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All Journal Jurnal Teknik Kimia USU JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Jurnal TIMES Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JKIE (Journal Knowledge Industrial Engineering) Jurnal Sistem Teknik Industri Prosiding National Conference for Community Service Project Jurnal Manajemen Bisnis Eka Prasetya GANDRUNG: Jurnal Pengabdian Kepada Masyarakat HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Jurnal Hurriah: Jurnal Evaluasi Pendidikan dan Penelitian Bulletin of Computer Science Research Jurnal Teknik Kimia USU Jurnal Armada Informatika Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) AMMA : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Smart Medika Tadulako: Jurnal Ilmiah Kedokteran Fakultas Kedokteran JoDENS: Journal of Digital Ecosystem for Natural Sustainability Computer & Science Industrial Engineering Journal
david
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Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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GAMBARAN HISTOPATOLOGI HATI TIKUS MODEL OBESITAS PASCA PEMBERIAN METFORMIN Ramadhanti, Rahna Nur; David
Medika Tadulako: Jurnal Ilmiah Kedokteran Fakultas Kedokteran Vol. 9 No. 2 (2024): Oktober
Publisher : Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/mtj.v9i2.1372

Abstract

Obesitas merupakan salah satu penyebab non alcoholic fatty liver disease (NAFLD) yang ditandai dengan inflamasi dan kerusakan hepatosit yang dapat berkembang menjadi fibrosis hati. Metformin sebagai antidiabetes memiliki efek antiinflamasi sehingga dapat mengurangi steatosis hati dan juga NAFLD. Penelitian ini bertujuan untuk mengetahui efek metformin terhadap gambaran histopatologi hati tikus model obesitas. Penelitian ini merupakan studi eksperimental dengan rancangan posttest only controlled group design dengan pendekatan kualitatif dan kuantitatif. Penelitian ini menggunakan tikus putih galur Wistar jantan, berusia 10-12 minggu, berat badan (BB) 200-250 gram, berjumlah 15 ekor. Tikus dibagi dalam 3 kelompok perlakuan; K1: kontrol normal; K2: kontrol negatif (model obesitas); K3: model obesitas + terapi metformin 250 mg/kgBB. Tikus dimodifikasi menjadi model obesitas dengan pemberian high fat diet (HFD). Dilakukan pengukuran BB secara berkala. Gambaran histopatologi didapatkan dari pewarnaan Hematoksilin eosin (HE). Data yang diperoleh dari pengamatan preparat histopatologi hati tikus wistar dianalisis secara deskriptif kualitatif dengan menilai tingkat kerusakan hepatosit dan analisis kuantitatif dengan menilai tingkat fibrosis. Ditemukan bahwa terapi metformin menunjukkan tingkat kerusakan hepatosit lebih sedikit atau tingkat sedang dan pembentukan fibrosis hati pada tikus model obesitas menunjukkan perbedaan bermakna (p=0,0002). Kesimpulan penelitan ini metformin dapat menunjukkan kerusakan hepatosit dan terbentuknya fibrosis hati tikus model obesitas lebih sedikit.
Improvement Of Production Quality With Improved Scheduling Of PT Jaya Baru Mandiri With Hodgson Algorithm Method Wati, Vera; David; Budiman, Irwan
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 1 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i1.2499

Abstract

Jaya Baru Mandiri company is a manufacturing company engaged in the manufacture of machinery spare parts. One of the spare parts products that are often made is mainshaft, for the purposes of palm oil mills. In the process of making mainshaft, there is still often a delay (lateness). So that in this study, it was done to improve the scheduling of the production process in order to deliver the product to consumers in a timely manner. To clarify the production process, the method that will be used in this study is hodgson algorithm method, shortest processing time (SPT). Hodgson's algorithmic method serves to minimize the number of tardy jobs in the scheduling of production machines. The purpose of hodgson's algorithm scheduling is to improve the efficiency of scheduling the ideal production process as well as minimize unnecessary waste of time with the improvements recommended in this study. It is expected that the production process of PT. Jaya Baru Mandiri can improve its production process effectively and efficiently.
PREDIKSI VOLUME PENJUALAN GAS PT PGN (PERSERO) MENGGUNAKAN REGRESI LINEAR BERGANDA Edison; David; Pangestu, Amora Antonio; Efanly; Rindiany
Journal of Digital Ecosystem for Natural Sustainability Vol 1 No 1 (2021): Juli 2021
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v1i1.23

Abstract

PT PGN (Persero) gets an erratic gas sales volume every year, this can affect the existing gas supply. If the existing gas supply can't fulfill the demand or vice versa, the existing supply becomes excessive and affect company performance. Of these problems, it is necessary to predict sales volume to determine future inventory. This research uses Multiple Linear Regression Algorithm by applying the Cross-Industry Standard Process for Data Mining (CRISP-DM) method. The Multiple Linear Regression Algorithm aims to find the value of the regression equation, after getting the regression equation, the next step is to do it. Error analysis to determine the accuracy of predictions using MAD, MSE, and MAPE through R.Studio software. From the processing results, the results obtained from the sales volume in 2016 amounted to 109 443.97, 2017 amounted to 79 521.42, 2018 amounted to 102 059.01 and in 2019 amounted to 86 799.89 at PT.PGN (Persero). Then with the resulting error analysis, the MAD value is 27741.58, the MSE value is 791516224.16 and the MAPE value is 27.18%.
Pelayanan Kesehatan Terhadap Lansia Dalam Meningkatkan Kualitas Hidup Di Kelurahan Meruya Selatan Jakarta Sisca; Dwi Hartanti, Monica; Roeslan, Orliando; David; Kurniawan, Yani; Edy Parwanto, ML; Joshua Vidova Tjahyadi, Joey
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 2 : Maret (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

