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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Innovation in Research of Informatics (INNOVATICS) Jutsi: Jurnal Teknologi dan Sistem Informasi Jurnal Teknisi Journal of Computer Science and Informatics Engineering Jurnal Teknik Informatika dan Desain Komunikasi Visual IC Tech: Majalah Ilmiah Journal of Innovative and Creativity Jurnal Pengabdian Kepada Masyarakat Indonesia
Taufik hidayat
Universitas Selamat Sri
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Analysis Development and Design of Local Area Network: Systematic Literature Review Tri Muji Waluyo; Dian Novitaningrum; Yuni Handayani; Taufik Hidayat
JURNAL TEKNISI Vol. 6 No. 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v6i1.5307

Abstract

Abstract: The development of information technology is very important, especially in computer networks. The lack of information related to the development of computer networks, particularly Local Area Networks (LAN), necessitates this research to improve network performance. Therefore, this necessitates analysis and planning of computer networks in offices and companies, which has been done previously. This study aims to evaluate the application of computer networks, particularly the development of LAN in previous studies. The solution to this problem is one of the factors behind this study. Meanwhile, the research method used is Systematic Literature Review (SLR) using journals published in 2022–2025 from Google Scholar. The results of the research obtained are references in the form of advantages, disadvantages, and recommendations for development in the majority of schools. Therefore, this study emphasises the importance of technological development as the basis for internet implementation. Thus, the conclusion is that the use of LAN networks is highly recommended for use in institutions, one of which is educational institutions or schools. Keyword: internet; local area network (LAN); technological development Abstrak: Perkembangan teknologi informasi sangat penting terutama pada jaringan komputer, minimnya informasi terkait perkembangan jaringan komputer khususnya Local Area Network (LAN) membuat diperlukannya penelitian ini untuk meningkatkan performa jaringan. Oleh karena itu hal tersebut melatar belakangi diperlukannya analisis dan perencanaan pada sebuah jaringan komputer pada kantor maupun perusahaan yang telah dilakukan sebelumnya. Penelitian ini bertujuan untuk mengevaluasi penerapan Jaringan Komputer utamanya pada perkembangan LAN pada penelitian sebelumnya. Solusi dari permasalahan tersebut menjadi salah satu factor dilakukannya penelitian ini. Sedangkan, metode penelitian yang digunakan yaitu Systematic Literature Review (SLR) dengan menggunakan jurnal yang terbit pada 2022 – 2025 dari Google Scholar. Hasil penelitian yang didapatkan adalah referensi berupa keunggulan, kelemahan, dan rekomendasi perkembangan pada mayoritas sekolah. Oleh karena itu, penelitian ini menekankan pentingnya perkembangan teknologi sebagai dasar dalam penerapan internet. Maka dari itu kesimpulannya bahwa penggunaan jaringan LAN sangat direkomendasikan untuk digunakan pada instansi salah satunya adalah instansi pendidikan atau sekolah.Kata kunci: internet; local area network (LAN); perkembangan teknologi
Mapping Leading Commodities of Community Forest Plantations Based on Productivity Using the K-Means Clustering Algorithm Taufik Hidayat; Yuni Handayani; Muhammad Khozin; Tri Muji Waluyo; Dian Novitaningrum; Tresi Aprilia; Muchamad Achsin Samas
Journal of Computer Science and Informatics Engineering Vol 5 No 3 (2026): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i3.1797

Abstract

Kendal Regency has significant potential in community forest plantations, which contribute to the regional economy. However, the mapping of leading commodities based on productivity has not been conducted optimally. This study aims to map leading community forest plantation commodities using the K-Means Clustering algorithm. The novelty of this study lies in the application of the K-Means Clustering algorithm by integrating land area and production volume as the basis for mapping leading commodities at the regency level. Secondary data from the Central Bureau of Statistics of Kendal Regency for the 2019–2023 period, covering seven community forest plantation commodities, were used. The research stages included data preprocessing using Min-Max normalization, clustering into three clusters using the K-Means algorithm, and cluster evaluation employing the Within-Cluster Sum of Squares (WCSS). The results show that the K-Means algorithm successfully grouped the commodities into three clusters based on their productivity characteristics. Sugarcane formed a distinct cluster as the leading commodity due to its highest productivity despite its relatively small cultivation area. These findings provide data-driven insights to support decision-making for the development of community forest plantations in Kendal Regency
Liquefied Petroleum Gas (LPG) Leak Detection Mitigation System with MQ-6 Sensor based on the Internet of Things (IoT) Dian Novitaningrum; Yuni Handayani; Taufik Hidayat
Innovation in Research of Informatics (Innovatics) Vol 7, No 2 (2025): September 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i2.16705

