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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Media Statistika Jurnal Studi Manajemen Organisasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Jiko (Jurnal Informatika dan komputer) JURNAL PENDIDIKAN TAMBUSAI Jurnal Pendidikan dan Konseling Jurnal Sistem informasi dan informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) International Journal of Advances in Data and Information Systems Al-Mutharahah: Jurnal Penelitian dan Kajian Sosial Keagamaan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) International Journal of Community Service International Journal of Data Science, Engineering, and Analytics (IJDASEA) Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Inkofar Kreatifitas: Jurnal Ilmiah Pendidikan Islam Bhakti Nagori (Jurnal Pengabdian kepada Masyarakat) Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Eksponensial Baitul Hikmah: Jurnal Ilmiah Keislaman Kohesi: Jurnal Sains dan Teknologi ITIJ Seminar Nasional Teknologi dan Multidisiplin Ilmu Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal ilmiah teknologi informasi Asia
Trimono, Trimono
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COMPARISON OF DECISION TREE AND RANDOM FOREST METHODS IN THE CLASSIFICATION OF DIABETES MELLITUS Maulidiyyah, Nova Auliyatul; Trimono, Trimono; Damaliana, Aviolla Terza; Prasetya, Dwi Arman
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8316

Abstract

Diabetes mellitus is a deadly disease caused by the failure of the pancreas to produce enough insulin. Indonesia ranks fifth in the world with the number of people with diabetes in 2021 at around 19.47 million, and this number continues to increase. One of the main challenges in diabetes management is to make the right classification between type 1 and type 2 diabetes, as misdiagnosis can result in inappropriate treatment and worsen the patient's condition. This study uses a machine learning approach to compare Decision Tree and Random Forest methods in classifying type 1 and type 2 diabetes mellitus. The goal is to identify the most effective model in predicting the type of diabetes based on medical record data. The comparison was done using k-fold cross validation and confusion matrix. The results showed that Random Forest provided an average accuracy of 94%, while Decision Tree reached 93% during cross validation testing. Although both models were able to perform well in classification, Random Forest showed a more stable performance and a slight edge in accuracy over Decision Tree. Evaluation with the confusion matrix showed that the Decision Tree model achieved 93% accuracy compared to Random Forest's 91%. In addition, the Decision Tree model also had a lower number of prediction errors, 7, compared to 9 for Random Forest. The most influential variables in classification also differed between the two models, showing the unique advantages and characteristics of each approach.
Tantangan Guru PAI Dalam Menghadapi Era Digital 5.0 Di Madrasah Aliyah Darul Ulum Pulau Kijang Indragiri Hilir Trimono, Trimono; Hasan; Bainar; Aisyah, Azni
Al-Mutharahah: Jurnal Penelitian dan Kajian Sosial Keagamaan Vol 22 No 02 (2025): Al-Mutharahah : Jurnal Penelitian dan Sosial Keagamaan
Publisher : LPPM Institut Agama Islam Diniyyah Pekanbaru

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

Abstract

Abstract This study aims to examine the challenges faced by Islamic Education (PAI) teachers in adapting to the Digital Era 5.0 at MA Darul Ulum Pulau Kijang, Indragiri Hilir, Riau. The Digital Era 5.0 requires teachers to master information technology in the learning process, including planning, implementation, and evaluation. Based on field observations, it was found that some teachers still rely on traditional methods, lack skills in using digital devices, and face limitations in facilities and infrastructure. This research identifies four main challenges faced by PAI teachers: operating digital platforms such as PMM, designing technology-based lessons, creating interactive learning experiences, and using digital assessment tools. To overcome these challenges, teachers engage in self-directed learning, peer discussions, and participate in both online and offline training programs. The study concludes that improving teachers’ digital competence is essential to support the effectiveness of learning in the era of digital transformation. Keywords: Challenges, of PAI Teachers, Digital Era 5.0 Abstrak Penelitian ini bertujuan untuk mengkaji tantangan yang dihadapi guru Pendidikan Agama Islam (PAI) dalam menghadapi era digital 5.0 di MA Darul Ulum Pulau Kijang, Indragiri Hilir, Riau. Era digital 5.0 menuntut guru untuk mampu menguasai teknologi informasi dalam proses pembelajaran, baik dalam aspek perencanaan, pelaksanaan, hingga evaluasi. Berdasarkan studi lapangan, ditemukan bahwa sebagian guru masih menggunakan metode tradisional, kurang terampil dalam menggunakan perangkat digital, serta menghadapi keterbatasan sarana dan prasarana. Penelitian ini mengidentifikasi empat tantangan utama yang dihadapi guru PAI, yaitu keterampilan mengoperasikan platform digital seperti Platform Merdeka Mengajar (PMM), kemampuan merancang pembelajaran berbasis teknologi, menciptakan pengalaman belajar yang interaktif, dan penggunaan alat evaluasi digital. Untuk mengatasi hal tersebut, para guru melakukan berbagai upaya seperti pembelajaran mandiri, diskusi dengan rekan sejawat, dan mengikuti pelatihan baik daring maupun luring. Penelitian ini menyimpulkan bahwa peningkatan kompetensi digital guru sangat penting guna menunjang efektivitas pembelajaran di era transformasi digital. Kata Kunci: Tantangan, Guru PAI, era digital 5.0,
Analisis Pengaruh Tingkat Kriminalitas dan Kepadatan Penduduk Terhadap Indikator Kualitas Hidup Masyarakat melalui Pendekatan Two-Way MANOVA Dewi, Ni Luh Ayu Nariswari; Zalfa Assyadida, Azizah; Salma Namira, Alivia; Nasrudin, Muhammad; Trimono, Trimono
EKSPONENSIAL Vol. 16 No. 2 (2025): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/6ssnd846

