sebuah sistem untuk seleksi karyawan baru berbasis web menggunakan skala likert dengan metode Fuzzy Tsukamoto. Metode tsukamoto digunakan untuk melakukan fuzzyfikasi nilai-nilai fuzzy pada skala likert. Pengembangan sistem dalam penelitian ini menggunakan metode sistem penunjang keputusan, tahapannya yaitu (1) Intelegensi, (2) desain, (3) pemilihan, dan (4) Implementasi. Untuk pemodelan sistem menggunakan diagram alir dan sitemap. Sistem diimplementasikan menggunakan bahasa pemrograman PHP, sublime text 3 sebagai webeditor, XAMPP sebagai webserver local, basis data MySQL dan codeigniter sebagai framework. Hasil dari implementasi skala likert seleksi karyawan baru berbasis web menggunakan metode fuzzy tsukamoto menghasilkan aplikasi penilaian karyawan baru yang dapat membantu divisi HCM area samarinda dalam penilaian hasil tes, dan memberikan laporan rekomendasi hasil seleksi karyawan baru kepada pimpinan perusahaan di area.

Perbandingan Kinerja Algoritma K-Nearest Neighbor dan Algoritma Random Forest Untuk Klasifikasi Data Mining Pada Penyakit Gagal Ginjal Salmon, Salmon; Azahari, Azahari; Ekawati, Hanifah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6476

Kidney failure is one of the most common chronic diseases worldwide. This condition occurs when the kidneys lose their ability to filter waste and excess fluid from the blood. Kidney failure is a serious condition that occurs when kidney function decreases significantly or stops altogether. Kidney failure has a wide impact on the physical, mental, and social health of patients. Therefore, early treatment and a holistic approach are needed to minimize its impact. In the health sector, technological advances have enabled more effective processing of medical data through the application of data mining. Data Mining is the process of exploring and analyzing large amounts of data to find patterns, relationships, or valuable information that was previously unknown. Classification in Data Mining is the process of grouping or categorizing data into certain classes or labels based on the attributes or features it has. In the classification itself, there are various algorithms in it such as the K-Nearest Neighbor (KNN) and Random Forest (RF) algorithms. The K-Nearest Neighbor (KNN) and Random Forest (RF) algorithms are two algorithms that are widely used in classification tasks. Therefore, this study will carry out a comparison process on the performance of the K-Nearest Neighbor algorithm and the Random Forest algorithm. Comparison of data mining algorithm performance to evaluate and determine which algorithm is the most effective and efficient in solving a particular problem based on various evaluation metrics. Overall, the accuracy value obtained is above 90%, but the Random Forest algorithm has better performance. Where the accuracy level results obtained from the Random Forest algorithm are 99.75%. Therefore, the model or pattern produced by the Random Forest algorithm will later be used to assist in the process of diagnosing kidney failure and the Random Forest algorithm is an algorithm that has better performance.

Perancangan Model Sistem Aspirasi Mahasiswa Berbasis Web Menggunakan Metode Rapid Application Development Di STMIK Widya Cipta Dharma Cembes, Yosefina; Ekawati, Hanifah; Pratiwi, Heny
JEKIN - Jurnal Teknik Informatika Vol. 5 No. 2 (2025)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v5i2.1439

Aspirasi mahasiswa merupakan bentuk partisipasi aktif dalam menyampaikan pendapat, kritik, dan saran terhadap sistem yang berlaku di lingkungan perguruan tinggi. Namun, mekanisme penyampaian aspirasi di STMIK Widya Cipta Dharma masih menggunakan Google Form yang belum terintegrasi, sehingga menimbulkan kendala dalam efisiensi, dokumentasi, dan transparansi pengelolaan. Penelitian ini bertujuan untuk merancang sistem aspirasi mahasiswa berbasis web sebagai solusi yang lebih terstruktur dan efektif. Pengembangan dilakukan menggunakan metode Rapid Application Development (RAD), yang memungkinkan proses iteratif dan melibatkan umpan balik langsung dari pengguna. Sistem ini dirancang untuk tiga jenis pengguna utama: mahasiswa, admin, dan penanggung jawab institusi. Salah satu kebaruan (novelty) sistem ini dibandingkan penelitian sebelumnya adalah adanya fitur pengajuan aspirasi secara anonim tanpa login serta pelacakan status aspirasi secara real-time. Selain itu, penelitian ini juga menambahkan evaluasi usability menggunakan System Usability Scale (SUS), yang belum banyak diterapkan pada penelitian serupa sebelumnya. Hasil pengujian blackbox menunjukkan bahwa seluruh fitur berfungsi dengan baik, dan evaluasi SUS terhadap 10 responden menghasilkan skor rata-rata 83,3, yang termasuk kategori Excellent. Secara praktis, sistem ini terbukti meningkatkan efisiensi, aksesibilitas, dan transparansi dalam pengelolaan aspirasi mahasiswa, serta memberikan pengalaman pengguna yang positif. Kontribusi utama dari penelitian ini adalah terciptanya sistem awal yang adaptif, aman, dan responsif terhadap kebutuhan mahasiswa, serta dapat dijadikan landasan untuk pengembangan sistem layanan aspirasi digital yang lebih komprehensif di masa mendatang.

