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All Journal Indonesian Journal on Software Engineering (IJSE) Jurnal Pilar Nusa Mandiri Jurnal Teknoinfo Journal of Innovation and Future Technology (IFTECH) Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Teknologika Jurnal Informatika dan Rekayasa Perangkat Lunak
Ade Christian, Ade
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Prediksi Penyakit Diabetes Melitus Menggunakan Metode Support Vector Machine dan Naive Bayes Maulidah, Nurlaelatul; Supriyadi, Riki; Utami, Dwi Yuni; Hasan, Fuad Nur; Fauzi, Ahmad; Christian, Ade
Indonesian Journal on Software Engineering (IJSE) Vol 7, No 1 (2021): IJSE 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v7i1.10279

Abstract

Diabetes melitus adalah penyakit metabolik yang ditandai terjadinya kenaikan gula darah yang disebabkan oleh terganggunya hormon insulin yang memiliki fungsi sebagai hormon dalam menjaga homeostatis tubuh menggunakan cara penurunan kadar gula darah (American Diabetes Association, 2017). World Health Organization (WHO) memperkirakan jumlah penderita diabetes melitus orang dewasa diatas 18 tahun dalam tahun 2014 berjumlah 422 juta (WHO, 2016:25). Prevalensi diabetes melitus Asia Tenggara sudah berkembang dalam tahun 1980 sebanyak 4,1% dan tahun 2014 menjadi sebanyak 8,6%. Menurut Riset Kementerian Kesehatan pada tahun 2018, Prevalensi diabetes Indonesia sebanyak 2,0%, sedangkan di Provinsi Jawa Timur sebanyak 2,6% pada penduduk umur diatas 15 tahun (KEMENKES RI, 2019). Penelitian ini dikembangkan melalui pengolahan data sekunder database kesehatan Dataset Diabetes yang diambil dari dataset Kaggle dan dapat diakses melalui https://www.kaggle.com/johndasilva/diabetes. Dimana datanya sendiri terdiri dari 2000 record dengan beberapa variabel prediktor medik (Pregnancies/Kehamilan, Glucose/Glukosa, BloodPressure/Tekanan Darah, SkinThickness/Ketebalan Kulit, Insulin, BMI/Indeks Masa Tubuh, DiabetesPedigreeFunction/Keturunan, Age/Umur and Outcome/Hasil). Kemudian data tersebut akan diolah dengan menggunakan metode Support Vector Machine dan metode Naive Bayes untuk mengetahui akurasi hasil diagnosa diabetes. Berdasarkan hasil dari penelitian yang sudah dilakukan metode Support Vector Machine memiliki nilai akurasi yang jauh lebih tinggi dibandingkan dengan menggunakan metode Naive Bayes. Nilai akurasi untuk model metode Support Vector Machine adalah 78,04% dan nilai akurasi untuk metode Naive Bayes 76,98%. Berdasarkan nilai ini, perbedaan akurasinya adalah 1,06%. Sehingga dapat disimpulkan bahwa penerapan metode Support Vector Machine mampu menghasilkan tingkat akurasi diagnosis diabetes yang lebih baik dibandingkan dengan menggunakan metode Naive Bayes.
OPTIMIZING ELECTRICITY SUBSIDIES: A TOPSIS-BASED DECISION-MAKING APPROACH Amin, Ruhul; Christian, Ade; Radiyah, Ummu; Sumanto, Sumanto; Hariyanto, Hariyanto; Yani, Ahmad
Jurnal Teknoinfo Vol 18, No 1 (2024): Januari
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i1.3608

Abstract

A individual or household is said to be in poverty if their income is insufficient to cover even the most basic requirements. According to BPS, 40% of Indonesians live in the country with the weakest economy. The use of power subsidies is one of the government's strategies for combating poverty. To combat poverty, the government works with PT. PLN to implement an electrical subsidy scheme that distributes payments to disadvantaged neighborhoods. The goal of the subsidy is to ensure the availability of power while assisting underprivileged customers and those who haven't heard from PT. PLN so they may take part in enjoying electrical energy. However, there are still challenges when there are several procedures, which makes it difficult to make judgments since they must take into account numerous factors. Using TOPSIS to solve 10 possibilities, including the following, is one way to get around the FMADM's various requirements: job, income, dependents, vehicle assets, home ownership, building area, source of drinking water, electrical power range, kind of floor, and type of house wall. According to the study's precise findings, only 11 residents out of 20 submissions received immediate recommendations for receiving power subsidies without having to wait a lengthy period. Additionally, although 9 people received recommendations for aid, only 1 received a recommendation against receiving support.
RANCANG BANGUN SISTEM INFORMASI PEMINJAMAN PERANGKAT DEMO VIDEO CONFERENCE BERBASIS WEB DENGAN MODEL WATERFALL Christian, Ade; Ariani, Fattya
Jurnal Pilar Nusa Mandiri Vol 14 No 1 (2018): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1088.726 KB) | DOI: 10.33480/pilar.v14i1.100

