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Algoritma C4.5 Dalam Mengklasifikasi Tindak Kejahatan Yang Sering Terjadi Di Kecamatan Siantar Barat Pematangsiantar Soleh, Muhammad; Andani, Sundari Retno; Qurniawan, Hendry
TIN: Terapan Informatika Nusantara Vol 2 No 5 (2021): Oktober 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Crime is a problem that often occurs in everyday life and is an action that can cause certain parties to be harmed both physically and materially. Factors that influence these crimes include immorality, molestation, theft, gambling, extortion/threatening, embezzlement, fraud, and vandalism. The increase in crime at this time is very significant. Over time, crime increased in an erratic pattern. In this study, the authors tried to mine data (data mining) reports of crimes that occurred at the Siantar Barat Police, Pematangsiantar City from the previous year. The data were analyzed using the C.45 algorithm, where this algorithm aims to classify data on certain crime classes. With the creation of this system, it is hoped that it can assist the police in classifying crimes and minimizing areas prone to crime
Harnessing Diversity: The Role of Inclusive HR Practices in Driving Innovation and Organizational Growth Qurniawan, Hendry; Saragihi, Ilham Syahputra; Suhendro, Dedi
INVEST : Jurnal Inovasi Bisnis dan Akuntansi Vol. 5 No. 1 (2024): INVEST : Jurnal Inovasi Bisnis dan Akuntansi
Publisher : Lembaga Riset dan Inovasi Al-Matani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/invest.v5i2.1014

Abstract

This study explores the impact of inclusive human resource practices and workforce diversity on organizational growth, with a focus on the mediating role of innovation capability. Using data from Balai Pengelola Transportasi Darat Kelas II Provinsi Sumatera Barat, the research employs a quantitative design with random sampling, resulting in 78 respondents from a population of 352. Path analysis, conducted using SmartPLS, reveals significant direct and indirect effects of inclusive human resource practices and workforce diversity on organizational growth, mediated through innovation capability. Inclusive human resource practices significantly enhance innovation capability, which in turn drives organizational growth. Similarly, workforce diversity contributes to organizational growth by improving innovation capabilities. These findings highlight the importance of fostering an inclusive and diverse work environment to promote innovation and achieve sustainable organizational success.
Analisa Kelayakan Penerima Program Keluarga Harapan (PKH) Menggunakan Algoritma C4.5 Tanjung, Muhammad Amirsyah; P, Poningsih; Qurniawan, Hendry
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.286

Abstract

In overcoming the problem of poverty, the Government implements the Family Hope Program (PKH) which is a program assistance that provides assistance (subsidies) in cash to poor households as long as they meet the requirements set out in the program. The purpose of this study is to determine whether the family is still eligible or not receive the Family Hope Program (PKH) assistance, where there are many other disadvantaged families who have not had the opportunity to receive this assistance program. Sources of data obtained from the Martoba Village Head Office. The method used in the study is a data mining technique with the C4.5 algorithm which is implemented with the RapidMiner application. The attributes used in determining the family's eligibility are still feasible or not receiving assistance from this assistance program, namely income, number of family dependents, vehicle ownership and residence status. The results of the classification algorithm C4.5 and testing with Rapid Miner software, it is found that the factor that most influences the eligibility of the Family Hope Program (PKH) recipients is the number of stages (C1) with an acquisition value of 0.51827179
Metode Data Mining Klasifikasi Pada Kualitas Pelayanan Terhadap Nasabah Bank Syariah Mandiri dengan Model C4.5 Supriadi, Ari; P, Poningsih; Qurniawan, Hendry
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 6, No 1 (2021): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v6i1.279

Abstract

Customer satisfaction is the most important thing in assessing the level of management and services provided by the bank to its customers. The existence of banking services in society is indeed more profitable, especially in the economic sector, where economic actors are more free to carry out the process of economic activities to support survival. Data mining is an analysis of observations of large amounts of data to find relationships that are not known beforehand, data processed by the data mining method will produce a new knowledge sourced from old data, the results of processing can be used to determine future decisions. Using the C4.5 algorithm will predict which aspects are more dominant towards customer satisfaction. The data source of this research was collected based on a questionnaire (questionnaire) filled out by customers of Bank Syariah Mandiri in Pematangsiantar City. Data will be processed by calculating the value of entropy, calculating the gain value. So that the final results obtained in the form of a decision tree are expected to be input to the Bank Syariah Mandiri in Pematangsiantar City in maintaining the quality of its services to customers and improving the quality so that customers are always satisfied with the services provided
DAMPAK FASILITAS, SIKAP INOVATIF, DAN DISIPLIN TERHADAP KINERJA Suhendro, Dedi; Qurniawan, Hendry
Kinerja Vol 6 No 02 (2023): KINERJA : Jurnal Ekonomi dan Bisnis
Publisher : Fakultas Ekonomi dan Bisnis Universitas Islam As-Syafi'iyah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34005/kinerja.v6i02.3377

