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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika INFORMAL: Informatics Journal Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Al Qalam: Jurnal Ilmiah Keagamaan dan Kemasyarakatan Kasuari: Physics Education Journal (KPEJ) Technologia: Jurnal Ilmiah Jurnal Mnemonic JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Indonesian Journal of Data and Science Aiti: Jurnal Teknologi Informasi Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer
Christian Dwi Suhendra, Christian Dwi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Physics Social Sciences

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Sistem Pendukung Keputusan Untuk Optimasi Rantai Pasok Kentang Di Kabupaten Manokwari Menggunakan Metode TOPSIS Yati, Fatimah Aszhara; Marini, Lion Ferdinand; Suhendra, Christian Dwi
Technologia : Jurnal Ilmiah Vol 15, No 4 (2024): Technologia (Oktober)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v15i4.16329

Abstract

Manajemen rantai pasok komoditas pertanian, khususnya hortikultura, memiliki peran penting dalam memastikan ketersediaan produk berkualitas dengan harga terjangkau. Di Kabupaten Manokwari, Papua Barat, pengelolaan rantai pasok sayuran seperti kentang masih menghadapi berbagai kendala, termasuk infrastruktur yang terbatas dan manajemen rantai pasok yang kurang efisien. Penelitian ini bertujuan untuk menganalisis rantai pasok kentang di Kabupaten Manokwari dengan menggunakan salah satu metode sistem pendukung keputusan (SPK), metode TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) yang merupakan salah satu metode sistem pendukung keputusan untuk menentukan alternatif rantai pasok yang paling optimal. Penelitian ini dilakukan dengan mengumpulkan data melalui wawancara mendalam dengan para pelaku rantai pasok, seperti petani, pedagang, dan konsumen. Metode TOPSIS digunakan untuk merangking alternatif pemasok berdasarkan kriteria seperti kualitas, stok barang, dan harga jual. Hasil analisis menunjukkan bahwa distributor dari luar kota Manokwari, khususnya dari Makassar, memiliki kinerja rantai pasok yang lebih optimal dibandingkan pemasok lokal. Kesimpulannya, metode TOPSIS terbukti efektif dalam memberikan rekomendasi dalam pemilihan distributor terbaik untuk komoditas kentang di Kabupaten Manokwari.
Sistem Persediaan Obat Berbasis Web Pada UPTD Puskesmas Amban Manokwari Lantang, Stefanie Stanly; Suhendra, Christian Dwi; Sanglise, Marlinda
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 2 (2025): JPTI - Februari 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.688

Abstract

Pada UPTD Puskesmas Amban sistem pengelolaan persediaan obat saat ini masih dilakukan secara manual menggunakan buku atau arsip, oleh karena itu sering terjadi kekeliruan dalam pengelolaan persediaan obat menyebabkan lamanya proses pencarian data, adanya kemungkinan dokumen yang hilang dan pembuatan laporan yang lama sehingga hal ini dianggap kurang efisien. Tujuan penelitian ini untuk membangun sistem persediaan obat berbasis web pada Puskesmas Amban Manokwari yang aman dan mudah untuk diakses dan dicari datanya. Metode pengembangan yang digunakan dalam penelitian ini adalah metode waterfall. Sistem ini dibangun menggunakan Unified Modeling language (UML) dengan bahasa pemrograman PHP dan MySQL sebagai database. Hasil yang diperoleh adalah sebuah sistem persediaan obat berbasis web yang memudahkan petugas dalam mengelola persediaan obat baik itu data stok obat, obat masuk dan obat keluar, mempercepat proses pembuatan laporan serta pencarian data dibandingkan dengan cara konvensional atau manual. Dengan Sistem persediaan yang dibangun ini diharapkan dapat membantu dalam proses pengelolaan persediaan obat puskesmas.
Analisis Perbandingan Metode Random Forest dan Adaptive Boosting Untuk Prediksi Leukemia dengan Data Microarray Heremba, Juleha Irianti; Suhendra, Christian Dwi; Sanglise, Marlinda
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6898

Abstract

Cancer is the uncontrolled growth of cells that spread to other parts of the body. There are different types of cancer that are named after the organ they originate from. One of them is blood cancer or leukemia, which is bone marrow cancer caused by genetic mutations. According to data from Global Cancer Statistics in 2020, there were an estimated 19.3 million new cancer cases and 10 million cancer deaths, and it is estimated that by 2040 it will increase globally by 47% from 19.3 million to 28.4 million new cancer cases. Leukemia is one type of cancer with the ninth rank in Indonesia in 2020, there are 14,979 new cases and 11,530 cases of death caused by leukemia. One of the efforts to prevent leukemia can be done by diagnosing the acute leukemia category using DNA and genetic information. The purpose of this study is to analyze the comparative performance between Random Forest and Adaptive Boosting methods in predicting leukemia types using microarray datasets to determine which method is more effective in performing classification. In this study, the dataset used is gene expression in bone marrow and blood consisting of two categories of acute leukemia, namely Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) obtained with DNA microarray technology. These genes will be classified using Random Forest and Adaboost methods to predict acute leukemia categories. The results of the analysis process show that the random forest method is a better method for predicting acute leukemia with an Area Under Curve value of 100%, Accuracy 92.9%, Precision 93.7%, Recall 92.9%, and F1-Score 92.7% compared to the AdaBoost method with an Area Under Curve value of 83.3%, Accuracy 85.7%, Precision 88.6%, Recall 85.7%, and F1-Score 85.1%.
Development of Augmented Reality Media to Enhance Students' Critical Thinking Skills in High Schools Yonathan, Alberto Yonathan Tangke; Pramanagara, Rio Octovinary; Suhendra, Christian Dwi
Kasuari: Physics Education Journal (KPEJ) Vol. 8 No. 1 (2025): June 2025
Publisher : Universitas Papua, Jurusan Pendidikan Fisika FKIP Unipa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37891/kpej.v8i1.494

Abstract

Based on observations carried out at public high schools and private high schools in Manokwari, it was found that the physics learning used had not adapted to current technological developments, so it was less relevant when used today. The purpose of this research is to develop Augmented Reality (AR) media that is valid, practical, and effective for improving students' critical thinking learning skills on the material of rotational dynamics and equilibrium of rigid bodies in high schools in Manokwari Regency. The development method used is the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) method. The research trial was carried out on students of class XI Science at SMA YPK Oikoumene and the reel research was on students of class XI Science 1 at SMA N 2 Manokwari. This research produces AR media on the topic of rotational dynamics and equilibrium of rigid bodies which can be accessed using a computer/laptop or smartphone connected to the internet, whereas the teaching media uses AR, which can be accessed anywhere and at any time, if the Physics Augmented Reality (Phy-AR) application has been installed on an Android Smartphone so that it can improve students' critical thinking learning outcomes. This research concludes that AR media has been developed to improve the critical thinking skills of high school students and is valid, practical, and effective for use in physics learning.
Co-Authors Albab, Elfan Ulil Asri, Windi Fahmi Edi Faizal Effan Najwaini FEBY SERU Hakim, Ilham Luqman Heremba, Juleha Irianti Jubita, Jubita Karubui, Raema Miryam Lantang, Stefanie Stanly Maria, Eny Marini, Lion Ferdinand Pramanagara, Rio Octovinary Sanglise, Marlinda Saputra, Agung Dwi Sarungallo, Ana Sihite, Rina Wati Nurlia Br Sihombing, Ester Ivo Yati, Fatimah Aszhara Yonathan, Alberto Yonathan Tangke