Abstract

Dalam era globalisasi sekarang ini, teknologi informasi melaju dengan cepatnya. Adapun komputer yang merupakan peralatan yang diciptakan untuk mempermudah pekerjaan manusia, saat mencapai kemajuan baik di dalam pembuatan hardware maupun software. PT. Aliansi Sakti membutukan sekali adanya suatu system database yang menunjang dan memberikan kemudahan dalam mendata perangkat demo unit. Dikarenakan masih dilakukan pendataan barang demo secara manual, sehingga sering terjadi penataan perangkat demo yang masih berantakan. Hal ini dipicu karena banyaknya perangkat demo unit milik PT. Aliansi Sakti. Dan saat proses berlangsung terjadi kesalahan dalam pencatatan, kurang akuratnya laporan yang dibuat dan keterlambatan dalam pencarian data-data yang diperlukan. Perancangan sistem database ini merupakan solusi yang terbaik untuk memecahkan permasalahan- permasalahan yang ada. Serta dengan sistem yang terkomputerisasi dapat tercapai suatu kegiatan yang efektif dan efisien dalam menunjang aktifitas pada perusahaan ini. Sistem yang terkomputerisasi lebih baik dari sistem yang manual agar berjalan lebih efektif dan efisien.
EVALUASI PENERAPAN INVENTORY SYSTEM MENGGUNAKAN TECHNOLOGY ACCEPTANCE MODEL (TAM) Christian, Ade
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (944.647 KB) | DOI: 10.33480/pilar.v15i1.401

Abstract

This research aim was to evaluate and analyze Inventory System implementation using the Technology Acceptance Model (TAM). The data used in this research are primary data and secondary data, collected using several data collection techniques, such as observation, interviews, questionnaires, and literature review. The variables in this research are Perceived Usefulness, Perceived Ease of Use, Attitude Toward Using, Perceived Enjoyment, Acceptance of IT. Processing and analysis of data in this research were using descriptive statistical analysis and simple linear regression analysis, which done by the support of the Application SPSS version 21. The results of this research are as follows 1) perceived ease of use Inventory System has given a positive and significant influence on Perceived Usefulness. 2) Perceived Usefulness Inventory System has given a positive and significant influence on user’s attitude. 3) Perceived Ease of Use has given positive and significant influence on the user’s attitude. 4) Perceived Enjoyment has given positive and significant influence on the user’s attitude. 5) Perceived Usefulness has given a positive and significant influence on the acceptance of IT. 6) Perceived Ease of Use has given positive and significant influence on the acceptance of IT.
Pelatihan Desain Grafis Untuk Memaksimalkan Peran Media Sosial Pada JPRMI Menggunakan Aplikasi Canva Supriyadi, Supriyadi; Christian, Ade; Suryani, Indah; Rusdi, Ibnu
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 4 No. 3 (2024): Mei 2024 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v4i3.542

Abstract

Penyajian informasi visual sangat penting dalam menyampaikan pesan secara efektif. Informasi visual memiliki kekuatan untuk menyampaikan ide, data, dan konsep secara cepat, menarik, dan mudah diingat. Informasi visual cenderung lebih mudah diingat daripada informasi dalam bentuk teks. Rasio pemrosesan visual dalam otak manusia jauh lebih tinggi, sehingga informasi visual dapat meninggalkan kesan yang lebih kuat dan tahan lama dalam ingatan. Canva adalah salah satu alat atau platform yang populer digunakan untuk mendesain informasi visual. Canva menawarkan berbagai fitur dan template yang memudahkan pengguna dalam membuat grafis, infografis, poster, presentasi, dan desain visual lainnya. Pengabdian kepada masyarakat dalam bentuk pelatihan Canva dapat memberikan manfaat yang signifikan bagi JPRMI dalam menciptakan materi dan konten yang menarik serta memperkuat komunikasi visual dalam lingkup tugas mereka. Dengan Canva, JPRMI dapat membuat brosur, poster, undangan, dan materi promosi lainnya dengan mudah dan cepat. Mereka dapat memilih template yang sesuai, menambahkan informasi acara, mengedit desain, dan menghasilkan materi promosi yang menarik dan profesional.
PEMILIHAN DOSEN TELADAN BERPRESTASI DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) Pujiastuti, Lise; Amin, Ruhul; Hariyanto, Hariyanto; Supriyatna, Adi; Christian, Ade; Sumanto, Sumanto
Journal of Innovation And Future Technology (IFTECH) Vol 6 No 2 (2024): Vol 6 No 2 (August 2024): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v6i2.3398