Abstract

Alasan dilakukannya penelitian ini untuk mengetahui seberapa besar dampak fasilitas terhadap kinerja guru, seberapa besar dampak sikap inovatif terhadap kinerja guru dan seberapa besar dampak disiplin terhadap kinerja guru. Sampel dalam penelitian ini berjumlah 35 orang guru. Teknik analisis data dalam penelitian ini menggunakan analisis deskriptif dan analisis regresi linier berganda. Hasil penelitian ini menjelaskan bahwa variabel fasilitas memiliki dampak positif dan signifikan terhadap kinerja guru sebesar 41.40%. Variabel sikap inovatif memiliki dampak positif dan signifikan terhadap kinerja guru sebesar 24.30% dan variabel disiplin memiliki dampak positif dan signifikan terhadap kinerja guru 46.80%. Sehingga secara keseluruhan dampak fasilitas, sikap inovatif dan disiplin berdampak positif dan signifikan terehadap kinerja guru sebesar 63.70%.
Implementasi Data Mining Menggunakan Algoritma Apriori Dalam Menentukan Persediaan Barang : Studi Kasus: Toko Sinar Harahap Tarigan, Putri Mai Sarah; Hardinata, Jaya Tata; Qurniawan, Hendry; Safii, M; Winanjaya, Riki
Jurnal Janitra Informatika dan Sistem Informasi Vol. 2 No. 1 (2022): April - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/janitra.v2i1.142

Abstract

UMKM ialah kegiatan usaha kecil ekonomi rakyat yang berskala kecil dan dilindungi dari kompetisi usaha yang tak sehat dan tak setara. Wirausaha yang bergerak dibidang pertokoan memiliki prospek yang menjanjikan, karena dapat melayanin masyarakat dengan kategori ekonomi menengah kebawah dan ke atas serta bisa mempermudah masyarakat untuk berbelanja keperluan tiap hari tanpa harus belanja ke supermarket atau swalayan. Namun persediaan barang atau bahan kebutuhan yang tidak dilakukan secara optimal dapat menyebabkan kekosongan pada barang atau bahan kebutuhan tersebut. Hal tersebut juga terjadi pada toko sinar harahap yang sering mengalami kekosongan pada persediaan beberapa barang dan kebutuhan yang di cari oleh pelanggan, ini di akibatkan dari tidak adanya kebiasaan pengontrolan persediaan pada toko. Maka penelitian ini bertujuan untuk melihat barang dan kebutuhan apa saja yang dibutuhkan oleh pelanggan toko. Penelitian ini menggunakan beberapa variabel yaitu tanggal transaksi, nama produk serta jumlah penjualan/pembelian. Maka, dari hasil penelitian menggunakan algoritma apriori tersebut akan di dapat data nama barang yang paling banyak terjual untuk di jadikan sebagai antisipasi persediaan barang agar tidak mengalami kekosongan yang dapat menyebabkan pelanggan kecewa.
Application of The Fuzzy Tsukamoto Method in Determining Household Industry Products Pasaribu, Nadra Savira; Hardinata, Jata Tata; Qurniawan, Hendry
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (560.05 KB) | DOI: 10.59934/jaiea.v1i1.57

Abstract

Production system at UD. Mie Akwang is a home industry that provides raw materials for noodle production. Uncertain consumer demand and supplies that are not in accordance with demand make it difficult for this industry to determine the amount of production that will be produced. Previously, this home industry did not have a valid rule to determine the amount of production that must be achieved. Therefore, a decision support system was developed using the Fuzzy Tsukamoto method. This method is the right method in making decisions that use several criteria to produce decisions on the amount of production. In this study, the data used is in the form of data on the amount of production in April 2021. From the calculation process that has been carried out, it can be concluded that if the demand is 28,950 portions and the supply is 30,000 portions, the total production produced is 31,207 portions. The results of these calculations are implemented in the form of a production system and the results obtained are the same, namely 31,207 portions.
Classification Model Optimization using Grid Search and Random Search in Machine Learning Algorithms Parinduri, Syawaluddin Kadafi; Alkhairi, Putrama; Irawan, Irawan; Qurniawan, Hendry
Bulletin of Informatics and Data Science Vol 4, No 2 (2025): November 2025
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v4i2.136

Abstract

The performance of a machine learning model is highly dependent on the selection and tuning of appropriate hyperparameters. The main problem in this study is how to improve the accuracy and stability of a classification model without sacrificing computational time efficiency, especially in the case of kidney disease classification that requires accurate and fast prediction results. This study aims to optimize the classification model by applying two hyperparameter search methods, namely Grid Search and Random Search, to the Random Forest algorithm. The kidney disease dataset is used as a case study with preprocessing processes including data cleaning, missing value imputation, categorical variable encoding, and normalization. Each model is tested using accuracy, precision, recall, and F1-Score metrics. The results show that the Grid Search_RF model produces the highest performance with perfect accuracy, precision, recall, and F1-Score values (1.0000), while Random Search_RF provides results close to (accuracy 0.9875 and F1-Score 0.9900) with more efficient training time. Meanwhile, the standard Random Forest without tuning still shows competitive performance (accuracy 0.9917 and F1-Score 0.9930). Based on these results, it can be concluded that hyperparameter optimization, using both Grid Search and Random Search, can significantly improve the performance of the classification model, with Random Search being the most efficient method for practical implementation in machine learning-based disease detection systems.