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All Journal Jurnal Fourier LOSARI: Jurnal Pengabdian Kepada Masyarakat Journal of Data Insights Emerging Statistics and Data Science Journal
M. Al Haris
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Transportation Other

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Survival Analysis of Kidney Failure Patients Using the Kaplan Meier Method and Log-Rank Test: Survival Analysis of Kidney Failure Patients Using the Kaplan Meier Method and Log-Rank Test Febrianti, Fatika Lovina; Firdatul Fahria; Siti Hamidah Ardhy; Rahma Nurmalita; Suci Laeliyah; Muhammad Rifqy Ardiansyah; Ihsan Fathoni; M. Al Haris
Emerging Statistics and Data Science Journal Vol. 3 No. 3 (2025): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol3.iss.3.art21

Abstract

Kidney failure is a global health issue that continues to rise, impacting patients' quality of life and placing significant pressure on healthcare systems. This study aims to analyze the factors influencing the survival probability of kidney failure patients using the Kaplan-Meier method and the log-rank test. Medical records from 106 kidney failure patients treated at Hasanuddin Hospital between 2018 and 2020 were used to examine the effects of age, gender, and disease severity on survival outcomes. The Kaplan-Meier analysis revealed that patients aged ≤ 50 years, females, and those with chronic conditions had better survival probabilities. However, the log-rank test indicated that survival differences based on these three variables were not statistically significant (p-value > 0,05). These findings provide an initial understanding of the survival patterns of kidney failure patients and highlight the need for further research with larger sample sizes or more advanced methods to support the development of personalized care strategies and improve patients' quality of life.
Peramalan Laju Inflasi Di Indonesia Menggunakan Metode Fuzzy Time Series Saxena-Easo indah fitriyani; M. Al Haris; Arum, Prizka Rismawati
Jurnal Fourier Vol. 13 No. 2 (2024)
Publisher : Program Studi Matematika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/fourier.2024.132.94-110

Abstract

Inflasi adalah fenomena dimana harga barang dan jasa umumnya naik. Inflasi yang stabil sangat penting untuk menjaga pertumbuhan ekonomi agar dapat meningkatkan kesejahteraan masyarakat. Inflasi tidak hanya merupakan fenomena jangka pendek, tetapi juga merupakan fenomena jangka Panjang. Untuk itu, perlu adanya antisipasi dan tindakan untuk mencegah inflasi agar tidak melambung tinggi dan terlalu rendah. Salah satu caranya dengan melakukan peramalan. Fuzzy time series (FTS) salah satu metode yang digunakan dalam peramalan. Fuzzy time series Saxena-Easo memperbaiki metode yang diperkenalkan oleh Stevenson dan Porter dengan melakukan modifikasi pada pembentukan subinterval kelas himpunan fuzzy, yang didasarkan pada jumlah anggota di setiap interval kelas. Data yang digunakan yaitu data laju inflasi di Indonesia bulan Januari 2013 hingga April 2024. Hasil penerapan metode fuzzy time series Saxena-Easo mampu meramalkan laju inflasi sangat baik. Karena menghasilkan kesalahan peramalan berdasarkan MAPE sebesar 1,029%, dan nilai RMSE yang diperoleh adalah 0,1016. Nilai peramalan satu periode kedepan pada bulan Juli 2024 sebesar 2,54%.
Peramalan Indeks Harga Konsumen Kota Semarang dengan Metode Autoregressive Integrated Moving Average: Forecasting Consumer Price Index (CPI) of Semarang City using Autoregressive Integrated Moving Average (ARIMA) Method Sesotyaning Harum Prabuningrat; M. Al Haris; Nadia Khoirunnafisa Salma; Putri Wahyu Muharamah; Muhammad Saifuddin Nur
Journal of Data Insights Vol 1 No 1 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i1.124

Abstract

Indeks Harga Konsumen (IHK) merupakan salah satu indikator untuk menentukan tingkat stabilitas ekonomi suatu negara. IHK dapat memberikan informasi mengenai perkembangan harga barang dan jasa yang dibayar oleh konsumen, khususnya masyarakat kota. Pemerintah selalu menjaga mengenai presentase perubahan nilai IHK agar tetap rendah dan stabil sehingga mampu memberikan kesejahteraan untuk masyarakat. Oleh karena itu, perlu adanya peramalan data IHK untuk membantu pemerintah dalam menyusun kebijakan kedepannya. Salah satu metode yang tepat untuk meramalkan data IHK Kota Semarang yaitu dengan menggunakan model time series dengan proses Autoregressive Integrated Moving Average (ARIMA). Berdasarkan hasil analisis diperoleh Model ARIMA terbaik adalah ARIMA (0,1,1). Model terbaik menghasilan nilai kesalahan prediksi berdasarkan nilai MAPE sebesar 6,07% yang menandakan bahwa kemampuan model dalam memprediksi IHK Kota Semarang sangat akurat.
Prediction of Covid-19 Cases in Indonesia Using the Auto Regressive Integrated Moving Average Method: Prediksi Kasus Covid-19 di Indonesia Menggunakan Metode ARIMA Sawiah Adam, Asriyanti; Safira, Rahma; M. Al Haris; Amri, Saeful
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.212

