Claim Missing Document
Check
Articles

Found 16 Documents
Search

SISTEM PENDUKUNG KEPUTUSAN UNTUK MENGEVALUASI KINERJA DOSEN PRODI DI STIKOM UYELINDO KUPANG MENGGUNAKAN METODE TOPSIS Bisilisin, Franki Yusuf; Naatonis, Remerta R.
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 10 No. 2 (2019): Jurnal HOAQ - Teknologi Informasi
Publisher : STIKOM Uyelindo Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol10no2.p59-65

Abstract

STIKOM Uyelindo Kupang was established in the year 2000 as an information technology-based tertiary institution which has three study programs, namely under graduate of informatics engineering, diploma three informatics engineering and under graduate of information systems. The three study programs always strive to improve the status of accreditation by continuously improving internal quality and making accreditation a strategy to compete with other universities. To maintain quality, STIKOM Uyelindo Kupang, especially the undergraduate informatics engineering study program routinely monitors and evaluates the performance of lecturers. The problem that is often faced in routine monitoring and evaluation of lecturer performance is the performance evaluation process that is still objective so that to overcome these problems, a decision support system is needed that can assist in evaluating the performance of lecturers at STIKOM Uyelindo Kupang. The purpose of this study is to make a decision support system for the assessment of performance of lecturers of the first-degree informatics engineering study program at STIKOM Uyelindo Kupang using TOPSIS method. The results of this study are in the form of a desktop-based application that can facilitate the monitoring and performance evaluation teams of lecturers in evaluating the performance of lecturers of study programs
Klasifikasi Pola Konsumsi Energi Listrik Rumah Tangga Menggunakan Metode K-Nearest Neighbor Febiola Hutni Mosa; Franki Yusuf Bisilisin
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 5 No. 3 (2025): November: Jurnal Ilmiah Teknik Informatika dan Komunikasi 
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v5i3.1676

Abstract

The increasing demand for electrical energy in Kupang City, particularly in the Kayu Putih Subdistrict, necessitates a system capable of efficiently and accurately identifying electricity consumption patterns. The continuously rising demand for electrical energy may lead to various problems if not properly managed, such as supply disruptions or energy wastage. Therefore, this study aims to classify household electricity consumption patterns using a data-driven approach based on the K-Nearest Neighbor (KNN) method. The KNN method was chosen for its effectiveness in classifying data with a high level of accuracy, especially for datasets with complex characteristics. The designed system categorizes household electricity consumption into three main classes: low, medium, and high. This classification considers several important factors, including the number of family members, the types of electrical appliances used, and their daily usage habits. The results of the study indicate that the KNN method successfully classified household electricity consumption patterns with good performance. Testing using a confusion matrix achieved the highest accuracy of 97% at K = 4. This model was selected for implementation in the household electricity consumption classification system using the K-Nearest Neighbor (KNN) method.
EKSITENSI KESEPAKATAN PERKAWINAN ADAT PADA ERA MODERN DALAM KEDUDUKAN HUKUM ADAT DI DESA HONUK KECAMATAN ANFOANG BARAT LAUT Latuan, Yosep Jacob; Bisilisin, Franki Yusuf
Jurnal Education and Development Vol 14 No 1 (2026): Vol 14 No 1 Januari 2026
Publisher : Institut Pendidikan Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37081/ed.v14i1.7905

Abstract

Setiap orang berhak membentuk keluarga dan melanjutkan keturunan melalui perkawinan yang sah”. Perkawinan adalah sebuah ikatan lahir batin antara seorang pria dengan seorang wanita sebagai suami isteri dengan tujuan untuk membentuk keluarga atau rumah tangga yang bahagia dan kekal yang didasarkan pada Ketuhanan Yang Maha Esa. Perkawinan menurut HAM yaitu peristiwa yang sangat penting dalam kehidupan manusia. Dengan terjalinnya pernikahan akan melahirkan keturunan yang merupakan dasar terbentuknya sebuah keluarga dan terbentuknya sebuah negara dan bangsa. Perkawinan menurut hukum Adat merupakan suatu hubungan kelamin antara laki-laki dengan perempuan, yang membawa hubungan lebih luas, yaitu antara kelompok kerabat laki-laki dan perempuan, bahkan antara masyarakat yang satu dengan masyarakat yang lain. Lahirnya Undang-Undang Desa Nomor 6 Tahun 2014 tentang Desa, bisa menjadi solusi karena adanya peraturan desa yang dapat memuat segala ketentuan-ketentuan dan pengaturan perkawinan adat yang tidak bisa di akomodir oleh Undang-undang No. 1 Tahun 1974 tentang perkawinan. Semua ketentuan adat perkawinan yang tidak tertulis dapat dibuat dalam satu aturan desa yang di sesuaikan dengan kondisi adat,budaya dan sosial masyarakat yang ada di Indonesia, karena sesuai kewenangan yang di berikan oleh Undang-undang maka Kepala Desa bersama BPD dapat membuat Peraturan –peraturan dan lebih khusus lagi tentang perkawinan adat untuk di jadikan patokan / standar dalam perkawinan adat di sesuaikan dengan kondisi sosial masyarakat masing- masing daerah yang ada dalam wilayah Negara Kesatuan Republik Indonesia. Bagaimanakah Penyuluhan Kesepakatan Perkawinan adat dalam kedudukan hukum adat di Indonesia?.Apakah Efektifitas Peraturan Desa / Kesepakatan sebagai salah satu aturan Perundang- Undangan mampu mengakomodir kepentingan perkawinan adat?
KLASIFIKASI JENIS SUARA PENYANYI MENGGUNAKAN PROBABILISTIC NEURAL NETWORK (PNN) Gogi Afrendo Inabuy; Franki Yusuf Bisilisin
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 02 (2026): Volume 11 No. 2, Juni 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i02.50787