Abstract

This study aims to evaluate the performance of lecturers in higher education using the Multi Attribute Utility Theory (MAUT) method. The main problem faced is the complexity of assessing lecturers based on the Tri Dharma of Higher Education-education, research, and community service-as well as the challenges of subjectivity and inefficiency in manual assessment. MAUT was chosen due to its ability to consider various assessment criteria in a structured and objective manner and follows the standardization of outstanding lecturer assessment including: Education, Research, Community Service, Discipline, Commitment, Cooperation Ability and Ability to innovate. The results showed that Adi Fajar Insani had the best performance with a total final score of 1.01, while Dian Eka Fitriani had the lowest score of 0.00. The MAUT method proved effective in providing a comprehensive and fair assessment, overcoming the limitations of traditional methods that are not thorough. The conclusion of this study is that the application of MAUT can improve the objectivity, efficiency, and accuracy of the lecturer evaluation process, thus encouraging the improvement of lecturer quality and productivity in various fields. Further research is recommended to develop more relevant assessment criteria, involve larger samples, and explore the use of more sophisticated technology to support the assessment process.
Supplier Selection Very Small Aperture Terminal using AHP-TOPSIS Framework Sumanto, Sumanto; Indriani, Karlena; Marita, Lita Sari; Christian, Ade
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6290

Abstract

There are several methods of decision making VSAT IT goods suppliers such as: Promethee, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytical Hierarchy Process (AHP). Decision-making in the selection of the best suppliers, we have the basis of assessment criteria, and we will also be faced with more than one alternative. If alternatives are only two, maybe still easy for us to choose, but if the alternative is a lot of choice, it is quite difficult for us to decide. Analytical Hierarchy Process (AHP) is a technique that was developed to help overcome this difficulty, because the Analytical Hierarchy Process (AHP) is a form of decision-making model with many criteria. One of the reliability of the Analytical Hierarchy Process (AHP) is able to perform simultaneous analysis and integrated between the parameters of qualitative or quantitative. In this study the authors use six criteria and alternatives 6, the results of these alternatives will be obtained perangkingan alternative used as a reference supplier selection VSAT IT goods company Total EP Indonesie
ANALISIS MACHINE LEARNING UNTUK PREDIKSI PENYAKIT PARU-PARU MENGGUNAKAN RANDOM FOREST Christian, Ade; Hariyanto, Hariyanto; Yani, Ahmad; Sumanto, Sumanto
Journal of Innovation And Future Technology (IFTECH) Vol. 7 No. 1 (2025): Vol 7 No 1 (Februari 2025): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v7i1.3906

Abstract

Lung diseases, including COPD, lung cancer, and asthma, are serious global health issues, causing over seven million deaths annually. Advanced technologies, such as deep learning and the Random Forest algorithm, have been effectively utilized to detect and classify lung diseases from imaging data with high accuracy. This study aims to demonstrate the effectiveness of Random Forest in predicting lung diseases. The dataset used consists of 30,000 records with 11 attributes, collected from Kaggle and processed using Orange software version 3.36.2. The implementation of the Random Forest algorithm was conducted with 10 decision trees and six attributes considered at each split. The model was tested using Cross Validation with 10 folds. The testing results showed an AUC value of 0.993, indicating a very high level of accuracy. A confusion matrix was used to measure the model's performance through various metrics, including accuracy, precision, recall, F1-score, and AUC. This model achieved high accuracy, with ROC AUC values of 0.453 for predicting the presence of lung disease and 0.547 for predicting its absence. These results confirm that the Random Forest algorithm is an effective predictive tool for identifying lung diseases. This study makes a significant contribution to the development of more accurate and efficient diagnostic techniques, assisting medical professionals in identifying lung diseases in patients. With a deeper understanding of how this algorithm operates in the healthcare domain, it is expected to significantly enhance the quality of patient diagnosis and care.
Modification of Multi-Attributive Border Approximation Area Comparison (MABAC) to Improve Multi-Criteria Assessment Hariyanto, Hariyanto; Christian, Ade; Nurhayati, M. Sinta; Sudarsono, Bibit
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 1 (2025): Volume 6 Number 1 March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i1.15