Abstract

The community is beginning to shift from the use of petroleum fuel to Liquefied Petroleum Gas (LPG). In 2023, the Kendal Regency Statistics Agency recorded 53 cases of fire. One of the factors contributing to these fires was gas cylinder leaks, which require preventive measures, education, and mitigation efforts for the proper use of LPG. This research was conducted by designing an LPG gas leak detection system based on the Internet of Things (IoT) using an MQ-6 sensor to notify users of emergencies. The systems aims to notify users via the Blynk application to prevent gas leaks. The research method includes designing the device by assembling and testing components. Additionally, software was developed to connect the sensor to the notification application using Blynk. The system can detect LPG gas leaks within a range of 1-16 cm. A safe threshold is defined as gas levels < 40 ppm, while levels >45 ppm indicate a hazardous status. The conclusions from this research shows that the average gas concentration when the green LED is on 33 ppm with a detection time of 0 seconds, the yellow LED at 40.6 ppm with a detection time of 11.6 seconds, and the red LED at 50 ppm with a detection time of 25.3 seconds, accompanied by a buzzer sounding as a warning of a gas leak in the LPG cylinder. Further research focused on improving the accuracy of the system connected to users WhatsApp accounts.
PERBANDINGAN ALGORITMA LOGISTIC REGRESSION DAN NAÏVE BAYES CLASSIFIER DALAM IDENTIFIKASI PENYAKIT LIVER Yuni Handayani; Taufik Hidayat; Dian Novitaningrum; Abdul Rahman Ismail
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.2892

Abstract

Abstract: Liver disease is a condition caused by various factors that can damage liver function, such as viral infections and alcohol consumption. Additionally, obesity is closely associated with liver damage. Over time, liver damage can lead to serious consequences. The presence of experts in this field is crucial to addressing liver disease by identifying the symptoms experienced by patients, determining the type of liver disease affecting them, and providing appropriate treatment guidance. The severity of this disease in Indonesia is evident from various studies, research, and related observations. In this study, researchers utilized and compared two data mining classification methods, namely Logistic Regression and Naïve Bayes, to diagnose liver disease. The findings revealed that the Logistic Regression method achieved an accuracy rate of 84.62% with an area under the curve (AUC) value of 0.841, while the Naïve Bayes method achieved an accuracy rate of 83.71% with an AUC value of 0.816. Based on the t-test, it was found that there was no significant difference between the two methods, with a p-value of 0.821 > 0.05. This indicates that the performance of Logistic Regression is comparable to Naïve Bayes in diagnosing liver disease.Keyword: Liver Disease, Logistic Regression, Naïve Bayes, Confusion Matrix, ROC CurveAbstrak: Penyakit hati atau liver adalah kondisi yang disebabkan oleh berbagai faktor yang dapat merusak fungsi hati, seperti infeksi virus dan konsumsi alkohol. Selain itu, obesitas juga memiliki kaitan erat dengan kerusakan hati. Dalam jangka panjang, kerusakan hati dapat menimbulkan konsekuensi serius. Kehadiran ahli di bidang ini sangat diperlukan untuk membantu menangani masalah penyakit hati dengan mengidentifikasi gejala yang dialami pasien, menentukan jenis penyakit hati yang diderita, serta memberikan panduan penanganan yang sesuai. Skala permasalahan penyakit ini di Indonesia dapat diamati melalui berbagai studi, penelitian, dan pengamatan yang telah dilakukan. Dalam penelitian ini, peneliti menerapkan serta membandingkan dua metode klasifikasi data mining, yaitu Logistic Regression dan Naïve Bayes, untuk mendeteksi penyakit liver. Hasil penelitian menunjukkan bahwa Logistic Regression memiliki tingkat akurasi sebesar 84,62% dengan nilai area under the curve (AUC) sebesar 0,841, sementara Naïve Bayes mencapai akurasi 83,71% dengan AUC sebesar 0,816. Berdasarkan hasil uji-t, tidak ditemukan perbedaan signifikan antara kedua metode tersebut, dengan nilai p = 0,821 yang lebih besar dari 0,05. Ini menunjukkan bahwa performa Logistic Regression sebanding dengan Naïve Bayes dalam proses diagnosis penyakit liver.Kata kunci: Penyakit Liver, Logistic Regression, Naïve Bayes, Confusion Matrix, ROC Curve
OPTIMASI KLASIFIKASI KEPUASAN KONSUMEN MENGGUNAKAN C4.5 DI ANEKA JAYA KENDAL Taufik Hidayat; Toriq Karismantoro; Muchamad Achsin Samas
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.4158