Abstract

Quality of a population life is shaped by various social and structural conditions, including socioeconomic disparities, crime levels, and population pressure. Understanding how these factors interact is essential for evaluating regional welfare. Therefore, this study aims to examine the influence of crime rates and population density on the quality of life in Indonesia using a Two-Way Multivariate Analysis of Variance (MANOVA) approach. The dependent variables analyzed include the Human Development Index (IPM), the percentage of the poor population, and the open unemployment rate. The independent variables consist of categories of crime rates and population density levels. Prior to conducting the MANOVA, assumption tests were performed to ensure data adequacy, including multivariate normality testing using Mardia’s test, independence testing via Bartlett's Test of Sphericity, and homogeneity of variance testing with Box’s M Test. The analysis results indicate that neither crime rates nor population density levels significantly influence the three quality of life indicators simultaneously, as evidenced by the Wilks’ Lambda and Pillai’s Trace test outcomes. These findings suggest that policies aimed at improving quality of life should not solely focus on crime rates and population density but require a multidimensional approach encompassing other factors such as education, healthcare, and economic conditions. 
Implementasi Spatial Durbin Model Berbasis Data Science Untuk Analisis Kemiskinan Jawa Timur Arif, Farah Yusnaida; Mohammad Idhom; Trimono, Trimono
Seminar Nasional Teknologi dan Multidisiplin Ilmu (SEMNASTEKMU) Vol. 5 No. 1 (2025): SEMNASTEKMU
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/9w9pye50

Abstract

Poverty remains a major development challenge that requires data-driven analysis to understand its variation across regions. This study focuses on East Java, where spatial interdependence is suspected to influence poverty distribution, making spatial analysis relevant for supporting regional policy design. The study examines determinants of poverty using the Spatial Durbin Model, which captures both direct effects and indirect spatial spillovers through lagged independent variables. The analytical workflow is implemented using a Python-based data science pipeline to ensure a systematic, transparent, and reproducible process, in line with current trends in technology-supported research. The dataset consists of 2024 secondary data from the Indonesian Central Bureau of Statistics. The analysis includes data preprocessing, construction of a Queen Contiguity spatial weight matrix, Moran’s I test to detect spatial autocorrelation, and SDM estimation. Results indicate significant positive spatial autocorrelation (I = 0.4099; p = 0.0008), showing that poverty is not randomly distributed. While the spatial lag of the dependent variable is not significant, an indirect spatial effect appears through the Gini Ratio (θ₄ = –39.42168; p = 0.03855). Moreover, the Human Development Index significantly reduces poverty. These findings highlight the roles of regional inequality and human development in shaping poverty dynamics and provide insights for more targeted policy interventions.
SOSIALISASI ORANG TUA TENTANG BAHAYA GADGET BAGI ANAK-ANAK Trimono, Trimono; Ningtiyas, Rona Wulan; Icha Rohmatul Jannah; Aliya Dasa Pramesthi; Putra, Andrawana; Wardah Ariij Adibah; Ade Irma Agustian
BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Vol. 5 No. 2 (2025): BHAKTI NAGORI (Jurnal Pengabdian kepada Masyarakat) Desember 2025
Publisher : LPPM UNIKS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/bhakti_nagori.v5i2.4773