Abstract

This study discusses the use of the ARIMA (Auto Regressive Integrated Moving Average) model to predict the number of COVID-19 cases in Indonesia based on previous data. The results of the analysis show that the ARIMA (1,0,0) model is the most accurate in predicting the spread of COVID-19. Based on this model, the prediction results obtained that confirmed COVID-19 data from January to December 2022 are predicted to decrease. The number of confirmed cases of COVID-19 until December 2022 is predicted to reach 20,0365 cases of spread. So this Covid-19 case still needs special and more serious attention from the government and the public must still be vigilant because based on the results of the study there have been no signs of a significant decrease in the spread of Covid-19 cases. This study provides important insights for the government, medical personnel, and the public in planning strategies for preventing and handling the pandemic
K-Nearest Neighbor (KNN) Method for Weather Data Prediction: Penerapan Metode K-Nearest Neighbour (KNN) Untuk Prediksi Data Cuaca Putri, Agata Dwi Putri; M. Al Haris; Fauzi, Fatkhurokhman; Amri, Saeful
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.214

Abstract

The weather tends to change frequently every day, so weather forecasts are made to be used as an early warning if sudden weather changes occur. By forecasting the weather, losses can be minimized and people are alert to carry out outdoor activities. From this problem, the K-Nearest Neighbor (KNN) method was applied. This method is expected to provide accurate and efficient information to obtain weather predictions for existing conditions. The data used is secondary data. After conducting research on training data (old data) amounting to 80% and test data (new data) amounting to 20%. The accuracy results from the testing data predictions are 75% with a value of k = 8.
Smart Village Application untuk Meningkatkan Pelayanan Publik Pemerintah Desa Katonsari Kabupaten Demak M. Al Haris; Prizka Rismawati Arum; Dannu Purwanto; Ali Imron; Linda Puspitasari; Miftakhul Haris
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2023): Desember 2023
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v5i2.161

Abstract

Pemerintah Desa Katonsari Kabupaten Demak, Provinsi Jawa Tengah, berkomitmen untuk memberikan pelayanan terbaik kepada warganya. Saat ini, pelayanan publik masih dilakukan secara manual yang mengakibatkan ketidakefektifan dan ketidakefisienan dalam pelayanan. Selain itu, sumber daya manusia di Desa Katonsari masih belum memiliki keterampilan teknologi informasi, sehingga perlu meningkatkan kemampuan dalam memanfaatkan teknologi. Untuk mengatasi permasalahan tersebut, tim pengabdian Universtas Muhammadiyah Semarang memberikan solusi dalam bentuk "Smart Village Application" untuk meningkatkan pelayanan publik pemerintah Desa Katonsari. Tahapan kegiatan diawali dengan identifikasi kebutuhan desa dengan pendekatan wawancara, perancangan sistem smart village application, pelatihan penggunaan sistem, dan evaluasi terhadap kinerja dan keefektifan sistem. Sasaran kegiatan ditujukan kepada perangkat desa dan beberapa warga Desa Katonsari sejumlah 30 orang. Berdasarkan kegiatan yang telah dilaksanakan, peserta kegiatan terlihat antusian dan puas terhadap program yang dilaksanakan. Hal tersebut didasarkan pada hasil survei kepuasan yang Tim pengabdian lakukan setelah selesai kegiatan.
Co-Authors Ali Imron Amri, Saeful Dannu Purwanto Fauzi, Fatkhurokhman Febrianti, Fatika Lovina Firdatul Fahria Ihsan Fathoni Indah Fitriyani Linda Puspitasari Miftakhul Haris Muhammad Rifqy Ardiansyah Muhammad Saifuddin Nur Nadia Khoirunnafisa Salma Prizka Rismawati Arum Putri Wahyu Muharamah Putri, Agata Dwi Putri Rahma Nurmalita Safira, Rahma Sawiah Adam, Asriyanti Sesotyaning Harum Prabuningrat Siti Hamidah Ardhy Suci Laeliyah