Elderly people are part of the life process that cannot be avoided and will be experienced by every human being. Objective: to help the elderly community in the area of the Lukas Church of Maria Kusuma Karmel Parish, West Jakarta, Meruya Selatan Subdistrict to improve their quality of life, especially in the physical domain, through counseling activities, health services and treatment so that it is hoped that it can improve the quality of life of the elderly. Method: Health services were provided to 60-70 elderly people in South Meruya Village. The service team consists of 6 lecturers and 3 students. Blood pressure, height and weight, glucose, uric acid and cholesterol were measured. Results: High blood pressure was checked for around 37% of elderly people, 33% for cholesterol, 10% for glucose and 57% for uric acid. Conclusion: Regular health checks are an important part of comprehensive prevention and management of chronic diseases. Family and local community support can help elderly residents undergo treatment to improve their quality of life.
ANALISIS SENTIMEN KOMENTAR BERPOTENSI TOXIC PADA MEDIA SOSIAL TIKTOK MENGGUNAKAN METODE DECISION TREE: SENTIMENT ANALYSIS OF POTENTIALLY TOXIC COMMENTS ON TIKTOK SOCIAL MEDIA USING THE DECISION TREE METHOD Jasno, Bobbin Ariyadi; Fathoni, Ahmad Ariful; David; Putra, Dwiki Dharma; Hasan, Mohammad Zidane; Amsury, Fachry; Supendar, Hendra
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 16 No. 2 (2025): Jurnal HOAQ - Teknologi Informasi
Publisher : STIKOM Uyelindo Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol16no2.p193-201

Abstract

Penelitian ini bertujuan untuk mengatasi tantangan dalam mendeteksi dan mengklasifikasikan komentar berpotensi toxic secara otomatis pada media sosial TikTok, yang dikenal padat dengan bahasa informal, slang, dan cyber-aggression, menggunakan Analisis Sentimen dengan algoritma Decision Tree. Dataset yang digunakan terdiri dari 271 komentar primer yang dikumpulkan langsung dari feed video TikTok dan diklasifikasikan secara seimbang ke dalam kategori Toxic (Label = 1) dan Non-Toxic (Label = 0). Tahapan metodologi mencakup normalisasi bahasa slang TikTok, preprocessing teks, dan pembobotan fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF) untuk menonjolkan fitur linguistik yang berkaitan dengan toksisitas. Hasil pengujian menunjukkan bahwa model menghasilkan akurasi sebesar 0,75, precision untuk kelas toxic sebesar 0,787, dan recall sebesar 0,765, sehingga mencerminkan performa aktual model dalam mendeteksi komentar toxic setelah proses preprocessing dan TF-IDF. Teknik post-pruning turut membantu mengurangi overfitting dan meningkatkan kemampuan generalisasi model terhadap data baru, meskipun penelitian ini tidak melakukan pengujian formal terhadap efisiensi komputasi maupun keandalan sistem. Secara keseluruhan, kombinasi normalisasi slang, TF-IDF, dan Decision Tree dengan post-pruning mampu menghasilkan performa klasifikasi yang stabil dalam identifikasi komentar toxic pada TikTok berbasis data primer.   This study aims to address the challenges of automatically detecting and classifying potentially toxic comments on the TikTok social media platform, which is characterized by heavy use of informal language, slang, and cyber-aggression, by applying Sentiment Analysis using the Decision Tree algorithm. The dataset consists of 271 primary comments collected directly from TikTok video feeds and evenly categorized into Toxic (Label = 1) and Non-Toxic (Label = 0). The methodological stages include TikTok-specific slang normalization, text preprocessing, and feature weighting using Term Frequency–Inverse Document Frequency (TF-IDF) to highlight linguistic features associated with toxicity. Experimental results show that the model achieves an accuracy of 0.75, a precision of 0.787, and a recall of 0.765 for the toxic class, reflecting the model’s actual performance after preprocessing and TF-IDF optimization. The application of post-pruning also helps reduce overfitting and improves the model’s generalization ability toward new data, although the study does not conduct formal evaluations of computational efficiency or system reliability. Overall, the combination of slang normalization, TF-IDF, and a pruned Decision Tree demonstrates stable classification performance in identifying toxic comments on TikTok based on the primary data used.
Co-Authors Alda Amsury, Fachry Anggraini Mudjiono, Sherina Bani, Okta Beny Budi Chandra Charless Lee Darren Anderson Diana Dwi Hartanti, Monica Edison Edy Parwanto, ML Efanly Elisa, Erlin ENDRI ENDRI Engmir Eric Prima Wijaya Evonne Fathoni, Ahmad Ariful Febianto, Toby Federline Yeo Gat Hasan, Mohammad Zidane Irwan Budiman Jasno, Bobbin Ariyadi Joanne Jolyn Joshua Vidova Tjahyadi, Joey Lina M. RIZA Manco Margaretha Kuwai, Susanti Margaretha Kuway, Susanti Mario Tangi Airaz Sitorus Natasia Novita Octara Pribadi Pangestu, Amora Antonio Putra, Dwiki Dharma Putra, Kianata Putri Klaudia Ramadhanti, Rahna Nur Rindiany Robby Wiranto Robert Robinson Roeslan, Orliando Rosari Oktaviana Sandy Kosasi saptawan, ferry Sari, Ika Sherina Siau Phe sisca Sofiani, Sendy SUSANTI Takbirullah Rizquha Tampubolon, Jusra Ticto Jonata Tony Honkley Tony Wijaya Wati, Vera Wilson Winadi Prasetyoningtyas, Ari Anggraini Yani Kurniawan, Yani