Abstract

Multi-criteria decision making (MCDM) is a field of study in decision-making that focuses on selecting or ranking alternatives based on several competing criteria. Multi-attributive border approximation area comparison (MABAC) is one of the methods in MCDM that is designed to evaluate and select the best alternative based on relevant criteria. The weakness of the MABAC method in the aspect of criterion weighting mainly lies in its dependence on the external weighting method. The data used in the Best Staff Selection case study included staff performance assessments based on several key criteria. The results of this data are then used in MCDM to determine the best staff based on the weight of objectively established criteria. The purpose of this study is to modify the MABAC method by integrating the geometric average method which aims to improve accuracy and objectivity in multi-criteria assessment. The results of the ranking with the MABAC-G method for the selection of the best employees show that employee 5 obtained the highest score of 0.2868 so that it is the best alternative in this assessment. The results of the comparison of the ranking of alternative selection of the best employees using the ranking from the company and the MABAC-G method obtained a Pearson correlation value of 0.9511 which shows that there is a very strong relationship between the two assessment systems. The application of research findings from MABAC-G in the future can be used in various fields that require multi-criteria decision-making with complex and uncertain data.
EVALUASI KINERJA TIM PENJUALAN: PENDEKATAN FUZZY AHP DALAM MODEL MCDM Indriani, Karlena; Saputra, Irwansyah; Nurmalasari; Yani, Ahmad; Christian, Ade
Jurnal Teknologika Vol 14 No 1 (2024): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v14i1.379

Abstract

Tenaga penjualan adalah aset paling penting bagi sebuah perusahaan. Pengembangan kompetensi tenaga penjualan tidak dapat sepenuhnya dievaluasi karena kompleksitas keterampilan yang langsung diperoleh dan digunakan. Kesulitan dalam menentukan kriteria penilaian yang sesuai untuk mengevaluasi kinerja tenaga penjualan di perusahaan tidak cukup hanya menggunakan persepsi manusia oleh manajemen. Hal tersebut karena penilaian dan persepsi manusia terhadap kriteria kualitatif selalu subjektif dan tidak tepat. Dalam menentukan beberapa kategori kriteria, diperlukan teknik kuantitatif dan kualitatif sebagai sarana pengambilan keputusan dalam organisasi. Penelitian kuantitatif menghasilkan data dalam bentuk angka, sedangkan penelitian kualitatif cenderung menghasilkan data yang disajikan dalam bentuk narasi dan teks. Dalam penelitian ini, diusulkan model MCDM menggunakan metode Fuzzy AHP untuk mengevaluasi kinerja tenaga penjualan di departemen pemasaran perusahaan guna menentukan prioritas dan peringkat objektif dari alternatif. Hasil penelitian menunjukkan bahwa konsistensi rasio validasi menggunakan metode Fuzzy AHP pada kriteria kuantitatif diperoleh nilai 0,016 dan 0,015 untuk kriteria kualitatif. Kemudian analisis sensitivitas digunakan untuk mengidentifikasi dampak dari perubahan pada bobot relatif kategori kriteria kuantitatif yang nilainya diturunkan sebesar 3,85%, sehingga mempengaruhi penilaian secara keseluruhan. Secara spesifik pada pre-test dengan nilai akurasi sebesar 85%, sedangkan pada post-test menghasilkan akurasi yang lebih besar dengan nilai 95%, dapat diinterpretasikan bahwa evaluasi kinerja tenaga penjualan menggunakan metode Fuzzy AHP menghasilkan prioritas dan peringkat alternatif yang lebih objektif dan sangat sesuai untuk diimplementasikan di perusahaan. Analisis uji t-produksi nilai p adalah 0,000494 yang lebih kecil dari nilai alpha (0,05), menunjukkan bahwa hasilnya efektif.
Co-Authors Adi Supriyatna ahmad yani Bibit Sudarsono Dwi Yuni Utami Fattya Ariani Fauzi Ahmad Muda HARIYANTO HARIYANTO Hasan, Fuad Nur Ibnu Rusdi Indah Suryani Karlena Indriani Lita Sari Marita Nurhayati, M Sinta Nurlaelatul Maulidah Nurmalasari Pujiastuti, Lise Riki Supriyadi Ruhul Amin, Ruhul Saputra, Irwansyah Sumanto, Sumanto Supriyadi Supriyadi Ummu Radiyah, Ummu