Abstract

Human voice is a sound produced when speaking, singing, laughing, and crying. In singing, each individual has unique voice characteristics, including variations in style, pitch, and vocal quality. Human voice types are generally divided into soprano, alto, tenor, and bass. However, identifying singers' voices still faces complex challenges. The main challenges include voice variability, overlapping characteristics between singers, and limited datasets. To overcome these, an accurate identification system is needed. This research uses 600 voice samples from 60 singers in the Talitakumi Pasir Panjang Church youth choir, with durations of 2-20 seconds in WAV format. The feature extraction method used is Mel-Frequency Cepstral Coefficients (MFCC), involving signal recording, preprocessing, signal segmentation, and Fourier transformation. For classification, Probabilistic Neural Network (PNN) is chosen due to its ability to generate probability distributions for each class. This research aims to develop a singer voice type classification system using PNN with MFCC feature extraction. It is hoped that this system can assist vocal trainers in classifying singer voice types more accurately, making a significant contribution to the field of voice and music analysis.
ANALISIS ROBUSTNESS CONVOLUTIONAL NEURAL NETWORK TERHADAP VARIASI PENCAHAYAAN PADA SISTEM PENGENALAN WAJAH Ezra Ananta Pandie; Franki Yusuf Bisilisin; Dewi Anggraini
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 2 (2026): Volume 12 Nomor 2 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i2.5833

Abstract

This study aims to evaluate the robustness of Convolutional Neural Networks (CNN) in face recognition systems under varying illumination conditions. The evaluation was conducted using a dataset comprising 36 subjects, with facial images captured under three distinct lighting scenarios: dim, normal, and bright. The research methodology involved training the CNN model using K-Fold Cross-Validation and assessing its stability against visual disturbances using artificial adversarial attacks based on the Fast Gradient Sign Method (FGSM). The novelty and main contribution of this study lie in the dual-evaluation approach, which simultaneously tests the model's resilience against natural illumination variations and artificial adversarial perturbations. Experimental results demonstrated that the CNN model achieved optimal face recognition performance at 50 epochs, maintaining an average accuracy rate of 81.48%. In conclusion, the evaluated CNN architecture is reliable and stable for face recognition in uncontrolled lighting environments, providing a solid foundation for developing more secure biometric systems against visual disturbances.
ANALISIS PENJUALAN PADA HAPPYMART MENGGUNAKAN ALGORITMA FP-GROWTH Hendrikus Lambertho Laba Kumanireng; Franki Yusuf Bisilisin; Dewi Anggraini
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 2 (2026): Volume 12 Nomor 2 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i2.5953

Abstract

Sales analysis is a crucial process for evaluating transaction data to understand consumption patterns and maximize business performance through a data-driven approach. HappyMart faces the challenge of significant transaction data growth, collecting a total of 1,500 transaction records during the period of August to October 2025. Inefficient manual analysis potentially triggers overstocking due to a lack of understanding of consumer purchasing patterns. This research aims to analyze purchasing patterns using the FP-Growth algorithm to formulate operational recommendations. The analysis stages include data collection, preprocessing, data transformation, and the extraction of association rules. System evaluation was conducted by comparing manual calculations in Excel, Python output, and RapidMiner. This experiment utilized a minimum support parameter of 0.2% and a minimum confidence of 60%. The research results identified product association patterns, where one of the strongest rules indicates: if consumers buy Terigu Kompas 1Kg and Aqua 1500ml, they will also buy Terigu Kompas 500G (support 0.2%, confidence 60%, and lift ratio 21.95). Practically, this highly correlated figure provides a direct contribution to the store in the form of recommendations for placing these products adjacent to each other in the same aisle, as well as implementing bundling promotion strategies to minimize stock accumulation.