Evaluation Of COCOMO Model Accuracy In Software Effort Estimation Jeklin, Umar; Ibnu Saad, Muhammad; ekawati, Hanifah
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2027

Accurate effort estimation underpins on-time,on-budget software delivery. This study empirically assesses the baseline Constructive cost Model (COCOMO) by applying standard organic-mode parameters (a = 2.4, b = 1.05) to the COCOMONASA dataset, which contains 63 NASA projects ranging from 2 KLOC to 100 KLOC. Model ourputs are benchmarked against recorded person-month effort using Mean Absolute Error (MAE), Mean Magnitude of Relative Error (MMRE), and Predcitions at 25 percent error (PRED 0.25). Results show MAE values 295-661 person-months and an MMRE near 1.0, indicating average relative error of ~100 percent. PRED (0.25) equals 0.0, meaning no project is estimated within the industry-accepted 25% band. Sensitivity tests on 5- and 20-project subsets reveal similar patterns, confiriming that the inaccuracy is systemic rather than dataset-specific. Using uncalibrated COCOMO in present-day projects poses a high risk of severe under- or over allocation of resources, potentially trigerring budget overruns and schedule slips. By quantitatively exposing where and how the baseline model fails, this work provides a benchmark for and a roadmap toward-targeted parameter calibration and hybrid approaches that incorporate additional cost drivers or machine-learning techniques. Future research should explore automatic parameter tuning and context-aware hybrid models to achieve dependable effort estimation in contemporary software engineering.

Development of a Financial Information System Website at Gkii Muara Asa Church Setiawan, Hendri; Ekawati, Hanifah; Harianto, Kusno
IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v9i1.402

Financial management in GKII Muara Asa Church has traditionally been conducted manually using physical books and spreadsheets, making it prone to recording errors, reporting delays, and lack of transparency for church members. To address these issues, a web-based Financial Information System (FIS) website was developed to facilitate transaction input, digital data storage, real-time financial reporting, and information access for members. The system was built using the Waterfall model of the System Development Life Cycle (SDLC), including planning, analysis, design, implementation, testing, and maintenance phases. Technologies used include Laravel as the backend, MySQL for database management, and Bootstrap for frontend development. Functional testing showed that all core features such as login, transaction input, data search, and backup operate as expected with an average response time under 2 seconds. The implementation proves that the system successfully improves efficiency, accuracy, and transparency in church financial management.

Development of a Financial Information System Website at Gkii Muara Asa Church Setiawan, Hendri; Ekawati, Hanifah; Harianto, Kusno
IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v9i1.402

Financial management in GKII Muara Asa Church has traditionally been conducted manually using physical books and spreadsheets, making it prone to recording errors, reporting delays, and lack of transparency for church members. To address these issues, a web-based Financial Information System (FIS) website was developed to facilitate transaction input, digital data storage, real-time financial reporting, and information access for members. The system was built using the Waterfall model of the System Development Life Cycle (SDLC), including planning, analysis, design, implementation, testing, and maintenance phases. Technologies used include Laravel as the backend, MySQL for database management, and Bootstrap for frontend development. Functional testing showed that all core features such as login, transaction input, data search, and backup operate as expected with an average response time under 2 seconds. The implementation proves that the system successfully improves efficiency, accuracy, and transparency in church financial management.

Clustering the Economic Conditions of Various Countries From 2010-2023 by Conducting A Comparative Analysis of the K-Means and K-Medoids Algorithms Yunita, Yunita; Ekawati, Hanifah; Yusnita, Amelia
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7330

Understanding the similarities and differences in economic conditions across countries is crucial for various stakeholders. This research investigates the global economic landscape by clustering countries based on their economic indicators, including GDP, inflation rate, unemployment rate, and economic growth, spanning the period of 2010 to 2023. This timeframe encompasses significant global economic events, making it pertinent for analysis. The study employs and compares two prominent clustering algorithms: K-Means and K-Medoids, to identify groups of countries exhibiting similar economic patterns. Utilizing secondary data from Kaggle encompassing 19 countries, the research assesses the ability of each algorithm to delineate meaningful economic clusters. The K-Means algorithm, with a determined optimal number of four clusters, demonstrated a reasonably good cluster separation and moderate internal cohesion, evidenced by a Silhouette Coefficient of 0.58 and a Davies-Bouldin Index of 0.63. In contrast, the K-Medoids algorithm yielded a distinct clustering structure with a lower Silhouette Coefficient (0.26) and a higher Davies-Bouldin Index (1.16), suggesting less distinct cluster separation and potential sensitivity to data characteristics. This comparative analysis provides insights into the applicability and performance of K-Means and K-Medoids in discerning global economic structures, contributing to a deeper understanding of the world economic map and the utility of clustering techniques in economic data analysis.

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