Abstract

Penggunaan gawai yang berlebihan pada anak-anak kini menjadi perhatian serius karena dapat memengaruhi perkembangan fisik, kognitif, dan sosial mereka. Kegiatan pengabdian kepada masyarakat ini dilaksanakan untuk meningkatkan kesadaran orang tua dan pengasuh mengenai risiko penggunaan gawai yang tidak terkontrol, sekaligus mendorong terciptanya kebiasaan digital yang lebih sehat dalam lingkungan keluarga. Program ini menggunakan pendekatan partisipatif melalui edukasi langsung, diskusi kelompok, serta pemanfaatan media interaktif seperti poster informatif dan video edukatif singkat agar materi lebih mudah dipahami oleh peserta. Kegiatan dilaksanakan di lingkungan masyarakat setempat dan melibatkan orang tua, guru, serta tokoh masyarakat yang memiliki peran penting dalam pengawasan anak. Selama pelaksanaan, peserta diberikan pemahaman mengenai dampak jangka panjang penggunaan gawai berlebihan, termasuk gangguan tidur, penurunan konsentrasi, dan rendahnya interaksi sosial anak. Hasil kegiatan menunjukkan peningkatan yang signifikan, di mana 85% peserta menyadari bahaya paparan gawai berlebihan, sementara 90% lainnya menyatakan kesediaan untuk meningkatkan kontrol terhadap penggunaan gawai di rumah. Melalui evaluasi pra-tes dan pasca-tes, terlihat peningkatan skor pengetahuan peserta sebesar 40%. Program ini diharapkan mampu menjadi upaya preventif dalam mengurangi risiko kecanduan digital pada anak usia dini
Co-Authors Abdullah Abdullah Ade Irma Agustian Adiwidyatma, Afdhal Reshanda Aliya Dasa Pramesthi Amanillah, Rahmatul Ardiani, Ardia Eva Arif, Farah Yusnaida Arifta, Septia Dini Aurelia, Cenditya Ayu Aviolla Terza Damaliana Awang, Wan Suryani Wan Aziziyah, Luqna Azni Aisyah Azzahra, Adelia Ramadhina Bainar Bainar, Bainar Bey Lirna, Cagiva Chaedar Carissa, Savvy Prissy Amellia Damaliana, Aviolla Terza Dewi, Ni Luh Ayu Nariswari Di Asih I Maruddani Di Asih I Maruddani Diash, Hakam Dzakwan Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Fahrudin, Tresna Maulana Fairuz Luthfia Winoto Putri, Maretta Febri Giantara Febriyanti, Alvi Yuana Febyanti, Iin Fitriani, Aulia Nur Hadi, Surjo Hadiyan Pradipta, Alvino Hasan Herlina Herlina Hervrizal, Hervrizal Hindrayani, Kartika Maulida I Gede Susrama Mas Diyasa Icha Rohmatul Jannah idhom, Mohammad Ikaningtyas, Maharani Irawan, Tanaya Anindita Kartini Kartini Kassim, Anuar bin Mohamed Khairunisa, Adenda Khosyi, Hanun Aufa Nur Kusdani, Kusdani Kuswardana, Dendy Arizki Linggasari, Dienna Eries Lisanthoni, Angela Maruddani, Di Asih Mas Diyasa, I Gede Susrama Mas Diyasa, I Gede Susrama Susrama Maulana Pasha, Naufal Ricko Maulidiyyah, Nova Auliyatul Mohammad Idhom Muhaimin, Amri Muhammad Nasrudin Nabila, Nasywa Azzah Nafiah, Fajria Ulumin Nariyana, Calvien Danny Nasution, Baktiar Nathania, Vannesa Ningrum, Imelda Widya Ningtiyas, Rona Wulan Novita Anggraini Nugraheni, Setiawati Oktaviani, Sheny Eka Panglima, Talitha Fujisai Prisma Hardi Aji Riyantoko Putra, Andrawana Putri Ariyani, Kinanthi Putri, Irma Amanda Putri, Nabila Rizky Amalia Rafiqah, Lailan Rafli Feandika Nugroho, Muhammad Ratna Yulistiani Renaldi, Sahat Rhomaningtias, Lina Riswanda, Mohammad Nizar Riyantoko, Prismahardi Aji Ryan Dana, Alvin Sabela, Sefilah Naurah Safira Devi, Arsita Safira, Alya Mirza Salma Namira, Alivia Saputra, Wahyu Syaifullah Jauharis Sihananto, Andreas Sonhaji, Abdulah Sugiarti, Nova Putri Dwi Suprapto, Rheinka Elyana Susrama Mas Diyasa , I Gede Syamsul Rizal Syukri Syukri Tarno Tarno Taufik, Ikbar Athallah Terza Damaliana, Aviolla Utami, Rianti Siswi Utriweni Mukhaiyar Valentina, Tiara Wardah Ariij Adibah Wardah, Salsabila Wibowo, Muhammad Bagas Satrio Widayawati, Eny Widison, Daffin Tanjiro Yuciana Wilandari yuliza, eva Zalfa Assyadida, Azizah