Abstract

Abstract: The development of industrial word, especially supermarkets, continues to experience a rapid increase, therefore there is competition among the supermarket industry in various regions, cv. aneka jaya kendal is one of the largest supermarkets in kendal, buyer satisfaction with the services and facilities provided by aneka jaya kendal will be an added value for consumers compared to other supermarkets. This will be a very profitable advantage for various jaya kendal, but the level of customer satisfaction of various jaya kendal consumers is difficult to assess the quality of service because it is intangible, subjective and varied, but by using one of the data mining techniques this can be done, the purpose of this study is to assess the level of customer satisfaction and facilitate the company in improving its services even better, the method used to calculate the level of customer satisfaction is one of the dalta mininlg techniques in classification using the c4 algorithm. 5 is expected to accurately calculate the level of consumer satisfaction and increase revenue. the results of the research obtained are the classification in the level of consumer satisfaction, namely 5 (five) puals decision rules and 4l (emplat) decision rules not pullak. the conclusion of the results of this study is obtained after calculating by calculating data with the c4.5 algorithm which gets an accuracy value for the classification of consumer satisfaction levels of 97.86%.                                                                              Keywords: classification; services; consumers; c4.5 algorithm; aneka jaya. Abstrak: Perkembangan dunia industri khususnya supermarket terus mengalami peningkatan yang pesat, oleh karna itu terjadilah persaingan di antara industri supermarket di berbagai wilayah, cv. aneka jaya kendal merupakan salah satu swalayan terbesar di kendal, kepuasan pembeli terhadap pelayanan dan fasilitas yang diberikan oleh aneka jaya kendal akan menjadi nilai tambah bagi konsumen di bandingkan swalayan yang lain. hal ini akan menjadi keuntungan yang sangat menguntungkan bagi aneka jaya kendal, akan tetapi tingkat kepuasan konsumen aneka jaya kendal sulit dinilai kualitas pelayanannya karna tidak berwujud, subjektif dan bervariasi, tetapi dengan menggunakan salah satu teknik data mining hal ini dapat di lakukan, tujuan penelitian ini untuk menilai tingkat kepuasan konsumen dan mempermudah pihak perusahaan dalam meningkatkan pelayanannya lebih baik lagi, metode yang digunakan untuk menghitung tingkat kepuasan konsumen adalah salah satu tleknik dalta mininlg dalam klasifikasi dengan menggunakan algoritma c4.5 diharapkan dapat menghitung secara akurat tingkat kepusan konsumen dan meningkatkan pendapatan. hasil dari penelitian yang di peroleh adalah klasifilkasi dalam tingkat kepuasan konsumen yaitu 5 (lima) aturan kelputusan puals danl 4l (emplat) aturan keplutusan tidlak pulas. kesimpulan hasil penelitian ini di dapatkan setelah di lakukan perhitungan dengan menghitung data dengan algoritma c4.5 yang di dapatkan nilai akurasi terhadap klasifikasi tingkat kepuasan konsumen sebesar 97.86%. Kata kunci: klasifikasi; pelayanan; konsumen; algoritma c4.5; aneka jaya
Co-Authors Atik Dina Nasikhah Bagus Aji Pradana Darnis, Rahmi Derry Setiawan Dian Novitaningrum Edi Hariyanto Hanif Arruhama Harry Soepandi Ismail, Abdul Rahman Muchamad Achsin Samas Muhammad Fabian Arrizqi Muhammad Khozin Pohan, Sry Dhina Riswanto To Adn Siroj Toriq Karismantoro Tresi Aprilia Tri Muji Waluyo Yuni Handayani Zumatul Firda Salsa Bella